Science.gov

Sample records for cancer risk prediction

  1. Cancer Risk Prediction and Assessment

    Cancer.gov

    Cancer prediction models provide an important approach to assessing risk and prognosis by identifying individuals at high risk, facilitating the design and planning of clinical cancer trials, fostering the development of benefit-risk indices, and enabling estimates of the population burden and cost of cancer.

  2. Liver Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  3. Cervical Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  4. Pancreatic Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  5. Prostate Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  6. Ovarian Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  7. Lung Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  8. Bladder Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  9. Testicular Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  10. Colorectal Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  11. Breast Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  12. Esophageal Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  13. Korean Risk Assessment Model for Breast Cancer Risk Prediction

    PubMed Central

    Park, Boyoung; Ma, Seung Hyun; Shin, Aesun; Chang, Myung-Chul; Choi, Ji-Yeob; Kim, Sungwan; Han, Wonshik; Noh, Dong-Young; Ahn, Sei-Hyun; Kang, Daehee; Yoo, Keun-Young; Park, Sue K.

    2013-01-01

    Purpose We evaluated the performance of the Gail model for a Korean population and developed a Korean breast cancer risk assessment tool (KoBCRAT) based upon equations developed for the Gail model for predicting breast cancer risk. Methods Using 3,789 sets of cases and controls, risk factors for breast cancer among Koreans were identified. Individual probabilities were projected using Gail's equations and Korean hazard data. We compared the 5-year and lifetime risk produced using the modified Gail model which applied Korean incidence and mortality data and the parameter estimators from the original Gail model with those produced using the KoBCRAT. We validated the KoBCRAT based on the expected/observed breast cancer incidence and area under the curve (AUC) using two Korean cohorts: the Korean Multicenter Cancer Cohort (KMCC) and National Cancer Center (NCC) cohort. Results The major risk factors under the age of 50 were family history, age at menarche, age at first full-term pregnancy, menopausal status, breastfeeding duration, oral contraceptive usage, and exercise, while those at and over the age of 50 were family history, age at menarche, age at menopause, pregnancy experience, body mass index, oral contraceptive usage, and exercise. The modified Gail model produced lower 5-year risk for the cases than for the controls (p = 0.017), while the KoBCRAT produced higher 5-year and lifetime risk for the cases than for the controls (p<0.001 and <0.001, respectively). The observed incidence of breast cancer in the two cohorts was similar to the expected incidence from the KoBCRAT (KMCC, p = 0.880; NCC, p = 0.878). The AUC using the KoBCRAT was 0.61 for the KMCC and 0.89 for the NCC cohort. Conclusions Our findings suggest that the KoBCRAT is a better tool for predicting the risk of breast cancer in Korean women, especially urban women. PMID:24204664

  14. Predicting cancer risks from dental computed tomography.

    PubMed

    Wu, T-H; Lin, W-C; Chen, W-K; Chang, Y-C; Hwang, J-J

    2015-01-01

    Dental computed tomography (CT) has become a common tool when carrying out dental implants, yet there is little information available on its associated cancer risk. The objective of this study was to estimate the lifetime-attributable risk (LAR) of cancer incidence that is associated with the radiation dose from dental CT scans and to evaluate the effect of scan position, sex, and age on the cancer risk. This retrospective cohort study involved 505 participants who underwent CT scans. The mean effective doses for male and female patients in the maxilla group were 408 and 389 µSv (P = 0.055), respectively, whereas the mean effective doses for male and female patients in the mandible groups were 475 and 450 µSv (P < 0.001), respectively. The LAR for cancer incidence after mandible CT scanning varied from 1 in 16,196 for a 30-y-old woman to 1 in 114,680 for a 70-y-old man. The organ-specific cancer risks for thyroid cancer, other cancers, leukemia, and lung cancer account for 99% of the LAR. Among patients of all ages, the estimated LAR of a mandible scan was higher than that of a maxilla scan. Furthermore, the LAR for female thyroid cancer had a peak before age 45 y. The risk for a woman aged 30 y is roughly 8 times higher than that of a woman aged 50 y. After undergoing a dental CT scan, the possible cancer risks related to sex and age across various different anatomical regions are not similar. The greatest risk due to a dental CT scan is for a mandible scan when the woman is younger than 45 y. Given the limits of the sample size, machine parameters, and the retrospective nature of this study, the results need to be interpreted within the context of this patient population. Future studies will be of value to corroborate these findings. PMID:25359782

  15. Submission Form for Peer-Reviewed Cancer Risk Prediction Models

    Cancer.gov

    If you have information about a peer-reviewd cancer risk prediction model that you would like to be considered for inclusion on this list, submit as much information as possible through the form on this page.

  16. Lung cancer in never smokers Epidemiology and risk prediction models

    PubMed Central

    McCarthy, William J.; Meza, Rafael; Jeon, Jihyoun; Moolgavkar, Suresh

    2012-01-01

    In this chapter we review the epidemiology of lung cancer incidence and mortality among never smokers/ nonsmokers and describe the never smoker lung cancer risk models used by CISNET modelers. Our review focuses on those influences likely to have measurable population impact on never smoker risk, such as secondhand smoke, even though the individual-level impact may be small. Occupational exposures may also contribute importantly to the population attributable risk of lung cancer. We examine the following risk factors in this chapter: age, environmental tobacco smoke, cooking fumes, ionizing radiation including radon gas, inherited genetic susceptibility, selected occupational exposures, preexisting lung disease, and oncogenic viruses. We also compare the prevalence of never smokers between the three CISNET smoking scenarios and present the corresponding lung cancer mortality estimates among never smokers as predicted by a typical CISNET model. PMID:22882894

  17. Risk prediction tools for cancer in primary care.

    PubMed

    Usher-Smith, Juliet; Emery, Jon; Hamilton, Willie; Griffin, Simon J; Walter, Fiona M

    2015-12-22

    Numerous risk tools are now available, which predict either current or future risk of a cancer diagnosis. In theory, these tools have the potential to improve patient outcomes through enhancing the consistency and quality of clinical decision-making, facilitating equitable and cost-effective distribution of finite resources such as screening tests or preventive interventions, and encouraging behaviour change. These potential uses have been recognised by the National Cancer Institute as an 'area of extraordinary opportunity' and an increasing number of risk prediction models continue to be developed. The data on predictive utility (discrimination and calibration) of these models suggest that some have potential for clinical application; however, the focus on implementation and impact is much more recent and there remains considerable uncertainty about their clinical utility and how to implement them in order to maximise benefits and minimise harms such as over-medicalisation, anxiety and false reassurance. If the potential benefits of risk prediction models are to be realised in clinical practice, further validation of the underlying risk models and research to assess the acceptability, clinical impact and economic implications of incorporating them in practice are needed. PMID:26633558

  18. Risk prediction tools for cancer in primary care

    PubMed Central

    Usher-Smith, Juliet; Emery, Jon; Hamilton, Willie; Griffin, Simon J; Walter, Fiona M

    2015-01-01

    Numerous risk tools are now available, which predict either current or future risk of a cancer diagnosis. In theory, these tools have the potential to improve patient outcomes through enhancing the consistency and quality of clinical decision-making, facilitating equitable and cost-effective distribution of finite resources such as screening tests or preventive interventions, and encouraging behaviour change. These potential uses have been recognised by the National Cancer Institute as an ‘area of extraordinary opportunity' and an increasing number of risk prediction models continue to be developed. The data on predictive utility (discrimination and calibration) of these models suggest that some have potential for clinical application; however, the focus on implementation and impact is much more recent and there remains considerable uncertainty about their clinical utility and how to implement them in order to maximise benefits and minimise harms such as over-medicalisation, anxiety and false reassurance. If the potential benefits of risk prediction models are to be realised in clinical practice, further validation of the underlying risk models and research to assess the acceptability, clinical impact and economic implications of incorporating them in practice are needed. PMID:26633558

  19. Performance of an Adipokine Pathway-Based Multilocus Genetic Risk Score for Prostate Cancer Risk Prediction

    PubMed Central

    Ribeiro, Ricardo J. T.; Monteiro, Cátia P. D.; Azevedo, Andreia S. M.; Cunha, Virgínia F. M.; Ramanakumar, Agnihotram V.; Fraga, Avelino M.; Pina, Francisco M.; Lopes, Carlos M. S.; Medeiros, Rui M.; Franco, Eduardo L.

    2012-01-01

    Few biomarkers are available to predict prostate cancer risk. Single nucleotide polymorphisms (SNPs) tend to have weak individual effects but, in combination, they have stronger predictive value. Adipokine pathways have been implicated in the pathogenesis. We used a candidate pathway approach to investigate 29 functional SNPs in key genes from relevant adipokine pathways in a sample of 1006 men eligible for prostate biopsy. We used stepwise multivariate logistic regression and bootstrapping to develop a multilocus genetic risk score by weighting each risk SNP empirically based on its association with disease. Seven common functional polymorphisms were associated with overall and high-grade prostate cancer (Gleason≥7), whereas three variants were associated with high metastatic-risk prostate cancer (PSA≥20 ng/mL and/or Gleason≥8). The addition of genetic variants to age and PSA improved the predictive accuracy for overall and high-grade prostate cancer, using either the area under the receiver-operating characteristics curves (P<0.02), the net reclassification improvement (P<0.001) and integrated discrimination improvement (P<0.001) measures. These results suggest that functional polymorphisms in adipokine pathways may act individually and cumulatively to affect risk and severity of prostate cancer, supporting the influence of adipokine pathways in the pathogenesis of prostate cancer. Use of such adipokine multilocus genetic risk score can enhance the predictive value of PSA and age in estimating absolute risk, which supports further evaluation of its clinical significance. PMID:22792137

  20. Predicting the use of Individualized Risk Assessment for Breast Cancer

    PubMed Central

    Bartle-Haring, Suzanne; Toviessi, Paula; Katafiasz, Heather

    2008-01-01

    Purpose The purpose of this study was to investigate the decision to obtain individualized risk assessment after a breast cancer education session. Methods A sample of both African American and Caucasian women was used to determine if there were differences by race/ethnicity in uptake of the assessment and differences in the variables that were most predictive of uptake. The sample included 166 women between the ages of 18 and 80. Sixty-two percent of the sample were African American women. Key Findings The results suggested that African American women and Caucasian women used different factors and used other factors differently to decide whether or not to obtain an individualized risk assessment. Conclusions and Implications These results are discussed within the context of health disparities among ethnic minority and Caucasian women with implications for breast cancer control programs. The results of this study would suggest that knowledge alone does not lead to opting for a personalized risk assessment, and that African American and Caucasian women use different pieces of information, or information differently to make decision about getting more personalized information about risk. PMID:18319147

  1. Observed and Predicted Risk of Breast Cancer Death in Randomized Trials on Breast Cancer Screening

    PubMed Central

    Autier, Philippe; Sullivan, Richard; Boyle, Peter

    2016-01-01

    Background The role of breast screening in breast cancer mortality declines is debated. Screening impacts cancer mortality through decreasing the number of advanced cancers with poor diagnosis, while cancer treatment works through decreasing the case-fatality rate. Hence, reductions in cancer death rates thanks to screening should directly reflect reductions in advanced cancer rates. We verified whether in breast screening trials, the observed reductions in the risk of breast cancer death could be predicted from reductions of advanced breast cancer rates. Patients and Methods The Greater New York Health Insurance Plan trial (HIP) is the only breast screening trial that reported stage-specific cancer fatality for the screening and for the control group separately. The Swedish Two-County trial (TCT)) reported size-specific fatalities for cancer patients in both screening and control groups. We computed predicted numbers of breast cancer deaths, from which we calculated predicted relative risks (RR) and (95% confidence intervals). The Age trial in England performed its own calculations of predicted relative risk. Results The observed and predicted RR of breast cancer death were 0.72 (0.56–0.94) and 0.98 (0.77–1.24) in the HIP trial, and 0.79 (0.78–1.01) and 0.90 (0.80–1.01) in the Age trial. In the TCT, the observed RR was 0.73 (0.62–0.87), while the predicted RR was 0.89 (0.75–1.05) if overdiagnosis was assumed to be negligible and 0.83 (0.70–0.97) if extra cancers were excluded. Conclusions In breast screening trials, factors other than screening have contributed to reductions in the risk of breast cancer death most probably by reducing the fatality of advanced cancers in screening groups. These factors were the better management of breast cancer patients and the underreporting of breast cancer as the underlying cause of death. Breast screening trials should publish stage-specific fatalities observed in each group. PMID:27100174

  2. Risk Prediction Models for Other Cancers or Multiple Sites

    Cancer.gov

    Developing statistical models that estimate the probability of developing other multiple cancers over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  3. Toward risk reduction: predicting the future burden of occupational cancer.

    PubMed

    Hutchings, Sally; Rushton, Lesley

    2011-05-01

    Interventions to reduce cancers related to certain occupations should be evidence-based. The authors have developed a method for forecasting the future burden of occupational cancer to inform strategies for risk reduction. They project risk exposure periods, accounting for cancer latencies of up to 50 years, forward in time to estimate attributable fractions for a series of forecast target years given past and projected exposure trends and under targeted reduction scenarios. Adjustment factors for changes in exposed numbers and levels are applied in estimation intervals within the risk-exposure periods. The authors illustrate the methods by using a range of scenarios for reducing lung cancer due to occupational exposure to respirable crystalline silica. Attributable fractions for lung cancer due to respirable crystalline silica could be potentially reduced from 2.07% in 2010 to nearly 0% by 2060, depending on the timing and success of interventions. Focusing on achieving compliance with current exposure standards in small industries can be more effective than setting standards at a lower level. The method can be used to highlight high-risk carcinogens, industries, and occupations. It is adaptable for other countries and other exposure situations in the general environment and can be extended to include socioeconomic impact assessment. PMID:21447477

  4. Risk factors predictive of atrial fibrillation after lung cancer surgery.

    PubMed

    Iwata, Takekazu; Nagato, Kaoru; Nakajima, Takahiro; Suzuki, Hidemi; Yoshida, Shigetoshi; Yoshino, Ichiro

    2016-08-01

    Postoperative atrial fibrillation (POAF), the most frequent arrhythmia after pulmonary resection, is a cause of both morbidity and mortality. Being able to predict the risk of POAF before surgery would help us evaluate the surgical risk and plan prophylaxis. We investigated the reported preoperative risk factors associated with the incidence of POAF and found that the recommended predictive factors were quite variable. Therefore, we evaluated the previously reported preoperative risk factors for POAF using our institutional data. We discuss our findings in this short review. Male gender, resected lung volume, brain natriuretic peptide (BNP), and left ventricular early transmitral velocity/mitral annular early diastolic velocity (E/e') calculated by echocardiography were suggested as independent predictors for POAF, but the predictive values of each individual parameter were not high. The lack of definitive predictors for POAF warrants further investigations by gathering the reported knowledge, to establish an effective preoperative examination strategy. PMID:26471506

  5. Predictive performance of prostate cancer risk in Chinese men using 33 reported prostate cancer risk-associated SNPs

    PubMed Central

    Zheng, Jie; Liu, Fang; Lin, Xiaoling; Wang, Xiang; Ding, Qiang; Jiang, Haowen; Chen, Hongyan; Lu, Daru; Jin, Guangfu; Hsing, Ann W.; Shao, Qiang; Qi, Jun; Ye, Yu; Wang, Zhong; Gao, Xin; Wang, Guozeng; Chu, Lisa W.; OuYang, Jun; Huang, Yichen; Chen, Yanbo; Gao, Yutang; Shi, Rong; Wu, Qijun; Wang, Meilin; Zhang, Zhengdong; Hu, Yanlin; Sun, Jielin; Zheng, S. Lilly; Gao, Xu; Xu, Chuanliang; Mo, Zengnan; Sun, Yinghao; Xu, Jianfeng

    2011-01-01

    Background Genome-wide association studies (GWAS) have identified more than 30 single nucleotide polymorphisms (SNPs) that were reproducibly associated with prostate cancer (PCa) risk in populations of European descent. In aggregate, these variants have shown potential to predict risk for PCa in European men. However, their utility for PCa risk prediction in Chinese men is unknown. Methods We selected 33 PCa risk-related SNPs that were originally identified in populations of European descent. Genetic scores were estimated for subjects in a Chinese case-control study (1,108 cases and 1,525 controls) based on these SNPs. To assess the performance of the genetic score on its ability to predict risk for PCa, we calculated Area under the curve (AUC) of the receiver operating characteristic (ROC) in combination with 10-fold cross-validation. Results The genetic score was significantly higher for cases than controls (P = 5.91×10-20), and was significantly associated with risk of PCa in a dose-dependent manner (P for trend: 4.78×10-18). The AUC of the genetic score was 0.604 for risk prediction of PCa in Chinese men. When ORs derived from this Chinese study population were used to calculate genetic score, the AUCs were 0.631 for all 33 SNPs and 0.617 when using only the 11 significant SNPs. Conclusion Our results indicate that genetic variants related to PCa risk may be useful for risk prediction in Chinese men. Prospective studies are warranted to further evaluate these findings. PMID:21796652

  6. Prediction of near-term breast cancer risk using a Bayesian belief network

    NASA Astrophysics Data System (ADS)

    Zheng, Bin; Ramalingam, Pandiyarajan; Hariharan, Harishwaran; Leader, Joseph K.; Gur, David

    2013-03-01

    Accurately predicting near-term breast cancer risk is an important prerequisite for establishing an optimal personalized breast cancer screening paradigm. In previous studies, we investigated and tested the feasibility of developing a unique near-term breast cancer risk prediction model based on a new risk factor associated with bilateral mammographic density asymmetry between the left and right breasts of a woman using a single feature. In this study we developed a multi-feature based Bayesian belief network (BBN) that combines bilateral mammographic density asymmetry with three other popular risk factors, namely (1) age, (2) family history, and (3) average breast density, to further increase the discriminatory power of our cancer risk model. A dataset involving "prior" negative mammography examinations of 348 women was used in the study. Among these women, 174 had breast cancer detected and verified in the next sequential screening examinations, and 174 remained negative (cancer-free). A BBN was applied to predict the risk of each woman having cancer detected six to 18 months later following the negative screening mammography. The prediction results were compared with those using single features. The prediction accuracy was significantly increased when using the BBN. The area under the ROC curve increased from an AUC=0.70 to 0.84 (p<0.01), while the positive predictive value (PPV) and negative predictive value (NPV) also increased from a PPV=0.61 to 0.78 and an NPV=0.65 to 0.75, respectively. This study demonstrates that a multi-feature based BBN can more accurately predict the near-term breast cancer risk than with a single feature.

  7. Assessment of uncertainties in radiation-induced cancer risk predictions at clinically relevant doses

    SciTech Connect

    Nguyen, J.; Moteabbed, M.; Paganetti, H.

    2015-01-15

    Purpose: Theoretical dose–response models offer the possibility to assess second cancer induction risks after external beam therapy. The parameters used in these models are determined with limited data from epidemiological studies. Risk estimations are thus associated with considerable uncertainties. This study aims at illustrating uncertainties when predicting the risk for organ-specific second cancers in the primary radiation field illustrated by choosing selected treatment plans for brain cancer patients. Methods: A widely used risk model was considered in this study. The uncertainties of the model parameters were estimated with reported data of second cancer incidences for various organs. Standard error propagation was then subsequently applied to assess the uncertainty in the risk model. Next, second cancer risks of five pediatric patients treated for cancer in the head and neck regions were calculated. For each case, treatment plans for proton and photon therapy were designed to estimate the uncertainties (a) in the lifetime attributable risk (LAR) for a given treatment modality and (b) when comparing risks of two different treatment modalities. Results: Uncertainties in excess of 100% of the risk were found for almost all organs considered. When applied to treatment plans, the calculated LAR values have uncertainties of the same magnitude. A comparison between cancer risks of different treatment modalities, however, does allow statistically significant conclusions. In the studied cases, the patient averaged LAR ratio of proton and photon treatments was 0.35, 0.56, and 0.59 for brain carcinoma, brain sarcoma, and bone sarcoma, respectively. Their corresponding uncertainties were estimated to be potentially below 5%, depending on uncertainties in dosimetry. Conclusions: The uncertainty in the dose–response curve in cancer risk models makes it currently impractical to predict the risk for an individual external beam treatment. On the other hand, the ratio

  8. Assessment of uncertainties in radiation-induced cancer risk predictions at clinically relevant doses

    PubMed Central

    Nguyen, J.; Moteabbed, M.; Paganetti, H.

    2015-01-01

    Purpose: Theoretical dose–response models offer the possibility to assess second cancer induction risks after external beam therapy. The parameters used in these models are determined with limited data from epidemiological studies. Risk estimations are thus associated with considerable uncertainties. This study aims at illustrating uncertainties when predicting the risk for organ-specific second cancers in the primary radiation field illustrated by choosing selected treatment plans for brain cancer patients. Methods: A widely used risk model was considered in this study. The uncertainties of the model parameters were estimated with reported data of second cancer incidences for various organs. Standard error propagation was then subsequently applied to assess the uncertainty in the risk model. Next, second cancer risks of five pediatric patients treated for cancer in the head and neck regions were calculated. For each case, treatment plans for proton and photon therapy were designed to estimate the uncertainties (a) in the lifetime attributable risk (LAR) for a given treatment modality and (b) when comparing risks of two different treatment modalities. Results: Uncertainties in excess of 100% of the risk were found for almost all organs considered. When applied to treatment plans, the calculated LAR values have uncertainties of the same magnitude. A comparison between cancer risks of different treatment modalities, however, does allow statistically significant conclusions. In the studied cases, the patient averaged LAR ratio of proton and photon treatments was 0.35, 0.56, and 0.59 for brain carcinoma, brain sarcoma, and bone sarcoma, respectively. Their corresponding uncertainties were estimated to be potentially below 5%, depending on uncertainties in dosimetry. Conclusions: The uncertainty in the dose–response curve in cancer risk models makes it currently impractical to predict the risk for an individual external beam treatment. On the other hand, the ratio

  9. An epidemiologic risk prediction model for ovarian cancer in Europe: the EPIC study

    PubMed Central

    Li, K; Hüsing, A; Fortner, R T; Tjønneland, A; Hansen, L; Dossus, L; Chang-Claude, J; Bergmann, M; Steffen, A; Bamia, C; Trichopoulos, D; Trichopoulou, A; Palli, D; Mattiello, A; Agnoli, C; Tumino, R; Onland-Moret, N C; Peeters, P H; Bueno-de-Mesquita, H B(as); Gram, I T; Weiderpass, E; Sánchez-Cantalejo, E; Chirlaque, M-D; Duell, E J; Ardanaz, E; Idahl, A; Lundin, E; Khaw, K-T; Travis, R C; Merritt, M A; Gunter, M J; Riboli, E; Ferrari, P; Terry, K; Cramer, D; Kaaks, R

    2015-01-01

    Background: Ovarian cancer has a high case-fatality ratio, largely due to late diagnosis. Epidemiologic risk prediction models could help identify women at increased risk who may benefit from targeted prevention measures, such as screening or chemopreventive agents. Methods: We built an ovarian cancer risk prediction model with epidemiologic risk factors from 202 206 women in the European Prospective Investigation into Cancer and Nutrition study. Results: Older age at menopause, longer duration of hormone replacement therapy, and higher body mass index were included as increasing ovarian cancer risk, whereas unilateral ovariectomy, longer duration of oral contraceptive use, and higher number of full-term pregnancies were decreasing risk. The discriminatory power (overall concordance index) of this model, as examined with five-fold cross-validation, was 0.64 (95% confidence interval (CI): 0.57, 0.70). The ratio of the expected to observed number of ovarian cancer cases occurring in the first 5 years of follow-up was 0.90 (293 out of 324, 95% CI: 0.81–1.01), in general there was no evidence for miscalibration. Conclusion: Our ovarian cancer risk model containing only epidemiological data showed modest discriminatory power for a Western European population. Future studies should consider adding informative biomarkers to possibly improve the predictive ability of the model. PMID:25742479

  10. Determining the main risk factors and high-risk groups of breast cancer using a predictive model for breast cancer risk assessment in South Korea.

    PubMed

    Lee, Eun-Ok; Ahn, Sei-Hyun; You, Chunghee; Lee, Dong-Suk; Han, Wonshik; Choe, Kuk-Jin; Noh, Dong-Young

    2004-01-01

    This study was aimed at developing a predictive model for assessing the breast cancer risk of Korean women under the assumption of differences in the risk factors between Westerners and Koreans. The cohort comprised 384 breast cancer patients and 2 control groups: one comprising 166 hospitalized patients and the other comprising 104 nurses and teachers. Two initial models were produced by comparing cases and the 2 control groups, and the final equations were established by selecting highly significant variables of the initial models to test the accuracy of the models in terms of disease probability and predictability. Both the initial models and the final disease-probability models were confirmed to exhibit high degrees of accuracy and predictability. Major risk factors determined by comparing the patients with hospitalized controls were a family history, menstrual regularity, total menstrual duration, age at first full-term pregnancy, and duration of breastfeeding. Major risk factors determined by comparing patients with nurse/teacher controls were age, education level, menstrual regularity, drinking status, and smoking status. The predictive model developed here shows that risk factors for breast cancer differ between Korean and Western subjects in the aspect of breastfeeding behavior. However, identifying the relationship between genetic susceptibility and breast cancer will require further studies with larger samples. In a model with nurse/teacher controls, drinking and higher education were found to be protective variables, whereas smoking was a risk factor. Hence the predictive model in this group could not be generalized to the Korean population; instead, breast cancer incidence needs to be compared among nurses and teachers in a nurse-and-teacher cohort. PMID:15525868

  11. Prediction of Potential Cancer-Risk Regions Based on Transcriptome Data: Towards a Comprehensive View

    PubMed Central

    Alisoltani, Arghavan; Fallahi, Hossein; Ebrahimi, Mahdi; Ebrahimi, Mansour; Ebrahimie, Esmaeil

    2014-01-01

    A novel integrative pipeline is presented for discovery of potential cancer-susceptibility regions (PCSRs) by calculating the number of altered genes at each chromosomal region, using expression microarray datasets of different human cancers (HCs). Our novel approach comprises primarily predicting PCSRs followed by identification of key genes in these regions to obtain potential regions harboring new cancer-associated variants. In addition to finding new cancer causal variants, another advantage in prediction of such risk regions is simultaneous study of different types of genomic variants in line with focusing on specific chromosomal regions. Using this pipeline we extracted numbers of regions with highly altered expression levels in cancer condition. Regulatory networks were also constructed for different types of cancers following the identification of altered mRNA and microRNAs. Interestingly, results showed that GAPDH, LIFR, ZEB2, mir-21, mir-30a, mir-141 and mir-200c, all located at PCSRs, are common altered factors in constructed networks. We found a number of clusters of altered mRNAs and miRNAs on predicted PCSRs (e.g.12p13.31) and their common regulators including KLF4 and SOX10. Large scale prediction of risk regions based on transcriptome data can open a window in comprehensive study of cancer risk factors and the other human diseases. PMID:24796549

  12. Relationship of Predicted Risk of Developing Invasive Breast Cancer, as Assessed with Three Models, and Breast Cancer Mortality among Breast Cancer Patients

    PubMed Central

    Pfeiffer, Ruth M.; Miglioretti, Diana L.; Kerlikowske, Karla; Tice, Jeffery; Vacek, Pamela M.; Gierach, Gretchen L.

    2016-01-01

    Purpose Breast cancer risk prediction models are used to plan clinical trials and counsel women; however, relationships of predicted risks of breast cancer incidence and prognosis after breast cancer diagnosis are unknown. Methods Using largely pre-diagnostic information from the Breast Cancer Surveillance Consortium (BCSC) for 37,939 invasive breast cancers (1996–2007), we estimated 5-year breast cancer risk (<1%; 1–1.66%; ≥1.67%) with three models: BCSC 1-year risk model (BCSC-1; adapted to 5-year predictions); Breast Cancer Risk Assessment Tool (BCRAT); and BCSC 5-year risk model (BCSC-5). Breast cancer-specific mortality post-diagnosis (range: 1–13 years; median: 5.4–5.6 years) was related to predicted risk of developing breast cancer using unadjusted Cox proportional hazards models, and in age-stratified (35–44; 45–54; 55–69; 70–89 years) models adjusted for continuous age, BCSC registry, calendar period, income, mode of presentation, stage and treatment. Mean age at diagnosis was 60 years. Results Of 6,021 deaths, 2,993 (49.7%) were ascribed to breast cancer. In unadjusted case-only analyses, predicted breast cancer risk ≥1.67% versus <1.0% was associated with lower risk of breast cancer death; BCSC-1: hazard ratio (HR) = 0.82 (95% CI = 0.75–0.90); BCRAT: HR = 0.72 (95% CI = 0.65–0.81) and BCSC-5: HR = 0.84 (95% CI = 0.75–0.94). Age-stratified, adjusted models showed similar, although mostly non-significant HRs. Among women ages 55–69 years, HRs approximated 1.0. Generally, higher predicted risk was inversely related to percentages of cancers with unfavorable prognostic characteristics, especially among women 35–44 years. Conclusions Among cases assessed with three models, higher predicted risk of developing breast cancer was not associated with greater risk of breast cancer death; thus, these models would have limited utility in planning studies to evaluate breast cancer mortality reduction strategies. Further, when offering

  13. A utility/cost analysis of breast cancer risk prediction algorithms

    NASA Astrophysics Data System (ADS)

    Abbey, Craig K.; Wu, Yirong; Burnside, Elizabeth S.; Wunderlich, Adam; Samuelson, Frank W.; Boone, John M.

    2016-03-01

    Breast cancer risk prediction algorithms are used to identify subpopulations that are at increased risk for developing breast cancer. They can be based on many different sources of data such as demographics, relatives with cancer, gene expression, and various phenotypic features such as breast density. Women who are identified as high risk may undergo a more extensive (and expensive) screening process that includes MRI or ultrasound imaging in addition to the standard full-field digital mammography (FFDM) exam. Given that there are many ways that risk prediction may be accomplished, it is of interest to evaluate them in terms of expected cost, which includes the costs of diagnostic outcomes. In this work we perform an expected-cost analysis of risk prediction algorithms that is based on a published model that includes the costs associated with diagnostic outcomes (true-positive, false-positive, etc.). We assume the existence of a standard screening method and an enhanced screening method with higher scan cost, higher sensitivity, and lower specificity. We then assess expected cost of using a risk prediction algorithm to determine who gets the enhanced screening method under the strong assumption that risk and diagnostic performance are independent. We find that if risk prediction leads to a high enough positive predictive value, it will be cost-effective regardless of the size of the subpopulation. Furthermore, in terms of the hit-rate and false-alarm rate of the of the risk prediction algorithm, iso-cost contours are lines with slope determined by properties of the available diagnostic systems for screening.

  14. A Utility/Cost Analysis of Breast Cancer Risk Prediction Algorithms

    PubMed Central

    Abbey, Craig K.; Wu, Yirong; Burnside, Elizabeth S.; Wunderlich, Adam; Samuelson, Frank W.; Boone, John M.

    2016-01-01

    Breast cancer risk prediction algorithms are used to identify subpopulations that are at increased risk for developing breast cancer. They can be based on many different sources of data such as demographics, relatives with cancer, gene expression, and various phenotypic features such as breast density. Women who are identified as high risk may undergo a more extensive (and expensive) screening process that includes MRI or ultrasound imaging in addition to the standard full-field digital mammography (FFDM) exam. Given that there are many ways that risk prediction may be accomplished, it is of interest to evaluate them in terms of expected cost, which includes the costs of diagnostic outcomes. In this work we perform an expected-cost analysis of risk prediction algorithms that is based on a published model that includes the costs associated with diagnostic outcomes (true-positive, false-positive, etc.). We assume the existence of a standard screening method and an enhanced screening method with higher scan cost, higher sensitivity, and lower specificity. We then assess expected cost of using a risk prediction algorithm to determine who gets the enhanced screening method under the strong assumption that risk and diagnostic performance are independent. We find that if risk prediction leads to a high enough positive predictive value, it will be cost-effective regardless of the size of the subpopulation. Furthermore, in terms of the hit-rate and false-alarm rate of the of the risk-prediction algorithm, iso-cost contours are lines with slope determined by properties of the available diagnostic systems for screening. PMID:27335532

  15. Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures.

    PubMed

    Stone, Jennifer; Thompson, Deborah J; Dos Santos Silva, Isabel; Scott, Christopher; Tamimi, Rulla M; Lindstrom, Sara; Kraft, Peter; Hazra, Aditi; Li, Jingmei; Eriksson, Louise; Czene, Kamila; Hall, Per; Jensen, Matt; Cunningham, Julie; Olson, Janet E; Purrington, Kristen; Couch, Fergus J; Brown, Judith; Leyland, Jean; Warren, Ruth M L; Luben, Robert N; Khaw, Kay-Tee; Smith, Paula; Wareham, Nicholas J; Jud, Sebastian M; Heusinger, Katharina; Beckmann, Matthias W; Douglas, Julie A; Shah, Kaanan P; Chan, Heang-Ping; Helvie, Mark A; Le Marchand, Loic; Kolonel, Laurence N; Woolcott, Christy; Maskarinec, Gertraud; Haiman, Christopher; Giles, Graham G; Baglietto, Laura; Krishnan, Kavitha; Southey, Melissa C; Apicella, Carmel; Andrulis, Irene L; Knight, Julia A; Ursin, Giske; Alnaes, Grethe I Grenaker; Kristensen, Vessela N; Borresen-Dale, Anne-Lise; Gram, Inger Torhild; Bolla, Manjeet K; Wang, Qin; Michailidou, Kyriaki; Dennis, Joe; Simard, Jacques; Pharoah, Paul; Dunning, Alison M; Easton, Douglas F; Fasching, Peter A; Pankratz, V Shane; Hopper, John L; Vachon, Celine M

    2015-06-15

    Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk. PMID:25862352

  16. An epidemiological model for prediction of endometrial cancer risk in Europe.

    PubMed

    Hüsing, Anika; Dossus, Laure; Ferrari, Pietro; Tjønneland, Anne; Hansen, Louise; Fagherazzi, Guy; Baglietto, Laura; Schock, Helena; Chang-Claude, Jenny; Boeing, Heiner; Steffen, Annika; Trichopoulou, Antonia; Bamia, Christina; Katsoulis, Michalis; Krogh, Vittorio; Palli, Domenico; Panico, Salvatore; Onland-Moret, N Charlotte; Peeters, Petra H; Bueno-de-Mesquita, H Bas; Weiderpass, Elisabete; Gram, Inger T; Ardanaz, Eva; Obón-Santacana, Mireia; Navarro, Carmen; Sánchez-Cantalejo, Emilio; Etxezarreta, Nerea; Allen, Naomi E; Khaw, Kay Tee; Wareham, Nick; Rinaldi, Sabina; Romieu, Isabelle; Merritt, Melissa A; Gunter, Marc; Riboli, Elio; Kaaks, Rudolf

    2016-01-01

    Endometrial cancer (EC) is the fourth most frequent cancer in women in Europe, and as its incidence is increasing, prevention strategies gain further pertinence. Risk prediction models can be a useful tool for identifying women likely to benefit from targeted prevention measures. On the basis of data from 201,811 women (mostly aged 30-65 years) including 855 incident EC cases from eight countries in the European Prospective Investigation into Cancer and Nutrition cohort, a model to predict EC was developed. A step-wise model selection process was used to select confirmed predictive epidemiologic risk factors. Piece-wise constant hazard rates in 5-year age-intervals were estimated in a cause-specific competing risks model, five-fold-cross-validation was applied for internal validation. Risk factors included in the risk prediction model were body-mass index (BMI), menopausal status, age at menarche and at menopause, oral contraceptive use, overall and by different BMI categories and overall duration of use, parity, age at first full-term pregnancy, duration of menopausal hormone therapy and smoking status (specific for pre, peri- and post-menopausal women). These variables improved the discriminating capacity to predict risk over 5 years from 71% for a model based on age alone to 77% (overall C statistic), and the model was well-calibrated (ratio of expected to observed cases = 0.99). Our model could be used for the identification of women at increased risk of EC in Western Europe. To achieve an EC-risk model with general validity, a large-scale cohort-consortium approach would be needed to assess and adjust for population variation. PMID:25968175

  17. Risk factors assessment and risk prediction models in lung cancer screening candidates.

    PubMed

    Adamek, Mariusz; Wachuła, Ewa; Szabłowska-Siwik, Sylwia; Boratyn-Nowicka, Agnieszka; Czyżewski, Damian

    2016-04-01

    From February 2015, low-dose computed tomography (LDCT) screening entered the armamentarium of diagnostic tools broadly available to individuals at high-risk of developing lung cancer. While a huge number of pulmonary nodules are identified, only a small fraction turns out to be early lung cancers. The majority of them constitute a variety of benign lesions. Although it entails a burden of the diagnostic work-up, the undisputable benefit emerges from: (I) lung cancer diagnosis at earlier stages (stage shift); (II) additional findings enabling the implementation of a preventive action beyond the realm of thoracic oncology. This review presents how to utilize the risk factors from distinct categories such as epidemiology, radiology and biomarkers to target the fraction of population, which may benefit most from the introduced screening modality. PMID:27195269

  18. Risk factors assessment and risk prediction models in lung cancer screening candidates

    PubMed Central

    Wachuła, Ewa; Szabłowska-Siwik, Sylwia; Boratyn-Nowicka, Agnieszka; Czyżewski, Damian

    2016-01-01

    From February 2015, low-dose computed tomography (LDCT) screening entered the armamentarium of diagnostic tools broadly available to individuals at high-risk of developing lung cancer. While a huge number of pulmonary nodules are identified, only a small fraction turns out to be early lung cancers. The majority of them constitute a variety of benign lesions. Although it entails a burden of the diagnostic work-up, the undisputable benefit emerges from: (I) lung cancer diagnosis at earlier stages (stage shift); (II) additional findings enabling the implementation of a preventive action beyond the realm of thoracic oncology. This review presents how to utilize the risk factors from distinct categories such as epidemiology, radiology and biomarkers to target the fraction of population, which may benefit most from the introduced screening modality. PMID:27195269

  19. The utility and predictive value of combinations of low penetrance genes for screening and risk prediction of colorectal cancer

    PubMed Central

    Hawken, Steven J.; Greenwood, Celia M. T.; Hudson, Thomas J.; Kustra, Rafal; McLaughlin, John; Yang, Quanhe; Zanke, Brent W.

    2010-01-01

    Despite the fact that colorectal cancer (CRC) is a highly treatable form of cancer if detected early, a very low proportion of the eligible population undergoes screening for this form of cancer. Integrating a genomic screening profile as a component of existing screening programs for CRC could potentially improve the effectiveness of population screening by allowing the assignment of individuals to different types and intensities of screening and also by potentially increasing the uptake of existing screening programs. We evaluated the utility and predictive value of genomic profiling as applied to CRC, and as a potential component of a population-based cancer screening program. We generated simulated data representing a typical North American population including a variety of genetic profiles, with a range of relative risks and prevalences for individual risk genes. We then used these data to estimate parameters characterizing the predictive value of a logistic regression model built on genetic markers for CRC. Meta-analyses of genetic associations with CRC were used in building science to inform the simulation work, and to select genetic variants to include in logistic regression model-building using data from the ARCTIC study in Ontario, which included 1,200 CRC cases and a similar number of cancer-free population-based controls. Our simulations demonstrate that for reasonable assumptions involving modest relative risks for individual genetic variants, that substantial predictive power can be achieved when risk variants are common (e.g., prevalence > 20%) and data for enough risk variants are available (e.g., ~140–160). Pilot work in population data shows modest, but statistically significant predictive utility for a small collection of risk variants, smaller in effect than age and gender alone in predicting an individual’s CRC risk. Further genotyping and many more samples will be required, and indeed the discovery of many more risk loci associated with

  20. Risk Prediction for Prostate Cancer Recurrence Through Regularized Estimation with Simultaneous Adjustment for Nonlinear Clinical Effects*

    PubMed Central

    Long, Qi; Chung, Matthias; Moreno, Carlos S.; Johnson, Brent A.

    2011-01-01

    In biomedical studies, it is of substantial interest to develop risk prediction scores using high-dimensional data such as gene expression data for clinical endpoints that are subject to censoring. In the presence of well-established clinical risk factors, investigators often prefer a procedure that also adjusts for these clinical variables. While accelerated failure time (AFT) models are a useful tool for the analysis of censored outcome data, it assumes that covariate effects on the logarithm of time-to-event are linear, which is often unrealistic in practice. We propose to build risk prediction scores through regularized rank estimation in partly linear AFT models, where high-dimensional data such as gene expression data are modeled linearly and important clinical variables are modeled nonlinearly using penalized regression splines. We show through simulation studies that our model has better operating characteristics compared to several existing models. In particular, we show that there is a non-negligible effect on prediction as well as feature selection when nonlinear clinical effects are misspecified as linear. This work is motivated by a recent prostate cancer study, where investigators collected gene expression data along with established prognostic clinical variables and the primary endpoint is time to prostate cancer recurrence. We analyzed the prostate cancer data and evaluated prediction performance of several models based on the extended c statistic for censored data, showing that 1) the relationship between the clinical variable, prostate specific antigen, and the prostate cancer recurrence is likely nonlinear, i.e., the time to recurrence decreases as PSA increases and it starts to level off when PSA becomes greater than 11; 2) correct specification of this nonlinear effect improves performance in prediction and feature selection; and 3) addition of gene expression data does not seem to further improve the performance of the resultant risk

  1. Validation of a modified clinical risk score to predict cancer-specific survival for stage II colon cancer

    PubMed Central

    Oliphant, Raymond; Horgan, Paul G; Morrison, David S; McMillan, Donald C

    2015-01-01

    Many patients with stage II colon cancer will die of their disease despite curative surgery. Therefore, identification of patients at high risk of poor outcome after surgery for stage II colon cancer is desirable. This study aims to validate a clinical risk score to predict cancer-specific survival in patients undergoing surgery for stage II colon cancer. Patients undergoing surgery for stage II colon cancer in 16 hospitals in the West of Scotland between 2001 and 2004 were identified from a prospectively maintained regional clinical audit database. Overall and cancer-specific survival rates up to 5 years were calculated. A total of 871 patients were included. At 5 years, cancer-specific survival was 81.9% and overall survival was 65.6%. On multivariate analysis, age ≥75 years (hazard ratio (HR) 2.11, 95% confidence intervals (CI) 1.57–2.85; P<0.001) and emergency presentation (HR 1.97, 95% CI 1.43–2.70; P<0.001) were independently associated with cancer-specific survival. Age and mode of presentation HRs were added to form a clinical risk score of 0–2. The cancer-specific survival at 5 years for patients with a cumulative score 0 was 88.7%, 1 was 78.2% and 2 was 65.9%. These results validate a modified simple clinical risk score for patients undergoing surgery for stage II colon cancer. The combination of these two universally documented clinical factors provides a solid foundation for the examination of the impact of additional clinicopathological and treatment factors on overall and cancer-specific survival. PMID:25487740

  2. Predicting Prostate Cancer Mortality Among Men With Intermediate to High-Risk Disease and Multiple Unfavorable Risk Factors

    SciTech Connect

    Nguyen, Paul L. Chen Minghui; Catalona, William J.; Moul, Judd W.; Sun, Leon; D'Amico, Anthony V.

    2009-03-01

    Purpose: To determine whether the number of unfavorable risk factors could be used to predict the risk of prostate cancer-specific mortality (PCSM) among men with intermediate- to high-risk prostate cancer. Methods and Materials: We studied 1,063 men who underwent radical prostatectomy (n = 559), external beam radiotherapy (n = 288), or radiotherapy plus androgen suppression therapy (n = 116) for prostate cancer between 1965 and 2002. Fine and Gray's regression analysis was used to determine whether an increasing number of unfavorable risk factors (prostate-specific antigen level >10 ng/mL, Gleason score of {>=}7, clinical Stage T2b or greater, or pretreatment prostate-specific antigen velocity >2.0 ng/mL/y) was associated with the interval to PCSM and all-cause mortality. Results: Median follow-up was 5.6 years. Compared with those with one risk factor, the adjusted hazard ratio for PCSM was 2.3 (95% confidence interval 1.1-4.8; p = 0.03) for two risk factors, 5.4 (95% confidence interval 2.7-10.7; p < 0.0001) for three risk factors, and 13.6 (95% confidence interval 6.3-29.2; p < 0.0001) for all four risk factors. The 5-year cumulative incidence of PCSM was 2.4% for one factor, 2.4% for two factors, 7.0% for three factors, and 14.7% for all four factors. Prostate cancer deaths as a proportion of all deaths was 19% for one factor, 33% for two factors, 53% for three factors, and 80% for four factors. Conclusion: The number of unfavorable risk factors was significantly associated with PCSM. Prostate cancer was the major cause of death in men with at least three risk factors. Therefore, these men should be considered for clinical trials designed to assess whether survival is prolonged with the addition of novel agents to current standards of practice.

  3. Assessment of two mammographic density related features in predicting near-term breast cancer risk

    NASA Astrophysics Data System (ADS)

    Zheng, Bin; Sumkin, Jules H.; Zuley, Margarita L.; Wang, Xingwei; Klym, Amy H.; Gur, David

    2012-02-01

    In order to establish a personalized breast cancer screening program, it is important to develop risk models that have high discriminatory power in predicting the likelihood of a woman developing an imaging detectable breast cancer in near-term (e.g., <3 years after a negative examination in question). In epidemiology-based breast cancer risk models, mammographic density is considered the second highest breast cancer risk factor (second to woman's age). In this study we explored a new feature, namely bilateral mammographic density asymmetry, and investigated the feasibility of predicting near-term screening outcome. The database consisted of 343 negative examinations, of which 187 depicted cancers that were detected during the subsequent screening examination and 155 that remained negative. We computed the average pixel value of the segmented breast areas depicted on each cranio-caudal view of the initial negative examinations. We then computed the mean and difference mammographic density for paired bilateral images. Using woman's age, subjectively rated density (BIRADS), and computed mammographic density related features we compared classification performance in estimating the likelihood of detecting cancer during the subsequent examination using areas under the ROC curves (AUC). The AUCs were 0.63+/-0.03, 0.54+/-0.04, 0.57+/-0.03, 0.68+/-0.03 when using woman's age, BIRADS rating, computed mean density and difference in computed bilateral mammographic density, respectively. Performance increased to 0.62+/-0.03 and 0.72+/-0.03 when we fused mean and difference in density with woman's age. The results suggest that, in this study, bilateral mammographic tissue density is a significantly stronger (p<0.01) risk indicator than both woman's age and mean breast density.

  4. SNPs and breast cancer risk prediction for African American and Hispanic women.

    PubMed

    Allman, Richard; Dite, Gillian S; Hopper, John L; Gordon, Ora; Starlard-Davenport, Athena; Chlebowski, Rowan; Kooperberg, Charles

    2015-12-01

    For African American or Hispanic women, the extent to which clinical breast cancer risk prediction models are improved by including information on susceptibility single nucleotide polymorphisms (SNPs) is unknown, even though these women comprise increasing proportions of the US population and represent a large proportion of the world's population. We studied 7539 African American and 3363 Hispanic women from the Women's Health Initiative. The age-adjusted 5-year risks from the BCRAT and IBIS risk prediction models were measured and combined with a risk score based on >70 independent susceptibility SNPs. Logistic regression, adjusting for age group, was used to estimate risk associations with log-transformed age-adjusted 5-year risks. Discrimination was measured by the odds ratio (OR) per standard deviation (SD) and the area under the receiver operator curve (AUC). When considered alone, the ORs for African American women were 1.28 for BCRAT, and 1.04 for IBIS. When combined with the SNP risk score (OR 1.23), the corresponding ORs were 1.39 and 1.22. For Hispanic women the corresponding ORs were 1.25 for BCRAT, and 1.15 for IBIS. When combined with the SNP risk score (OR 1.39), the corresponding ORs were 1.48 and 1.42. There was no evidence that any of the combined models were not well calibrated. Including information on known breast cancer susceptibility loci provides approximately 10 and 19% improvement in risk prediction using BCRAT for African Americans and Hispanics, respectively. The corresponding figures for IBIS are approximately 18 and 26%, respectively. PMID:26589314

  5. Prediction of near-term risk of developing breast cancer using computerized features from bilateral mammograms.

    PubMed

    Sun, Wenqing; Zheng, Bin; Lure, Fleming; Wu, Teresa; Zhang, Jianying; Wang, Benjamin Y; Saltzstein, Edward C; Qian, Wei

    2014-07-01

    Asymmetry of bilateral mammographic tissue density and patterns is a potentially strong indicator of having or developing breast abnormalities or early cancers. The purpose of this study is to design and test the global asymmetry features from bilateral mammograms to predict the near-term risk of women developing detectable high risk breast lesions or cancer in the next sequential screening mammography examination. The image dataset includes mammograms acquired from 90 women who underwent routine screening examinations, all interpreted as negative and not recalled by the radiologists during the original screening procedures. A computerized breast cancer risk analysis scheme using four image processing modules, including image preprocessing, suspicious region segmentation, image feature extraction, and classification was designed to detect and compute image feature asymmetry between the left and right breasts imaged on the mammograms. The highest computed area under curve (AUC) is 0.754±0.024 when applying the new computerized aided diagnosis (CAD) scheme to our testing dataset. The positive predictive value and the negative predictive value were 0.58 and 0.80, respectively. PMID:24725671

  6. Nottingham prognostic index plus (NPI+) predicts risk of distant metastases in primary breast cancer.

    PubMed

    Green, Andrew R; Soria, D; Powe, D G; Nolan, C C; Aleskandarany, M; Szász, M A; Tőkés, A M; Ball, G R; Garibaldi, J M; Rakha, E A; Kulka, J; Ellis, I O

    2016-05-01

    The Nottingham prognostic index plus (NPI+) is based on the assessment of biological class combined with established clinicopathologic prognostic variables providing improved patient outcome stratification for breast cancer superior to the traditional NPI. This study aimed to determine prognostic capability of the NPI+ in predicting risk of development of distant disease. A well-characterised series of 1073 primary early-stage BC cases treated in Nottingham and 251 cases from Budapest were immunohistochemically assessed for cytokeratin (Ck)5/6, Ck18, EGFR, oestrogen receptor (ER), progesterone receptor, HER2, HER3, HER4, Mucin 1 and p53 expression. NPI+ biological class and prognostic scores were assigned using individual algorithms for each biological class incorporating clinicopathologic parameters and investigated in terms of prediction of distant metastases-free survival (MFS). The NPI+ identified distinct prognostic groups (PG) within each molecular class which were predictive of MFS providing improved patient outcome stratification superior to the traditional NPI. NPI+ PGs, between series, were comparable in predicting patient outcome between series in luminal A, basal p53 altered and HER2+/ER+ (p > 0.01) tumours. The low-risk groups were similarly validated in luminal B, luminal N, basal p53 normal tumours (p > 0.01). Due to small patient numbers the remaining PGs could not be validated. NPI+ was additionally able to predict a higher risk of metastases at certain distant sites. This study may indicate the NPI+ as a useful tool in predicting the risk of metastases. The NPI+ provides accurate risk stratification allowing improved individualised clinical decision making for breast cancer. PMID:27116185

  7. Estrogen Metabolism and Exposure in a Genotypic-Phenotypic Model for Breast Cancer Risk Prediction

    PubMed Central

    Crooke, Philip S.; Justenhoven, Christina; Brauch, Hiltrud; Dawling, Sheila; Roodi, Nady; Higginbotham, Kathryn S. P.; Plummer, W. Dale; Schuyler, Peggy A.; Sanders, Melinda E; Page, David L.; Smith, Jeffrey R.; Dupont, William D.; Parl, Fritz F.

    2012-01-01

    Background Current models of breast cancer risk prediction do not directly reflect mammary estrogen metabolism or genetic variability in exposure to carcinogenic estrogen metabolites. Methods We developed a model that simulates the kinetic effect of genetic variants of the enzymes CYP1A1, CYP1B1, and COMT on the production of the main carcinogenic estrogen metabolite, 4-hydroxyestradiol (4-OHE2), expressed as area under the curve metric (4-OHE2-AUC). The model also incorporates phenotypic factors (age, body mass index, hormone replacement therapy, oral contraceptives, family history), which plausibly influence estrogen metabolism and the production of 4-OHE2. We applied the model to two independent, population-based breast cancer case-control groups, the German GENICA study (967 cases, 971 controls) and the Nashville Breast Cohort (NBC; 465 cases, 885 controls). Results In the GENICA study, premenopausal women at the 90th percentile of 4-OHE2-AUC among control subjects had a risk of breast cancer that was 2.30 times that of women at the 10th control 4-OHE2-AUC percentile (95% CI 1.7 – 3.2, P = 2.9 × 10−7). This relative risk was 1.89 (95% CI 1.5 – 2.4, P = 2.2 × 10−8) in postmenopausal women. In the NBC, this relative risk in postmenopausal women was 1.81 (95% CI 1.3 – 2.6, P = 7.6 × 10−4), which increased to 1.83 (95% CI 1.4 – 2.3, P = 9.5 × 10−7) when a history of proliferative breast disease was included in the model. Conclusions The model combines genotypic and phenotypic factors involved in carcinogenic estrogen metabolite production and cumulative estrogen exposure to predict breast cancer risk. Impact The estrogen carcinogenesis-based model has the potential to provide personalized risk estimates. PMID:21610218

  8. Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures

    PubMed Central

    Stone, Jennifer; Thompson, Deborah J.; dos-Santos-Silva, Isabel; Scott, Christopher; Tamimi, Rulla M.; Lindstrom, Sara; Kraft, Peter; Hazra, Aditi; Li, Jingmei; Eriksson, Louise; Czene, Kamila; Hall, Per; Jensen, Matt; Cunningham, Julie; Olson, Janet E.; Purrington, Kristen; Couch, Fergus J.; Brown, Judith; Leyland, Jean; Warren, Ruth M. L.; Luben, Robert N.; Khaw, Kay-Tee; Smith, Paula; Wareham, Nicholas J.; Jud, Sebastian M.; Heusinger, Katharina; Beckmann, Matthias W.; Douglas, Julie A.; Shah, Kaanan P.; Chan, Heang-Ping; Helvie, Mark A.; Le Marchand, Loic; Kolonel, Laurence N.; Woolcott, Christy; Maskarinec, Gertraud; Haiman, Christopher; Giles, Graham G.; Baglietto, Laura; Krishnan, Kavitha; Southey, Melissa C.; Apicella, Carmel; Andrulis, Irene L.; Knight, Julia A.; Ursin, Giske; Grenaker Alnaes, Grethe I.; Kristensen, Vessela N.; Borresen-Dale, Anne-Lise; Gram, Inger Torhild; Bolla, Manjeet K.; Wang, Qin; Michailidou, Kyriaki; Dennis, Joe; Simard, Jacques; Paroah, Paul; Dunning, Alison M.; Easton, Douglas F.; Fasching, Peter A.; Pankratz, V. Shane; Hopper, John; Vachon, Celine M.

    2015-01-01

    Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute non-dense area adjusted for study, age and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1) and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all p <10−5). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and non-dense areas, and between rs17356907 (NTN4) and adjusted absolute non-dense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiological pathways implicated in how mammographic density predicts breast cancer risk. PMID:25862352

  9. Risk factors predictive of occult cancer detection in patients with unprovoked venous thromboembolism

    PubMed Central

    Ihaddadene, Ryma; Corsi, Daniel J.; Lazo-Langner, Alejandro; Shivakumar, Sudeep; Zarychanski, Ryan; Tagalakis, Vicky; Solymoss, Susan; Routhier, Nathalie; Douketis, James; Le Gal, Gregoire

    2016-01-01

    Risk factors predictive of occult cancer detection in patients with a first unprovoked symptomatic venous thromboembolism (VTE) are unknown. Cox proportional hazard models and multivariate analyses were performed to assess the effect of specific risk factors on occult cancer detection within 1 year of a diagnosis of unprovoked VTE in patients randomized in the Screening for Occult Malignancy in Patients with Idiopathic Venous Thromboembolism (SOME) trial. A total of 33 (3.9%; 95% CI, 2.8%-5.4%) out of the 854 included patients received a new diagnosis of cancer at 1-year follow-up. Age ≥ 60 years (hazard ratio [HR], 3.11; 95% CI, 1.41-6.89; P = .005), previous provoked VTE (HR, 3.20; 95% CI, 1.19-8.62; P = .022), and current smoker status (HR, 2.80; 95% CI, 1.24-6.33; P = .014) were associated with occult cancer detection. Age, prior provoked VTE, and smoking status may be important predictors of occult cancer detection in patients with first unprovoked VTE. This trial was registered at www.clinicaltrials.gov as #NCT00773448. PMID:26817957

  10. Risk factors predictive of occult cancer detection in patients with unprovoked venous thromboembolism.

    PubMed

    Ihaddadene, Ryma; Corsi, Daniel J; Lazo-Langner, Alejandro; Shivakumar, Sudeep; Zarychanski, Ryan; Tagalakis, Vicky; Solymoss, Susan; Routhier, Nathalie; Douketis, James; Le Gal, Gregoire; Carrier, Marc

    2016-04-21

    Risk factors predictive of occult cancer detection in patients with a first unprovoked symptomatic venous thromboembolism (VTE) are unknown. Cox proportional hazard models and multivariate analyses were performed to assess the effect of specific risk factors on occult cancer detection within 1 year of a diagnosis of unprovoked VTE in patients randomized in the Screening for Occult Malignancy in Patients with Idiopathic Venous Thromboembolism (SOME) trial. A total of 33 (3.9%; 95% CI, 2.8%-5.4%) out of the 854 included patients received a new diagnosis of cancer at 1-year follow-up. Age ≥ 60 years (hazard ratio [HR], 3.11; 95% CI, 1.41-6.89; ITALIC! P= .005), previous provoked VTE (HR, 3.20; 95% CI, 1.19-8.62; ITALIC! P= .022), and current smoker status (HR, 2.80; 95% CI, 1.24-6.33; ITALIC! P= .014) were associated with occult cancer detection. Age, prior provoked VTE, and smoking status may be important predictors of occult cancer detection in patients with first unprovoked VTE. This trial was registered atwww.clinicaltrials.govas #NCT00773448. PMID:26817957

  11. Using SNP genotypes to improve the discrimination of a simple breast cancer risk prediction model

    PubMed Central

    Dite, Gillian S; Mahmoodi, Maryam; Bickerstaffe, Adrian; Hammet, Fleur; Macinnis, Robert J; Tsimiklis, Helen; Dowty, James G; Apicella, Carmel; Phillips, Kelly-Anne; Giles, Graham G; Southey, Melissa C; Hopper, John L

    2014-01-01

    It has been shown that, for women aged 50 years or older, the discriminatory accuracy of the Breast Cancer Risk Prediction Tool (BCRAT) can be modestly improved by the inclusion of information on common single nucleotide polymorphisms (SNPs) that are associated with increased breast cancer risk. We aimed to determine whether a similar improvement is seen for earlier onset disease. We used the Australian Breast Cancer Family Registry to study a population-based sample of 962 cases aged 35 to 59 years and 463 controls frequency matched for age and for whom genotyping data was available. Overall, the inclusion of data on seven SNPs improved the area under the receiver operating characteristic curve (AUC) from 0.58 (95% confidence interval [CI]=0.55–0.61) for BCRAT alone to 0.61 (95% CI=0.58–0.64) for BCRAT and SNP data combined (p<0.001). For women aged 35 to 39 years at interview, the corresponding improvement in AUC was from 0.61 (95% CI=0.56–0.66) to 0.65 (95% CI=0.60–0.70; p=0.03), while for women aged 40 to 49 years at diagnosis, the AUC improved from 0.61 (95% CI=0.55–0.66) to 0.63 (95% CI=0.57–0.69; p=0.04). Using previously used classifications of low, intermediate and high risk, 2.1% of cases and none of the controls aged 35 to 39 years, and 10.9% of cases and 4.0% of controls aged 40 to 49 years were classified into a higher risk group. Including information on seven SNPs associated with breast cancer risk improves the discriminatory accuracy of BCRAT for women aged 35 to 39 years and 40 to 49 years. Given the low absolute risk for women in these age groups, only a small proportion are reclassified into a higher category for predicted 5-year risk of breast cancer. PMID:23774992

  12. Using SNP genotypes to improve the discrimination of a simple breast cancer risk prediction model.

    PubMed

    Dite, Gillian S; Mahmoodi, Maryam; Bickerstaffe, Adrian; Hammet, Fleur; Macinnis, Robert J; Tsimiklis, Helen; Dowty, James G; Apicella, Carmel; Phillips, Kelly-Anne; Giles, Graham G; Southey, Melissa C; Hopper, John L

    2013-06-01

    It has been shown that, for women aged 50 years or older, the discriminatory accuracy of the Breast Cancer Risk Prediction Tool (BCRAT) can be modestly improved by the inclusion of information on common single nucleotide polymorphisms (SNPs) that are associated with increased breast cancer risk. We aimed to determine whether a similar improvement is seen for earlier onset disease. We used the Australian Breast Cancer Family Registry to study a population-based sample of 962 cases aged 35-59 years, and 463 controls frequency matched for age and for whom genotyping data was available. Overall, the inclusion of data on seven SNPs improved the area under the receiver operating characteristic curve (AUC) from 0.58 (95 % confidence interval [CI] 0.55-0.61) for BCRAT alone to 0.61 (95 % CI 0.58-0.64) for BCRAT and SNP data combined (p < 0.001). For women aged 35-39 years at interview, the corresponding improvement in AUC was from 0.61 (95 % CI 0.56-0.66) to 0.65 (95 % CI 0.60-0.70; p = 0.03), while for women aged 40-49 years at diagnosis, the AUC improved from 0.61 (95 % CI 0.55-0.66) to 0.63 (95 % CI 0.57-0.69; p = 0.04). Using previously used classifications of low, intermediate and high risk, 2.1 % of cases and none of the controls aged 35-39 years, and 10.9 % of cases and 4.0 % of controls aged 40-49 years were classified into a higher risk group. Including information on seven SNPs associated with breast cancer risk, improves the discriminatory accuracy of BCRAT for women aged 35-39 years and 40-49 years. Given, the low absolute risk for women in these age groups, only a small proportion are reclassified into a higher category for predicted 5-year risk of breast cancer. PMID:23774992

  13. In silico approaches to predicting cancer potency for risk assessment of genotoxic impurities in drug substances.

    PubMed

    Bercu, Joel P; Morton, Stuart M; Deahl, J Thom; Gombar, Vijay K; Callis, Courtney M; van Lier, Robert B L

    2010-01-01

    The current risk assessment approach for addressing the safety of very small concentrations of genotoxic impurities (GTIs) in drug substances is the threshold of toxicological concern (TTC). The TTC is based on several conservative assumptions because of the uncertainty associated with deriving an excess cancer risk when no carcinogenicity data are available for the impurity. It is a default approach derived from a distribution of carcinogens and does not take into account the properties of a specific chemical. The purpose of the study was to use in silico tools to predict the cancer potency (TD(50)) of a compound based on its structure. Structure activity relationship (SAR) models (classification/regression) were developed from the carcinogenicity potency database using MultiCASE and VISDOM. The MultiCASE classification models allowed the prediction of carcinogenic potency class, while the VISDOM regression models predicted a numerical TD(50). A step-wise approach is proposed to calculate predicted numerical TD(50) values for compounds categorized as not potent. This approach for non-potent compounds can be used to establish safe levels greater than the TTC for GTIs in a drug substance. PMID:20363275

  14. Incorporating epistasis interaction of genetic susceptibility single nucleotide polymorphisms in a lung cancer risk prediction model

    PubMed Central

    MARCUS, MICHAEL W.; RAJI, OLAIDE Y.; DUFFY, STEPHEN W.; YOUNG, ROBERT P.; HOPKINS, RAEWYN J.; FIELD, JOHN K.

    2016-01-01

    Incorporation of genetic variants such as single nucleotide polymorphisms (SNPs) into risk prediction models may account for a substantial fraction of attributable disease risk. Genetic data, from 2385 subjects recruited into the Liverpool Lung Project (LLP) between 2000 and 2008, consisting of 20 SNPs independently validated in a candidate-gene discovery study was used. Multifactor dimensionality reduction (MDR) and random forest (RF) were used to explore evidence of epistasis among 20 replicated SNPs. Multivariable logistic regression was used to identify similar risk predictors for lung cancer in the LLP risk model for the epidemiological model and extended model with SNPs. Both models were internally validated using the bootstrap method and model performance was assessed using area under the curve (AUC) and net reclassification improvement (NRI). Using MDR and RF, the overall best classifier of lung cancer status were SNPs rs1799732 (DRD2), rs5744256 (IL-18), rs2306022 (ITGA11) with training accuracy of 0.6592 and a testing accuracy of 0.6572 and a cross-validation consistency of 10/10 with permutation testing P<0.0001. The apparent AUC of the epidemiological model was 0.75 (95% CI 0.73–0.77). When epistatic data were incorporated in the extended model, the AUC increased to 0.81 (95% CI 0.79–0.83) which corresponds to 8% increase in AUC (DeLong's test P=2.2e-16); 17.5% by NRI. After correction for optimism, the AUC was 0.73 for the epidemiological model and 0.79 for the extended model. Our results showed modest improvement in lung cancer risk prediction when the SNP epistasis factor was added. PMID:27121382

  15. Incorporating epistasis interaction of genetic susceptibility single nucleotide polymorphisms in a lung cancer risk prediction model.

    PubMed

    Marcus, Michael W; Raji, Olaide Y; Duffy, Stephen W; Young, Robert P; Hopkins, Raewyn J; Field, John K

    2016-07-01

    Incorporation of genetic variants such as single nucleotide polymorphisms (SNPs) into risk prediction models may account for a substantial fraction of attributable disease risk. Genetic data, from 2385 subjects recruited into the Liverpool Lung Project (LLP) between 2000 and 2008, consisting of 20 SNPs independently validated in a candidate-gene discovery study was used. Multifactor dimensionality reduction (MDR) and random forest (RF) were used to explore evidence of epistasis among 20 replicated SNPs. Multivariable logistic regression was used to identify similar risk predictors for lung cancer in the LLP risk model for the epidemiological model and extended model with SNPs. Both models were internally validated using the bootstrap method and model performance was assessed using area under the curve (AUC) and net reclassification improvement (NRI). Using MDR and RF, the overall best classifier of lung cancer status were SNPs rs1799732 (DRD2), rs5744256 (IL-18), rs2306022 (ITGA11) with training accuracy of 0.6592 and a testing accuracy of 0.6572 and a cross-validation consistency of 10/10 with permutation testing P<0.0001. The apparent AUC of the epidemiological model was 0.75 (95% CI 0.73-0.77). When epistatic data were incorporated in the extended model, the AUC increased to 0.81 (95% CI 0.79-0.83) which corresponds to 8% increase in AUC (DeLong's test P=2.2e-16); 17.5% by NRI. After correction for optimism, the AUC was 0.73 for the epidemiological model and 0.79 for the extended model. Our results showed modest improvement in lung cancer risk prediction when the SNP epistasis factor was added. PMID:27121382

  16. Risk of colon cancer in hereditary non-polyposis colorectal cancer patients as predicted by fuzzy modeling: Influence of smoking

    PubMed Central

    Brand, Rhonda M; Jones, David D; Lynch, Henry T; Brand, Randall E; Watson, Patrice; Ashwathnayaran, Ramesh; Roy, Hemant K

    2006-01-01

    AIM: To investigate whether a fuzzy logic model could predict colorectal cancer (CRC) risk engendered by smoking in hereditary non-polyposis colorectal cancer (HNPCC) patients. METHODS: Three hundred and forty HNPCC mismatch repair (MMR) mutation carriers from the Creighton University Hereditary Cancer Institute Registry were selected for modeling. Age-dependent curves were generated to elucidate the joint effects between gene mutation (hMLH1 or hMSH2), gender, and smoking status on the probability of developing CRC. RESULTS: Smoking significantly increased CRC risk in male hMSH2 mutation carriers (P < 0.05). hMLH1 mutations augmented CRC risk relative to hMSH2 mutation carriers for males (P < 0.05). Males had a significantly higher risk of CRC than females for hMLH1 non smokers (P < 0.05), hMLH1 smokers (P < 0.1) and hMSH2 smokers (P < 0.1). Smoking promoted CRC in a dose-dependent manner in hMSH2 in males (P < 0.05). Females with hMSH2 mutations and both sexes with the hMLH1 groups only demonstrated a smoking effect after an extensive smoking history (P < 0.05). CONCLUSION: CRC promotion by smoking in HNPCC patients is dependent on gene mutation, gender and age. These data demonstrate that fuzzy modeling may enable formulation of clinical risk scores, thereby allowing individualization of CRC prevention strategies. PMID:16874859

  17. Concepts and challenges in cancer risk prediction for the space radiation environment.

    PubMed

    Barcellos-Hoff, Mary Helen; Blakely, Eleanor A; Burma, Sandeep; Fornace, Albert J; Gerson, Stanton; Hlatky, Lynn; Kirsch, David G; Luderer, Ulrike; Shay, Jerry; Wang, Ya; Weil, Michael M

    2015-07-01

    Cancer is an important long-term risk for astronauts exposed to protons and high-energy charged particles during travel and residence on asteroids, the moon, and other planets. NASA's Biomedical Critical Path Roadmap defines the carcinogenic risks of radiation exposure as one of four type I risks. A type I risk represents a demonstrated, serious problem with no countermeasure concepts, and may be a potential "show-stopper" for long duration spaceflight. Estimating the carcinogenic risks for humans who will be exposed to heavy ions during deep space exploration has very large uncertainties at present. There are no human data that address risk from extended exposure to complex radiation fields. The overarching goal in this area to improve risk modeling is to provide biological insight and mechanistic analysis of radiation quality effects on carcinogenesis. Understanding mechanisms will provide routes to modeling and predicting risk and designing countermeasures. This white paper reviews broad issues related to experimental models and concepts in space radiation carcinogenesis as well as the current state of the field to place into context recent findings and concepts derived from the NASA Space Radiation Program. PMID:26256633

  18. Concepts and challenges in cancer risk prediction for the space radiation environment

    NASA Astrophysics Data System (ADS)

    Barcellos-Hoff, Mary Helen; Blakely, Eleanor A.; Burma, Sandeep; Fornace, Albert J.; Gerson, Stanton; Hlatky, Lynn; Kirsch, David G.; Luderer, Ulrike; Shay, Jerry; Wang, Ya; Weil, Michael M.

    2015-07-01

    Cancer is an important long-term risk for astronauts exposed to protons and high-energy charged particles during travel and residence on asteroids, the moon, and other planets. NASA's Biomedical Critical Path Roadmap defines the carcinogenic risks of radiation exposure as one of four type I risks. A type I risk represents a demonstrated, serious problem with no countermeasure concepts, and may be a potential "show-stopper" for long duration spaceflight. Estimating the carcinogenic risks for humans who will be exposed to heavy ions during deep space exploration has very large uncertainties at present. There are no human data that address risk from extended exposure to complex radiation fields. The overarching goal in this area to improve risk modeling is to provide biological insight and mechanistic analysis of radiation quality effects on carcinogenesis. Understanding mechanisms will provide routes to modeling and predicting risk and designing countermeasures. This white paper reviews broad issues related to experimental models and concepts in space radiation carcinogenesis as well as the current state of the field to place into context recent findings and concepts derived from the NASA Space Radiation Program.

  19. Common breast cancer susceptibility alleles and the risk of breast cancer for BRCA1 and BRCA2 mutation carriers: implications for risk prediction.

    PubMed

    Antoniou, Antonis C; Beesley, Jonathan; McGuffog, Lesley; Sinilnikova, Olga M; Healey, Sue; Neuhausen, Susan L; Ding, Yuan Chun; Rebbeck, Timothy R; Weitzel, Jeffrey N; Lynch, Henry T; Isaacs, Claudine; Ganz, Patricia A; Tomlinson, Gail; Olopade, Olufunmilayo I; Couch, Fergus J; Wang, Xianshu; Lindor, Noralane M; Pankratz, Vernon S; Radice, Paolo; Manoukian, Siranoush; Peissel, Bernard; Zaffaroni, Daniela; Barile, Monica; Viel, Alessandra; Allavena, Anna; Dall'Olio, Valentina; Peterlongo, Paolo; Szabo, Csilla I; Zikan, Michal; Claes, Kathleen; Poppe, Bruce; Foretova, Lenka; Mai, Phuong L; Greene, Mark H; Rennert, Gad; Lejbkowicz, Flavio; Glendon, Gord; Ozcelik, Hilmi; Andrulis, Irene L; Thomassen, Mads; Gerdes, Anne-Marie; Sunde, Lone; Cruger, Dorthe; Birk Jensen, Uffe; Caligo, Maria; Friedman, Eitan; Kaufman, Bella; Laitman, Yael; Milgrom, Roni; Dubrovsky, Maya; Cohen, Shimrit; Borg, Ake; Jernström, Helena; Lindblom, Annika; Rantala, Johanna; Stenmark-Askmalm, Marie; Melin, Beatrice; Nathanson, Kate; Domchek, Susan; Jakubowska, Ania; Lubinski, Jan; Huzarski, Tomasz; Osorio, Ana; Lasa, Adriana; Durán, Mercedes; Tejada, Maria-Isabel; Godino, Javier; Benitez, Javier; Hamann, Ute; Kriege, Mieke; Hoogerbrugge, Nicoline; van der Luijt, Rob B; van Asperen, Christi J; Devilee, Peter; Meijers-Heijboer, E J; Blok, Marinus J; Aalfs, Cora M; Hogervorst, Frans; Rookus, Matti; Cook, Margaret; Oliver, Clare; Frost, Debra; Conroy, Don; Evans, D Gareth; Lalloo, Fiona; Pichert, Gabriella; Davidson, Rosemarie; Cole, Trevor; Cook, Jackie; Paterson, Joan; Hodgson, Shirley; Morrison, Patrick J; Porteous, Mary E; Walker, Lisa; Kennedy, M John; Dorkins, Huw; Peock, Susan; Godwin, Andrew K; Stoppa-Lyonnet, Dominique; de Pauw, Antoine; Mazoyer, Sylvie; Bonadona, Valérie; Lasset, Christine; Dreyfus, Hélène; Leroux, Dominique; Hardouin, Agnès; Berthet, Pascaline; Faivre, Laurence; Loustalot, Catherine; Noguchi, Tetsuro; Sobol, Hagay; Rouleau, Etienne; Nogues, Catherine; Frénay, Marc; Vénat-Bouvet, Laurence; Hopper, John L; Daly, Mary B; Terry, Mary B; John, Esther M; Buys, Saundra S; Yassin, Yosuf; Miron, Alexander; Goldgar, David; Singer, Christian F; Dressler, Anne Catharina; Gschwantler-Kaulich, Daphne; Pfeiler, Georg; Hansen, Thomas V O; Jønson, Lars; Agnarsson, Bjarni A; Kirchhoff, Tomas; Offit, Kenneth; Devlin, Vincent; Dutra-Clarke, Ana; Piedmonte, Marion; Rodriguez, Gustavo C; Wakeley, Katie; Boggess, John F; Basil, Jack; Schwartz, Peter E; Blank, Stephanie V; Toland, Amanda Ewart; Montagna, Marco; Casella, Cinzia; Imyanitov, Evgeny; Tihomirova, Laima; Blanco, Ignacio; Lazaro, Conxi; Ramus, Susan J; Sucheston, Lara; Karlan, Beth Y; Gross, Jenny; Schmutzler, Rita; Wappenschmidt, Barbara; Engel, Christoph; Meindl, Alfons; Lochmann, Magdalena; Arnold, Norbert; Heidemann, Simone; Varon-Mateeva, Raymonda; Niederacher, Dieter; Sutter, Christian; Deissler, Helmut; Gadzicki, Dorothea; Preisler-Adams, Sabine; Kast, Karin; Schönbuchner, Ines; Caldes, Trinidad; de la Hoya, Miguel; Aittomäki, Kristiina; Nevanlinna, Heli; Simard, Jacques; Spurdle, Amanda B; Holland, Helene; Chen, Xiaoqing; Platte, Radka; Chenevix-Trench, Georgia; Easton, Douglas F

    2010-12-01

    The known breast cancer susceptibility polymorphisms in FGFR2, TNRC9/TOX3, MAP3K1, LSP1, and 2q35 confer increased risks of breast cancer for BRCA1 or BRCA2 mutation carriers. We evaluated the associations of 3 additional single nucleotide polymorphisms (SNPs), rs4973768 in SLC4A7/NEK10, rs6504950 in STXBP4/COX11, and rs10941679 at 5p12, and reanalyzed the previous associations using additional carriers in a sample of 12,525 BRCA1 and 7,409 BRCA2 carriers. Additionally, we investigated potential interactions between SNPs and assessed the implications for risk prediction. The minor alleles of rs4973768 and rs10941679 were associated with increased breast cancer risk for BRCA2 carriers (per-allele HR = 1.10, 95% CI: 1.03-1.18, P = 0.006 and HR = 1.09, 95% CI: 1.01-1.19, P = 0.03, respectively). Neither SNP was associated with breast cancer risk for BRCA1 carriers, and rs6504950 was not associated with breast cancer for either BRCA1 or BRCA2 carriers. Of the 9 polymorphisms investigated, 7 were associated with breast cancer for BRCA2 carriers (FGFR2, TOX3, MAP3K1, LSP1, 2q35, SLC4A7, 5p12, P = 7 × 10(-11) - 0.03), but only TOX3 and 2q35 were associated with the risk for BRCA1 carriers (P = 0.0049, 0.03, respectively). All risk-associated polymorphisms appear to interact multiplicatively on breast cancer risk for mutation carriers. Based on the joint genotype distribution of the 7 risk-associated SNPs in BRCA2 mutation carriers, the 5% of BRCA2 carriers at highest risk (i.e., between 95th and 100th percentiles) were predicted to have a probability between 80% and 96% of developing breast cancer by age 80, compared with 42% to 50% for the 5% of carriers at lowest risk. Our findings indicated that these risk differences might be sufficient to influence the clinical management of mutation carriers. PMID:21118973

  20. To predict or not to predict? The dilemma of predicting the risk of suboptimal cytoreduction in ovarian cancer.

    PubMed

    Kang, S; Park, S-Y

    2011-12-01

    Although maximal cytoreduction is the cornerstone of current treatment for patients with advanced ovarian cancer, optimal cytoreduction is not always achievable in the clinic. Therefore, using clinical characteristics, diagnostic imaging, serum biomarkers or laparoscopic findings, many studies have attempted to find models for predicting surgical resectability. However, most of these prediction models showed limited effectiveness and have not been properly validated. To establish a reliable prediction model, several requirements should be met. First, the goal of surgical cytoreduction should be adequately defined. Second, the desired accuracy for making the model clinically useful should be defined. Third, the model should test all relevant predictors, including clinical, radiological and biochemical predictors, and be developed using a large dataset that provides a sufficient number of events. Fourth, any prediction model should be validated with a relevant external dataset. Lastly, the prediction model should be able to aid decision making and, thereby, improve the outcome of patients. Therefore, randomized clinical trials with decision making based on prediction models are urgently required. PMID:22180395

  1. Nonvisible tumors on multiparametric magnetic resonance imaging does not predict low-risk prostate cancer

    PubMed Central

    Lee, Seung Hwan; Koo, Kyo Chul; Lee, Dong Hoon; Chung, Byung Ha

    2015-01-01

    Purpose To determine whether multiparametric MRI could help predict the diagnosis of low-risk prostate cancer (PCA). Methods We retrospectively analyzed consecutive 623 patients with PCA who underwent multiparametric MRI before radical prostatectomy(RP). High-resolution T1- and T2-weighted, diffusion-weighted, and dynamic precontrast and postcontrast image sequences were obtained for each patient. Of the 623 patients, 177(28.4%) exhibited non visible tumors on MRI of clinical stage T1c. The imaging results were compared with the pathological findings with respect to both stage and Gleason scores (GS). Results Of the 177 prostatectomy patients with non visible tumors on MRI, pathological findings resulted in the upgrading of 49(27.7%) patients to a sum of GS 7 or more. 101(57.1%) patients exhibited tumor volumes greater than 0.5cc. The biochemical recurrence rate was significantly higher in the pathological upgraded group compared with the nonupgraded group after a mean follow-up time of 29 months. In the multiple logistic analysis, non visible tumor on MRI was not a significant predictor of low-risk PCA. Conclusions Even though cancer foci were not visualized by postbiopsy MRI, the pathological tumor volumes and extent of GS upgrading were relatively high. Therefore, nonvisible tumors by multiparametric MRI do not appear to be predictive of low-risk PCA. PMID:26779459

  2. Predicting the Risk of Pelvic Node Involvement Among Men With Prostate Cancer in the Contemporary Era

    SciTech Connect

    Nguyen, Paul L. Chen, M.-H.; Hoffman, Karen E.; Katz, Matthew S.; D'Amico, Anthony V.

    2009-05-01

    Purpose: The 'Roach formula' for the risk of pelvic lymph node metastases [(2/3) * PSA + (Gleason score - 6) * 10] was developed in the early prostate-specific antigen (PSA) era. We examined the accuracy of this formula in contemporary patients. Methods: We included men in the Surveillance, Epidemiology, and End Results Registry with a diagnosis of clinical T1c-T4 prostate cancer in 2004 who had a surgical lymph node evaluation, Gleason score (typically from prostatectomy), and baseline PSA level (n = 9,387). Expected and observed rates of node positivity were compared. Results: Ninety-eight percent were clinical T1c/T2, and 97% underwent prostatectomy. Overall, 309 patients (3.29%) had positive lymph nodes. Roach scores overestimated the actual rate of positive lymph nodes in the derivation set by 16-fold for patients with Roach score less than or equal to 10%, by 7-fold for scores greater than 10-20%, and by approximately 2.5-fold for scores greater than 20%. Applying these adjustment factors to Roach scores in the validation data set yielded accurate predictions of risk. For those with Roach score less than or equal to 10%, adjusted expected risk was 0.2% and observed risk was 0.2%. For Roach score greater than 10-20%, adjusted expected risk was 2.0% and observed risk was 2.1%. For Roach score greater than 20-30%, adjusted expected risk was 9.7% and observed risk was 6.5%. For Roach score greater than 30-40%, adjusted expected risk was 13.9% and observed risk was 13.9%. Conclusion: Applied to contemporary patients with mainly T1c/T2 disease, the Roach formula appears to overestimate pelvic lymph node risk. The adjustment factors presented here should be validated by using biopsy Gleason scores and extended lymphadenectomies.

  3. Meta-Prediction of MTHFR Gene Polymorphism Mutations and Associated Risk for Colorectal Cancer

    PubMed Central

    Yu, C. H.

    2016-01-01

    The methylenetetrahydrofolate reductase (MTHFR) gene is one of the most investigated of the genes associated with chronic human diseases because of its associations with hyperhomocysteinemia and toxicity. It has been proposed as a prototype gene for the prevention of colorectal cancer (CRC). The major objectives of this meta-analysis were to examine the polymorphism-mutation patterns of MTHFR and their associations with risk for CRC as well as potential contributing factors for mutations and disease risks. This analysis included 33,626 CRC cases and 48,688 controls across 92 studies for MTHFR 677 and 16,367 cases and 24,874 controls across 54 studies for MTHFR 1298, comprising data for various racial and ethnic groups, both genders, and multiple cancer sites. MTHFR 677 homozygous TT genotype was protective (p < .05) for CRC for all included populations; however, with heterogeneity across various racial–ethnic groups and opposing findings, it was a risk genotype for the subgroup of Hispanics (p < .01). Additional countries for which subgroup analyses resulted in 677 TT as a risk genotype included Turkey, Romania, Croatia, Hungary, Portugal, Mexico, Brazil, U.S. Hawai’i, Taiwan, India, and Egypt. Countries with the highest mutation rates and risks for both MTHFR 677 and 1298 genotypes are presented using global maps to visualize the grouping patterns. Meta-predictive analyses revealed that air pollution levels were associated with gene polymorphisms for both genotypes. Future nursing research should be conducted to develop proactive measures to protect populations in cities where air pollution causes more deaths. PMID:26858257

  4. Meta-Prediction of MTHFR Gene Polymorphism Mutations and Associated Risk for Colorectal Cancer.

    PubMed

    Shiao, S P K; Yu, C H

    2016-07-01

    The methylenetetrahydrofolate reductase (MTHFR) gene is one of the most investigated of the genes associated with chronic human diseases because of its associations with hyperhomocysteinemia and toxicity. It has been proposed as a prototype gene for the prevention of colorectal cancer (CRC). The major objectives of this meta-analysis were to examine the polymorphism-mutation patterns of MTHFR and their associations with risk for CRC as well as potential contributing factors for mutations and disease risks. This analysis included 33,626 CRC cases and 48,688 controls across 92 studies for MTHFR 677 and 16,367 cases and 24,874 controls across 54 studies for MTHFR 1298, comprising data for various racial and ethnic groups, both genders, and multiple cancer sites. MTHFR 677 homozygous TT genotype was protective (p <05) for CRC for all included populations; however, with heterogeneity across various racial-ethnic groups and opposing findings, it was a risk genotype for the subgroup of Hispanics (p <01). Additional countries for which subgroup analyses resulted in 677 TT as a risk genotype included Turkey, Romania, Croatia, Hungary, Portugal, Mexico, Brazil, U.S. Hawai'i, Taiwan, India, and Egypt. Countries with the highest mutation rates and risks for both MTHFR 677 and 1298 genotypes are presented using global maps to visualize the grouping patterns. Meta-predictive analyses revealed that air pollution levels were associated with gene polymorphisms for both genotypes. Future nursing research should be conducted to develop proactive measures to protect populations in cities where air pollution causes more deaths. PMID:26858257

  5. Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants

    PubMed Central

    Pharoah, Paul D. P.; Michailidou, Kyriaki; Tyrer, Jonathan; Brook, Mark N.; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Dunning, Alison M.; Shah, Mitul; Luben, Robert; Brown, Judith; Bojesen, Stig E.; Nordestgaard, Børge G.; Nielsen, Sune F.; Flyger, Henrik; Czene, Kamila; Darabi, Hatef; Eriksson, Mikael; Peto, Julian; dos-Santos-Silva, Isabel; Dudbridge, Frank; Johnson, Nichola; Schmidt, Marjanka K.; Broeks, Annegien; Verhoef, Senno; Rutgers, Emiel J.; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk J.; Figueroa, Jonine; Chanock, Stephen J.; Brinton, Louise; Lissowska, Jolanta; Couch, Fergus J.; Olson, Janet E.; Vachon, Celine; Pankratz, Vernon S.; Lambrechts, Diether; Wildiers, Hans; Van Ongeval, Chantal; van Limbergen, Erik; Kristensen, Vessela; Grenaker Alnæs, Grethe; Nord, Silje; Borresen-Dale, Anne-Lise; Nevanlinna, Heli; Muranen, Taru A.; Aittomäki, Kristiina; Blomqvist, Carl; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Fasching, Peter A.; Haeberle, Lothar; Ekici, Arif B.; Beckmann, Matthias W.; Burwinkel, Barbara; Marme, Frederik; Schneeweiss, Andreas; Sohn, Christof; Trentham-Dietz, Amy; Newcomb, Polly; Titus, Linda; Egan, Kathleen M.; Hunter, David J.; Lindstrom, Sara; Tamimi, Rulla M.; Kraft, Peter; Rahman, Nazneen; Turnbull, Clare; Renwick, Anthony; Seal, Sheila; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Benitez, Javier; Pilar Zamora, M.; Arias Perez, Jose Ignacio; Menéndez, Primitiva; Jakubowska, Anna; Lubinski, Jan; Jaworska-Bieniek, Katarzyna; Durda, Katarzyna; Bogdanova, Natalia V.; Antonenkova, Natalia N.; Dörk, Thilo; Anton-Culver, Hoda; Neuhausen, Susan L.; Ziogas, Argyrios; Bernstein, Leslie; Devilee, Peter; Tollenaar, Robert A. E. M.; Seynaeve, Caroline; van Asperen, Christi J.; Cox, Angela; Cross, Simon S.; Reed, Malcolm W. R.; Khusnutdinova, Elza; Bermisheva, Marina; Prokofyeva, Darya; Takhirova, Zalina; Meindl, Alfons; Schmutzler, Rita K.; Sutter, Christian; Yang, Rongxi; Schürmann, Peter; Bremer, Michael; Christiansen, Hans; Park-Simon, Tjoung-Won; Hillemanns, Peter; Guénel, Pascal; Truong, Thérèse; Menegaux, Florence; Sanchez, Marie; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Pensotti, Valeria; Hopper, John L.; Tsimiklis, Helen; Apicella, Carmel; Southey, Melissa C.; Brauch, Hiltrud; Brüning, Thomas; Ko, Yon-Dschun; Sigurdson, Alice J.; Doody, Michele M.; Hamann, Ute; Torres, Diana; Ulmer, Hans-Ulrich; Försti, Asta; Sawyer, Elinor J.; Tomlinson, Ian; Kerin, Michael J.; Miller, Nicola; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Marie Mulligan, Anna; Chenevix-Trench, Georgia; Balleine, Rosemary; Giles, Graham G.; Milne, Roger L.; McLean, Catriona; Lindblom, Annika; Margolin, Sara; Haiman, Christopher A.; Henderson, Brian E.; Schumacher, Fredrick; Le Marchand, Loic; Eilber, Ursula; Wang-Gohrke, Shan; Hooning, Maartje J.; Hollestelle, Antoinette; van den Ouweland, Ans M. W.; Koppert, Linetta B.; Carpenter, Jane; Clarke, Christine; Scott, Rodney; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M.; Brenner, Hermann; Arndt, Volker; Stegmaier, Christa; Karina Dieffenbach, Aida; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Offit, Kenneth; Vijai, Joseph; Robson, Mark; Rau-Murthy, Rohini; Dwek, Miriam; Swann, Ruth; Annie Perkins, Katherine; Goldberg, Mark S.; Labrèche, France; Dumont, Martine; Eccles, Diana M.; Tapper, William J.; Rafiq, Sajjad; John, Esther M.; Whittemore, Alice S.; Slager, Susan; Yannoukakos, Drakoulis; Toland, Amanda E.; Yao, Song; Zheng, Wei; Halverson, Sandra L.; González-Neira, Anna; Pita, Guillermo; Rosario Alonso, M.; Álvarez, Nuria; Herrero, Daniel; Tessier, Daniel C.; Vincent, Daniel; Bacot, Francois; Luccarini, Craig; Baynes, Caroline; Ahmed, Shahana; Maranian, Mel; Healey, Catherine S.; Simard, Jacques; Hall, Per; Easton, Douglas F.; Garcia-Closas, Montserrat

    2015-01-01

    Background: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. Methods: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. Results: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. Conclusions: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report. PMID:25855707

  6. KOHBRA BRCA risk calculator (KOHCal): a model for predicting BRCA1 and BRCA2 mutations in Korean breast cancer patients.

    PubMed

    Kang, Eunyoung; Park, Sue K; Lee, Jong Won; Kim, Zisun; Noh, Woo-Chul; Jung, Yongsik; Yang, Jung-Hyun; Jung, Sung Hoo; Kim, Sung-Won

    2016-05-01

    The widely used Western BRCA mutation prediction models underestimated the risk of having a BRCA mutation in Korean breast cancer patients. This study aimed to identify predictive factors for BRCA1/2 mutations and to develop a Korean BRCA risk calculator. The model was constructed by logistic regression model, and it was based on the Korean Hereditary Breast Cancer study, in which 1669 female patients were enrolled between May 2007 and December 2010. A separate data set of 402 patients, who were enrolled from Jan 2011 to August 2012, was used to test the performance of our model. In total, 264 (15.8%) and 67 (16.7%) BRCA mutation carriers were identified in the model and validation set, respectively. Multivariate analysis showed that age at breast cancer diagnosis, bilateral breast cancer, triple-negative breast cancer (TNBC) and the number of relatives with breast or ovarian cancer within third-degree relatives were independent predictors of the BRCA mutation among familial breast cancer patients. An age <35 years at diagnosis, bilateral breast cancer, both breast and ovarian cancer and TNBC remained significant predictors in non-familial breast cancer cases. Our model was developed based on logistic regression models. The validation results showed no differences between the observed and expected carrier probabilities. This model will be a useful tool for providing genetic risk assessments in Korean populations. PMID:26763880

  7. Rs488087 single nucleotide polymorphism as predictive risk factor for pancreatic cancers.

    PubMed

    Martinez, Emmanuelle; Silvy, Françoise; Fina, Fréderic; Bartoli, Marc; Krahn, Martin; Barlesi, Fabrice; Figarella-Branger, Dominique; Iovanna, Juan; Laugier, René; Ouaissi, Mehdi; Lombardo, Dominique; Mas, Eric

    2015-11-24

    Pancreatic cancer (PC) is a devastating disease progressing asymptomatically until death within months after diagnosis. Defining at-risk populations should promote its earlier diagnosis and hence also avoid its development. Considering the known involvement in pancreatic disease of exon 11 of the bile salt-dependent lipase (BSDL) gene that encodes variable number of tandem repeat (VNTR) sequences, we hypothesized upon the existence of a genetic link between predisposition to PC and mutations in VNTR loci. To test this, BSDL VNTR were amplified by touchdown-PCR performed on genomic DNA extracted from cancer tissue or blood samples from a French patient cohort and amplicons were Sanger sequenced. A robust method using probes for droplet digital (dd)-PCR was designed to discriminate the C/C major from C/T or T/T minor genotypes. We report that the c.1719C > T transition (SNP rs488087) present in BSDL VNTR may be a useful marker for defining a population at risk of developing PC (occurrence: 63.90% in the PC versus 27.30% in the control group). The odds ratio of 4.7 for the T allele was larger than those already determined for other SNPs suspected to be predictive of PC. Further studies on tumor pancreatic tissue suggested that a germline T allele may favor Kras G12R/G12D somatic mutations which represent negative prognostic factors associated with reduced survival. We propose that the detection of the T allele in rs488087 SNP should lead to an in-depth follow-up of patients in whom an association with other potential risk factors of pancreatic cancer may be present. PMID:26498142

  8. Childhood body mass index and adult mammographic density measures that predict breast cancer risk.

    PubMed

    Hopper, John L; Nguyen, Tuong L; Stone, Jennifer; Aujard, Kelly; Matheson, Melanie C; Abramson, Michael J; Burgess, John A; Walters, E Haydn; Dite, Gillian S; Bui, Minh; Evans, Christopher; Makalic, Enes; Schmidt, Daniel F; Ward, Gail; Jenkins, Mark A; Giles, Graham G; Dharmage, Shyamali C; Apicella, Carmel

    2016-02-01

    The aim of the present study is to determine if body mass index (BMI) during childhood is associated with the breast cancer risk factor 'adult mammographic density adjusted for age and BMI'. In 1968, the Tasmanian Longitudinal Health Study studied every Tasmanian school child born in 1961. We obtained measured heights and weights from annual school medical records across ages 7-15 years and imputed missing values. Between 2009 and 2012, we administered to 490 women a questionnaire that asked current height and weight and digitised at least one mammogram per woman. Absolute and percent mammographic densities were measured using the computer-assisted method CUMULUS. We used linear regression and adjusted for age at interview and log current BMI. The mammographic density measures were negatively associated: with log BMI at each age from 7 to 15 years (all p < 0.05); with the average of standardised log BMIs across ages 7-15 years (p < 0.0005); and more strongly with standardised log BMI measures closer to age 15 years (p < 0.03). Childhood BMI measures explained 7 and 10 % of the variance in absolute and percent mammographic densities, respectively, and 25 and 20 % of the association between current BMI and absolute and percent mammographic densities, respectively. Associations were not altered by adjustment for age at menarche. There is a negative association between BMI in late childhood and the adult mammographic density measures that predict breast cancer risk. This could explain, at least in part, why BMI in adolescence is negatively associated with breast cancer risk. PMID:26907766

  9. Rs488087 single nucleotide polymorphism as predictive risk factor for pancreatic cancers

    PubMed Central

    Martinez, Emmanuelle; Silvy, Françoise; Fina, Fréderic; Bartoli, Marc; Krahn, Martin; Barlesi, Fabrice; Figarella-Branger, Dominique; Iovanna, Juan; Laugier, René; Ouaissi, Mehdi; Lombardo, Dominique; Mas, Eric

    2015-01-01

    Pancreatic cancer (PC) is a devastating disease progressing asymptomatically until death within months after diagnosis. Defining at-risk populations should promote its earlier diagnosis and hence also avoid its development. Considering the known involvement in pancreatic disease of exon 11 of the bile salt-dependent lipase (BSDL) gene that encodes variable number of tandem repeat (VNTR) sequences, we hypothesized upon the existence of a genetic link between predisposition to PC and mutations in VNTR loci. To test this, BSDL VNTR were amplified by touchdown-PCR performed on genomic DNA extracted from cancer tissue or blood samples from a French patient cohort and amplicons were Sanger sequenced. A robust method using probes for droplet digital (dd)-PCR was designed to discriminate the C/C major from C/T or T/T minor genotypes. We report that the c.1719C > T transition (SNP rs488087) present in BSDL VNTR may be a useful marker for defining a population at risk of developing PC (occurrence: 63.90% in the PC versus 27.30% in the control group). The odds ratio of 4.7 for the T allele was larger than those already determined for other SNPs suspected to be predictive of PC. Further studies on tumor pancreatic tissue suggested that a germline T allele may favor Kras G12R/G12D somatic mutations which represent negative prognostic factors associated with reduced survival. We propose that the detection of the T allele in rs488087 SNP should lead to an in-depth follow-up of patients in whom an association with other potential risk factors of pancreatic cancer may be present. PMID:26498142

  10. A new approach to reduce uncertainties in space radiation cancer risk predictions.

    PubMed

    Cucinotta, Francis A

    2015-01-01

    The prediction of space radiation induced cancer risk carries large uncertainties with two of the largest uncertainties being radiation quality and dose-rate effects. In risk models the ratio of the quality factor (QF) to the dose and dose-rate reduction effectiveness factor (DDREF) parameter is used to scale organ doses for cosmic ray proton and high charge and energy (HZE) particles to a hazard rate for γ-rays derived from human epidemiology data. In previous work, particle track structure concepts were used to formulate a space radiation QF function that is dependent on particle charge number Z, and kinetic energy per atomic mass unit, E. QF uncertainties where represented by subjective probability distribution functions (PDF) for the three QF parameters that described its maximum value and shape parameters for Z and E dependences. Here I report on an analysis of a maximum QF parameter and its uncertainty using mouse tumor induction data. Because experimental data for risks at low doses of γ-rays are highly uncertain which impacts estimates of maximum values of relative biological effectiveness (RBEmax), I developed an alternate QF model, denoted QFγAcute where QFs are defined relative to higher acute γ-ray doses (0.5 to 3 Gy). The alternate model reduces the dependence of risk projections on the DDREF, however a DDREF is still needed for risk estimates for high-energy protons and other primary or secondary sparsely ionizing space radiation components. Risk projections (upper confidence levels (CL)) for space missions show a reduction of about 40% (CL∼50%) using the QFγAcute model compared the QFs based on RBEmax and about 25% (CL∼35%) compared to previous estimates. In addition, I discuss how a possible qualitative difference leading to increased tumor lethality for HZE particles compared to low LET radiation and background tumors remains a large uncertainty in risk estimates. PMID:25789764

  11. A New Approach to Reduce Uncertainties in Space Radiation Cancer Risk Predictions

    PubMed Central

    Cucinotta, Francis A.

    2015-01-01

    The prediction of space radiation induced cancer risk carries large uncertainties with two of the largest uncertainties being radiation quality and dose-rate effects. In risk models the ratio of the quality factor (QF) to the dose and dose-rate reduction effectiveness factor (DDREF) parameter is used to scale organ doses for cosmic ray proton and high charge and energy (HZE) particles to a hazard rate for γ-rays derived from human epidemiology data. In previous work, particle track structure concepts were used to formulate a space radiation QF function that is dependent on particle charge number Z, and kinetic energy per atomic mass unit, E. QF uncertainties where represented by subjective probability distribution functions (PDF) for the three QF parameters that described its maximum value and shape parameters for Z and E dependences. Here I report on an analysis of a maximum QF parameter and its uncertainty using mouse tumor induction data. Because experimental data for risks at low doses of γ-rays are highly uncertain which impacts estimates of maximum values of relative biological effectiveness (RBEmax), I developed an alternate QF model, denoted QFγAcute where QFs are defined relative to higher acute γ-ray doses (0.5 to 3 Gy). The alternate model reduces the dependence of risk projections on the DDREF, however a DDREF is still needed for risk estimates for high-energy protons and other primary or secondary sparsely ionizing space radiation components. Risk projections (upper confidence levels (CL)) for space missions show a reduction of about 40% (CL∼50%) using the QFγAcute model compared the QFs based on RBEmax and about 25% (CL∼35%) compared to previous estimates. In addition, I discuss how a possible qualitative difference leading to increased tumor lethality for HZE particles compared to low LET radiation and background tumors remains a large uncertainty in risk estimates. PMID:25789764

  12. Predicted reduction in lung cancer risk following cessation of smoking and radon exposure

    SciTech Connect

    Ennever, F.K. )

    1990-03-01

    Recently there has been considerable public and regulatory concern that radon, produced by the decay of naturally occurring uranium, can accumulate in homes, offices, and schools at levels that may substantially increase the risk of lung cancer. The major cause of lung cancer is smoking, and radon appears to interact multiplicatively with smoking in causing lung cancer. Thus, the most effective way to reduce the increased risk of lung cancer resulting from radon exposure is to cease smoking. In this paper, a model for the risks associated with radon exposure that was developed by a committee of the National Academy of Sciences is used to calculate the benefits, in terms of reduction in lifetime risk of lung cancer, of ceasing to smoke, ceasing radon exposure, or ceasing both. Ceasing to smoke is considerably more beneficial than ceasing radon exposure, and thus policymakers addressing the health effects of radon should place priority on encouraging individuals to stop smoking.

  13. Using Clinical Factors and Mammographic Breast Density to Estimate Breast Cancer Risk: Development and Validation of a New Predictive Model

    PubMed Central

    Tice, Jeffrey A.; Cummings, Steven R.; Smith-Bindman, Rebecca; Ichikawa, Laura; Barlow, William E.; Kerlikowske, Karla

    2009-01-01

    Background Current models for assessing breast cancer risk are complex and do not include breast density, a strong risk factor for breast cancer that is routinely reported with mammography. Objective To develop and validate an easy-to-use breast cancer risk prediction model that includes breast density. Design Empirical model based on Surveillance, Epidemiology, and End Results incidence, and relative hazards from a prospective cohort. Setting Screening mammography sites participating in the Breast Cancer Surveillance Consortium. Patients 1 095 484 women undergoing mammography who had no previous diagnosis of breast cancer. Measurements Self-reported age, race or ethnicity, family history of breast cancer, and history of breast biopsy. Community radiologists rated breast density by using 4 Breast Imaging Reporting and Data System categories. Results During 5.3 years of follow-up, invasive breast cancer was diagnosed in 14 766 women. The breast density model was well calibrated overall (expected–observed ratio, 1.03 [95% CI, 0.99 to 1.06]) and in racial and ethnic subgroups. It had modest discriminatory accuracy (concordance index, 0.66 [CI, 0.65 to 0.67]). Women with low-density mammograms had 5-year risks less than 1.67% unless they had a family history of breast cancer and were older than age 65 years. Limitation The model has only modest ability to discriminate between women who will develop breast cancer and those who will not. Conclusion A breast cancer prediction model that incorporates routinely reported measures of breast density can estimate 5-year risk for invasive breast cancer. Its accuracy needs to be further evaluated in independent populations before it can be recommended for clinical use. PMID:18316752

  14. Prostate cancer risk prediction based on complete prostate cancer family history

    PubMed Central

    Albright, Frederick; Stephenson, Robert A; Agarwal, Neeraj; Teerlink, Craig C; Lowrance, William T; Farnham, James M; Albright, Lisa A Cannon

    2015-01-01

    Background Prostate cancer (PC) relative risks (RRs) are typically estimated based on status of close relatives or presence of any affected relatives. This study provides RR estimates using extensive and specific PC family history. Methods A retrospective population-based study was undertaken to estimate RRs for PC based on complete family history of PC. A total of 635,443 males, all with ancestral genealogy data, were analyzed. RRs for PC were determined based upon PC rates estimated from males with no PC family history (without PC in first, second, or third degree relatives). RRs were determined for a variety of constellations, for example, number of first through third degree relatives; named (grandfather, father, uncle, cousins, brothers); maternal, paternal relationships, and age of onset. Results In the 635,443 males analyzed, 18,105 had PC. First-degree RRs ranged from 2.46 (=1 first-degree relative affected, CI = 2.39–2.53) to 7.65 (=4 first-degree relatives affected, CI = 6.28–9.23). Second-degree RRs for probands with 0 affected first-degree relatives ranged from 1.51 (≥1 second-degree relative affected, CI = 1.47–1.56) to 3.09 (≥5 second-degree relatives affected, CI = 2.32–4.03). Third-degree RRs with 0 affected first- and 0 affected second-degree relatives ranged from 1.15 (≥1 affected third-degree relative, CI = 1.12–1.19) to 1.50 (≥5 affected third-degree relatives, CI = 1.35–1.66). RRs based on age at diagnosis were higher for earlier age at diagnoses; for example, RR = 5.54 for ≥1 first-degree relative diagnosed before age 50 years (CI = 1.12–1.19) and RR = 1.78 for >1 second-degree relative diagnosed before age 50 years, CI = 1.33, 2.33. RRs for equivalent maternal versus paternal family history were not significantly different. Conclusions A more complete PC family history using close and distant relatives and age at diagnosis results in a wider range of estimates of individual RR

  15. Semi-automated and fully automated mammographic density measurement and breast cancer risk prediction.

    PubMed

    Llobet, Rafael; Pollán, Marina; Antón, Joaquín; Miranda-García, Josefa; Casals, María; Martínez, Inmaculada; Ruiz-Perales, Francisco; Pérez-Gómez, Beatriz; Salas-Trejo, Dolores; Pérez-Cortés, Juan-Carlos

    2014-09-01

    -automated MD assessments present a good correlation. Both the methods also found an association between MD and breast cancer risk, which warrants the proposed tools for breast cancer risk prediction and clinical decision making. A full version of the DM-Scan is freely available. PMID:24636804

  16. Negative HPV screening test predicts low cervical cancer risk better than negative Pap test

    Cancer.gov

    Based on a study that included more than 1 million women, investigators at NCI have determined that a negative test for HPV infection compared to a negative Pap test provides greater safety, or assurance, against future risk of cervical cancer.

  17. Common genetic variants in prostate cancer risk prediction – Results from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3)

    PubMed Central

    Lindström, Sara; Schumacher, Fredrick R.; Cox, David; Travis, Ruth C.; Albanes, Demetrius; Allen, Naomi E.; Andriole, Gerald; Berndt, Sonja I.; Boeing, Heiner; Bueno-de-Mesquita, H. Bas; Crawford, E. David; Diver, W. Ryan; Ganziano, J. Michael; Giles, Graham G.; Giovannucci, Edward; Gonzalez, Carlos A.; Henderson, Brian; Hunter, David J.; Johansson, Mattias; Kolonel, Laurence N.; Ma, Jing; Le Marchand, Loic; Pala, Valeria; Stampfer, Meir; Stram, Daniel O.; Thun, Michael J.; Tjonneland, Anne; Trichopoulos, Dimitrios; Virtamo, Jarmo; Weinstein, Stephanie J.; Willett, Walter C.; Yeager, Meredith; Hayes, Richard B.; Severi, Gianluca; Haiman, Christopher A.; Chanock, Stephen J.; Kraft, Peter

    2012-01-01

    Background One of the goals of personalized medicine is to generate individual risk profiles that could identify individuals in the population that exhibit high risk. The discovery of more than two-dozen independent SNP markers in prostate cancer has raised the possibility for such risk stratification. In this study, we evaluated the discriminative and predictive ability for prostate cancer risk models incorporating 25 common prostate cancer genetic markers, family history of prostate cancer and age. Methods We fit a series of risk models and estimated their performance in 7,509 prostate cancer cases and 7,652 controls within the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). We also calculated absolute risks based on SEER incidence data. Results The best risk model (C-statistic=0.642) included individual genetic markers and family history of prostate cancer. We observed a decreasing trend in discriminative ability with advancing age (P=0.009), with highest accuracy in men younger than 60 years (C-statistic=0.679). The absolute ten-year risk for 50-year old men with a family history ranged from 1.6% (10th percentile of genetic risk) to 6.7% (90th percentile of genetic risk). For men without family history, the risk ranged from 0.8% (10th percentile) to 3.4% (90th percentile). Conclusions Our results indicate that incorporating genetic information and family history in prostate cancer risk models can be particularly useful for identifying younger men that might benefit from PSA screening. Impact Although adding genetic risk markers improves model performance, the clinical utility of these genetic risk models is limited. PMID:22237985

  18. Comparison of Nodal Risk Formula and MR Lymphography for Predicting Lymph Node Involvement in Prostate Cancer

    SciTech Connect

    Deserno, Willem M.L.L.G.; Debats, Oscar A.; Rozema, Tom; Fortuin, Ansje S.; Heesakkers, Roel A.M.; Hoogeveen, Yvonne; Peer, Petronella G.M.; Barentsz, Jelle O.; Lin, Emile N.J.T. van

    2011-09-01

    Purpose: To compare the nodal risk formula (NRF) as a predictor for lymph node (LN) metastasis in patients with prostate cancer with magnetic resonance lymphography (MRL) using Ultrasmall Super-Paramagnetic particles of Iron Oxide (USPIO) and with histology as gold standard. Methods and Materials: Logistic regression analysis was performed with the results of histopathological evaluation of the LN as dependent variable and the nodal risk according to the NRF and the result of MRL as independent input variables. Receiver operating characteristic (ROC) analysis was performed to assess the performance of the models. Results: The analysis included 375 patients. In the single-predictor regression models, the NRF and MRL results were both significantly (p <0.001) predictive of the presence of LN metastasis. In the models with both predictors included, NRF was nonsignificant (p = 0.126), but MRL remained significant (p <0.001). For NRF, sensitivity was 0.79 and specificity was 0.38; for MRL, sensitivity was 0.82 and specificity was 0.93. After a negative MRL result, the probability of LN metastasis is 4% regardless of the NRF result. After a positive MRL, the probability of having LN metastasis is 68%. Conclusions: MRL is a better predictor of the presence of LN metastasis than NRF. Using only the NRF can lead to a significant overtreatment on the pelvic LN by radiation therapy. When the MRL result is available, the NRF is no longer of added value.

  19. A Functional Copy-Number Variation in MAPKAPK2 Predicts Risk and Prognosis of Lung Cancer

    PubMed Central

    Liu, Bin; Yang, Lei; Huang, Binfang; Cheng, Mei; Wang, Hui; Li, Yinyan; Huang, Dongsheng; Zheng, Jian; Li, Qingchu; Zhang, Xin; Ji, Weidong; Zhou, Yifeng; Lu, Jiachun

    2012-01-01

    Mitogen-activated protein kinase-activated protein kinase 2 (MAPKAPK2) may promote cancer development and progression by inducing tumorigenesis and drug resistance. To assess whether the copy-number variation g.CNV-30450 located in the MAPKAPK2 promoter has any effect on lung cancer risk or prognosis, we investigated the association between g.CNV-30450 and cancer risk in three independent case-control studies of 2,332 individuals with lung cancer and 2,457 controls and the effects of g.CNV-30450 on cancer prognosis in 1,137 individuals with lung cancer with survival data in southern and eastern Chinese populations. We found that those subjects who had four copies of g.CNV-30450 had an increased cancer risk (odds ratio = 1.94, 95% confidence interval [CI] = 1.61–2.35) and a worse prognosis for individuals with lung cancer (with a median survival time of only 9 months) (hazard ratio = 1.47, 95% CI = 1.22–1.78) compared with those with two or three copies (with a median survival time of 14 months). Meanwhile, four copies of g.CNV-30450 significantly increased MAPKAPK2 expression, both in vitro and in vivo, compared with two or three copies. Our study establishes a robust association between the functional g.CNV-30450 in MAPKAPK2 and risk as well as prognosis of lung cancer, and it presents this functional copy-number variation as a potential biomarker for susceptibility to and prognosis for lung cancer. PMID:22883146

  20. Nomogram to Predict Risk of Lymph Node Metastases in Patients With Endometrioid Endometrial Cancer.

    PubMed

    Pollom, Erqi L; Conklin, Christopher M J; von Eyben, Rie; Folkins, Ann K; Kidd, Elizabeth A

    2016-09-01

    Pelvic lymphadenectomy in early-stage endometrial cancer is controversial, but the findings influence prognosis and treatment decisions. Noninvasive tools to identify women at high risk of lymph node metastasis can assist in determining the need for lymph node dissection and adjuvant treatment for patients who do not have a lymph node dissection performed initially. A retrospective review of surgical pathology was conducted for endometrioid endometrial adenocarcinoma at our institution. Univariate and multivariate logistic regression analysis of selected pathologic features were performed. A nomogram to predict for lymph node metastasis was constructed. From August 1996 to October 2013, 296 patients underwent total abdominal or laparoscopic hysterectomy, bilateral salpingo-oophorectomy, and selective lymphadenectomy for endometrioid endometrial adenocarcinoma. Median age at surgery was 62.7 yr (range, 24.9-93.6 yr). Median number of lymph nodes removed was 13 (range, 1-72). Of all patients, 38 (12.8%) had lymph node metastases. On univariate analysis, tumor size ≥4 cm, grade, lymphovascular space involvement, cervical stromal involvement, adnexal or serosal or parametrial involvement, positive pelvic washings, and deep (more than one half) myometrial invasion were all significantly associated with lymph node involvement. In a multivariate model, lymphovascular space involvement, deep myometrial invasion, and cervical stromal involvement remained significant predictors of nodal involvement, whereas tumor size of ≥4 cm was borderline significant. A lymph node predictive nomogram was constructed using these factors. Our nomogram can help estimate risk of nodal disease and aid in directing the need for additional surgery or adjuvant therapy in patients without lymph node surgery. Lymphovascular space involvement is the most important predictor for lymph node metastases, regardless of grade, and should be consistently assessed. PMID:26598977

  1. Unilateral Prostate Cancer Cannot be Accurately Predicted in Low-Risk Patients

    SciTech Connect

    Isbarn, Hendrik; Karakiewicz, Pierre I.; Vogel, Susanne

    2010-07-01

    Purpose: Hemiablative therapy (HAT) is increasing in popularity for treatment of patients with low-risk prostate cancer (PCa). The validity of this therapeutic modality, which exclusively treats PCa within a single prostate lobe, rests on accurate staging. We tested the accuracy of unilaterally unremarkable biopsy findings in cases of low-risk PCa patients who are potential candidates for HAT. Methods and Materials: The study population consisted of 243 men with clinical stage {<=}T2a, a prostate-specific antigen (PSA) concentration of <10 ng/ml, a biopsy-proven Gleason sum of {<=}6, and a maximum of 2 ipsilateral positive biopsy results out of 10 or more cores. All men underwent a radical prostatectomy, and pathology stage was used as the gold standard. Univariable and multivariable logistic regression models were tested for significant predictors of unilateral, organ-confined PCa. These predictors consisted of PSA, %fPSA (defined as the quotient of free [uncomplexed] PSA divided by the total PSA), clinical stage (T2a vs. T1c), gland volume, and number of positive biopsy cores (2 vs. 1). Results: Despite unilateral stage at biopsy, bilateral or even non-organ-confined PCa was reported in 64% of all patients. In multivariable analyses, no variable could clearly and independently predict the presence of unilateral PCa. This was reflected in an overall accuracy of 58% (95% confidence interval, 50.6-65.8%). Conclusions: Two-thirds of patients with unilateral low-risk PCa, confirmed by clinical stage and biopsy findings, have bilateral or non-organ-confined PCa at radical prostatectomy. This alarming finding questions the safety and validity of HAT.

  2. Does perceived risk predict breast cancer screening use? Findings from a prospective cohort study of female relatives from the Ontario site of the breast cancer family registry.

    PubMed

    Walker, Meghan J; Mirea, Lucia; Glendon, Gord; Ritvo, Paul; Andrulis, Irene L; Knight, Julia A; Chiarelli, Anna M

    2014-08-01

    While the relationship between perceived risk and breast cancer screening use has been studied extensively, most studies are cross-sectional. We prospectively examined this relationship among 913 women, aged 25-72 with varying levels of familial breast cancer risk from the Ontario site of the Breast Cancer Family Registry. Associations between perceived lifetime breast cancer risk and subsequent use of mammography, clinical breast examination (CBE) and genetic testing were assessed using logistic regression. Overall, perceived risk did not predict subsequent use of mammography, CBE or genetic testing. Among women at moderate/high familial risk, those reporting a perceived risk greater than 50% were significantly less likely to have a CBE (odds ratio (OR) = 0.52, 95% confidence interval (CI): 0.30-0.91, p = 0.04), and non-significantly less likely to have a mammogram (OR = 0.70, 95% CI: 0.40-1.20, p = 0.70) or genetic test (OR = 0.61, 95% CI: 0.34-1.10, p = 0.09) compared to women reporting a perceived risk of 50%. In contrast, among women at low familial risk, those reporting a perceived risk greater than 50% were non-significantly more likely to have a mammogram (OR = 1.13, 95% CI: 0.59-2.16, p = 0.78), CBE (OR = 1.11, 95% CI: 0.63-1.95, p = 0.74) or genetic test (OR = 1.29, 95% CI: 0.50-3.33, p = 0.35) compared to women reporting a perceived risk of 50%. Perceived risk did not significantly predict screening use overall, however this relationship may be moderated by level of familial risk. Results may inform risk education and management strategies for women with varying levels of familial breast cancer risk. PMID:24821458

  3. Age and Prostate-Specific Antigen Level Prior to Diagnosis Predict Risk of Death from Prostate Cancer

    PubMed Central

    MacKintosh, F. Roy; Sprenkle, Preston C.; Walter, Louise C.; Rawson, Lori; Karnes, R. Jeffrey; Morrell, Christopher H.; Kattan, Michael W.; Nawaf, Cayce B.; Neville, Thomas B.

    2016-01-01

    A single early prostate-specific antigen (PSA) level has been correlated with a higher likelihood of prostate cancer diagnosis and death in younger men. PSA testing in older men has been considered of limited utility. We evaluated prostate cancer death in relation to age and PSA level immediately prior to prostate cancer diagnosis. Using the Veterans Affairs database, we identified 230,081 men aged 50–89 years diagnosed with prostate cancer and at least one prior PSA test between 1999 and 2009. Prostate cancer-specific death over time was calculated for patients stratified by age group (e.g., 50–59 years, through 80–89 years) and PSA range at diagnosis (10 ranges) using Kaplan–Meier methods. Risk of 10-year prostate cancer mortality across age and PSA was compared using log-rank tests with a Bonferroni adjustment for multiple testing. 10.5% of men diagnosed with prostate cancer died of cancer during the 10-year study period (mean follow-up = 3.7 years). Higher PSA values prior to diagnosis predict a higher risk of death in all age groups (p < 0.0001). Within the same PSA range, older age groups are at increased risk for death from prostate cancer (p < 0.0001). For PSA of 7–10 ng/mL, cancer-specific death, 10 years after diagnosis, increased from 7% for age 50–59 years to 51% for age 80–89 years. Men older than 70 years are more likely to die of prostate cancer at any PSA level than younger men, suggesting prostate cancer remains a significant problem among older men (even those aged 80+) and deserves additional study. PMID:27446803

  4. Development and validation of risk prediction algorithms to estimate future risk of common cancers in men and women: prospective cohort study

    PubMed Central

    Hippisley-Cox, Julia; Coupland, Carol

    2015-01-01

    Objective To derive and validate a set of clinical risk prediction algorithm to estimate the 10-year risk of 11 common cancers. Design Prospective open cohort study using routinely collected data from 753 QResearch general practices in England. We used 565 practices to develop the scores and 188 for validation. Subjects 4.96 million patients aged 25–84 years in the derivation cohort; 1.64 million in the validation cohort. Patients were free of the relevant cancer at baseline. Methods Cox proportional hazards models in the derivation cohort to derive 10-year risk algorithms. Risk factors considered included age, ethnicity, deprivation, body mass index, smoking, alcohol, previous cancer diagnoses, family history of cancer, relevant comorbidities and medication. Measures of calibration and discrimination in the validation cohort. Outcomes Incident cases of blood, breast, bowel, gastro-oesophageal, lung, oral, ovarian, pancreas, prostate, renal tract and uterine cancers. Cancers were recorded on any one of four linked data sources (general practitioner (GP), mortality, hospital or cancer records). Results We identified 228 241 incident cases during follow-up of the 11 types of cancer. Of these 25 444 were blood; 41 315 breast; 32 626 bowel, 12 808 gastro-oesophageal; 32 187 lung; 4811 oral; 6635 ovarian; 7119 pancreatic; 35 256 prostate; 23 091 renal tract; 6949 uterine cancers. The lung cancer algorithm had the best performance with an R2 of 64.2%; D statistic of 2.74; receiver operating characteristic curve statistic of 0.91 in women. The sensitivity for the top 10% of women at highest risk of lung cancer was 67%. Performance of the algorithms in men was very similar to that for women. Conclusions We have developed and validated a prediction models to quantify absolute risk of 11 common cancers. They can be used to identify patients at high risk of cancers for prevention or further assessment. The algorithms could be integrated into clinical

  5. Evidence of Differential Effects of Vitamin D Receptor Variants on Epithelial Ovarian Cancer Risk by Predicted Vitamin D Status

    PubMed Central

    Prescott, Jennifer; Bertrand, Kimberly A.; Reid, Brett M.; Permuth-Wey, Jennifer; De Vivo, Immaculata; Cramer, Daniel W.; Terry, Kathryn L.; Tworoger, Shelley S.

    2014-01-01

    Introduction: Experimental studies suggest vitamin D inhibits ovarian carcinogenesis. Yet, epidemiologic studies of ovarian cancer risk and lifestyle correlates of vitamin D status, plasma 25-hydroxyvitamin D [25(OH)D], or vitamin D receptor (VDR) variants have been inconsistent. Objective: To evaluate VDR genetic associations by high vs. low predicted 25(OH)D, scores derived from known determinants of plasma 25(OH)D. To assess ovarian cancer associations with variants identified in genome-wide association studies (GWAS) of plasma 25(OH)D. Methods: We genotyped up to seven VDR and eight 25(OH)D GWAS variants in the Nurses’ Health Studies (562 cases, 1,553 controls) and New England Case–Control study (1,821 cases, 1,870 controls). We estimated haplotype scores using expectation-maximization-based algorithms. We used unconditional logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (CI). We combined study results using DerSimonian and Laird meta-analysis. Results: Ovarian cancer risk increased per A allele of rs7975232 (VDR; OR = 1.12, 95% CI = 1.01–1.25) among all women. When stratified by predicted 25(OH)D, ovarian cancer was associated with rs731236 (VDR; per C allele OR = 1.31) and rs7975232 (OR = 1.38) among women with high predicted 25(OH)D, but not among women with low levels (P ≤ 0.009). We also observed heterogeneity by predicted 25(OH)D for the ovarian cancer association with VDR 3′ end haplotypes (P = 0.009). Of 25(OH)D-associated GWAS loci, rs7041 was associated with reduced ovarian cancer risk (per T allele OR = 0.92, 95% CI = 0.85-0.99), which did not differ by predicted 25(OH)D status. Conclusion: Our study suggests an influence of VDR 3′ end variants on ovarian cancer risk may be observed in women with high predicted 25(OH)D, which remained even after taking multiple comparisons into consideration. Future studies are needed to confirm our results and explore further the relation

  6. Tumour morphology of early-onset breast cancers predicts breast cancer risk for first-degree relatives: the Australian Breast Cancer Family Registry

    PubMed Central

    2012-01-01

    Introduction We hypothesised that breast cancer risk for relatives of women with early-onset breast cancer could be predicted by tumour morphological features. Methods We studied female first-degree relatives of a population-based sample of 452 index cases with a first primary invasive breast cancer diagnosed before the age of 40 years. For the index cases, a standardised tumour morphology review had been conducted for all; estrogen (ER) and progesterone receptor (PR) status was available for 401 (89%), and 77 (17%) had a high-risk mutation in a breast cancer susceptibility gene or methylation of the BRCA1 promoter region in peripheral blood DNA. We calculated standardised incidence ratios (SIR) by comparing the number of mothers and sisters with breast cancer with the number expected based on Australian incidence rates specific for age and year of birth. Results Using Cox proportional hazards modelling, absence of extensive sclerosis, extensive intraductal carcinoma, absence of acinar and glandular growth patterns, and the presence of trabecular and lobular growth patterns were independent predictors with between a 1.8- and 3.1-fold increased risk for relatives (all P <0.02). Excluding index cases with known genetic predisposition or BRCA1 promoter methylation, absence of extensive sclerosis, circumscribed growth, extensive intraductal carcinoma and lobular growth pattern were independent predictors with between a 2.0- and 3.3-fold increased risk for relatives (all P <0.02). Relatives of the 128 (34%) index cases with none of these four features were at population risk (SIR = 1.03, 95% CI = 0.57 to 1.85) while relatives of the 37 (10%) index cases with two or more features were at high risk (SIR = 5.18, 95% CI = 3.22 to 8.33). Conclusions This wide variation in risks for relatives based on tumour characteristics could be of clinical value, help discover new breast cancer susceptibility genes and be an advance on the current clinical practice of using ER and PR as

  7. A predictive signature for therapy assignment and risk assessment in prostate cancer

    PubMed Central

    Bonci, Désirée; De Maria, Ruggero

    2015-01-01

    Prostate cancer remains the second leading cause of death in men. It is imperative to improve patient management in identifying bio-markers for personalized treatment. We demonstrated miR-15/miR-16 loss and miR-21 up-regulation and deregulation of their target genes, which represent a promising signature for ameliorating therapy assignment and risk assessment in prostate cancer. PMID:26697526

  8. Predictive Risk of Radiation Induced Cerebral Necrosis in Pediatric Brain Cancer Patients after VMAT Versus Proton Therapy

    PubMed Central

    Freund, Derek; Zhang, Rui; Sanders, Mary; Newhauser, Wayne

    2015-01-01

    Cancer of the brain and central nervous system (CNS) is the second most common of all pediatric cancers. Treatment of many of these cancers includes radiation therapy of which radiation induced cerebral necrosis (RICN) can be a severe and potentially devastating side effect. Risk factors for RICN include brain volume irradiated, the dose given per fraction and total dose. Thirteen pediatric patients were selected for this study to determine the difference in predicted risk of RICN when treating with volumetric modulated arc therapy (VMAT) compared to passively scattered proton therapy (PSPT) and intensity modulated proton therapy (IMPT). Plans were compared on the basis of dosimetric endpoints in the planned treatment volume (PTV) and brain and a radiobiological endpoint of RICN calculated using the Lyman-Kutcher-Burman probit model. Uncertainty tests were performed to determine if the predicted risk of necrosis was sensitive to positional errors, proton range errors and selection of risk models. Both PSPT and IMPT plans resulted in a significant increase in the maximum dose to the brain, a significant reduction in the total brain volume irradiated to low doses, and a significant lower predicted risk of necrosis compared with the VMAT plans. The findings of this study were upheld by the uncertainty analysis. PMID:25866999

  9. Common breast cancer susceptibility alleles and the risk of breast cancer for BRCA1 and BRCA2 mutation carriers: implications for risk prediction

    PubMed Central

    Antoniou, Antonis C; Beesley, Jonathan; McGuffog, Lesley; Sinilnikova, Olga M.; Healey, Sue; Neuhausen, Susan L.; Ding, Yuan Chun; Rebbeck, Timothy R.; Weitzel, Jeffrey N.; Lynch, Henry T.; Isaacs, Claudine; Ganz, Patricia A.; Tomlinson, Gail; Olopade, Olufunmilayo I.; Couch, Fergus J.; Wang, Xianshu; Lindor, Noralane M.; Pankratz, Vernon S.; Radice, Paolo; Manoukian, Siranoush; Peissel, Bernard; Zaffaroni, Daniela; Barile, Monica; Viel, Alessandra; Allavena, Anna; Dall’Olio, Valentina; Peterlongo, Paolo; Szabo, Csilla I.; Zikan, Michal; Claes, Kathleen; Poppe, Bruce; Foretova, Lenka; Mai, Phuong L.; Greene, Mark H.; Rennert, Gad; Lejbkowicz, Flavio; Glendon, Gord; Ozcelik, Hilmi; Andrulis, Irene L.; Thomassen, Mads; Gerdes, Anne-Marie; Sunde, Lone; Cruger, Dorthe; Jensen, Uffe Birk; Caligo, Maria; Friedman, Eitan; Kaufman, Bella; Laitman, Yael; Milgrom, Roni; Dubrovsky, Maya; Cohen, Shimrit; Borg, Ake; Jernström, Helena; Lindblom, Annika; Rantala, Johanna; Stenmark-Askmalm, Marie; Melin, Beatrice; Nathanson, Kate; Domchek, Susan; Jakubowska, Ania; Lubinski, Jan; Huzarski, Tomasz; Osorio, Ana; Lasa, Adriana; Durán, Mercedes; Tejada, Maria-Isabel; Godino, Javier; Benitez, Javier; Hamann, Ute; Kriege, Mieke; Hoogerbrugge, Nicoline; van der Luijt, Rob B; van Asperen, Christi J; Devilee, Peter; Meijers-Heijboer, E.J.; Blok, Marinus J; Aalfs, Cora M.; Hogervorst, Frans; Rookus, Matti; Cook, Margaret; Oliver, Clare; Frost, Debra; Conroy, Don; Evans, D. Gareth; Lalloo, Fiona; Pichert, Gabriella; Davidson, Rosemarie; Cole, Trevor; Cook, Jackie; Paterson, Joan; Hodgson, Shirley; Morrison, Patrick J.; Porteous, Mary E.; Walker, Lisa; Kennedy, M. John; Dorkins, Huw; Peock, Susan; Godwin, Andrew K.; Stoppa-Lyonnet, Dominique; de Pauw, Antoine; Mazoyer, Sylvie; Bonadona, Valérie; Lasset, Christine; Dreyfus, Hélène; Leroux, Dominique; Hardouin, Agnès; Berthet, Pascaline; Faivre, Laurence; Loustalot, Catherine; Noguchi, Tetsuro; Sobol, Hagay; Rouleau, Etienne; Nogues, Catherine; Frénay, Marc; Vénat-Bouvet, Laurence; Hopper, John L.; Daly, Mary B.; Terry, Mary B.; John, Esther M.; Buys, Saundra S.; Yassin, Yosuf; Miron, Alex; Goldgar, David; Singer, Christian F.; Dressler, Anne Catharina; Gschwantler-Kaulich, Daphne; Pfeiler, Georg; Hansen, Thomas V. O.; Jønson, Lars; Agnarsson, Bjarni A.; Kirchhoff, Tomas; Offit, Kenneth; Devlin, Vincent; Dutra-Clarke, Ana; Piedmonte, Marion; Rodriguez, Gustavo C.; Wakeley, Katie; Boggess, John F.; Basil, Jack; Schwartz, Peter E.; Blank, Stephanie V.; Toland, Amanda Ewart; Montagna, Marco; Casella, Cinzia; Imyanitov, Evgeny; Tihomirova, Laima; Blanco, Ignacio; Lazaro, Conxi; Ramus, Susan J.; Sucheston, Lara; Karlan, Beth Y.; Gross, Jenny; Schmutzler, Rita; Wappenschmidt, Barbara; Engel, Christoph; Meindl, Alfons; Lochmann, Magdalena; Arnold, Norbert; Heidemann, Simone; Varon-Mateeva, Raymonda; Niederacher, Dieter; Sutter, Christian; Deissler, Helmut; Gadzicki, Dorothea; Preisler-Adams, Sabine; Kast, Karin; Schönbuchner, Ines; Caldes, Trinidad; de la Hoya, Miguel; Aittomäki, Kristiina; Nevanlinna, Heli; Simard, Jacques; Spurdle, Amanda B.; Holland, Helene; Chen, Xiaoqing; Platte, Radka; Chenevix-Trench, Georgia; Easton, Douglas F.

    2010-01-01

    The known breast cancer (BC) susceptibility polymorphisms in FGFR2, TNRC9/TOX3, MAP3K1,LSP1 and 2q35 confer increased risks of BC for BRCA1 or BRCA2 mutation carriers. We evaluated the associations of three additional SNPs, rs4973768 in SLC4A7/NEK10, rs6504950 in STXBP4/COX11 and rs10941679 at 5p12 and reanalyzed the previous associations using additional carriers in a sample of 12,525 BRCA1 and 7,409 BRCA2 carriers. Additionally, we investigated potential interactions between SNPs and assessed the implications for risk prediction. The minor alleles of rs4973768 and rs10941679 were associated with increased BC risk for BRCA2 carriers (per-allele Hazard Ratio (HR)=1.10, 95%CI:1.03-1.18, p=0.006 and HR=1.09, 95%CI:1.01-1.19, p=0.03, respectively). Neither SNP was associated with BC risk for BRCA1 carriers and rs6504950 was not associated with BC for either BRCA1 or BRCA2 carriers. Of the nine polymorphisms investigated, seven were associated with BC for BRCA2 carriers (FGFR2, TOX3, MAP3K1, LSP1, 2q35, SLC4A7, 5p12, p-values:7×10−11-0.03), but only TOX3 and 2q35 were associated with the risk for BRCA1 carriers (p=0.0049, 0.03 respectively). All risk associated polymorphisms appear to interact multiplicatively on BC risk for mutation carriers. Based on the joint genotype distribution of the seven risk associated SNPs in BRCA2 mutation carriers, the 5% of BRCA2 carriers at highest risk (i.e. between 95th and 100th percentiles) were predicted to have a probability between 80% and 96% of developing BC by age 80, compared with 42-50% for the 5% of carriers at lowest risk. Our findings indicated that these risk differences may be sufficient to influence the clinical management of mutation carriers. PMID:21118973

  10. Tumor size interpretation for predicting cervical lymph node metastasis using a differentiated thyroid cancer risk model.

    PubMed

    Shi, Rong-Liang; Qu, Ning; Yang, Shu-Wen; Ma, Ben; Lu, Zhong-Wu; Wen, Duo; Sun, Guo-Hua; Wang, Yu; Ji, Qing-Hai

    2016-01-01

    Lymph node metastasis (LNM) is common in differentiated thyroid cancer (DTC), but management of clinically negative DTC is controversial. This study evaluated primary tumor size as a predictor of LNM. Multivariate logistic regression analysis was used for DTC patients who were treated with surgery between 2002 and 2012 in the Surveillance, Epidemiology, and End Results (SEER) database, to determine the association of tumor size at 10 mm increments with LNM. A predictive model was then developed to estimate the risk of LNM in DTC, using tumor size and other clinicopathological characteristics identified from the multivariate analysis. We identified 80,565 eligible patients with DTC in the SEER database. Final histology confirmed 9,896 (12.3%) cases affected with N1a disease and 8,194 (10.2%) cases with N1b disease. After the patients were classified into subgroups by tumor size, we found that the percentages of male sex, white race, follicular histology, gross extrathyroidal extension, lateral lymph node metastasis, and distant metastasis gradually increased with size. In multivariate analysis, tumor size was a significant independent prognostic factor for LNM; in particular, the odds ratio for lateral lymph node metastasis continued to increase by size relative to a 1-10 mm baseline. The coefficient for tumor size in the LNM predictive model waŝ0.20, indicating extra change in log(odds ratio) for LNM as 0.2 per unit increment in size relative to baseline. In conclusion, larger tumors are likely to have aggressive features and metastasize to a cervical compartment. Multistratification by size could provide more precise estimates of the likelihood of LNM before surgery. PMID:27574443

  11. Tumor size interpretation for predicting cervical lymph node metastasis using a differentiated thyroid cancer risk model

    PubMed Central

    Shi, Rong-liang; Qu, Ning; Yang, Shu-wen; Ma, Ben; Lu, Zhong-wu; Wen, Duo; Sun, Guo-hua; Wang, Yu; Ji, Qing-hai

    2016-01-01

    Lymph node metastasis (LNM) is common in differentiated thyroid cancer (DTC), but management of clinically negative DTC is controversial. This study evaluated primary tumor size as a predictor of LNM. Multivariate logistic regression analysis was used for DTC patients who were treated with surgery between 2002 and 2012 in the Surveillance, Epidemiology, and End Results (SEER) database, to determine the association of tumor size at 10 mm increments with LNM. A predictive model was then developed to estimate the risk of LNM in DTC, using tumor size and other clinicopathological characteristics identified from the multivariate analysis. We identified 80,565 eligible patients with DTC in the SEER database. Final histology confirmed 9,896 (12.3%) cases affected with N1a disease and 8,194 (10.2%) cases with N1b disease. After the patients were classified into subgroups by tumor size, we found that the percentages of male sex, white race, follicular histology, gross extrathyroidal extension, lateral lymph node metastasis, and distant metastasis gradually increased with size. In multivariate analysis, tumor size was a significant independent prognostic factor for LNM; in particular, the odds ratio for lateral lymph node metastasis continued to increase by size relative to a 1–10 mm baseline. The coefficient for tumor size in the LNM predictive model waŝ0.20, indicating extra change in log(odds ratio) for LNM as 0.2 per unit increment in size relative to baseline. In conclusion, larger tumors are likely to have aggressive features and metastasize to a cervical compartment. Multistratification by size could provide more precise estimates of the likelihood of LNM before surgery. PMID:27574443

  12. CHRNA5 Risk Variant Predicts Delayed Smoking Cessation and Earlier Lung Cancer Diagnosis—A Meta-Analysis

    PubMed Central

    Hung, Rayjean J.; Baker, Timothy; Horton, Amy; Culverhouse, Rob; Saccone, Nancy; Cheng, Iona; Deng, Bo; Han, Younghun; Hansen, Helen M.; Horsman, Janet; Kim, Claire; Lutz, Sharon; Rosenberger, Albert; Aben, Katja K.; Andrew, Angeline S.; Breslau, Naomi; Chang, Shen-Chih; Dieffenbach, Aida Karina; Dienemann, Hendrik; Frederiksen, Brittni; Han, Jiali; Hatsukami, Dorothy K.; Johnson, Eric O.; Pande, Mala; Wrensch, Margaret R.; McLaughlin, John; Skaug, Vidar; van der Heijden, Henricus F.; Wampfler, Jason; Wenzlaff, Angela; Woll, Penella; Zienolddiny, Shanbeh; Bickeböller, Heike; Brenner, Hermann; Duell, Eric J.; Haugen, Aage; Heinrich, Joachim; Hokanson, John E.; Hunter, David J.; Kiemeney, Lambertus A.; Lazarus, Philip; Le Marchand, Loic; Liu, Geoffrey; Mayordomo, Jose; Risch, Angela; Schwartz, Ann G.; Teare, Dawn; Wu, Xifeng; Wiencke, John K.; Yang, Ping; Zhang, Zuo-Feng; Spitz, Margaret R.; Kraft, Peter; Amos, Christopher I.; Bierut, Laura J.

    2015-01-01

    Background: Recent meta-analyses show strong evidence of associations among genetic variants in CHRNA5 on chromosome 15q25, smoking quantity, and lung cancer. This meta-analysis tests whether the CHRNA5 variant rs16969968 predicts age of smoking cessation and age of lung cancer diagnosis. Methods: Meta-analyses examined associations between rs16969968, age of quitting smoking, and age of lung cancer diagnosis in 24 studies of European ancestry (n = 29 072). In each dataset, we used Cox regression models to evaluate the association between rs16969968 and the two primary phenotypes (age of smoking cessation among ever smokers and age of lung cancer diagnosis among lung cancer case patients) and the secondary phenotype of smoking duration. Heterogeneity across studies was assessed with the Cochran Q test. All statistical tests were two-sided. Results: The rs16969968 allele (A) was associated with a lower likelihood of smoking cessation (hazard ratio [HR] = 0.95, 95% confidence interval [CI] = 0.91 to 0.98, P = .0042), and the AA genotype was associated with a four-year delay in median age of quitting compared with the GG genotype. Among smokers with lung cancer diagnoses, the rs16969968 genotype (AA) was associated with a four-year earlier median age of diagnosis compared with the low-risk genotype (GG) (HR = 1.08, 95% CI = 1.04 to 1.12, P = 1.1*10–5). Conclusion: These data support the clinical significance of the CHRNA5 variant rs16969968. It predicts delayed smoking cessation and an earlier age of lung cancer diagnosis in this meta-analysis. Given the existing evidence that this CHRNA5 variant predicts favorable response to cessation pharmacotherapy, these findings underscore the potential clinical and public health importance of rs16969968 in CHRNA5 in relation to smoking cessation success and lung cancer risk. PMID:25873736

  13. Alcohol and Cancer Risk

    MedlinePlus

    ... Overview Cancer Prevention Overview–for health professionals Research Alcohol and Cancer Risk On This Page What is ... in the risk of colorectal cancer. Research on alcohol consumption and other cancers: Numerous studies have examined ...

  14. Uterine Cancer Risk Questionnaire

    MedlinePlus

    ... University School of Medicine Uterine cancer (also called endometrial cancer) is one of the most common cancers in ... help protect themselves. To estimate your risk of uterine cancer and learn about ways to lower that risk, ...

  15. Methodology to predict long-term cancer survival from short-term data using Tobacco Cancer Risk and Absolute Cancer Cure models

    NASA Astrophysics Data System (ADS)

    Mould, R. F.; Lederman, M.; Tai, P.; Wong, J. K. M.

    2002-11-01

    Three parametric statistical models have been fully validated for cancer of the larynx for the prediction of long-term 15, 20 and 25 year cancer-specific survival fractions when short-term follow-up data was available for just 1-2 years after the end of treatment of the last patient. In all groups of cases the treatment period was only 5 years. Three disease stage groups were studied, T1N0, T2N0 and T3N0. The models are the Standard Lognormal (SLN) first proposed by Boag (1949 J. R. Stat. Soc. Series B 11 15-53) but only ever fully validated for cancer of the cervix, Mould and Boag (1975 Br. J. Cancer 32 529-50), and two new models which have been termed Tobacco Cancer Risk (TCR) and Absolute Cancer Cure (ACC). In each, the frequency distribution of survival times of defined groups of cancer deaths is lognormally distributed: larynx only (SLN), larynx and lung (TCR) and all cancers (ACC). All models each have three unknown parameters but it was possible to estimate a value for the lognormal parameter S a priori. By reduction to two unknown parameters the model stability has been improved. The material used to validate the methodology consisted of case histories of 965 patients, all treated during the period 1944-1968 by Dr Manuel Lederman of the Royal Marsden Hospital, London, with follow-up to 1988. This provided a follow-up range of 20- 44 years and enabled predicted long-term survival fractions to be compared with the actual survival fractions, calculated by the Kaplan and Meier (1958 J. Am. Stat. Assoc. 53 457-82) method. The TCR and ACC models are better than the SLN model and for a maximum short-term follow-up of 6 years, the 20 and 25 year survival fractions could be predicted. Therefore the numbers of follow-up years saved are respectively 14 years and 19 years. Clinical trial results using the TCR and ACC models can thus be analysed much earlier than currently possible. Absolute cure from cancer was also studied, using not only the prediction models which

  16. Fall-risk prediction in older adults with cancer: an unmet need.

    PubMed

    Wildes, Tanya M; Depp, Brittany; Colditz, Graham; Stark, Susan

    2016-09-01

    Falls in older adults with cancer are more common than in noncancer controls, yet no fall-risk screening tool has been validated in this population. We undertook a cross-sectional pilot study of the Falls Risk Questionnaire (FRQ) in 21 adults aged ≥65 receiving systemic cancer therapy. Participants completed the FRQ, geriatric assessment measures, and a measure of fear-of-falling. The recruitment rate was 87.5 %, with 95.2 % completion of the FRQ and additional geriatric assessment and quality of life measures. The FRQ correlated significantly with the Timed Up and Go test (Pearson r 0.479, p = 0.028). In addition, the FRQ score correlated directly with fear-of-falling and inversely with QOL, particularly physical health and neurotoxicity subscales. In conclusion, the FRQ was feasible in older adults receiving cancer therapy and correlates with measures of physical performance, functional status, and fear-of-falling. The FRQ may prove to be a valuable fall-risk screening tool to implement fall-prevention interventions in this vulnerable population of older adults with cancer. PMID:27341803

  17. Development of a novel approach for breast cancer prediction and early detection using minimally invasive procedures and molecular analysis: how cytomorphology became a breast cancer risk predictor.

    PubMed

    Masood, Shahla

    2015-01-01

    With enhanced public awareness, advances in breast imaging, and emphasis on early breast cancer detection and prevention, more women are seeking consultation to assess the status of their breast health. Risk assessment has become an integral part of established multi-disciplinary breast care, and breast cancer risk reduction interventions have received a great deal of attention. Similarly, interest in identification of high-risk individuals has increased significantly. Atypical proliferative changes in breast epithelial cells are ranked high among various known breast cancer risk factors and, in recent years, have been the subject of several investigations. Breast tissue and fluid in the ductal system provide a rich source of cells and biomarkers that have the potential to aid in the assessment of short-term risk of breast cancer development, and assess responses to interventional prevention efforts. There are three minimally invasive procedures currently being utilized to sample breast tissue in asymptomatic high-risk individuals. These procedures are: fine-needle aspiration biopsy, nipple aspiration fluid, and ductal lavage. In this review article, the merits and limitations of each procedure are presented, and the contribution of cytomorphology and molecular analysis in breast cancer prediction is highlighted. In addition, the role of Masood Cytology Index as a surrogate endpoint biomarker in chemopreventative trials is discussed. PMID:25556774

  18. Monocyte-derived macrophage assisted breast cancer cell invasion as a personalized, predictive metric to score metastatic risk

    PubMed Central

    Park, Keon-Young; Li, Gande; Platt, Manu O.

    2015-01-01

    Patient-to-patient variability in breast cancer progression complicates clinical treatment decisions. Of women undergoing prophylactic mastectomies, many may not have progressed to indolent forms of disease and could have benefited from milder, localized therapy. Tumor associated macrophages contribute significantly to tumor invasion and metastasis, with cysteine cathepsin proteases as important contributors. Here, a method is demonstrated by which variability in macrophage expression of cysteine cathepsins, their inhibitor cystatin C, and kinase activation can be used to train a multivariate model and score patients for invasion risk. These enzymatic profiles were used to predict macrophage-assisted MCF-7 breast cancer cell invasion in the trained computational model. To test these predictions, a priori, signals from monocytes isolated from women undergoing mastectomies were input to score their cancer invasion potential in a patient-specific manner, and successfully predicted that patient monocytes with highest predicted invasion indices matched those with more invasive initial diagnoses of the nine patients tested. Together this establishes proof-of-principle that personalized information acquired from minimally invasive blood draws may provide useful information to inform oncologists and patients of invasive/metastatic risk, helping to make decisions regarding radical mastectomy or milder, conservative treatments to save patients from hardship and surgical recovery. PMID:26349896

  19. Melanoma Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  20. Does perceived risk predict breast cancer screening use? Findings from a prospective cohort study of female relatives from the Ontario site of the Breast Cancer Family Registry

    PubMed Central

    Walker, Meghan J.; Mirea, Lucia; Glendon, Gord; Ritvo, Paul; Andrulis, Irene L.; Knight, Julia A.; Chiarelli, Anna M.

    2014-01-01

    Summary Objective While the relationship between perceived risk and adherence to breast cancer screening guidelines has been studied extensively, the majority of studies are cross-sectional. We prospectively examined this relationship among women with familial risk. Materials and Methods The prospective association between perceived risk and screening behaviors was examined in 913 women aged 25 to 72, with varying levels of familial breast cancer risk from the Ontario site of the Breast Cancer Family Registry. Associations between perceived lifetime breast cancer risk and subsequent use of screening mammography, clinical breast examination (CBE) and genetic testing were assessed using logistic regression. Results Overall, perceived risk did not predict subsequent use of screening mammography, CBE or genetic testing. Women at moderate/high familial risk who perceived their risk as greater than 50% were significantly less likely to have a CBE (odds ratio (OR) = 0.52, 95% confidence interval (CI): 0.30–0.91, p=0.04), and less likely to have a mammogram (OR = 0.70, 95% CI: 0.40–1.20, p=0.70) or genetic test (OR = 0.61, 95% CI: 0.34–1.10, p=0.09) compared to women who perceive their risk as 50%. In contrast, women at low familial risk who perceived their risk as greater than 50% were non-significantly more likely to have a mammogram (OR = 1.13, 95% CI: 0.59–2.16, p=0.78), CBE (OR = 1.11, 95% CI: 0.63–1.95, p=0.74) or genetic test (OR = 1.29, 95% CI: 0.50– 3.33, p=0.35) compared to women who perceive their risk as 50%. Conclusion Perceived risk did not significantly predict subsequent screening use overall, however this relationship may be moderated by level of familial risk. Results may inform risk education and management strategies among women with varying levels of familial breast cancer risk. PMID:24821458

  1. A Risk Prediction Model Based on Lymph-Node Metastasis in Poorly Differentiated–Type Intramucosal Gastric Cancer

    PubMed Central

    Pyo, Jeung Hui; Lee, Hyuk; Min, Byung-Hoon; Lee, Jun Haeng; Choi, Min Gew; Lee, Jun Ho; Sohn, Tae Sung; Bae, Jae Moon; Kim, Kyoung-Mee; Ahn, Hyeon Seon; Jung, Sin-Ho; Kim, Sung; Kim, Jae J.

    2016-01-01

    Background and Aim Endoscopic submucosal dissection (ESD) for undifferentiated type early gastric cancer is regarded as an investigational treatment. Few studies have tried to identify the risk factors that predict lymph-node metastasis (LNM) in intramucosal poorly differentiated adenocarcinomas (PDC). This study was designed to develop a risk scoring system (RSS) for predicting LNM in intramucosal PDC. Methods From January 2002 to July 2015, patients diagnosed with mucosa-confined PDC, among those who underwent curative gastrectomy with lymph node dissection were reviewed. A risk model based on independent predicting factors of LNM was developed, and its performance was internally validated using a split sample approach. Results Overall, LNM was observed in 5.2% (61) of 1169 patients. Four risk factors [Female sex, tumor size ≥ 3.2 cm, muscularis mucosa (M3) invasion, and lymphatic-vascular involvement] were significantly associated with LNM, which were incorporated into the RSS. The area under the receiver operating characteristic curve for predicting LNM after internal validation was 0.69 [95% confidence interval (CI), 0.59–0.79]. A total score of 2 points corresponded to the optimal RSS threshold with a discrimination of 0.75 (95% CI 0.69–0.81). The LNM rates were 1.6% for low risk (<2 points) and 8.9% for high-risk (≥2 points) patients, with a negative predictive value of 98.6% (95% CI 0.98–1.00). Conclusions A RSS could be useful in clinical practice to determine which patients with intramucosal PDC have low risk of LNM. PMID:27228258

  2. Constructing access in predictive medicine. Comparing classification for hereditary breast cancer risks in England, Germany and the Netherlands.

    PubMed

    Aarden, Erik; Van Hoyweghen, Ine; Horstman, Klasien

    2011-02-01

    In the first decade of the twenty-first century, predictive forms of medicine, largely associated with genetics, have become increasingly prominent. This has given rise to questions about the social consequences of this development, for example with regard to the distribution of health care access. Drawing on qualitative interviews with clinic staff and public officials and on document analyses, we analyse how access to risk assessment and monitoring for hereditary breast cancer predispositions in Germany, the Netherlands and England is produced through the interaction of risk classification and health care organisation. For each of the three countries, we show how particular combinations of genetic testing and family history data, classification of risks and allocation of monitoring services in practice contribute to specific forms of inclusion and exclusion. Thus, we show how risk assessment and monitoring in Germany attributes a large role to genetic testing; how family history information plays a large role in the Netherlands; and how regional differences in health care have a significant influence in England. On the basis of our case study, we argue that health care organisation is an important facet of the allocation of health care access, as it plays an important role in mediating the influence of risk assessment technologies and risk categories in health care access. We conclude that the allocation of risk assessment and monitoring in predictive medicine deserve more extensive political attention. PMID:21208700

  3. A rank-based transcriptional signature for predicting relapse risk of stage II colorectal cancer identified with proper data sources

    PubMed Central

    Zhao, Wenyuan; Chen, Beibei; Guo, Xin; Wang, Ruiping; Chang, Zhiqiang; Dong, Yu; Song, Kai; Wang, Wen; Qi, Lishuang; Gu, Yunyan; Wang, Chenguang; Yang, Da; Guo, Zheng

    2016-01-01

    The irreproducibility problem seriously hinders the studies on transcriptional signatures for predicting relapse risk of early stage colorectal cancer (CRC) patients. Through reviewing recently published 34 literatures for the development of CRC prognostic signatures based on gene expression profiles, we revealed a surprising phenomenon that 33 of these studies analyzed CRC samples with and without adjuvant chemotherapy together in the training and/or validation datasets. This data misuse problem could be partially attributed to the unclear and incomplete data annotation in public data sources. Furthermore, all the signatures proposed by these studies were based on risk scores summarized from gene expression levels, which are sensitive to experimental batch effects and risk compositions of the samples analyzed together. To avoid the above-mentioned problems, we carefully selected three qualified large datasets to develop and validate a signature consisting of three pairs of genes. The within-sample relative expression orderings of these gene pairs could robustly predict relapse risk of stage II CRC samples assessed in different laboratories. The transcriptional and functional analyses provided clear evidence that the high risk patients predicted by the proposed signature represent patients with micro-metastases. PMID:26967049

  4. Computer-aided detection of lung cancer: combining pulmonary nodule detection systems with a tumor risk prediction model

    NASA Astrophysics Data System (ADS)

    Setio, Arnaud A. A.; Jacobs, Colin; Ciompi, Francesco; van Riel, Sarah J.; Winkler Wille, Mathilde M.; Dirksen, Asger; van Rikxoort, Eva M.; van Ginneken, Bram

    2015-03-01

    Computer-Aided Detection (CAD) has been shown to be a promising tool for automatic detection of pulmonary nodules from computed tomography (CT) images. However, the vast majority of detected nodules are benign and do not require any treatment. For effective implementation of lung cancer screening programs, accurate identification of malignant nodules is the key. We investigate strategies to improve the performance of a CAD system in detecting nodules with a high probability of being cancers. Two strategies were proposed: (1) combining CAD detections with a recently published lung cancer risk prediction model and (2) the combination of multiple CAD systems. First, CAD systems were used to detect the nodules. Each CAD system produces markers with a certain degree of suspicion. Next, the malignancy probability was automatically computed for each marker, given nodule characteristics measured by the CAD system. Last, CAD degree of suspicion and malignancy probability were combined using the product rule. We evaluated the method using 62 nodules which were proven to be malignant cancers, from 180 scans of the Danish Lung Cancer Screening Trial. The malignant nodules were considered as positive samples, while all other findings were considered negative. Using a product rule, the best proposed system achieved an improvement in sensitivity, compared to the best individual CAD system, from 41.9% to 72.6% at 2 false positives (FPs)/scan and from 56.5% to 88.7% at 8 FPs/scan. Our experiment shows that combining a nodule malignancy probability with multiple CAD systems can increase the performance of computerized detection of lung cancer.

  5. Predicting the Risk of Recurrent Adenoma and Incident Colorectal Cancer Based on Findings of the Baseline Colonoscopy

    PubMed Central

    Fairley, Kimberly J; Li, Jinhong; Komar, Michael; Steigerwalt, Nancy; Erlich, Porat

    2014-01-01

    Objectives: The decision tree underlying current practice guidelines for post polypectomy surveillance relies on risk stratification based on predictive attributes gleaned from adenomas removed on screening colonoscopy examination. Our primary aim was to estimate the magnitude of association between baseline adenoma attributes and the risk of adenoma recurrence and invasive colorectal adenocarcinoma (CRC). Our secondary aims were to estimate the adenoma detection rate (ADR) of surveillance compared with screening colonoscopies and describe time trends in preventive colonoscopy utilization. Methods: We used prospective analyses of retrospectively collected clinical data from electronic health records. A cohort of primary care patients eligible for colorectal cancer screening was assembled encompassing 110,452 subjects, of which 3,300 had adenomas removed on screening examination. Of those patients who had a follow-up surveillance colonoscopy (defined as a patient with a documented adenoma on prior colonoscopy) recorded during the study period, 537 had a recurrent adenoma. Results: Of those recurrent adenomas, 354 had a high-risk attributes. High-risk attributes were described at >3 adenomas, at least one adenoma >10 mm in size, high-grade dysplasia, or villous features. The risk of developing invasive CRC among post polypectomy patients was significantly higher if the baseline adenomas displayed any of the following attributes: more numerous than 3 (4.3-fold higher risk, 95% confidence interval (CI) low, high 1.4, 12.9), larger than 10 mm in size (5.2-fold higher risk, 95% CI low, high 1.8, 15.1), high-grade dysplasia (13.2-fold risk, 95% CI low, high 2.8, 62.1), or villous features (7.4-fold higher risk, 95% CI low, high 2.5, 21.5). These attributes combined added a net value of 22.8% to the probability of correctly predicting CRC. There was a threefold increase in surveillance utilization relative to screening from 2005 to 2011. The ADR of surveillance (34

  6. Predicting cancer outcome

    SciTech Connect

    Gardner, S N; Fernandes, M

    2005-03-24

    We read with interest the paper by Michiels et al on the prediction of cancer with microarrays and the commentary by Ioannidis listing the potential as well as the limitations of this approach (February 5, p 488 and 454). Cancer is a disease characterized by complex, heterogeneous mechanisms and studies to define factors that can direct new drug discovery and use should be encouraged. However, this is easier said than done. Casti teaches that a better understanding does not necessarily extrapolate to better prediction, and that useful prediction is possible without complete understanding (1). To attempt both, explanation and prediction, in a single nonmathematical construct, is a tall order (Figure 1).

  7. Genetically Predicted Body Mass Index and Breast Cancer Risk: Mendelian Randomization Analyses of Data from 145,000 Women of European Descent

    PubMed Central

    Guo, Yan; Warren Andersen, Shaneda; Shu, Xiao-Ou; Michailidou, Kyriaki; Bolla, Manjeet K.; Wang, Qin; Garcia-Closas, Montserrat; Milne, Roger L.; Schmidt, Marjanka K.; Chang-Claude, Jenny; Dunning, Allison; Bojesen, Stig E.; Ahsan, Habibul; Aittomäki, Kristiina; Andrulis, Irene L.; Anton-Culver, Hoda; Beckmann, Matthias W.; Beeghly-Fadiel, Alicia; Benitez, Javier; Bogdanova, Natalia V.; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Brand, Judith; Brauch, Hiltrud; Brenner, Hermann; Brüning, Thomas; Burwinkel, Barbara; Casey, Graham; Chenevix-Trench, Georgia; Couch, Fergus J.; Cross, Simon S.; Czene, Kamila; Dörk, Thilo; Dumont, Martine; Fasching, Peter A.; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fostira, Florentia; Gammon, Marilie; Giles, Graham G.; Guénel, Pascal; Haiman, Christopher A.; Hamann, Ute; Hooning, Maartje J.; Hopper, John L.; Jakubowska, Anna; Jasmine, Farzana; Jenkins, Mark; John, Esther M.; Johnson, Nichola; Jones, Michael E.; Kabisch, Maria; Knight, Julia A.; Koppert, Linetta B.; Kosma, Veli-Matti; Kristensen, Vessela; Le Marchand, Loic; Lee, Eunjung; Li, Jingmei; Lindblom, Annika; Lubinski, Jan; Malone, Kathi E.; Mannermaa, Arto; Margolin, Sara; McLean, Catriona; Meindl, Alfons; Neuhausen, Susan L.; Nevanlinna, Heli; Neven, Patrick; Olson, Janet E.; Perez, Jose I. A.; Perkins, Barbara; Phillips, Kelly-Anne; Pylkäs, Katri; Rudolph, Anja; Santella, Regina; Sawyer, Elinor J.; Schmutzler, Rita K.; Seynaeve, Caroline; Shah, Mitul; Shrubsole, Martha J.; Southey, Melissa C.; Swerdlow, Anthony J.; Toland, Amanda E.; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Ursin, Giske; Van Der Luijt, Rob B.; Verhoef, Senno; Whittemore, Alice S.; Winqvist, Robert; Zhao, Hui; Zhao, Shilin; Hall, Per; Simard, Jacques; Kraft, Peter; Hunter, David; Easton, Douglas F.; Zheng, Wei

    2016-01-01

    Background Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors. Methods We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases  =  46,325, controls  =  42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively. Results In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR]  =  0.65 per 5 kg/m2 increase, 95% confidence interval [CI]: 0.56–0.75, p = 3.32 × 10−10). The associations were similar for both premenopausal (OR   =   0.44, 95% CI:0.31–0.62, p  =  9.91 × 10−8) and postmenopausal breast cancer (OR  =  0.57, 95% CI: 0.46–0.71, p  =  1.88 × 10−8). This association was replicated in the data from the DRIVE consortium (OR  =  0.72, 95% CI: 0.60–0.84, p   =   1.64 × 10−7). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p

  8. Stomach Cancer Risk Questionnaire

    MedlinePlus

    ... Jewish Hospital and Washington University School of Medicine Stomach cancer is fairly rare in the US, but ... the early stages. To estimate your risk of stomach cancer and learn about ways to lower that ...

  9. Race-specific genetic risk score is more accurate than nonrace-specific genetic risk score for predicting prostate cancer and high-grade diseases.

    PubMed

    Na, Rong; Ye, Dingwei; Qi, Jun; Liu, Fang; Lin, Xiaoling; Helfand, Brian T; Brendler, Charles B; Conran, Carly; Gong, Jian; Wu, Yishuo; Gao, Xu; Chen, Yaqing; Zheng, S Lilly; Mo, Zengnan; Ding, Qiang; Sun, Yinghao; Xu, Jianfeng

    2016-01-01

    Genetic risk score (GRS) based on disease risk-associated single nucleotide polymorphisms (SNPs) is an informative tool that can be used to provide inherited information for specific diseases in addition to family history. However, it is still unknown whether only SNPs that are implicated in a specific racial group should be used when calculating GRSs. The objective of this study is to compare the performance of race-specific GRS and nonrace-specific GRS for predicting prostate cancer (PCa) among 1338 patients underwent prostate biopsy in Shanghai, China. A race-specific GRS was calculated with seven PCa risk-associated SNPs implicated in East Asians (GRS7), and a nonrace-specific GRS was calculated based on 76 PCa risk-associated SNPs implicated in at least one racial group (GRS76). The means of GRS7 and GRS76 were 1.19 and 1.85, respectively, in the study population. Higher GRS7 and GRS76 were independent predictors for PCa and high-grade PCa in univariate and multivariate analyses. GRS7 had a better area under the receiver-operating curve (AUC) than GRS76 for discriminating PCa (0.602 vs 0.573) and high-grade PCa (0.603 vs 0.575) but did not reach statistical significance. GRS7 had a better (up to 13% at different cutoffs) positive predictive value (PPV) than GRS76. In conclusion, a race-specific GRS is more robust and has a better performance when predicting PCa in East Asian men than a GRS calculated using SNPs that are not shown to be associated with East Asians. PMID:27140652

  10. Race-specific genetic risk score is more accurate than nonrace-specific genetic risk score for predicting prostate cancer and high-grade diseases

    PubMed Central

    Na, Rong; Ye, Dingwei; Qi, Jun; Liu, Fang; Lin, Xiaoling; Helfand, Brian T; Brendler, Charles B; Conran, Carly; Gong, Jian; Wu, Yishuo; Gao, Xu; Chen, Yaqing; Zheng, S Lilly; Mo, Zengnan; Ding, Qiang; Sun, Yinghao; Xu, Jianfeng

    2016-01-01

    Genetic risk score (GRS) based on disease risk-associated single nucleotide polymorphisms (SNPs) is an informative tool that can be used to provide inherited information for specific diseases in addition to family history. However, it is still unknown whether only SNPs that are implicated in a specific racial group should be used when calculating GRSs. The objective of this study is to compare the performance of race-specific GRS and nonrace-specific GRS for predicting prostate cancer (PCa) among 1338 patients underwent prostate biopsy in Shanghai, China. A race-specific GRS was calculated with seven PCa risk-associated SNPs implicated in East Asians (GRS7), and a nonrace-specific GRS was calculated based on 76 PCa risk-associated SNPs implicated in at least one racial group (GRS76). The means of GRS7 and GRS76 were 1.19 and 1.85, respectively, in the study population. Higher GRS7 and GRS76 were independent predictors for PCa and high-grade PCa in univariate and multivariate analyses. GRS7 had a better area under the receiver-operating curve (AUC) than GRS76 for discriminating PCa (0.602 vs 0.573) and high-grade PCa (0.603 vs 0.575) but did not reach statistical significance. GRS7 had a better (up to 13% at different cutoffs) positive predictive value (PPV) than GRS76. In conclusion, a race-specific GRS is more robust and has a better performance when predicting PCa in East Asian men than a GRS calculated using SNPs that are not shown to be associated with East Asians. PMID:27140652

  11. The PER (Preoperative Esophagectomy Risk) Score: A Simple Risk Score to Predict Short-Term and Long-Term Outcome in Patients with Surgically Treated Esophageal Cancer

    PubMed Central

    Reeh, Matthias; Metze, Johannes; Uzunoglu, Faik G.; Nentwich, Michael; Ghadban, Tarik; Wellner, Ullrich; Bockhorn, Maximilian; Kluge, Stefan; Izbicki, Jakob R.; Vashist, Yogesh K.

    2016-01-01

    Abstract Esophageal resection in patients with esophageal cancer (EC) is still associated with high mortality and morbidity rates. We aimed to develop a simple preoperative risk score for the prediction of short-term and long-term outcomes for patients with EC treated by esophageal resection. In total, 498 patients suffering from esophageal carcinoma, who underwent esophageal resection, were included in this retrospective cohort study. Three preoperative esophagectomy risk (PER) groups were defined based on preoperative functional evaluation of different organ systems by validated tools (revised cardiac risk index, model for end-stage liver disease score, and pulmonary function test). Clinicopathological parameters, morbidity, and mortality as well as disease-free survival (DFS) and overall survival (OS) were correlated to the PER score. The PER score significantly predicted the short-term outcome of patients with EC who underwent esophageal resection. PER 2 and PER 3 patients had at least double the risk of morbidity and mortality compared to PER 1 patients. Furthermore, a higher PER score was associated with shorter DFS (P < 0.001) and OS (P < 0.001). The PER score was identified as an independent predictor of tumor recurrence (hazard ratio [HR] 2.1; P < 0.001) and OS (HR 2.2; P < 0.001). The PER score allows preoperative objective allocation of patients with EC into different risk categories for morbidity, mortality, and long-term outcomes. Thus, multicenter studies are needed for independent validation of the PER score. PMID:26886613

  12. Prostate-specific antigen density predicts favorable pathology and biochemical recurrence in patients with intermediate-risk prostate cancer.

    PubMed

    Kang, Ho Won; Jung, Hae Do; Lee, Joo Yong; Kwon, Jong Kyou; Jeh, Seong Uk; Cho, Kang Su; Ham, Won Sik; Choi, Young Deuk

    2016-01-01

    This study was designed to identify clinical predictors of favorable pathology and biochemical recurrence (BCR) in patients with intermediate-risk prostate cancer (IRPCa). Between 2006 and 2012, clinicopathological and oncological data from 203 consecutive men undergoing robot-assisted radical prostatectomy (RARP) for IRPCa were reviewed in a single-institutional retrospective study. Favorable pathology was defined as Gleason score ≤6 and organ-confined cancer as detected by surgical pathology. Logistic regression analysis was used to determine predictive variables of favorable pathology, and the Kaplan-Meier and multivariate Cox regression model were used to estimate BCR-free survival after RARP. Overall, 38 patients (18.7%) had favorable pathology after RARP. Lower quartile prostate-specific antigen density (PSAD) was associated with favorable pathology compared to the highest quartile PSAD after adjusting for preoperative PSA, clinical stage and biopsy Gleason score (odds ratio, 5.42; 95% confidence interval, 1.01-28.97; P = 0.048). During a median 37.8 (interquartile range, 24.6-60.2) months of follow-up, 66 patients experienced BCR. There were significant differences with regard to BCR free survival by PSAD quartiles (log rank, P = 0.003). Using a multivariable Cox proportion hazard model, PSAD was found to be an independent predictor of BCR in patients with IRPCa after RARP (hazard ratio, 4.641; 95% confidence interval, 1.109-19.417; P = 0.036). The incorporation of the PSAD into risk assessments might provide additional prognostic information and identify some patients in whom active surveillance would be appropriate in patients with IRPCa. PMID:26178393

  13. Use of CA125 and HE4 serum markers to predict ovarian cancer in elevated-risk women

    PubMed Central

    Karlan, Beth Y.; Thorpe, Jason; Watabayashi, Kate; Drescher, Charles W.; Palomares, Melanie; Daly, Mary B.; Paley, Pam; Hillard, Paula; Andersen, M Robyn; Anderson, Garnet; Drapkin, Ronny; Urban, Nicole

    2014-01-01

    Background Serum markers are used prior to pelvic imaging to improve specificity and positive predictive value (PPV) of ovarian cancer multimodal screening strategies. Methods We conducted a randomized controlled pilot trial to estimate surgical PPV of a “2 of 3 tests positive” screening rule, and to compare use of HE4 as a 1st-line (Arm 1) vs. a 2nd-line (Arm 2) screen, in women at high and elevated risk for EOC at five study sites. Semi-annual screening was offered to 208 women aged 25-80 with deleterious BRCA germ-line mutations, and to 834 women aged 35-80 with pedigrees suggesting inherited susceptibility. Annual screening was offered to 130 women aged 45-80 (Risk Group 3) with epidemiologic and serum marker risk factors. Rising marker levels were identified using the parametric empirical Bayes algorithm. Results Both strategies yielded surgical PPV above 25%. Protocol-indicated surgery was performed in six women, identifying two ovarian malignancies and yielding a surgical PPV in both arms combined of 33% (95% CI: 4%-78%), 25% in Arm 1 and 50% in Arm 2. Surgical consultation was recommended for 37 women (26 in Arm 1, 11 in Arm 2). Based on 12 women with at least 2 of 3 tests positive (CA125, HE4 or imaging), an intent-to-treat analysis yielded PPV of 14% in Arm 1 and 20% in Arm 2. Conclusions Positive screens were more frequent when HE4 was included in the primary screen. Impact. HE4 may be useful as a confirmatory screen when rising CA125 is used alone as a primary screen. PMID:24789859

  14. Risk Prediction for Breast, Endometrial, and Ovarian Cancer in White Women Aged 50 y or Older: Derivation and Validation from Population-Based Cohort Studies

    PubMed Central

    Pfeiffer, Ruth M.; Park, Yikyung; Kreimer, Aimée R.; Lacey, James V.; Pee, David; Greenlee, Robert T.; Buys, Saundra S.; Hollenbeck, Albert; Rosner, Bernard; Gail, Mitchell H.; Hartge, Patricia

    2013-01-01

    Background Breast, endometrial, and ovarian cancers share some hormonal and epidemiologic risk factors. While several models predict absolute risk of breast cancer, there are few models for ovarian cancer in the general population, and none for endometrial cancer. Methods and Findings Using data on white, non-Hispanic women aged 50+ y from two large population-based cohorts (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial [PLCO] and the National Institutes of Health–AARP Diet and Health Study [NIH-AARP]), we estimated relative and attributable risks and combined them with age-specific US-population incidence and competing mortality rates. All models included parity. The breast cancer model additionally included estrogen and progestin menopausal hormone therapy (MHT) use, other MHT use, age at first live birth, menopausal status, age at menopause, family history of breast or ovarian cancer, benign breast disease/biopsies, alcohol consumption, and body mass index (BMI); the endometrial model included menopausal status, age at menopause, BMI, smoking, oral contraceptive use, MHT use, and an interaction term between BMI and MHT use; the ovarian model included oral contraceptive use, MHT use, and family history or breast or ovarian cancer. In independent validation data (Nurses' Health Study cohort) the breast and ovarian cancer models were well calibrated; expected to observed cancer ratios were 1.00 (95% confidence interval [CI]: 0.96–1.04) for breast cancer and 1.08 (95% CI: 0.97–1.19) for ovarian cancer. The number of endometrial cancers was significantly overestimated, expected/observed = 1.20 (95% CI: 1.11–1.29). The areas under the receiver operating characteristic curves (AUCs; discriminatory power) were 0.58 (95% CI: 0.57–0.59), 0.59 (95% CI: 0.56–0.63), and 0.68 (95% CI: 0.66–0.70) for the breast, ovarian, and endometrial models, respectively. Conclusions These models predict absolute risks for breast, endometrial, and

  15. Discovery of potential prognostic long non-coding RNA biomarkers for predicting the risk of tumor recurrence of breast cancer patients

    PubMed Central

    Zhou, Meng; Zhong, Lei; Xu, Wanying; Sun, Yifan; Zhang, Zhaoyue; Zhao, Hengqiang; Yang, Lei; Sun, Jie

    2016-01-01

    Deregulation of long non-coding RNAs (lncRNAs) expression has been proven to be involved in the development and progression of cancer. However, expression pattern and prognostic value of lncRNAs in breast cancer recurrence remain unclear. Here, we analyzed lncRNA expression profiles of breast cancer patients who did or did not develop recurrence by repurposing existing microarray datasets from the Gene Expression Omnibus database, and identified 12 differentially expressed lncRNAs that were closely associated with tumor recurrence of breast cancer patients. We constructed a lncRNA-focus molecular signature by the risk scoring method based on the expression levels of 12 relapse-related lncRNAs from the discovery cohort, which classified patients into high-risk and low-risk groups with significantly different recurrence-free survival (HR = 2.72, 95% confidence interval 2.07–3.57; p = 4.8e-13). The 12-lncRNA signature also represented similar prognostic value in two out of three independent validation cohorts. Furthermore, the prognostic power of the 12-lncRNA signature was independent of known clinical prognostic factors in at least two cohorts. Functional analysis suggested that the predicted relapse-related lncRNAs may be involved in known breast cancer-related biological processes and pathways. Our results highlighted the potential of lncRNAs as novel candidate biomarkers to identify breast cancer patients at high risk of tumor recurrence. PMID:27503456

  16. Discovery of potential prognostic long non-coding RNA biomarkers for predicting the risk of tumor recurrence of breast cancer patients.

    PubMed

    Zhou, Meng; Zhong, Lei; Xu, Wanying; Sun, Yifan; Zhang, Zhaoyue; Zhao, Hengqiang; Yang, Lei; Sun, Jie

    2016-01-01

    Deregulation of long non-coding RNAs (lncRNAs) expression has been proven to be involved in the development and progression of cancer. However, expression pattern and prognostic value of lncRNAs in breast cancer recurrence remain unclear. Here, we analyzed lncRNA expression profiles of breast cancer patients who did or did not develop recurrence by repurposing existing microarray datasets from the Gene Expression Omnibus database, and identified 12 differentially expressed lncRNAs that were closely associated with tumor recurrence of breast cancer patients. We constructed a lncRNA-focus molecular signature by the risk scoring method based on the expression levels of 12 relapse-related lncRNAs from the discovery cohort, which classified patients into high-risk and low-risk groups with significantly different recurrence-free survival (HR = 2.72, 95% confidence interval 2.07-3.57; p = 4.8e-13). The 12-lncRNA signature also represented similar prognostic value in two out of three independent validation cohorts. Furthermore, the prognostic power of the 12-lncRNA signature was independent of known clinical prognostic factors in at least two cohorts. Functional analysis suggested that the predicted relapse-related lncRNAs may be involved in known breast cancer-related biological processes and pathways. Our results highlighted the potential of lncRNAs as novel candidate biomarkers to identify breast cancer patients at high risk of tumor recurrence. PMID:27503456

  17. Potential usefulness of a topic model-based categorization of lung cancers as quantitative CT biomarkers for predicting the recurrence risk after curative resection

    NASA Astrophysics Data System (ADS)

    Kawata, Y.; Niki, N.; Ohmatsu, H.; Satake, M.; Kusumoto, M.; Tsuchida, T.; Aokage, K.; Eguchi, K.; Kaneko, M.; Moriyama, N.

    2014-03-01

    In this work, we investigate a potential usefulness of a topic model-based categorization of lung cancers as quantitative CT biomarkers for predicting the recurrence risk after curative resection. The elucidation of the subcategorization of a pulmonary nodule type in CT images is an important preliminary step towards developing the nodule managements that are specific to each patient. We categorize lung cancers by analyzing volumetric distributions of CT values within lung cancers via a topic model such as latent Dirichlet allocation. Through applying our scheme to 3D CT images of nonsmall- cell lung cancer (maximum lesion size of 3 cm) , we demonstrate the potential usefulness of the topic model-based categorization of lung cancers as quantitative CT biomarkers.

  18. Barrett's esophagus. Correlation between mucin histochemistry, flow cytometry, and histologic diagnosis for predicting increased cancer risk.

    PubMed Central

    Haggitt, R. C.; Reid, B. J.; Rabinovitch, P. S.; Rubin, C. E.

    1988-01-01

    A predominance of sulfated mucin in the nongoblet columnar cells of Barrett's specialized metaplastic epithelium has been postulated to be a form of mild dysplasia and to indicate an increased risk of adenocarcinoma. Flow cytometry for the analysis of nuclear DNA content and cell cycle parameters has also been postulated to be an objective aid in the diagnosis of dysplasia and carcinoma in Barrett's esophagus. The authors investigated the relationship among sulfated mucin, flow cytometric data, and histologic diagnosis in each of 152 biopsies from 42 patients who had Barrett's specialized metaplastic epithelium. Sulfated mucin, as detected by the high iron diamine-Alcian blue stain, was present in biopsies from 8 of 11 (73%) patients with the histologic diagnosis of dysplasia or carcinoma, in 7 of 9 (78%) patients whose biopsies were indefinite for dysplasia, and in 12 of 22 (55%) patients whose biopsies were negative for dysplasia (P = 0.37). Sulfated mucins predominated in 9%, 22%, and 9% of the patients, respectively (P = 0.56). Abnormal flow cytometry (aneuploidy or increased G2/tetraploid fraction) was found in all patients with the histologic diagnosis of dysplasia or carcinoma, in 3 of 9 (33%) indefinite for dysplasia, and in 1 of 22 (5%) negative for dysplasia (P = less than 0.0001). Neither the presence nor the predominance of sulfated mucin in the specialized metaplastic epithelium of Barrett's esophagus has sufficiently high sensitivity or specificity for dysplasia or carcinoma to be of value in managing patients. Abnormal flow cytometry shows excellent correlation with the histologic diagnosis of dysplasia and carcinoma; it detects a subset of patients whose biopsies are histologically indefinite or negative for dysplasia, but who have flow cytometric abnormalities similar to those otherwise seen only in dysplasia and carcinoma. Images Figure 1 Figure 2 Figure 3 PMID:3354644

  19. Age and Cancer Risk

    PubMed Central

    White, Mary C.; Holman, Dawn M.; Boehm, Jennifer E.; Peipins, Lucy A.; Grossman, Melissa; Henley, S. Jane

    2015-01-01

    This article challenges the idea that cancer cannot be prevented among older adults by examining different aspects of the relationship between age and cancer. Although the sequential patterns of aging cannot be changed, several age-related factors that contribute to disease risk can be. For most adults, age is coincidentally associated with preventable chronic conditions, avoidable exposures, and modifiable risk behaviors that are causally associated with cancer. Midlife is a period of life when the prevalence of multiple cancer risk factors is high and incidence rates begin to increase for many types of cancer. However, current evidence suggests that for most adults, cancer does not have to be an inevitable consequence of growing older. Interventions that support healthy environments, help people manage chronic conditions, and promote healthy behaviors may help people make a healthier transition from midlife to older age and reduce the likelihood of developing cancer. Because the number of adults reaching older ages is increasing rapidly, the number of new cancer cases will also increase if current incidence rates remain unchanged. Thus, the need to translate the available research into practice to promote cancer prevention, especially for adults at midlife, has never been greater. PMID:24512933

  20. Functional Polymorphisms of CHRNA3 Predict Risks of Chronic Obstructive Pulmonary Disease and Lung Cancer in Chinese

    PubMed Central

    Yang, Lei; Qiu, Fuman; Lu, Xiaoxiao; Huang, Dongsheng; Ma, Guanpei; Guo, Yuan; Hu, Min; Zhou, Yumin; Pan, Mingan; Tan, Yigang; Zhong, Haibo; Ji, Weidong; Wei, Qingyi; Ran, Pixin; Zhong, Nanshan; Zhou, Yifeng; Lu, Jiachun

    2012-01-01

    Recently, several genome-wide association studies (GWAS) have identified many susceptible single nucleotide polymorphisms (SNPs) for chronic obstructive pulmonary disease (COPD) and lung cancer which are two closely related diseases. Among those SNPs, some of them are shared by both the diseases, reflecting there is possible genetic similarity between the diseases. Here we tested the hypothesis that whether those shared SNPs are common predictor for risks or prognosis of COPD and lung cancer. Two SNPs (rs6495309 and rs1051730) located in nicotinic acetylcholine receptor alpha 3 (CHRNA3) gene were genotyped in 1511 patients with COPD, 1559 lung cancer cases and 1677 controls in southern and eastern Chinese populations. We found that the rs6495309CC and rs6495309CT/CC variant genotypes were associated with increased risks of COPD (OR = 1.32, 95% C.I. = 1.14–1.54) and lung cancer (OR = 1.57; 95% CI = 1.31–1.87), respectively. The rs6495309CC genotype contributed to more rapid decline of annual Forced expiratory volume in one second (FEV1) in both COPD cases and controls (P<0.05), and it was associated with advanced stages of COPD (P = 0.033); the rs6495309CT/CC genotypes conferred a poor survival for lung cancer (HR = 1.41, 95%CI = 1.13–1.75). The luciferase assays further showed that nicotine and other tobacco chemicals had diverse effects on the luciferase activity of the rs6495309C or T alleles. However, none of these effects were found for another SNP, rs1051730G>A. The data show a statistical association and suggest biological plausibility that the rs6495309T>C polymorphism contributed to increased risks and poor prognosis of both COPD and lung cancer. PMID:23056235

  1. Cancer Risk Assessment Primer.

    ERIC Educational Resources Information Center

    Aidala, Jim

    1985-01-01

    Describes the scientific basis of cancer risk assessment, outlining the dominant controversies surrounding the use of different methods for identifying carcinogens (short-term tests, animal bioassays, and epidemiological studies). Points out that risk assessment is as much an art as it is a science. (DH)

  2. Prevalence of delirium among patients at a cancer ward: Clinical risk factors and prediction by bedside cognitive tests.

    PubMed

    Grandahl, Mia Gall; Nielsen, Svend Erik; Koerner, Ejnar Alex; Schultz, Helga Holm; Arnfred, Sidse Marie

    2016-08-01

    Background Delirium is a frequent psychiatric complication to cancer, but rarely recognized by oncologists. Aims 1. To estimate the prevalence of delirium among inpatients admitted at an oncological cancer ward 2. To investigate whether simple clinical factors predict delirium 3. To examine the value of cognitive testing in the assessment of delirium. Methods On five different days, we interviewed and assessed patients admitted to a Danish cancer ward. The World Health Organization International Classification of Diseases Version 10, WHO ICD-10 Diagnostic System and the Confusion Assessment Method (CAM) were used for diagnostic categorization. Clinical information was gathered from medical records and all patients were tested with Mini Cognitive Test, The Clock Drawing Test, and the Digit Span Test. Results 81 cancer patients were assessed and 33% were diagnosed with delirium. All delirious participants were CAM positive. Poor performance on the cognitive tests was associated with delirium. Medical records describing CNS metastases, benzodiazepine or morphine treatment were associated with delirium. Conclusions Delirium is prevalent among cancer inpatients. The Mini Cognitive Test, The Clock Drawing Test, and the Digit Span Test can be used as screening tools for delirium among inpatients with cancer, but even in synergy, they lack specificity. Combining cognitive testing and attention to nurses' records might improve detection, yet further studies are needed to create a more detailed patient profile for the detection of delirium. PMID:26882016

  3. Patient-specific driver gene prediction and risk assessment through integrated network analysis of cancer omics profiles.

    PubMed

    Bertrand, Denis; Chng, Kern Rei; Sherbaf, Faranak Ghazi; Kiesel, Anja; Chia, Burton K H; Sia, Yee Yen; Huang, Sharon K; Hoon, Dave S B; Liu, Edison T; Hillmer, Axel; Nagarajan, Niranjan

    2015-04-20

    Extensive and multi-dimensional data sets generated from recent cancer omics profiling projects have presented new challenges and opportunities for unraveling the complexity of cancer genome landscapes. In particular, distinguishing the unique complement of genes that drive tumorigenesis in each patient from a sea of passenger mutations is necessary for translating the full benefit of cancer genome sequencing into the clinic. We address this need by presenting a data integration framework (OncoIMPACT) to nominate patient-specific driver genes based on their phenotypic impact. Extensive in silico and in vitro validation helped establish OncoIMPACT's robustness, improved precision over competing approaches and verifiable patient and cell line specific predictions (2/2 and 6/7 true positives and negatives, respectively). In particular, we computationally predicted and experimentally validated the gene TRIM24 as a putative novel amplified driver in a melanoma patient. Applying OncoIMPACT to more than 1000 tumor samples, we generated patient-specific driver gene lists in five different cancer types to identify modes of synergistic action. We also provide the first demonstration that computationally derived driver mutation signatures can be overall superior to single gene and gene expression based signatures in enabling patient stratification and prognostication. Source code and executables for OncoIMPACT are freely available from http://sourceforge.net/projects/oncoimpact. PMID:25572314

  4. Refinement of the prediction of N-acetyltransferase 2 (NAT2) phenotypes with respect to enzyme activity and urinary bladder cancer risk.

    PubMed

    Selinski, Silvia; Blaszkewicz, Meinolf; Ickstadt, Katja; Hengstler, Jan G; Golka, Klaus

    2013-12-01

    Polymorphisms of N-acetyltransferase 2 (NAT2) are well known to modify urinary bladder cancer risk as well as efficacy and toxicity of pharmaceuticals via reduction in the enzyme's acetylation capacity. Nevertheless, the discussion about optimal NAT2 phenotype prediction, particularly differentiation between different degrees of slow acetylation, is still controversial. Therefore, we investigated the impact of single nucleotide polymorphisms and their haplotypes on slow acetylation in vivo and on bladder cancer risk. For this purpose, we used a study cohort of 1,712 bladder cancer cases and 2,020 controls genotyped for NAT2 by RFLP-PCR and for the tagSNP rs1495741 by TaqMan(®) assay. A subgroup of 344 individuals was phenotyped by the caffeine test in vivo. We identified an 'ultra-slow' acetylator phenotype based on combined *6A/*6A, *6A/*7B and *7B/*7B genotypes containing the homozygous minor alleles of C282T (rs1041983, *6A, *7B) and G590A (rs1799930, *6A). 'Ultra-slow' acetylators have significantly about 32 and 46 % lower activities of caffeine metabolism compared with other slow acetylators and with the *5B/*5B genotypes, respectively (P < 0.01, both). The 'ultra-slow' genotype showed an association with bladder cancer risk in the univariate analysis (OR = 1.31, P = 0.012) and a trend adjusted for age, gender and smoking habits (OR = 1.22, P = 0.082). In contrast, slow acetylators in general were not associated with bladder cancer risk, neither in the univariate (OR = 1.02, P = 0.78) nor in the adjusted (OR = 0.98, P = 0.77) analysis. In conclusion, this study suggests that NAT2 phenotype prediction should be refined by consideration of an 'ultra-slow' acetylation genotype. PMID:24221535

  5. Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer

    PubMed Central

    Chauhan, S S; Kaur, J; Kumar, M; Matta, A; Srivastava, G; Alyass, A; Assi, J; Leong, I; MacMillan, C; Witterick, I; Colgan, T J; Shukla, N K; Thakar, A; Sharma, M C; Siu, K W M; Walfish, P G; Ralhan, R

    2015-01-01

    Loco-regional recurrence in 50% of oral squamous cell carcinoma (OSCC) patients poses major challenge for oncologists. Lack of biomarkers that can predict disease aggressiveness and recurrence risk makes the scenario more dismal. On the basis of our earlier global proteomic analyses we identified five differentially expressed proteins in OSCC. This study aimed to develop protein biomarkers-based prognostic risk prediction model for OSCC. Sub-cellular expression of five proteins, S100A7, heterogeneous nuclear ribonucleoproteinK (hnRNPK), prothymosin α (PTMA), 14-3-3ζ and 14-3-3σ was analyzed by immunohistochemistry in test set (282 Indian OSCCs and 209 normal tissues), correlated with clinic–pathological parameters and clinical outcome over 12 years to develop a risk model for prediction of recurrence-free survival. This risk classifier was externally validated in 135 Canadian OSCC and 96 normal tissues. Biomarker signature score based on PTMA, S100A7 and hnRNPK was associated with recurrence free survival of OSCC patients (hazard ratio=1.11; 95% confidence interval 1.08, 1.13, P<0.001, optimism-corrected c-statistic=0.69) independent of clinical parameters. Biomarker signature score stratified OSCC patients into high- and low-risk groups with significant difference for disease recurrence. The high-risk group had median survival 14 months, and 3-year survival rate of 30%, whereas low-risk group survival probability did not reach 50%, and had 3-year survival rate of 71%. As a powerful predictor of 3-year recurrence-free survival in OSCC patients, the newly developed biomarkers panel risk classifier will facilitate patient counseling for personalized treatment. PMID:25893634

  6. Prediction of long-term cumulative incidences based on short-term parametric model for competing risks: application in early breast cancer.

    PubMed

    Cabarrou, B; Belin, L; Somda, S M; Falcou, M C; Pierga, J Y; Kirova, Y; Delord, J P; Asselain, B; Filleron, T

    2016-04-01

    Use of parametric statistical models can be a solution to reduce the follow-up period time required to estimate long-term survival. Mould and Boag were the first to use the lognormal model. Competing risks methodology seems more suitable when a particular event type is of interest than classical survival analysis. The objective was to evaluate the ability of the Jeong and Fine model to predict long-term cumulative incidence. Survival data recorded by Institut Curie (Paris) from 4761 breast cancer patients treated and followed between 1981 and 2013 were used. Long-term cumulative incidence rates predicted by the model using short-term follow-up data were compared to non-parametric estimation using complete follow-up data. 20- or 25-year cumulative incidence rates for loco-regional recurrence and distant metastasis predicted by the model using a maximum of 10 years of follow-up data had a maximum difference of around 6 % compared to non-parametric estimation. Prediction rates were underestimated for the third and composite event (contralateral or second cancer or death). Predictive ability of Jeong and Fine model on breast cancer data was generally good considering the short follow-up period time used for the estimation especially when a proportion of patient did not experience loco-regional recurrence or distant metastasis. PMID:27075918

  7. Comparison of fully and semi-automated area-based methods for measuring mammographic density and predicting breast cancer risk

    PubMed Central

    Sovio, U; Li, J; Aitken, Z; Humphreys, K; Czene, K; Moss, S; Hall, P; McCormack, V; dos-Santos-Silva, I

    2014-01-01

    Background: Mammographic density is a strong risk factor for breast cancer but the lack of valid fully automated methods for quantifying it has precluded its use in clinical and screening settings. We compared the performance of a recently developed automated approach, based on the public domain ImageJ programme, to the well-established semi-automated Cumulus method. Methods: We undertook a case-control study within the intervention arm of the Age Trial, in which ∼54 000 British women were offered annual mammography at ages 40–49 years. A total of 299 breast cancer cases diagnosed during follow-up and 422 matched (on screening centre, date of birth and dates of screenings) controls were included. Medio-lateral oblique (MLO) images taken closest to age 41 and at least one year before the index case's diagnosis were digitised for each participant. Cumulus readings were performed in the left MLO and ImageJ-based readings in both left and right MLOs. Conditional logistic regression was used to examine density–breast cancer associations. Results: The association between density readings taken from one single MLO and breast cancer risk was weaker for the ImageJ-based method than for Cumulus (age–body mass index-adjusted odds ratio (OR) per one s.d. increase in percent density (95% CI): 1.52 (1.24–1.86) and 1.61 (1.33–1.94), respectively). The ImageJ-based density–cancer association strengthened when the mean of left–right MLO readings was used: OR=1.61 (1.31–1.98). Conclusions: The mean of left–right MLO readings yielded by the ImageJ-based method was as strong a predictor of risk as Cumulus readings from a single MLO image. The ImageJ-based method, using the mean of two measurements, is a valid automated alternative to Cumulus for measuring density in analogue films. PMID:24556624

  8. Lifestyle and cancer risk.

    PubMed

    Weiderpass, Elisabete

    2010-11-01

    The main behavioural and environmental risk factors for cancer mortality in the world are related to diet and physical inactivity, use of addictive substances, sexual and reproductive health, exposure to air pollution and use of contaminated needles. The population attributable fraction for all cancer sites worldwide considering the joint effect of these factors is about 35% (34 % for low-and middle-income countries and 37% for high-income countries). Seventy-one percent(71%) of lung cancer deaths are caused by tobacco use (lung cancer is the leading cause of cancer death globally). The combined effects of tobacco use, low fruit and vegetable intake, urban air pollution, and indoor smoke from household use of solid fuels cause 76% of lung cancer deaths. Exposure to these behavioural and environmental factors is preventable; modifications in lifestyle could have a large impact in reducing the cancer burden worldwide (WHO, 2009). The evidence of association between lifestyle factors and cancer, as well as the main international recommendations for prevention are briefly reviewed and commented upon here. PMID:21139406

  9. The Use of Exome Genotyping to Predict Pathological Gleason Score Upgrade after Radical Prostatectomy in Low-Risk Prostate Cancer Patients

    PubMed Central

    Oh, Jong Jin; Park, Seunghyun; Lee, Sang Eun; Hong, Sung Kyu; Lee, Sangchul; Choe, Gheeyoung

    2014-01-01

    Background Active surveillance (AS) is a promising option for patients with low-risk prostate cancer (PCa), however current criteria could not select the patients correctly, many patients who fulfilled recent AS criteria experienced pathological Gleason score upgrade (PGU) after radical prostatectomy (RP). In this study, we aimed to develop an accurate model for predicting PGU among low-risk PCa patients by using exome genotyping. Methods We genotyped 242,221 single nucleotide polymorphisms (SNP)s on a custom HumanExome BeadChip v1.0 (Illuminam Inc.) in blood DNA from 257 low risk PCa patients (PSA <10 ng/ml, biopsy Gleason score (GS) ≤6 and clinical stage ≤T2a) who underwent radical prostatectomy. Genetic data were analyzed using an unconditional logistic regression to calculate an odds ratio as an estimate of relative risk of PGU, which defined pathologic GS above 7. Among them, we selected persistent SNPs after multiple testing using FDR method, and we compared accuracies from the multivariate logistic model incorporating clinical factors between included and excluded selected SNP information. Results After analysis of exome genotyping, 15 SNPs were significant to predict PGU in low risk PCa patients. Among them, one SNP – rs33999879 remained significant after multiple testing. When a multivariate model incorporating factors in Epstein definition – PSA density, biopsy GS, positive core number, tumor per core ratio and age was devised for the prediction of PGU, the predictive accuracy of the multivariate model was 78.4% (95%CI: 0.726–0.834). By addition the factor of rs33999879 in aforementioned multivariate model, the predictive accuracy was 82.9%, which was significantly increased (p = 0.0196). Conclusion The rs33999879 SNP is a predictor for PGU. The addition of genetic information from the exome sequencing effectively enhanced the predictive accuracy of the multivariate model to establish suitable active surveillance criteria. PMID:25093842

  10. Post-traumatic Stress Symptoms and Post-traumatic Growth in 223 Childhood Cancer Survivors: Predictive Risk Factors

    PubMed Central

    Tremolada, Marta; Bonichini, Sabrina; Basso, Giuseppe; Pillon, Marta

    2016-01-01

    With modern therapies and supportive care, survival rates of childhood cancer have increased considerably. However, there are long-term psychological sequelae of these treatments that may not manifest until pediatric survivors are into adulthood. The prevalence of post-traumatic stress disorder in young adult survivors of childhood cancer ranges from 6.2 to 22%; associated risk factors are young age at the assessment, female gender, low education level, and some disease-related factors. The aim of this study was to investigate, in adolescent and young adult (AYA) survivors of childhood cancer, the incidence and severity of post-traumatic stress symptoms (PTSSs), and to identify the risk factors and the associated post-traumatic growth (PTG) index. Participants were 223 AYA cancer survivors recruited during follow-up visits in the Oncohematology Clinic of the Department of Child and Woman’s Health, University of Padua. Data were collected from self-report questionnaires on PTSS incidence, PTG mean score, perceived social support, and medical and socio-demographic factors. Ex-patients’ mean age at the assessment was 19.33 years (SD = 3.01, 15–25), 123 males and 100 females, with a mean of years off-therapy of 9.64 (SD = 4.17). Most (52.5%) had survived an hematological disorder and 47.5% a solid tumor when they were aged, on average, 8.02 years (SD = 4.40). The main results indicated a moderate presence of clinical (≥9 symptoms: 9.4%) and sub-clinical PTSS (6–8 symptoms: 11.2%), with the avoidance criterion most often encountered. Re-experience symptoms and PTG mean score were significantly associated (r = 0.24; p = 0.0001). A hierarchical regression model (R2 = 0.08; F = 1.46; p = 0.05) identified female gender (β = 0.16; p = 0.05) and less perceived social support (β = -0.43; p = 0.05) as risk factors to developing PTSS. Another hierarchical regression model assessed the possible predictors of the PTG total score (R2 = 0.36; F = 9.1; p = 0.0001), with

  11. Salivary Gland Cancer: Risk Factors

    MedlinePlus

    ... Factors Request Permissions Print to PDF Salivary Gland Cancer: Risk Factors Approved by the Cancer.Net Editorial Board , 08/ ... anything that increases a person’s chance of developing cancer. Although risk factors often influence the development of cancer, most do ...

  12. Space Radiation Cancer Risks

    NASA Technical Reports Server (NTRS)

    Cucinotta, Francis A.

    2007-01-01

    Space radiation presents major challenges to astronauts on the International Space Station and for future missions to the Earth s moon or Mars. Methods used to project risks on Earth need to be modified because of the large uncertainties in projecting cancer risks from space radiation, and thus impact safety factors. We describe NASA s unique approach to radiation safety that applies uncertainty based criteria within the occupational health program for astronauts: The two terrestrial criteria of a point estimate of maximum acceptable level of risk and application of the principle of As Low As Reasonably Achievable (ALARA) are supplemented by a third requirement that protects against risk projection uncertainties using the upper 95% confidence level (CL) in the radiation cancer projection model. NASA s acceptable level of risk for ISS and their new lunar program have been set at the point-estimate of a 3-percent risk of exposure induced death (REID). Tissue-averaged organ dose-equivalents are combined with age at exposure and gender-dependent risk coefficients to project the cumulative occupational radiation risks incurred by astronauts. The 95% CL criteria in practice is a stronger criterion than ALARA, but not an absolute cut-off as is applied to a point projection of a 3% REID. We describe the most recent astronaut dose limits, and present a historical review of astronaut organ doses estimates from the Mercury through the current ISS program, and future projections for lunar and Mars missions. NASA s 95% CL criteria is linked to a vibrant ground based radiobiology program investigating the radiobiology of high-energy protons and heavy ions. The near-term goal of research is new knowledge leading to the reduction of uncertainties in projection models. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. The current model for projecting space radiation

  13. Understanding your breast cancer risk

    MedlinePlus

    ... the chance that you could get cancer. Some risk factors you can control, such as drinking alcohol. Others, such as family ... Risk factors you cannot control includes: Age . Your risk for breast cancer increases as you age. Most cancers are found in ...

  14. Toxicogenomic outcomes predictive of forestomach carcinogenesis following exposure to benzo(a)pyrene: Relevance to human cancer risk

    SciTech Connect

    Labib, Sarah Guo, Charles H. Williams, Andrew Yauk, Carole L. White, Paul A. Halappanavar, Sabina

    2013-12-01

    Forestomach tumors are observed in mice exposed to environmental carcinogens. However, the relevance of this data to humans is controversial because humans lack a forestomach. We hypothesize that an understanding of early molecular changes after exposure to a carcinogen in the forestomach will provide mode-of-action information to evaluate the applicability of forestomach cancers to human cancer risk assessment. In the present study we exposed mice to benzo(a)pyrene (BaP), an environmental carcinogen commonly associated with tumors of the rodent forestomach. Toxicogenomic tools were used to profile gene expression response in the forestomach. Adult Muta™Mouse males were orally exposed to 25, 50, and 75 mg BaP/kg-body-weight/day for 28 consecutive days. The forestomach was collected three days post-exposure. DNA microarrays, real-time RT-qPCR arrays, and protein analyses were employed to characterize responses in the forestomach. Microarray results showed altered expression of 414 genes across all treatment groups (± 1.5 fold; false discovery rate adjusted P ≤ 0.05). Significant downregulation of genes associated with phase II xenobiotic metabolism and increased expression of genes implicated in antigen processing and presentation, immune response, chemotaxis, and keratinocyte differentiation were observed in treated groups in a dose-dependent manner. A systematic comparison of the differentially expressed genes in the forestomach from the present study to differentially expressed genes identified in human diseases including human gastrointestinal tract cancers using the NextBio Human Disease Atlas showed significant commonalities between the two models. Our results provide molecular evidence supporting the use of the mouse forestomach model to evaluate chemically-induced gastrointestinal carcinogenesis in humans. - Highlights: • Benzo(a)pyrene-mediated transcriptomic response in the forestomach was examined. • The immunoproteosome subunits and MHC class I

  15. Human respiratory tract cancer risks of inhaled formaldehyde: dose-response predictions derived from biologically-motivated computational modeling of a combined rodent and human dataset.

    PubMed

    Conolly, Rory B; Kimbell, Julia S; Janszen, Derek; Schlosser, Paul M; Kalisak, Darin; Preston, Julian; Miller, Frederick J

    2004-11-01

    Formaldehyde inhalation at 6 ppm and above causes nasal squamous cell carcinoma (SCC) in F344 rats. The quantitative implications of the rat tumors for human cancer risk are of interest, since epidemiological studies have provided only equivocal evidence that formaldehyde is a human carcinogen. Conolly et al. (Toxicol. Sci. 75, 432-447, 2003) analyzed the rat tumor dose-response assuming that both DNA-reactive and cytotoxic effects of formaldehyde contribute to SCC development. The key elements of their approach were: (1) use of a three-dimensional computer reconstruction of the rat nasal passages and computational fluid dynamics (CFD) modeling to predict regional dosimetry of formaldehyde; (2) association of the flux of formaldehyde into the nasal mucosa, as predicted by the CFD model, with formation of DNA-protein cross-links (DPX) and with cytolethality/regenerative cellular proliferation (CRCP); and (3) use of a two-stage clonal growth model to link DPX and CRCP with tumor formation. With this structure, the prediction of the tumor dose response was extremely sensitive to cell kinetics. The raw dose-response data for CRCP are J-shaped, and use of these data led to a predicted J-shaped dose response for tumors, notwithstanding a concurrent low-dose-linear, directly mutagenic effect of formaldehyde mediated by DPX. In the present work the modeling approach used by Conolly et al. (ibid.) was extended to humans. Regional dosimetry predictions for the entire respiratory tract were obtained by merging a three-dimensional CFD model for the human nose with a one-dimensional typical path model for the lower respiratory tract. In other respects, the human model was structurally identical to the rat model. The predicted human dose response for DPX was obtained by scale-up of a computational model for DPX calibrated against rat and rhesus monkey data. The rat dose response for CRCP was used "as is" for the human model, since no preferable alternative was identified. Three

  16. A Radio-genomics Approach for Identifying High Risk Estrogen Receptor-positive Breast Cancers on DCE-MRI: Preliminary Results in Predicting OncotypeDX Risk Scores.

    PubMed

    Wan, Tao; Bloch, B Nicolas; Plecha, Donna; Thompson, CheryI L; Gilmore, Hannah; Jaffe, Carl; Harris, Lyndsay; Madabhushi, Anant

    2016-01-01

    To identify computer extracted imaging features for estrogen receptor (ER)-positive breast cancers on dynamic contrast enhanced (DCE)-MRI that are correlated with the low and high OncotypeDX risk categories. We collected 96 ER-positive breast lesions with low (< 18, N = 55) and high (> 30, N = 41) OncotypeDX recurrence scores. Each lesion was quantitatively characterize via 6 shape features, 3 pharmacokinetics, 4 enhancement kinetics, 4 intensity kinetics, 148 textural kinetics, 5 dynamic histogram of oriented gradient (DHoG), and 6 dynamic local binary pattern (DLBP) features. The extracted features were evaluated by a linear discriminant analysis (LDA) classifier in terms of their ability to distinguish low and high OncotypeDX risk categories. Classification performance was evaluated by area under the receiver operator characteristic curve (Az). The DHoG and DLBP achieved Az values of 0.84 and 0.80, respectively. The 6 top features identified via feature selection were subsequently combined with the LDA classifier to yield an Az of 0.87. The correlation analysis showed that DHoG (ρ = 0.85, P < 0.001) and DLBP (ρ = 0.83, P < 0.01) were significantly associated with the low and high risk classifications from the OncotypeDX assay. Our results indicated that computer extracted texture features of DCE-MRI were highly correlated with the high and low OncotypeDX risk categories for ER-positive cancers. PMID:26887643

  17. Understanding your breast cancer risk

    MedlinePlus

    ... what you can do to help prevent breast cancer. Risk Factors You Cannot Control Risk factors you cannot control ... risk. Race . White women are diagnosed with breast cancer more often than African American/black, ... Can Control Risk factors you can control ...

  18. Predicted Risk of Radiation-Induced Cancers After Involved Field and Involved Node Radiotherapy With or Without Intensity Modulation for Early-Stage Hodgkin Lymphoma in Female Patients

    SciTech Connect

    Weber, Damien C.; Johanson, Safora; Peguret, Nicolas; Cozzi, Luca; Olsen, Dag R.

    2011-10-01

    Purpose: To assess the excess relative risk (ERR) of radiation-induced cancers (RIC) in female patients with Hodgkin lymphoma (HL) female patients treated with conformal (3DCRT), intensity modulated (IMRT), or volumetric modulated arc (RA) radiation therapy. Methods and Materials: Plans for 10 early-stage HL female patients were computed for 3DCRT, IMRT, and RA with involved field RT (IFRT) and involvednode RT (INRT) radiation fields. Organs at risk dose--volume histograms were computed and inter-compared for IFRT vs. INRT and 3DCRT vs. IMRT/RA, respectively. The ERR for cancer induction in breasts, lungs, and thyroid was estimated using both linear and nonlinear models. Results: The mean estimated ERR for breast, lung, and thyroid were significantly lower (p < 0.01) with INRT than with IFRT planning, regardless of the radiation delivery technique used, assuming a linear dose-risk relationship. We found that using the nonlinear model, the mean ERR values were significantly (p < 0.01) increased with IMRT or RA compared to those with 3DCRT planning for the breast, lung, and thyroid, using an IFRT paradigm. After INRT planning, IMRT or RA increased the risk of RIC for lung and thyroid only. Conclusions: In this comparative planning study, using a nonlinear dose--risk model, IMRT or RA increased the estimated risk of RIC for breast, lung, and thyroid for HL female patients. This study also suggests that INRT planning, compared to IFRT planning, may reduce the ERR of RIC when risk is predicted using a linear model. Observing the opposite effect, with a nonlinear model, however, questions the validity of these biologically parameterized models.

  19. Risk prediction for invasive candidiasis

    PubMed Central

    Ahmed, Armin; Azim, Afzal; Baronia, Arvind Kumar; Marak, K. Rungmei S. K.; Gurjar, Mohan

    2014-01-01

    Over past few years, treatment of invasive candidiasis (IC) has evolved from targeted therapy to prophylaxis, pre-emptive and empirical therapy. Numerous predisposing factors for IC have been grouped together in various combinations to design risk prediction models. These models in general have shown good negative predictive value, but poor positive predictive value. They are useful in selecting the population which is less likely to benefit from empirical antifungal therapy and thus prevent overuse of antifungal agents. Current article deals with various risk prediction models for IC and their external validation studies. PMID:25316979

  20. Androgen receptor coactivators lysine-specific histone demethylase 1 and four and a half LIM domain protein 2 predict risk of prostate cancer recurrence.

    PubMed

    Kahl, Philip; Gullotti, Lucia; Heukamp, Lukas Carl; Wolf, Susanne; Friedrichs, Nicolaus; Vorreuther, Roland; Solleder, Gerold; Bastian, Patrick J; Ellinger, Jörg; Metzger, Eric; Schüle, Roland; Buettner, Reinhard

    2006-12-01

    Prostate cancer biology varies from locally confined tumors with low risk for relapse to tumors with high risk for progression even after radical prostatectomy. Currently, there are no reliable biomarkers to predict tumor relapse and poor clinical outcome. In this study, we correlated expression patterns of the androgen receptor (AR) coactivators lysine-specific histone demethylase 1 (LSD1) and four and a half LIM-domain protein 2 (FHL2), AR, Gleason score, Gleason grade, and p53 expression in clinically organ confined prostate cancers with relapse after radical prostatectomy. Our data reveal that high levels of LSD1, nuclear expression of the FHL2 coactivator, high Gleason score and grade, and very strong staining of nuclear p53 correlate significantly with relapse during follow-up. No correlation exists with relapse and the expression of AR and cytoplasmic expression of FHL2. To confirm these data, we did quantitative reverse transcription-PCR and Western blot analyses in a subset of tumor specimens. Consistently, both LSD1 mRNA and protein levels were significantly up-regulated in high-risk tumors. We previously identified LSD1 and FHL2 as nuclear cofactors interacting specifically with the AR in prostate cells and showed that both stimulate androgen-dependent gene transcription. Our present study suggests that LSD1 and nuclear FHL2 may serve as novel biomarkers predictive for prostate cancer with aggressive biology and point to a role of LSD1 and FHL2 in constitutive activation of AR-mediated growth signals. PMID:17145880

  1. A Radio-genomics Approach for Identifying High Risk Estrogen Receptor-positive Breast Cancers on DCE-MRI: Preliminary Results in Predicting OncotypeDX Risk Scores

    PubMed Central

    Wan, Tao; Bloch, B. Nicolas; Plecha, Donna; Thompson, CheryI L.; Gilmore, Hannah; Jaffe, Carl; Harris, Lyndsay; Madabhushi, Anant

    2016-01-01

    To identify computer extracted imaging features for estrogen receptor (ER)-positive breast cancers on dynamic contrast en-hanced (DCE)-MRI that are correlated with the low and high OncotypeDX risk categories. We collected 96 ER-positivebreast lesions with low (<18, N = 55) and high (>30, N = 41) OncotypeDX recurrence scores. Each lesion was quantitatively charac-terize via 6 shape features, 3 pharmacokinetics, 4 enhancement kinetics, 4 intensity kinetics, 148 textural kinetics, 5 dynamic histogram of oriented gradient (DHoG), and 6 dynamic local binary pattern (DLBP) features. The extracted features were evaluated by a linear discriminant analysis (LDA) classifier in terms of their ability to distinguish low and high OncotypeDX risk categories. Classification performance was evaluated by area under the receiver operator characteristic curve (Az). The DHoG and DLBP achieved Az values of 0.84 and 0.80, respectively. The 6 top features identified via feature selection were subsequently combined with the LDA classifier to yield an Az of 0.87. The correlation analysis showed that DHoG (ρ = 0.85, P < 0.001) and DLBP (ρ = 0.83, P < 0.01) were significantly associated with the low and high risk classifications from the OncotypeDX assay. Our results indicated that computer extracted texture features of DCE-MRI were highly correlated with the high and low OncotypeDX risk categories for ER-positive cancers. PMID:26887643

  2. International multicenter tool to predict the risk of four or more tumor-positive axillary lymph nodes in breast cancer patients with sentinel node macrometastases.

    PubMed

    Meretoja, Tuomo J; Audisio, R A; Heikkilä, P S; Bori, R; Sejben, I; Regitnig, P; Luschin-Ebengreuth, G; Zgajnar, J; Perhavec, A; Gazic, B; Lázár, G; Takács, T; Kővári, B; Saidan, Z A; Nadeem, R M; Castellano, I; Sapino, A; Bianchi, S; Vezzosi, V; Barranger, E; Lousquy, R; Arisio, R; Foschini, M P; Imoto, S; Kamma, H; Tvedskov, T F; Jensen, M-B; Cserni, G; Leidenius, M H K

    2013-04-01

    Recently, many centers have omitted routine axillary lymph node dissection (ALND) after metastatic sentinel node biopsy in breast cancer due to a growing body of literature. However, existing guidelines of adjuvant treatment planning are strongly based on axillary nodal stage. In this study, we aim to develop a novel international multicenter predictive tool to estimate a patient-specific risk of having four or more tumor-positive axillary lymph nodes (ALN) in patients with macrometastatic sentinel node(s) (SN). A series of 675 patients with macrometastatic SN and completion ALND from five European centers were analyzed by logistic regression analysis. A multivariate predictive model was created and validated internally by 367 additional patients and then externally by 760 additional patients from eight different centers. All statistical tests were two-sided. Prevalence of four or more tumor-positive ALN in each center's series (P = 0.010), number of metastatic SNs (P < 0.0001), number of negative SNs (P = 0.003), histological size of the primary tumor (P = 0.020), and extra-capsular extension of SN metastasis (P < 0.0001) were included in the predictive model. The model's area under the receiver operating characteristics curve was 0.766 in the internal validation and 0.774 in external validation. Our novel international multicenter-based predictive tool reliably estimates the risk of four or more axillary metastases after identifying macrometastatic SN(s) in breast cancer. Our tool performs well in internal and external validation, but needs to be further validated in each center before application to clinical use. PMID:23558360

  3. Breast cancer risk factors

    PubMed Central

    Ciszewski, Tomasz; Łopacka-Szatan, Karolina; Miotła, Paweł; Starosławska, Elżbieta

    2015-01-01

    Breast cancer is the most frequently diagnosed neoplastic disease in women around menopause often leading to a significant reduction of these women's ability to function normally in everyday life. The increased breast cancer incidence observed in epidemiological studies in a group of women actively participating in social and professional life implicates the necessity of conducting multidirectional studies in order to identify risk factors associated with the occurrence of this type of neoplasm. Taking the possibility of influencing the neoplastic transformation process in individuals as a criterion, all the risk factors initiating the process can be divided into two groups. The first group would include inherent factors such as age, sex, race, genetic makeup promoting familial occurrence of the neoplastic disease or the occurrence of benign proliferative lesions of the mammary gland. They all constitute independent parameters and do not undergo simple modification in the course of an individual's life. The second group would include extrinsic factors conditioned by lifestyle, diet or long-term medical intervention such as using oral hormonal contraceptives or hormonal replacement therapy and their influence on the neoplastic process may be modified to a certain degree. Identification of modifiable factors may contribute to development of prevention strategies decreasing breast cancer incidence. PMID:26528110

  4. Abortion, Miscarriage, and Breast Cancer Risk

    MedlinePlus

    ... Cancers Breast Cancer Screening Research Abortion, Miscarriage, and Breast Cancer Risk A woman’s hormone levels normally change throughout ... the development of breast cancer. Important Information about Breast Cancer Risk Factors At present, the factors known to ...

  5. Breast Cancer Risk in American Women

    MedlinePlus

    ... of Breast & Gynecologic Cancers Breast Cancer Screening Research Breast Cancer Risk in American Women On This Page What ... risk of developing the disease. Personal history of breast cancer : Women who have had breast cancer are more ...

  6. Environmental cancer risks

    NASA Astrophysics Data System (ADS)

    Bell, Peter M.

    In a long-awaited report (‘Assessment of Technologies for Determining Cancer Risks From the Environment’), the U.S. Office of Technology Assessment (OTA) has evaluated the role of environmental factors in cancer diseases. Environment is interpreted broadly as encompassing anything that interacts with humans, including the natural environment, food, radiation, the workplace, etc. Geologic factors range from geographic location to radiation and specific minerals. The report, however, is based on an inadequate data base in most instances, and its major recommendations are related to the establishment of a national cancer registry to record cancer statistics, as is done for many other diseases. Presently, hard statistics are lacking in the establishment of some association between the cause-effect relationship of most environmental factors and most carcinogens. Of particular interest, but unfortunately based on unreliable data, are the effects of mineral substances such as ‘asbestos.’ USGS mineralogist Malcolm Ross will review asbestos and its effects on human health in the forthcoming Mineralogical Society of America's Short Course on the Amphiboles (Reviews in Mineralogy, 9, in press, 1981).

  7. HIV Infection and Cancer Risk

    MedlinePlus

    ... Other Funding Find NCI funding for small business innovation, technology transfer, and contracts Training Cancer Training at ... Engels EA, Pfeiffer RM, Goedert JJ, et al. Trends in cancer risk among people with AIDS in ...

  8. Neuroanatomy Predicts Individual Risk Attitudes

    PubMed Central

    Gilaie-Dotan, Sharon; Tymula, Agnieszka; Cooper, Nicole; Kable, Joseph W.; Glimcher, Paul W.

    2014-01-01

    Over the course of the last decade a multitude of studies have investigated the relationship between neural activations and individual human decision-making. Here we asked whether the anatomical features of individual human brains could be used to predict the fundamental preferences of human choosers. To that end, we quantified the risk attitudes of human decision-makers using standard economic tools and quantified the gray matter cortical volume in all brain areas using standard neurobiological tools. Our whole-brain analysis revealed that the gray matter volume of a region in the right posterior parietal cortex was significantly predictive of individual risk attitudes. Participants with higher gray matter volume in this region exhibited less risk aversion. To test the robustness of this finding we examined a second group of participants and used econometric tools to test the ex ante hypothesis that gray matter volume in this area predicts individual risk attitudes. Our finding was confirmed in this second group. Our results, while being silent about causal relationships, identify what might be considered the first stable biomarker for financial risk-attitude. If these results, gathered in a population of midlife northeast American adults, hold in the general population, they will provide constraints on the possible neural mechanisms underlying risk attitudes. The results will also provide a simple measurement of risk attitudes that could be easily extracted from abundance of existing medical brain scans, and could potentially provide a characteristic distribution of these attitudes for policy makers. PMID:25209279

  9. Neuroanatomy predicts individual risk attitudes.

    PubMed

    Gilaie-Dotan, Sharon; Tymula, Agnieszka; Cooper, Nicole; Kable, Joseph W; Glimcher, Paul W; Levy, Ifat

    2014-09-10

    Over the course of the last decade a multitude of studies have investigated the relationship between neural activations and individual human decision-making. Here we asked whether the anatomical features of individual human brains could be used to predict the fundamental preferences of human choosers. To that end, we quantified the risk attitudes of human decision-makers using standard economic tools and quantified the gray matter cortical volume in all brain areas using standard neurobiological tools. Our whole-brain analysis revealed that the gray matter volume of a region in the right posterior parietal cortex was significantly predictive of individual risk attitudes. Participants with higher gray matter volume in this region exhibited less risk aversion. To test the robustness of this finding we examined a second group of participants and used econometric tools to test the ex ante hypothesis that gray matter volume in this area predicts individual risk attitudes. Our finding was confirmed in this second group. Our results, while being silent about causal relationships, identify what might be considered the first stable biomarker for financial risk-attitude. If these results, gathered in a population of midlife northeast American adults, hold in the general population, they will provide constraints on the possible neural mechanisms underlying risk attitudes. The results will also provide a simple measurement of risk attitudes that could be easily extracted from abundance of existing medical brain scans, and could potentially provide a characteristic distribution of these attitudes for policy makers. PMID:25209279

  10. Developmental dyslexia: predicting individual risk

    PubMed Central

    Thompson, Paul A; Hulme, Charles; Nash, Hannah M; Gooch, Debbie; Hayiou-Thomas, Emma; Snowling, Margaret J

    2015-01-01

    Background Causal theories of dyslexia suggest that it is a heritable disorder, which is the outcome of multiple risk factors. However, whether early screening for dyslexia is viable is not yet known. Methods The study followed children at high risk of dyslexia from preschool through the early primary years assessing them from age 3 years and 6 months (T1) at approximately annual intervals on tasks tapping cognitive, language, and executive-motor skills. The children were recruited to three groups: children at family risk of dyslexia, children with concerns regarding speech, and language development at 3;06 years and controls considered to be typically developing. At 8 years, children were classified as ‘dyslexic’ or not. Logistic regression models were used to predict the individual risk of dyslexia and to investigate how risk factors accumulate to predict poor literacy outcomes. Results Family-risk status was a stronger predictor of dyslexia at 8 years than low language in preschool. Additional predictors in the preschool years include letter knowledge, phonological awareness, rapid automatized naming, and executive skills. At the time of school entry, language skills become significant predictors, and motor skills add a small but significant increase to the prediction probability. We present classification accuracy using different probability cutoffs for logistic regression models and ROC curves to highlight the accumulation of risk factors at the individual level. Conclusions Dyslexia is the outcome of multiple risk factors and children with language difficulties at school entry are at high risk. Family history of dyslexia is a predictor of literacy outcome from the preschool years. However, screening does not reach an acceptable clinical level until close to school entry when letter knowledge, phonological awareness, and RAN, rather than family risk, together provide good sensitivity and specificity as a screening battery. PMID:25832320

  11. MiR-34a Expression Has an Effect for Lower Risk of Metastasis and Associates with Expression Patterns Predicting Clinical Outcome in Breast Cancer

    PubMed Central

    Heikkinen, Tuomas; Kaur, Sippy; Bartkova, Jirina; Jamshidi, Maral; Aittomäki, Kristiina; Heikkilä, Päivi; Bartek, Jiri; Blomqvist, Carl; Bützow, Ralf; Nevanlinna, Heli

    2011-01-01

    MiR-34a acts as a candidate tumour suppressor gene, and its expression is reduced in several cancer types. We aimed to study miR-34a expression in breast cancer and its correlation with tumour characteristics and clinical outcome, and regulatory links with other genes. We analysed miR-34a expression in 1,172 breast tumours on TMAs. 25% of the tumours showed high, 43% medium and 32% low expression of miR-34a. High miR-34a expression associated with poor prognostic factors for breast cancer: positive nodal status (p = 0.006), high tumour grade (p<0.0001), ER-negativity (p = 0.0002), HER2-positivity (p = 0.0002), high proliferation rate (p<0.0001), p53-positivity (p<0.0001), high cyclin E (p<0.0001) and γH2AX (p<0.0001). However, multivariate analysis adjusting for conventional prognostic factors indicated that high miR-34a expression in fact associated with a lower risk of recurrence or death from breast cancer (HR = 0.63, 95% CI = 0.41–0.96, p = 0.031). Gene expression analysis by differential miR-34a expression revealed an expression signature with an effect on both the 5-year and 10-year survival of the patients (p<0.001). Functional genomic analysis highlighted a novel regulatory role of the transcription factor MAZ, apart from the known control by p53, on the expression of miR-34a and a number of miR-34a targets. Our findings suggest that while miR-34a expression activation is a marker of aggressive breast tumour phenotype it exerts an independent effect for a lower risk of recurrence or death from breast cancer. We also present an expression signature of 190 genes associated with miR-34a expression. Our analysis for regulatory loops suggest that MAZ and p53 transcription factors co-operate in modulating miR-34a, as well as miR-34a targets involved in several cellular pathways. Taken together, these results suggest that the network of genes co-regulated with and targeted by miR-34a form a group of down-stream effectors that maybe of

  12. Cancer risks: Strategies for elimination

    SciTech Connect

    Bannasch, P.

    1987-01-01

    This book deals with the possibilities for identifying and eliminating cancer risk factors. The current state of knowledge on the detection, assessment and elimination of chemical, physical (radiation), and biological (viruses) risk factors are comprehensively presented in 15 contributions. Chemical risk factors resulting from smoking and environmental contamination are given special attention. The coverage of cancer risks by radiation includes some of the consequences of the Chernobyl disaster. Finally, the discussion of the possible risks that certain viruses hold for cancer in man is intended to further the development of vaccinations against these viral infections. The information is directed not only at specialists, but also at a wider interested audience. Its primary aim is to convey established findings that are already being used for cancer prevention. Furthermore, the book aims to promote more intense research in the field of primary cancer prevention. Contents: General aspects; chemical carcinogens: Risk assessment; chemical carcinogens: Primary prevention; physical carcinogens - Oncogenic viruses and subject index.

  13. Prostate Stem Cell Antigen Expression in Radical Prostatectomy Specimens Predicts Early Biochemical Recurrence in Patients with High Risk Prostate Cancer Receiving Neoadjuvant Hormonal Therapy.

    PubMed

    Kim, Sung Han; Park, Weon Seo; Kim, Sun Ho; Park, Boram; Joo, Jungnam; Lee, Geon Kook; Joung, Jae Young; Seo, Ho Kyung; Chung, Jinsoo; Lee, Kang Hyun

    2016-01-01

    We aimed to identify tissue biomarkers that predict early biochemical recurrence (BCR) in patients with high-risk prostate cancer (PC), toward the goal of increasing the benefits of neoadjuvant hormonal therapy (NHT). In 2005-2012, prostatectomy specimens were collected from 134 PC patients who had received NHT and radical prostatectomy. The expression of 13 tissue biomarkers was assessed in the specimens via immunohistochemistry. Time to BCR and factors predictive of BCR were determined by using the Cox proportional hazards model. During the follow-up period (median, 57.5 months), 67 (50.0%) patients experienced BCR. Four (3.0%) patients were tumor-free in the final pathology assessment, and 101 (75.4%) had negative resection margins. Prostate stem cell antigen (PSCA) was the only significant prognostic tissue biomarker of BCR [hazard ratio (HR), 2.58; 95% confidence interval (CI), 1.06-6.27; p = 0.037] in a multivariable analysis adjusted by the clinicopathological variables that also significantly predicted BCR; these were seminal vesicle invasion (HR, 2.39; 95% CI, 1.32-4.34), initial prostate serum antigen level (HR 1.01; 95% CI, 1.001-1.020), prostate size (HR, 0.93; 95% CI, 0.90-0.97), and the Gleason score of preoperative biopsies (HR, 1.34; 95% CI, 1.01-1.79). We suggest that PSCA is a useful tissue marker for predicting BCR in patients with high risk PC receiving NHT and radical prostatectomy. PMID:26982980

  14. Prediction of outcome in cancer patients with febrile neutropenia: comparison of the Multinational Association of Supportive Care in Cancer risk-index score with procalcitonin, C-reactive protein, serum amyloid A, and interleukins-1beta, -6, -8 and -10.

    PubMed

    Uys, A; Rapoport, B L; Fickl, H; Meyer, P W A; Anderson, R

    2007-11-01

    The primary objective of the study was to compare the predictive potential of procalcitonin (PCT), C-reactive protein (CRP), serum amyloid A (SAA), and interleukin (IL)-1beta, IL-6, IL-8, and IL-10, with that of the Multinational Association of Supportive Care in Cancer (MASCC) risk-index score in cancer patients on presentation with chemotherapy-induced febrile neutropenia (FN). Seventy-eight consecutive FN episodes in 63 patients were included, and MASCC scores, as well as concentrations of CRP, SAA, PCT, and IL-1beta, IL-6, IL-8 and IL-10, and haematological parameters were determined on presentation, 72 h later and at outcome. Multivariate analysis of data revealed the MASCC score, but none of the laboratory parameters, to be an accurate, independent variable (P < 0.0001) for prediction of resolution with or without complications and death. Of the various laboratory parameters, PCT had the strongest association with the MASCC score (r = -0.51; P < 0.0001). In cancer patients who present with FN, the MASCC risk-index score is a useful predictor of outcome, while measurement of PCT, CRP, SAA, or IL-1beta, IL-6, IL-8 and IL-10, is of limited value. PMID:17944761

  15. Risk stratification strategies for cancer-associated thrombosis: an update.

    PubMed

    Khorana, Alok A; McCrae, Keith R

    2014-05-01

    Rates of venous thromboembolism (VTE) vary substantially between cancer patients. Multiple clinical risk factors including primary site of cancer and systemic therapy, and biomarkers including leukocyte and platelet counts and tissue factor are associated with increased risk of VTE. However, risk cannot be reliably predicted based on single risk factors or biomarkers. New American Society of Clinical Guidelines recommend that patients with cancer be assessed for VTE risk at the time of chemotherapy initiation and periodically thereafter. This narrative review provides an update on risk stratification approaches including a validated Risk Score. Potential applications of risk assessment including targeted thromboprophylaxis are outlined. © 2014 Elsevier Ltd. All rights reserved. PMID:24862143

  16. Characterizing Tumor Heterogeneity With Functional Imaging and Quantifying High-Risk Tumor Volume for Early Prediction of Treatment Outcome: Cervical Cancer as a Model

    SciTech Connect

    Mayr, Nina A.; Huang Zhibin; Wang, Jian Z.; Lo, Simon S.; Fan, Joline M.; Grecula, John C.; Sammet, Steffen; Sammet, Christina L.; Jia Guang; Zhang Jun; Knopp, Michael V.; Yuh, William T.C.

    2012-07-01

    Purpose: Treatment response in cancer has been monitored by measuring anatomic tumor volume (ATV) at various times without considering the inherent functional tumor heterogeneity known to critically influence ultimate treatment outcome: primary tumor control and survival. This study applied dynamic contrast-enhanced (DCE) functional MRI to characterize tumors' heterogeneous subregions with low DCE values, at risk for treatment failure, and to quantify the functional risk volume (FRV) for personalized early prediction of treatment outcome. Methods and Materials: DCE-MRI was performed in 102 stage IB{sub 2}-IVA cervical cancer patients to assess tumor perfusion heterogeneity before and during radiation/chemotherapy. FRV represents the total volume of tumor voxels with critically low DCE signal intensity (<2.1 compared with precontrast image, determined by previous receiver operator characteristic analysis). FRVs were correlated with treatment outcome (follow-up: 0.2-9.4, mean 6.8 years) and compared with ATVs (Mann-Whitney, Kaplan-Meier, and multivariate analyses). Results: Before and during therapy at 2-2.5 and 4-5 weeks of RT, FRVs >20, >13, and >5 cm{sup 3}, respectively, significantly predicted unfavorable 6-year primary tumor control (p = 0.003, 7.3 Multiplication-Sign 10{sup -8}, 2.0 Multiplication-Sign 10{sup -8}) and disease-specific survival (p = 1.9 Multiplication-Sign 10{sup -4}, 2.1 Multiplication-Sign 10{sup -6}, 2.5 Multiplication-Sign 10{sup -7}, respectively). The FRVs were superior to the ATVs as early predictors of outcome, and the differentiating power of FRVs increased during treatment. Discussion: Our preliminary results suggest that functional tumor heterogeneity can be characterized by DCE-MRI to quantify FRV for predicting ultimate long-term treatment outcome. FRV is a novel functional imaging heterogeneity parameter, superior to ATV, and can be clinically translated for personalized early outcome prediction before or as early as 2-5 weeks

  17. Predictive Models of Liver Cancer

    EPA Science Inventory

    Predictive models of chemical-induced liver cancer face the challenge of bridging causative molecular mechanisms to adverse clinical outcomes. The latent sequence of intervening events from chemical insult to toxicity are poorly understood because they span multiple levels of bio...

  18. An internally and externally validated nomogram for predicting the risk of irinotecan-induced severe neutropenia in advanced colorectal cancer patients

    PubMed Central

    Ichikawa, W; Uehara, K; Minamimura, K; Tanaka, C; Takii, Y; Miyauchi, H; Sadahiro, S; Fujita, K; Moriwaki, T; Nakamura, M; Takahashi, T; Tsuji, A; Shinozaki, K; Morita, S; Ando, Y; Okutani, Y; Sugihara, M; Sugiyama, T; Ohashi, Y; Sakata, Y

    2015-01-01

    Background: In Asians, the risk of irinotecan-induced severe toxicities is related in part to UGT1A1*6 (UGT, UDP glucuronosyltransferase) and UGT1A1*28, variant alleles that reduce the elimination of SN-38, the active metabolite of irinotecan. We prospectively studied the relation between the UGT1A1 genotype and the safety of irinotecan-based regimens in Japanese patients with advanced colorectal cancer, and then constructed a nomogram for predicting the risk of severe neutropenia in the first treatment cycle. Methods: Safety data were obtained from 1312 patients monitored during the first 3 cycles of irinotecan-based regimen in a prospective observational study. In development of the nomogram, multivariable logistic regression analysis was used to test the associations of candidate factors to severe neutropenia in the first cycle. The final nomogram based on the results of multivariable analysis was constructed and validated internally using a bootstrapping technique and externally in an independent data set (n=350). Results: The UGT1A1 genotype was confirmed to be associated with increased risks of irinotecan-induced grade 3 or 4 neutropenia and diarrhoea. The final nomogram included type of regimen, administered dose of irinotecan, gender, age, UGT1A1 genotype, Eastern Cooperative Oncology Group performance status, pre-treatment absolute neutrophil count, and total bilirubin level. The model was validated both internally (bootstrap-adjusted concordance index, 0.69) and externally (concordance index, 0.70). Conclusions: Our nomogram can be used before treatment to accurately predict the probability of irinotecan-induced severe neutropenia in the first cycle of therapy. Additional studies should evaluate the effect of nomogram-guided dosing on efficacy in patients receiving irinotecan. PMID:25880011

  19. Infective Endocarditis and Cancer Risk

    PubMed Central

    Sun, Li-Min; Wu, Jung-Nan; Lin, Cheng-Li; Day, Jen-Der; Liang, Ji-An; Liou, Li-Ren; Kao, Chia-Hung

    2016-01-01

    Abstract This study investigated the possible relationship between endocarditis and overall and individual cancer risk among study participants in Taiwan. We used data from the National Health Insurance program of Taiwan to conduct a population-based, observational, and retrospective cohort study. The case group consisted of 14,534 patients who were diagnosed with endocarditis between January 1, 2000 and December 31, 2010. For the control group, 4 patients without endocarditis were frequency matched to each endocarditis patient according to age, sex, and index year. Competing risks regression analysis was conducted to determine the effect of endocarditis on cancer risk. A large difference was noted in Charlson comorbidity index between endocarditis and nonendocarditis patients. In patients with endocarditis, the risk for developing overall cancer was significant and 119% higher than in patients without endocarditis (adjusted subhazard ratio = 2.19, 95% confidence interval = 1.98–2.42). Regarding individual cancers, in addition to head and neck, uterus, female breast and hematological malignancies, the risks of developing colorectal cancer, and some digestive tract cancers were significantly higher. Additional analyses determined that the association of cancer with endocarditis is stronger within the 1st 5 years after endocarditis diagnosis. This population-based cohort study found that patients with endocarditis are at a higher risk for colorectal cancer and other cancers in Taiwan. The risk was even higher within the 1st 5 years after endocarditis diagnosis. It suggested that endocarditis is an early marker of colorectal cancer and other cancers. The underlying mechanisms must still be explored and may account for a shared risk factor of infection in both endocarditis and malignancy. PMID:27015220

  20. Prostate-specific antigen nadir after high-dose-rate brachytherapy predicts long-term survival outcomes in high-risk prostate cancer

    PubMed Central

    Satoh, Takefumi; Ishiyama, Hiromichi; Tabata, Ken-ichi; Komori, Shouko; Sekiguchi, Akane; Ikeda, Masaomi; Kurosaka, Shinji; Fujita, Tetsuo; Kitano, Masashi; Hayakawa, Kazushige; Iwamura, Masatsugu

    2016-01-01

    Purpose To evaluate the prognostic value of prostate-specific antigen nadir (nPSA) after high-dose-rate (HDR) brachytherapy in clinically non-metastatic high-risk prostate cancer patients. Material and methods Data from 216 patients with high-risk or locally advanced prostate cancer who underwent HDR brachytherapy and external beam radiation therapy with long-term androgen deprivation therapy (ADT) between 2003 and 2008 were analyzed. The median prostate-specific antigen (PSA) level at diagnosis was 24 ng/ml (range: 3-338 ng/ml). The clinical stage was T1c-2a in 55 cases (26%), T2b-2c in 48 (22%), T3a in 75 (35%), and T3b-4 in 38 (17%). The mean dose to 90% of the planning target volume was 6.3 Gy/fraction of HDR brachytherapy. After 5 fractions, external beam radiation therapy with 10 fractions of 3 Gy was administered. All patients initially underwent neoadjuvant ADT for at least 6 months, and adjuvant ADT was continued for 36 months. The median follow-up was 7 years from the start of radiotherapy. Results The 7-year PSA relapse-free rate among patients with a post-radiotherapy nPSA level of ≤ 0.02 ng/ml was 94%, compared with 23% for patients with higher nPSA values (HR = 28.57; 95% CI: 12.04-66.66; p < 0.001). Multivariate analysis revealed that the nPSA value after radiotherapy was a significant independent predictor of biochemical failure, whereas pretreatment predictive values for worse biochemical control including higher level of initial PSA, Gleason score ≥ 8, positive biopsy core rate ≥ 67%, and T3b-T4, failed to reach independent predictor status. The 7-year cancer-specific survival rate among patients with a post-radiotherapy nPSA level of ≤ 0.02 ng/ml was 99%, compared with 82% for patients with higher nPSA values (HR = 32.25; 95% CI: 3.401-333.3; p = 0.002). Conclusions A post-radiotherapy nPSA value of ≤ 0.02 ng/ml was associated with better long-term biochemical tumor control even if patients had pretreatment predictive values for worse

  1. Reproduction and Breast Cancer Risk

    PubMed Central

    Hanf, Volker; Hanf, Dorothea

    2014-01-01

    Summary Reproduction is doubtlessly one of the main biological meanings of life. It is therefore not surprising that various aspects of reproduction impact on breast cancer risk. Various developmental levels may become targets of breast tumorigenesis. This review follows the chronologic sequence of events in the life of a female at risk, starting with the intrauterine development. Furthermore, the influence of both contraceptive measures and fertility treatment on breast cancer development is dealt with, as well as various pregnancy-associated factors, events, and perinatal outcomes. Finally, the contribution of breast feeding to a reduced breast cancer risk is discussed. PMID:25759622

  2. Predictive diagnosis of the risk of breast cancer recurrence after surgery by single-particle quantum dot imaging

    PubMed Central

    Gonda, Kohsuke; Miyashita, Minoru; Higuchi, Hideo; Tada, Hiroshi; Watanabe, Tomonobu M.; Watanabe, Mika; Ishida, Takanori; Ohuchi, Noriaki

    2015-01-01

    In breast cancer, the prognosis of human epidermal growth factor receptor 2 (HER2)-positive patients (20–25%) has been dramatically improved by the clinical application of the anti-HER2 antibody drugs trastuzumab and pertuzumab. However, the clinical outcomes of HER2-negative cases with a poor prognosis have not improved, and novel therapeutic antibody drugs or diagnostic molecular markers of prognosis are urgently needed. Here, we targeted protease-activated receptor 1 (PAR1) as a new biomarker for HER2-negative patients. The developed anti-PAR1 antibody inhibited PAR1 activation by matrix metalloprotease 1 and thereby prevented cancer-cell migration and invasion. To estimate PAR1 expression levels in HER2-negative patient tissues using the antibody, user-friendly immunohistochemistry with fluorescence nanoparticles or quantum dots (QDs) was developed. Previously, immunohistochemistry with QDs was affected by tissue autofluorescence, making quantitative measurement extremely difficult. We significantly improved the quantitative sensitivity of immunohistochemistry with QDs by using an autofluorescence-subtracted image and single-QD imaging. The immunohistochemistry showed that PAR1 expression was strongly correlated with relapse-free survival time in HER2-negative breast cancer patients. Therefore, the developed anti-PAR1 antibody is a strong candidate for use as an anticancer drug and a prognostic biomarker for HER2-negative patients. PMID:26392299

  3. [Predictive microbiology and risk assessment].

    PubMed

    Hildebrandt, G; Kleer, J

    2004-05-01

    Predictive microbiology (predictive modelling PM), in spite of its limits and short-comings, may often contribute to a reduction of the problems arising when HACCP systems are established or microbiological risk assessment is done. Having identified the agents which constitute a risk and the contamination rate and density in the raw material, the influences of production steps and storage on these microorganisms have to be examined. Finally, there should be an exposure assessment, i.e. an estimate of the contamination density in the final product at the time of consumption. Should the exposure assessment together with data from dose response assessments reveal a potential for intake of inacceptable numbers of organisms, the risk identified has to be characterized. As a consequence, risk management should result in a modification of the composition of the product and/or of the production process so that the risk does not surpass an acceptable limit. For this approach it is indispensable to have product- and process-specific information on the multiplication of pathogens prior to heat treatment, on reduction of their density by thermal treatment and on growth or dying of organisms having survived heat treatment or penetrated into the product after heat treatment as post-process contaminant. Commonly, challenge tests are conducted to provide such information. But they are time consuming and, as their results are only valid for the specific product tested and the conditions prevailing during the experiment, the have to be repeated if there is any modification of intrinsic or extrinsic factors. At least partially, the PM may replace the challenge tests. The efficiency of the models is rated particularly high if they are used already at the stage of product development when the question has to be answered whether a planned recipe or process of production are already save or have to be modified to become save. PMID:15233338

  4. Risks of Skin Cancer Screening

    MedlinePlus

    ... the body's largest organ . It protects against heat, sunlight, injury, and infection . Skin also helps control body ... cancer risk factors include: Being exposed to natural sunlight or artificial sunlight (such as from tanning beds) ...

  5. Oral Contraceptives and Cancer Risk

    MedlinePlus

    ... oral contraceptives are available in the United States today? How could oral contraceptives influence cancer risk? How ... oral contraceptives are available in the United States today? Two types of oral contraceptives (birth control pills) ...

  6. Cancer risks after radiation exposures

    SciTech Connect

    Voelz, G.L.

    1980-01-01

    A general overview of the effects of ionizing radiation on cancer induction is presented. The relationship between the degree of risk and absorbed dose is examined. Mortality from radiation-induced cancer in the US is estimated and percentages attributable to various sources are given. (ACR)

  7. Lower Gastrointestinal Bleeding And Risk of Gastrointestinal Cancer

    PubMed Central

    Viborg, Søren; Søgaard, Kirstine Kobberøe; Farkas, Dóra Körmendiné; Nørrelund, Helene; Pedersen, Lars; Sørensen, Henrik Toft

    2016-01-01

    OBJECTIVES: Lower gastrointestinal (GI) bleeding is a well-known symptom of colorectal cancer (CRC). Whether incident GI bleeding is also a marker of other GI cancers remains unclear. METHODS: This nationwide cohort study examined the risk of various GI cancer types in patients with lower GI bleeding. We used Danish medical registries to identify all patients with a first-time hospital diagnosis of lower GI bleeding during 1995–2011 and followed them for 10 years to identify subsequent GI cancer diagnoses. We computed absolute risks of cancer, treating death as a competing risk, and calculated standardized incidence ratios (SIRs) by comparing observed cancer cases with expected cancer incidence rates in the general population. RESULTS: Among 58,593 patients with lower GI bleeding, we observed 2,806 GI cancers during complete 10-year follow-up. During the first year of follow-up, the absolute GI cancer risk was 3.6%, and the SIR of any GI cancer was 16.3 (95% confidence interval (CI): 15.6–17.0). Colorectal cancers accounted for the majority of diagnoses, but risks of all GI cancers were increased. During 1–5 years of follow-up, the SIR of any GI cancer declined to 1.36 (95% CI: 1.25–1.49), but risks remained increased for several GI cancers. Beyond 5 years of follow-up, the overall GI cancer risk was close to unity, with reduced risk of rectal cancer and increased risk of liver and pancreatic cancers. CONCLUSIONS: A hospital-based diagnosis of lower GI bleeding is a strong clinical marker of prevalent GI cancer, particularly CRC. It also predicts an increased risk of any GI cancer beyond 1 year of follow-up. PMID:27054580

  8. Genomic approaches to outcome prediction in prostate cancer.

    PubMed

    Febbo, Phillip G

    2009-07-01

    Prostate cancer remains a common cause of cancer death in men. Applications of emerging genomic technologies to high-quality prostate cancer models and patient samples in multiple contexts have made significant contributions to our molecular understanding of the development and progression of prostate cancer. Genomic analysis of DNA, RNA, and protein alterations allows for the global assessment of this disease and provides the molecular framework to improve risk classification, outcome prediction, and development of targeted therapies. In this review, the author focused on highlighting recent work in genomics and its role in evaluating molecular modifiers of prostate cancer risk and behavior and the development of predictive models that anticipate the risk of developing prostate cancer, prostate cancer progression, and the response of prostate cancer to therapy. This framework has the exciting potential to be predictive and to provide personalized and individual treatment to the large number of men diagnosed with prostate cancer each year. Cancer 2009;115(13 suppl):3046-57. (c) 2009 American Cancer Society. PMID:19544546

  9. Experiences of predictive testing in young people at risk of Huntington's disease, familial cardiomyopathy or hereditary breast and ovarian cancer

    PubMed Central

    MacLeod, Rhona; Beach, Anna; Henriques, Sasha; Knopp, Jasmin; Nelson, Katie; Kerzin-Storrar, Lauren

    2014-01-01

    While debate has focused on whether testing of minors for late onset genetic disorders should be carried out if there is no medical benefit, less is known about the impact on young people (<25 years) who have had predictive testing often many years before the likely onset of symptoms. We looked at the experiences of young people who had had predictive testing for a range of conditions with variable ages at onset and options for screening and treatment. A consecutive series of 61 young people who had a predictive test aged 15–25 years at the Clinical Genetic Service, Manchester, for HD, HBOC (BrCa 1 or 2) or FCM (Hypertrophic Cardiomyopathy or Dilated Cardiomyopathy), were invited to participate. Thirty-six (36/61; 59%) agreed to participate (10 HD, 16 HBOC and 10 FCM) and telephone interviews were audiotaped, transcribed and analysed using Interpretative Phenomenological Analysis. None of the participants expressed regret at having the test at a young age. Participants saw the value of pretest counselling not in facilitating a decision, but rather as a source of information and support. Differences emerged among the three groups in parent/family involvement in the decision to be tested. Parents in FCM families were a strong influence in favour of testing, in HBOC the decision was autonomous but usually congruent with the views of parents, whereas in HD the decision was autonomous and sometimes went against the opinions of parents/grandparents. Participants from all three groups proposed more tailoring of predictive test counselling to the needs of young people. PMID:23860040

  10. Blood Pressure Patterns May Predict Stroke Risk

    MedlinePlus

    ... fullstory_158731.html Blood Pressure Patterns May Predict Stroke Risk Odds increase with rapid rise in middle ... overall pattern to predict a patient's risk of stroke or early death, new research suggests. "Our study ...

  11. Gene Tied to Breast Cancer Raises Uterine Cancer Risk Too

    MedlinePlus

    ... news/fullstory_159652.html Gene Tied to Breast Cancer Raises Uterine Cancer Risk Too Women with BRCA1 may want to ... increased risk for a deadly form of uterine cancer, a new study finds. The BRCA1 gene mutation ...

  12. Association analysis of a chemo-response signature identified within The Cancer Genome Atlas aimed at predicting genetic risk for chemo-response in ovarian cancer

    PubMed Central

    Salinas, Erin A; Newtson, Andreea M; Leslie, Kimberly K; Gonzalez-Bosquet, Jesus

    2016-01-01

    Background: A gene signature associated with chemo-response in ovarian cancer was created through integration of biological data in The Cancer Genome Atlas (TCGA) and validated in five independent microarray experiments. Our study aimed to determine if single nucleotide polymorphisms (SNPs) within the 422-gene signature were associated with a genetic predisposition to platinum-based chemotherapy response in serous ovarian cancer. Methods: An association analysis between SNPs within the 422-gene signature and chemo-response in serous ovarian cancer was performed under the log-additive genetic model using the ‘SNPassoc’ package within the R environment (p<0.0001). Subsequent validation of statistically significant SNPs was done in the Ovarian Cancer Association Consortium (OCAC) database. Results: 19 SNPs were found to be associated with chemo-response with statistical significance. None of the SNPs found significant in TCGA were validated within OCAC for the outcome of interest, chemo-response. Conclusions: SNPs associated with chemo-response in ovarian cancer within TGCA database were not validated in a larger database of patients and controls from OCAC. New strategies integrating somatic and germline information may help to characterize genetic predictors for treatment response in ovarian cancer. PMID:27186327

  13. Understanding your colon cancer risk

    MedlinePlus

    ... the chance that you could get cancer. Some risk factors you can control, such as drinking alcohol. Others, such as family ... cannot be changed. But just because you have risk factors you cannot control does not mean you cannot take steps to ...

  14. Occupational risk for laryngeal cancer

    SciTech Connect

    Flanders, W.D.; Rothman, K.J.

    1982-04-01

    In a case-control analysis, we studied the effects of type of employment on laryngeal cancer risk using the interview data from the Third National Cancer Survey. Effects were measured relative to the risk for those employed in a group of arbitrarily defined industries and occupations with low risk. We excluded females and controlled for age, tobacco use, alcohol use, and race in the analysis. We found ratio estimates above 3.0 for workers in the railroad industry and the lumber industry; and for sheetmetal workers, grinding wheel operators, and automobile mechanics.

  15. Healthy eating index and breast cancer risk among Malaysian women.

    PubMed

    Shahril, Mohd Razif; Sulaiman, Suhaina; Shaharudin, Soraya Hanie; Akmal, Sharifah Noor

    2013-07-01

    Healthy Eating Index-2005 (HEI-2005), an index-based dietary pattern, has been shown to predict the risk of chronic diseases among Americans. This study aims to examine the ability of HEI-2005 in predicting the probability for risk of premenopausal and postmenopausal breast cancer among Malaysian women. Data from a case-control nutritional epidemiology study among 764 participants including 382 breast cancer cases and 382 healthy women were extracted and scored. Multivariate odds ratios (OR) with 95% confidence intervals (CI) were used to evaluate the relationship between the risk of breast cancer and quartiles (Q) of HEI-2005 total scores and its component, whereas the risk prediction ability of HEI-2005 was investigated using diagnostics analysis. The results of this study showed that there is a significant reduction in the risk of breast cancer, with a higher HEI-2005 total score among premenopausal women (OR Q1 vs. Q4=0.34, 95% CI; 0.15-0.76) and postmenopausal women (OR Q1 vs. Q4=0.20, 95% CI; 0.06-0.63). However, HEI-2005 has a sensitivity of 56-60%, a specificity of 55-60%, and a positive predictive value and negative predictive value of 57-58%, which indicates a moderate ability to predict the risk of breast cancer according to menopausal status. The breast cancer incidence observed poorly agrees with risk outcomes from HEI-2005 as shown by low κ statistics (κ=0.15). In conclusion, although the total HEI-2005 scores were associated with a risk of breast cancer among Malaysian women, the ability of HEI-2005 to predict risk is poor as indicated by the diagnostic analysis. A local index-based dietary pattern, which is disease specific, is required to predict the risk of breast cancer among Malaysian women for early prevention. PMID:23702680

  16. Interval to Biochemical Failure Predicts Clinical Outcomes in Patients With High-Risk Prostate Cancer Treated by Combined-Modality Radiation Therapy

    SciTech Connect

    Shilkrut, Mark; McLaughlin, P. William; Merrick, Gregory S.; Vainshtein, Jeffrey M.; Feng, Felix Y.; Hamstra, Daniel A.

    2013-07-15

    Purpose: To validate the prognostic value of interval to biochemical failure (IBF) in patients with high-risk prostate cancer (HiRPCa) treated with combined-modality radiation therapy (CMRT) with or without androgen deprivation therapy (ADT). Methods and Materials: We conducted a retrospective review of HiRPCa (prostate-specific antigen >20 ng/mL, Gleason score [GS] 8-10, or clinical T stage T3-T4) treated with either dose-escalated external beam radiation therapy (EBRT) or CMRT. Interval to biochemical failure was classified as ≤18 or >18 months from the end of all therapy to the date of biochemical failure (BF). Kaplan-Meier methods and Cox proportional hazards regression were used to evaluate the prognostic value of IBF ≤18 months for distant metastasis (DM) and prostate cancer-specific mortality (PCSM). Results: Of 958 patients with a median follow-up of 63.2 months, 175 patients experienced BF. In those with BF, there were no differences in pretreatment clinical characteristics between the EBRT and CMRT groups, except for a higher proportion of patients with GS 8-10 in the CMRT group (70% vs 52%, P=.02). Median IBF after all therapy was 24.0 months (interquartile range 9.6-46.0) in the EBRT group and 18.9 months (interquartile range 9.2-34.5) in the CMRT group (P=.055). On univariate analysis, IBF ≤18 months was associated with increased risk of DM and PCSM in the entire cohort and the individual EBRT and CMRT groups. On multivariate analysis, only GS 9-10 and IBF ≤18 months, but not the radiation therapy regimen or ADT use, predicted DM (hazard ratio [HR] 3.7, P<.01, 95% confidence interval [CI] 1.4-10.3 for GS 9-10; HR 3.9, P<.0001, 95% CI 2.4-6.5 for IBF ≤18 months) and PCSM (HR 14.8, P<.009, 95% CI 2.0-110 for GS 9-10; HR 4.4, P<.0001, 95% CI 2.4-8.1 for IBF ≤18 months). Conclusions: Short IBF was highly prognostic for higher DM and PCSM in patients with HiRPCa. The prognostic value of IBF for DM and PCSM was not affected by the radiation

  17. Tumor angiogenesis as prognostic and predictive marker for chemotherapy dose-intensification efficacy in high-risk breast cancer patients within the WSG AM-01 trial.

    PubMed

    Gluz, Oleg; Wild, Peter; Liedtke, Cornelia; Kates, Ronald; Mendrik, Heiko; Ehm, Elisabeth; Artinger, Verena; Diallo-Danebrock, Raihanatou; Ting, Evelyn; Mohrmann, Svjetlana; Poremba, Christopher; Harbeck, Nadia; Nitz, Ulrike; Hartmann, Arndt; Gaumann, Andreas

    2011-04-01

    The goal of this analysis was to characterize the survival impact of angiogenesis in the patients with high-risk breast cancer, particularly the predictive impact on benefit from dose intensification of adjuvant chemotherapy. Formalin-fixed tissue sample of 152 patients treated as part of the WSG AM-01 trial by either high-dose or conventional dose-dense chemotherapy were analyzed. Angiogenic activity was measured using microvessel count and vascular surface area (VSA) determined by the expression of vascular markers CD31 (n = 128) and CD105/endoglin (n = 130). Protein molecular breast cancer subclasses were analyzed by k-means clustering (k = 5). The univariate impact of factors on event-free (EFS) and overall survival (OS) was tested by log-rank statistics and quantified by univariate Cox analysis. Multivariate survival analysis included factors significant in univariate analysis, as well as interactions was performed for EFS. Both VSA/CD31 (P = 0.004) and VSA/CD105 (P = 0.003) were significantly higher among cases with increased Ki-67. A significant association with molecular subtypes was also found for VSA/CD105: in patients with basal-like/Her-2 subtypes, mean was 1.72 versus 1.24 in patients with other subtypes (P < 0.001). Elevated VSA/CD105 was associated with both significantly decreased EFS (P = 0.01) and OS (P = 0.02). Increased tumor size and positive Her-2 status were also prognostic for poorer EFS. The benefit of dose intensification for EFS was seen in those low-VSA/CD105 patients. The result was evident both in univariate and in multivariate survival analysis including all factors that were significant at the univariate level. Expression of angiogenesis markers may mirror or confer resistance to chemotherapy in the patients with breast cancer, particularly within the context of dose intensified chemotherapy. Highly angiogenic tumors may not derive sufficient benefit from dose intensification of chemotherapy alone. Our findings may serve as a

  18. Obesity and Cancer Risk

    MedlinePlus

    ... cancer screening among obese adults. National Collaborative on Childhood Obesity Research (NCCOR) NCCOR brings together four of the nation’s leading funders of childhood obesity research: the CDC, NIH, Robert Wood Johnson Foundation, ...

  19. Endometrial Cancer Risk Factors

    MedlinePlus

    ... Women with a condition called polycystic ovarian syndrome (PCOS) have abnormal hormone levels, such as higher androgen ( ... increase a woman's chance of getting endometrial cancer. PCOS is also a leading cause of infertility in ...

  20. Cancer prevention strategies greatly exaggerate risks

    SciTech Connect

    Ames, B.N. ); Gold, L.S. )

    1991-01-07

    This paper reports on the attempt to prevent cancer by regulating low levels of synthetic chemicals by risk assessment. Testing chemicals for carcinogenicity at near-toxic doses in rodents does not provide enough information to predict the excess numbers of human cancers that might occur at low-dose exposures. In addition, this cancer prevention strategy is enormously costly, is counterproductive because it diverts resources from much more important risks, and, in the case of synthetic pesticides, makes fruits and vegetables more expensive, thus serving to decrease consumption of foods that help prevent cancer. The regulatory process doesn't take into account that: The world of natural chemicals makes up the vast bulk of chemicals humans are exposed to. The toxicology of synthetic and natural toxins is not fundamentally different. About half the natural chemicals tested chronically in rats and mice at the maximum tolerated dose are carcinogens. Testing at the maximum tolerated dose frequently can cause chronic cell killing and consequent cell replacement (a risk factor for cancer that can be limited to high doses), and ignoring this greatly exaggerates risks. An extrapolation from high to low doses should be based on an understanding of the mechanisms of carcinogenesis.

  1. Circulating Adiponectin and Risk of Endometrial Cancer

    PubMed Central

    Zheng, Qiaoli; Wu, Haijian; Cao, Jiang

    2015-01-01

    Background Adiponectin is an insulin-sensitizing hormone produced by adipocytes. It has been suggested to be involved in endometrial tumorigenesis. Published data have shown inconsistent results for the association between circulating adiponectin levels and endometrial cancer. In this study, we conducted a meta-analysis to evaluate the predictive value of circulating adiponectin levels on the development of endometrial cancer. Methods PubMed, Embase, ISI web of knowledge, and Cochrane databases were searched for all eligible studies, and the summary relative risk (SRR) was calculated. Additionally, we performed dose-response analysis with eight eligible studies. Results A total of 1,955 cases and 3,458 controls from 12 studies were included. The SRR for the ‘highest’ vs ‘lowest’ adiponectin levels indicated high adiponectin level reduced the risk of endometrial cancer [SRR = 0.40, 95% confidence interval (CI), 0.33–0.66]. Results from the subgroup analyses were consistent with the overall analysis. The SRR for each 1 µg/ml increase of adiponectin indicated a 3% reduction in endometrial cancer risk (95% CI: 2%–4%), and a 14% reduction for each increase of 5 µg/ml (95% CI: 9%–19%). No evidence of publication bias was found. Conclusions This meta-analysis demonstrates that low level of circulating adiponectin is a risk factor for endometrial cancer. PMID:26030130

  2. Risk Stratification System for Oral Cancer Screening.

    PubMed

    Pereira, Lutécia H Mateus; Reis, Isildinha M; Reategui, Erika P; Gordon, Claudia; Saint-Victor, Sandra; Duncan, Robert; Gomez, Carmen; Bayers, Stephanie; Fisher, Penelope; Perez, Aymee; Goodwin, W Jarrard; Hu, Jennifer J; Franzmann, Elizabeth J

    2016-06-01

    Oral cavity and oropharyngeal cancer (oral cancer) is a deadly disease that is increasing in incidence. Worldwide 5-year survival is only 50% due to delayed intervention with more than half of the diagnoses at stage III and IV, whereas earlier detection (stage I and II) yields survival rates up to 80% to 90%. Salivary soluble CD44 (CD44), a tumor-initiating marker, and total protein levels may facilitate oral cancer risk assessment and early intervention. This study used a hospital-based design with 150 cases and 150 frequency-matched controls to determine whether CD44 and total protein levels in oral rinses were associated with oral cancer independent of age, gender, race, ethnicity, tobacco and alcohol use, and socioeconomic status (SES). High-risk subjects receiving oral cancer prevention interventions as part of a community-based program (n = 150) were followed over 1 year to determine marker specificity and variation. CD44 ≥5.33 ng/mL was highly associated with case status [adjusted OR 14.489; 95% confidence interval (CI), 5.973-35.145; P < .0001, vs. reference group CD44 <2.22 ng/mL and protein <1.23 mg/mL]. Total protein aided prediction above CD44 alone. Sensitivity and specificity in the frequency-matched study was 80% and 48.7%, respectively. However, controls were not representative of the target screening population due, in part, to a high rate of prior cancer. In contrast, specificity in the high-risk community was 74% and reached 95% after annual retesting. Simple and inexpensive salivary CD44 and total protein measurements may help identify individuals at heightened risk for oral cancer from the millions who partake in risky behaviors. Cancer Prev Res; 9(6); 445-55. ©2016 AACR. PMID:27020654

  3. Pelvic Lymph Node Status Assessed by 18F-Fluorodeoxyglucose Positron Emission Tomography Predicts Low-Risk Group for Distant Recurrence in Locally Advanced Cervical Cancer: A Prospective Study

    SciTech Connect

    Kang, Sokbom; Park, Jung-Yeol; Lim, Myung-Chul; Song, Yong-Joong; Park, Se-Hyun; Kim, Seok-Ki; Chung, Dae-Chul; Seo, Sang-Soo; Kim, Joo-Young; Park, Sang-Yoon

    2011-03-01

    Purpose: To develop a prediction model to identify a low-risk group for distant recurrence in patients with locally advanced cervical cancer treated by concurrent chemoradiation. Methods and Materials: Prospectively, 62 patients with locally advanced cervical cancer were recruited as a training cohort. Clinical variables and parameters obtained from positron emission tomography (PET) and magnetic resonance imaging were analyzed by logistic regression. For the test set, 54 patients were recruited independently. To identify the low-risk group, negative likelihood ratio (LR) less than 0.2 was set to be a cutoff. Results: Among the training cohort, multivariate logistic analysis revealed that advanced International Federation of Gynecology and Obstetrics (FIGO) stage and a high serum squamous cancer cell (SCC) antigen level were significant risk factors (p = 0.015 and 0.025, respectively). Using the two parameters, criteria to determine a low-risk subset for distant recurrence were postulated: (1) FIGO Stage IIB or less and (2) pretreatment SCC < 2.4 (Model A). Positive pelvic node on PET completely predicted all cases with distant recurrence and thus was considered as another prediction model (Model B). In the test cohort, although Model A did not showed diagnostic performance, Model B completely predicted all cases with distant recurrence and showed a sensitivity of 100% with negative LR of 0. Across the training and test cohort (n = 116), the false negative rate was 0 (95% confidence interval 0%-7.6%). Conclusions: Positive pelvic node on PET is a useful marker in prediction of distant recurrence in patients with locally advanced cervical cancer who are treated with concurrent chemoradiation.

  4. Breast cancer risk assessment using genetic variants and risk factors in a Singapore Chinese population

    PubMed Central

    2014-01-01

    Introduction Genetic variants for breast cancer risk identified in genome-wide association studies (GWAS) in Western populations require further testing in Asian populations. A risk assessment model incorporating both validated genetic variants and established risk factors may improve its performance in risk prediction of Asian women. Methods A nested case-control study of female breast cancer (411 cases and 1,212 controls) within the Singapore Chinese Health Study was conducted to investigate the effects of 51 genetic variants identified in previous GWAS on breast cancer risk. The independent effect of these genetic variants was assessed by creating a summed genetic risk score (GRS) after adjustment for body mass index and the Gail model risk factors for breast cancer. Results The GRS was an independent predictor of breast cancer risk in Chinese women. The multivariate-adjusted odds ratios (95% confidence intervals) of breast cancer for the second, third, and fourth quartiles of the GRS were 1.26 (0.90 to 1.76), 1.47 (1.06 to 2.04) and 1.75 (1.27 to 2.41) respectively (P for trend <0.001). In addition to established risk factors, the GRS improved the classification of 6.2% of women for their absolute risk of breast cancer in the next five years. Conclusions Genetic variants on top of conventional risk factors can improve the risk prediction of breast cancer in Chinese women. PMID:24941967

  5. Genetic testing for cancer risk.

    PubMed

    Ponder, B

    1997-11-01

    Genetic testing for cancer susceptibility is already part of the clinical management of families with some of the well-defined (but uncommon) inherited cancer syndromes. In cases where the risks associated with a predisposing mutation are less certain, or where there is no clearly effective intervention to offer those with a positive result, its use is more controversial. Careful evaluation of costs and benefits, and of the efficacy of interventions in those found to be at risk, is essential and is only just beginning. An immediate challenge is to ensure that both health professionals and the public understand clearly the issues involved. PMID:9353178

  6. BRCA1-like profile predicts benefit of tandem high dose epirubicin-cyclophospamide-thiotepa in high risk breast cancer patients randomized in the WSG-AM01 trial.

    PubMed

    Schouten, Philip C; Gluz, Oleg; Harbeck, Nadia; Mohrmann, Svjetlana; Diallo-Danebrock, Raihana; Pelz, Enrico; Kruizinga, Janneke; Velds, Arno; Nieuwland, Marja; Kerkhoven, Ron M; Liedtke, Cornelia; Frick, Markus; Kates, Ronald; Linn, Sabine C; Nitz, Ulrike; Marme, Frederik

    2016-08-15

    BRCA1 is an important protein in the repair of DNA double strand breaks (DSBs), which are induced by alkylating chemotherapy. A BRCA1-like DNA copy number signature derived from tumors with a BRCA1 mutation is indicative for impaired BRCA1 function and associated with good outcome after high dose (HD) and tandem HD DSB inducing chemotherapy. We investigated whether BRCA1-like status was a predictive biomarker in the WSG AM 01 trial. WSG AM 01 randomized high-risk breast cancer patients to induction (2× epirubicin-cyclophosphamide) followed by tandem HD chemotherapy with epirubicin, cyclophosphamide and thiotepa versus dose dense chemotherapy (4× epirubicin-cyclophospamide followed by 3× cyclophosphamide-methotrexate-5-fluorouracil). We generated copy number profiles for 143 tumors and classified them as being BRCA1-like or non-BRCA1-like. Twenty-six out of 143 patients were BRCA1-like. BRCA1-like status was associated with high grade and triple negative tumors. With regard to event-free-survival, the primary endpoint of the trial, patients with a BRCA1-like tumor had a hazard rate of 0.2, 95% confidence interval (CI): 0.07-0.63, p = 0.006. In the interaction analysis, the combination of BRCA1-like status and HD chemotherapy had a hazard rate of 0.19, 95% CI: 0.067-0.54, p = 0.003. Similar results were observed for overall survival. These findings suggest that BRCA1-like status is a predictor for benefit of tandem HD chemotherapy with epirubicin-thiotepa-cyclophosphamide. PMID:26946057

  7. Are Short Telomeres Predictive of Advanced Cancer?

    PubMed Central

    Shay, Jerry W.

    2013-01-01

    Summary The combination of variable telomere length in cancer cells combined with shorter telomere length in cancer-associated stromal cells, strongly correlate with progression to prostate cancer metastasis and cancer death. The implications are that telomere length measurements not only have the potential as a prognostic indicator of prostate cancer outcomes but also as a risk stratification enrichment biomarker for individualized therapeutic interventions. PMID:24124228

  8. Polygenic risk score is associated with increased disease risk in 52 Finnish breast cancer families.

    PubMed

    Muranen, Taru A; Mavaddat, Nasim; Khan, Sofia; Fagerholm, Rainer; Pelttari, Liisa; Lee, Andrew; Aittomäki, Kristiina; Blomqvist, Carl; Easton, Douglas F; Nevanlinna, Heli

    2016-08-01

    The risk of developing breast cancer is increased in women with family history of breast cancer and particularly in families with multiple cases of breast or ovarian cancer. Nevertheless, many women with a positive family history never develop the disease. Polygenic risk scores (PRSs) based on the risk effects of multiple common genetic variants have been proposed for individual risk assessment on a population level. We investigate the applicability of the PRS for risk prediction within breast cancer families. We studied the association between breast cancer risk and a PRS based on 75 common genetic variants in 52 Finnish breast cancer families including 427 genotyped women and pedigree information on ~4000 additional individuals by comparing the affected to healthy family members, as well as in a case-control dataset comprising 1272 healthy population controls and 1681 breast cancer cases with information on family history. Family structure was summarized using the BOADICEA risk prediction model. The PRS was associated with increased disease risk in women with family history of breast cancer as well as in women within the breast cancer families. The odds ratio (OR) for breast cancer within the family dataset was 1.55 [95 % CI 1.26-1.91] per unit increase in the PRS, similar to OR in unselected breast cancer cases of the case-control dataset (1.49 [1.38-1.62]). High PRS-values were informative for risk prediction in breast cancer families, whereas for the low PRS-categories the results were inconclusive. The PRS is informative in women with family history of breast cancer and should be incorporated within pedigree-based clinical risk assessment. PMID:27438779

  9. Providing access to risk prediction tools via the HL7 XML-formatted risk web service.

    PubMed

    Chipman, Jonathan; Drohan, Brian; Blackford, Amanda; Parmigiani, Giovanni; Hughes, Kevin; Bosinoff, Phil

    2013-07-01

    Cancer risk prediction tools provide valuable information to clinicians but remain computationally challenging. Many clinics find that CaGene or HughesRiskApps fit their needs for easy- and ready-to-use software to obtain cancer risks; however, these resources may not fit all clinics' needs. The HughesRiskApps Group and BayesMendel Lab therefore developed a web service, called "Risk Service", which may be integrated into any client software to quickly obtain standardized and up-to-date risk predictions for BayesMendel tools (BRCAPRO, MMRpro, PancPRO, and MelaPRO), the Tyrer-Cuzick IBIS Breast Cancer Risk Evaluation Tool, and the Colorectal Cancer Risk Assessment Tool. Software clients that can convert their local structured data into the HL7 XML-formatted family and clinical patient history (Pedigree model) may integrate with the Risk Service. The Risk Service uses Apache Tomcat and Apache Axis2 technologies to provide an all Java web service. The software client sends HL7 XML information containing anonymized family and clinical history to a Dana-Farber Cancer Institute (DFCI) server, where it is parsed, interpreted, and processed by multiple risk tools. The Risk Service then formats the results into an HL7 style message and returns the risk predictions to the originating software client. Upon consent, users may allow DFCI to maintain the data for future research. The Risk Service implementation is exemplified through HughesRiskApps. The Risk Service broadens the availability of valuable, up-to-date cancer risk tools and allows clinics and researchers to integrate risk prediction tools into their own software interface designed for their needs. Each software package can collect risk data using its own interface, and display the results using its own interface, while using a central, up-to-date risk calculator. This allows users to choose from multiple interfaces while always getting the latest risk calculations. Consenting users contribute their data for future

  10. CANCER RISK ASSESSMENT FOR CHLOROFORM

    EPA Science Inventory

    Chloroform is a common chlorination by-product in drinking water. EPA has regulated chloroform as a probable human carcinogen under the Safe Drinking Water Act. The cancer risk estimate via ingestion was based on the 1985 Jorgenson study identifying kidney tumors in male Osborne ...

  11. Thyroid Cancer Risk Factors

    MedlinePlus

    ... and radiation fallout from power plant accidents or nuclear weapons. Having had head or neck radiation treatments in childhood is a risk factor for ... should be done using the lowest dose of radiation that still provides a clear ... from nuclear weapons or power plant accidents. For instance, thyroid ...

  12. Reproductive History and Breast Cancer Risk

    MedlinePlus

    ... Overview–for health professionals Research Reproductive History and Breast Cancer Risk On This Page Is there a relationship between pregnancy and breast cancer risk? Are any pregnancy-related factors associated with ...

  13. Colon Cancer Risk Assessment - Gauss Program

    Cancer.gov

    An executable file (in GAUSS) that projects absolute colon cancer risk (with confidence intervals) according to NCI’s Colorectal Cancer Risk Assessment Tool (CCRAT) algorithm. GAUSS is not needed to run the program.

  14. Alcohol, Obesity Could Raise Esophageal Cancer Risk

    MedlinePlus

    ... https://medlineplus.gov/news/fullstory_160133.html Alcohol, Obesity Could Raise Esophageal Cancer Risk A third of ... at the American Institute for Cancer Research (AICR). "Obesity is now linked to 11 types of cancer ...

  15. Risk of Ovarian Cancer Relapse Score

    PubMed Central

    Rizzuto, Ivana; Stavraka, Chara; Chatterjee, Jayanta; Borley, Jane; Hopkins, Thomas Glass; Gabra, Hani; Ghaem-Maghami, Sadaf; Huson, Les; Blagden, Sarah P.

    2015-01-01

    Objective The aim of this study was to construct a prognostic index that predicts risk of relapse in women who have completed first-line treatment for ovarian cancer (OC). Methods A database of OC cases from 2000 to 2010 was interrogated for International Federation of Gynecology and Obstetrics stage, grade and histological subtype of cancer, preoperative and posttreatment CA-125 level, presence or absence of residual disease after cytoreductive surgery and on postchemotherapy computed tomography scan, and time to progression and death. The strongest predictors of relapse were included into an algorithm, the Risk of Ovarian Cancer Relapse (ROVAR) score. Results Three hundred fifty-four cases of OC were analyzed to generate the ROVAR score. Factors selected were preoperative serum CA-125, International Federation of Gynecology and Obstetrics stage and grade of cancer, and presence of residual disease at posttreatment computed tomography scan. In the validation data set, the ROVAR score had a sensitivity and specificity of 94% and 61%, respectively. The concordance index for the validation data set was 0.91 (95% confidence interval, 0.85-0.96). The score allows patient stratification into low (<0.33), intermediate (0.34–0.67), and high (>0.67) probability of relapse. Conclusions The ROVAR score stratifies patients according to their risk of relapse following first-line treatment for OC. This can broadly facilitate the appropriate tailoring of posttreatment care and support. PMID:25647256

  16. Risks of Endometrial Cancer Screening

    MedlinePlus

    ... Laboratory for Cancer Research Partners & Collaborators Spotlight on Scientists Research Areas Cancer Biology Cancer Genomics Causes of Cancer ... Centers Frederick National Lab Partners & Collaborators Spotlight on Scientists NCI Research Areas Cancer Biology Cancer Genomics Causes of Cancer ...

  17. Risks of Prostate Cancer Screening

    MedlinePlus

    ... Laboratory for Cancer Research Partners & Collaborators Spotlight on Scientists Research Areas Cancer Biology Cancer Genomics Causes of Cancer ... Centers Frederick National Lab Partners & Collaborators Spotlight on Scientists NCI Research Areas Cancer Biology Cancer Genomics Causes of Cancer ...

  18. Risks of Cervical Cancer Screening

    MedlinePlus

    ... Laboratory for Cancer Research Partners & Collaborators Spotlight on Scientists Research Areas Cancer Biology Cancer Genomics Causes of Cancer ... Centers Frederick National Lab Partners & Collaborators Spotlight on Scientists NCI Research Areas Cancer Biology Cancer Genomics Causes of Cancer ...

  19. Risks of Breast Cancer Screening

    MedlinePlus

    ... of Breast & Gynecologic Cancers Breast Cancer Screening Research Breast Cancer Screening (PDQ®)–Patient Version What is screening? Go ... cancer screening: Cancer Screening Overview General Information About Breast Cancer Key Points Breast cancer is a disease in ...

  20. Topics in cancer risk assessment.

    PubMed Central

    Olin, S S; Neumann, D A; Foran, J A; Scarano, G J

    1997-01-01

    The estimation of carcinogenic risks from exposure to chemicals has become an integral part of the regulatory process in the United States within the past decade. With it have come considerable controversy and debate over the scientific merits and shortcomings of the methods and their impact on risk management decisions. In this paper we highlight selected topics of current interest in the debate. As an indication of the level of public concern, we note the major recent reports on risk assessment from the National Academy of Sciences and the U.S Environmental Protection Agency's proposed substantial revisions to its Guidelines for Carcinogen Risk Assessment. We identify and briefly frame several key scientific issues in cancer risk assessment, including the growing recognition of the importance of understanding the mode of action of carcinogenesis in experimental animals and in humans, the methodologies and challenges in quantitative extrapolation of cancer risks, and the question of how to assess and account for human variability in susceptibility to carcinogens. In addition, we discuss initiatives in progress that may fundamentally alter the carcinogenesis testing paradigm. PMID:9114281

  1. Moving Forward in Human Cancer Risk Assessment

    PubMed Central

    Paules, Richard S.; Aubrecht, Jiri; Corvi, Raffaella; Garthoff, Bernward; Kleinjans, Jos C.

    2011-01-01

    Background The current safety paradigm for assessing carcinogenic properties of drugs, cosmetics, industrial chemicals, and environmental exposures relies mainly on in vitro genotoxicity testing followed by 2-year rodent bioassays. This testing battery is extremely sensitive but has low specificity. Furthermore, rodent bioassays are associated with high costs, high animal burden, and limited predictive value for human risks. Objectives We provide a response to a growing appeal for a paradigm change in human cancer risk assessment. Methods To facilitate development of a road map for this needed paradigm change in carcinogenicity testing, a workshop titled “Genomics in Cancer Risk Assessment” brought together toxicologists from academia and industry and government regulators and risk assessors from the United States and the European Union. Participants discussed the state-of-the-art in developing alternative testing strategies for carcinogenicity, with emphasis on potential contributions from omics technologies. Results and Conclusions The goal of human risk assessment is to decide whether a given exposure to an agent is acceptable to human health and to provide risk management measures based on evaluating and predicting the effects of exposures on human health. Although exciting progress is being made using genomics approaches, a new paradigm that uses these methods and human material when possible would provide mechanistic insights that may inform new predictive approaches (e.g., in vitro assays) and facilitate the development of genomics-derived biomarkers. Regulators appear to be willing to accept such approaches where use is clearly defined, evidence is strong, and approaches are qualified for regulatory use. PMID:21147607

  2. A predictive model to guide management of the overlap region between target volume and organs at risk in prostate cancer volumetric modulated arc therapy

    PubMed Central

    Lee, Jennifer C.; Elnaiem, Sara; Guirguis, Adel; Ikoro, N. C.; Ashamalla, Hani

    2014-01-01

    Purpose The goal of this study is to determine whether the magnitude of overlap between planning target volume (PTV) and rectum (Rectumoverlap) or PTV and bladder (Bladderoverlap) in prostate cancer volumetric-modulated arc therapy (VMAT) is predictive of the dose-volume relationships achieved after optimization, and to identify predictive equations and cutoff values using these overlap volumes beyond which the Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC) dose-volume constraints are unlikely to be met. Materials and Methods Fifty-seven patients with prostate cancer underwent VMAT planning using identical optimization conditions and normalization. The PTV (for the 50.4 Gy primary plan and 30.6 Gy boost plan) included 5 to 10 mm margins around the prostate and seminal vesicles. Pearson correlations, linear regression analyses, and receiver operating characteristic (ROC) curves were used to correlate the percentage overlap with dose-volume parameters. Results The percentage Rectumoverlap and Bladderoverlap correlated with sparing of that organ but minimally impacted other dose-volume parameters, predicted the primary plan rectum V45 and bladder V50 with R2 = 0.78 and R2 = 0.83, respectively, and predicted the boost plan rectum V30 and bladder V30 with R2 = 0.53 and R2 = 0.81, respectively. The optimal cutoff value of boost Rectumoverlap to predict rectum V75 >15% was 3.5% (sensitivity 100%, specificity 94%, p < 0.01), and the optimal cutoff value of boost Bladderoverlap to predict bladder V80 >10% was 5.0% (sensitivity 83%, specificity 100%, p < 0.01). Conclusion The degree of overlap between PTV and bladder or rectum can be used to accurately guide physicians on the use of interventions to limit the extent of the overlap region prior to optimization. PMID:24724048

  3. Developmental Dyslexia: Predicting Individual Risk

    ERIC Educational Resources Information Center

    Thompson, Paul A.; Hulme, Charles; Nash, Hannah M.; Gooch, Debbie; Hayiou-Thomas, Emma; Snowling, Margaret J.

    2015-01-01

    Background: Causal theories of dyslexia suggest that it is a heritable disorder, which is the outcome of multiple risk factors. However, whether early screening for dyslexia is viable is not yet known. Methods: The study followed children at high risk of dyslexia from preschool through the early primary years assessing them from age 3 years and 6…

  4. Cancer Risk Assessment for Space Radiation

    NASA Technical Reports Server (NTRS)

    Richmond, Robert C.; Curreri, Peter A. (Technical Monitor)

    2002-01-01

    Predicting the occurrence of human cancer following exposure to any agent causing genetic damage is a difficult task. This is because the uncertainty of uniform exposure to the damaging agent, and the uncertainty of uniform processing of that damage within a complex set of biological variables, degrade the confidence of predicting the delayed expression of cancer as a relatively rare event within any given clinically normal individual. The radiation health research priorities for enabling long-duration human exploration of space were established in the 1996 NRC Report entitled "Radiation Hazards to Crews of Interplanetary Missions: Biological Issues and Research Strategies". This report emphasized that a 15-fold uncertainty in predicting radiation-induced cancer incidence must be reduced before NASA can commit humans to extended interplanetary missions. That report concluded that the great majority of this uncertainty is biologically based, while a minority is physically based due to uncertainties in radiation dosimetry and radiation transport codes. Since that report, the biologically based uncertainty has remained large, and the relatively small uncertainty associated with radiation dosimetry has increased due to the considerations raised by concepts of microdosimetry. In a practical sense, however, the additional uncertainties introduced by microdosimetry are encouraging since they are in a direction of lowered effective dose absorbed through infrequent interactions of any given cell with the high energy particle component of space radiation. The biological uncertainty in predicting cancer risk for space radiation derives from two primary facts. 1) One animal tumor study has been reported that includes a relevant spectrum of particle radiation energies, and that is the Harderian gland model in mice. Fact #1: Extension of cancer risk from animal models, and especially from a single study in an animal model, to humans is inherently uncertain. 2) One human database

  5. Family Factors Predicting Categories of Suicide Risk

    ERIC Educational Resources Information Center

    Randell, Brooke P.; Wang, Wen-Ling; Herting, Jerald R.; Eggert, Leona L.

    2006-01-01

    We compared family risk and protective factors among potential high school dropouts with and without suicide-risk behaviors (SRB) and examined the extent to which these factors predict categories of SRB. Subjects were randomly selected from among potential dropouts in 14 high schools. Based upon suicide-risk status, 1,083 potential high school…

  6. Dosimetric parameters as predictive factors for biochemical control in patients with higher risk prostate cancer treated with Pd-103 and supplemental beam radiation

    SciTech Connect

    Orio, Peter; Wallner, Kent . E-mail: kent.Wallner@med.va.gov; Merrick, Gregory; Herstein, Andrew; Mitsuyama, Paul; Thornton, Ken; Butler, Wayne; Sutlief, Steven

    2007-02-01

    Purpose: To analyze the role of dosimetric quality parameters in maximizing cancer eradication in higher risk prostate cancer patients treated with palladium (Pd)-103 and supplemental beam radiation. Methods: One-hundred-seventy-nine patients treated with Pd-103 and supplemental beam radiation, with minimum 2 years follow-up prostate-specific antigen (PSA) values and posttreatment computed tomography scans were analyzed. Dosimetric parameters included the V100 (percent of the postimplant volume covered by the prescription dose), the D90 (the minimum dose that covered 90% of the post implant volume), and the treatment margins (the radial distance between the prostatic edge and the prescription isodose). Treatment margins (TMs) were calculated using premarket software. Results: Freedom from biochemical failure was 79% at 3 years, with 92 of the 179 patients (51%) followed beyond 3 years. In comparing patients who did or did not achieve biochemical control, the most striking differences were in biologic factors of pretreatment PSA and Gleason score. The V100, D90, and average TM all showed nonsignificant trends to higher values in patients with biochemical control. In multivariate analysis of each of the three dosimetric parameters against PSA and Gleason score, TM showed the strongest correlation with biochemical control (p = 0.19). Conclusions: For patients with intermediate and high-risk prostate cancer treated with Pd-103 brachytherapy and external beam radiation, biologic factors (PSA and Gleason score) were the most important determinants of cancer eradication. However, there is a trend to better outcomes among patients with higher quality implant parameters, suggesting that attention to implant quality will maximize the likelihood of cure.

  7. The genomic expression test EndoPredict is a prognostic tool for identifying risk of local recurrence in postmenopausal endocrine receptor-positive, her2neu-negative breast cancer patients randomised within the prospective ABCSG 8 trial

    PubMed Central

    Fitzal, F; Filipits, M; Rudas, M; Greil, R; Dietze, O; Samonigg, H; Lax, S; Herz, W; Dubsky, P; Bartsch, R; Kronenwett, R; Gnant, M

    2015-01-01

    Background: The aim of this study was to examine whether EndoPredict (EP), a novel genomic expression test, is effective in predicting local recurrence (LR)-free survival (LRFS) following surgery for breast cancer in postmenopausal women. In addition, we examined whether EP may help tailor local therapy in these patients. Methods: From January 1996 to June 2004, 3714 postmenopausal patients were randomly assigned to either tamoxifen or tamoxifen followed by anastrozole within the prospective ABCSG 8 trial. Using assay scores from EP, we classified breast tumour blocks as either low or high risk for recurrence. Results: Data were gathered from 1324 patients. The median follow-up was 72.3 months and the cumulative incidence of LR was 2.6% (0.4% per year). The risk of LR over a 10-year period among patients with high-risk lesions (n=683) was significantly higher (LRFS=91%) when compared with patients with low-risk lesions (n=641) (10-year LRFS=97.5%) (HR: 1.31 (1.16–1.48) P<0.005). The groups that received breast conservation surgery (BCT) and mastectomy (MX) had similar LR rates (P=0.879). Radiotherapy (RT) after BCT significantly improved LRFS in the cohorts predicted by EP to be low-risk for LR (received RT: n=436, 10-year LRFS 99.8% did not receive RT: n=63, 10-year LRFS 83.6%, P<0.005). Conclusions: EndoPredict is an effective prognostic tool for predicting LRFS. Among postmenopausal, low-risk patients, EP does not appear to be useful for tailoring local therapy. PMID:25867274

  8. Predicting toxicity in radiotherapy for prostate cancer.

    PubMed

    Landoni, Valeria; Fiorino, Claudio; Cozzarini, Cesare; Sanguineti, Giuseppe; Valdagni, Riccardo; Rancati, Tiziana

    2016-03-01

    This comprehensive review addresses most organs at risk involved in planning optimization for prostate cancer. It can be considered an update of a previous educational review that was published in 2009 (Fiorino et al., 2009). The literature was reviewed based on PubMed and MEDLINE database searches (from January 2009 up to September 2015), including papers in press; for each section/subsection, key title words were used and possibly combined with other more general key-words (such as radiotherapy, dose-volume effects, NTCP, DVH, and predictive model). Publications generally dealing with toxicity without any association with dose-volume effects or correlations with clinical risk factors were disregarded, being outside the aim of the review. A focus was on external beam radiotherapy, including post-prostatectomy, with conventional fractionation or moderate hypofractionation (<4Gy/fraction); extreme hypofractionation is the topic of another paper in this special issue. Gastrointestinal and urinary toxicity are the most investigated endpoints, with quantitative data published in the last 5years suggesting both a dose-response relationship and the existence of a number of clinical/patient related risk factors acting as dose-response modifiers. Some results on erectile dysfunction, bowel toxicity and hematological toxicity are also presented. PMID:27068274

  9. Association of breast cancer risk loci with breast cancer survival.

    PubMed

    Barrdahl, Myrto; Canzian, Federico; Lindström, Sara; Shui, Irene; Black, Amanda; Hoover, Robert N; Ziegler, Regina G; Buring, Julie E; Chanock, Stephen J; Diver, W Ryan; Gapstur, Susan M; Gaudet, Mia M; Giles, Graham G; Haiman, Christopher; Henderson, Brian E; Hankinson, Susan; Hunter, David J; Joshi, Amit D; Kraft, Peter; Lee, I-Min; Le Marchand, Loic; Milne, Roger L; Southey, Melissa C; Willett, Walter; Gunter, Marc; Panico, Salvatore; Sund, Malin; Weiderpass, Elisabete; Sánchez, María-José; Overvad, Kim; Dossus, Laure; Peeters, Petra H; Khaw, Kay-Tee; Trichopoulos, Dimitrios; Kaaks, Rudolf; Campa, Daniele

    2015-12-15

    The survival of breast cancer patients is largely influenced by tumor characteristics, such as TNM stage, tumor grade and hormone receptor status. However, there is growing evidence that inherited genetic variation might affect the disease prognosis and response to treatment. Several lines of evidence suggest that alleles influencing breast cancer risk might also be associated with breast cancer survival. We examined the associations between 35 breast cancer susceptibility loci and the disease over-all survival (OS) in 10,255 breast cancer patients from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) of which 1,379 died, including 754 of breast cancer. We also conducted a meta-analysis of almost 35,000 patients and 5,000 deaths, combining results from BPC3 and the Breast Cancer Association Consortium (BCAC) and performed in silico analyses of SNPs with significant associations. In BPC3, the C allele of LSP1-rs3817198 was significantly associated with improved OS (HRper-allele =0.70; 95% CI: 0.58-0.85; ptrend  = 2.84 × 10(-4) ; HRheterozygotes  = 0.71; 95% CI: 0.55-0.92; HRhomozygotes  = 0.48; 95% CI: 0.31-0.76; p2DF  = 1.45 × 10(-3) ). In silico, the C allele of LSP1-rs3817198 was predicted to increase expression of the tumor suppressor cyclin-dependent kinase inhibitor 1C (CDKN1C). In the meta-analysis, TNRC9-rs3803662 was significantly associated with increased death hazard (HRMETA =1.09; 95% CI: 1.04-1.15; ptrend  = 6.6 × 10(-4) ; HRheterozygotes  = 0.96 95% CI: 0.90-1.03; HRhomozygotes  = 1.21; 95% CI: 1.09-1.35; p2DF =1.25 × 10(-4) ). In conclusion, we show that there is little overlap between the breast cancer risk single nucleotide polymorphisms (SNPs) identified so far and the SNPs associated with breast cancer prognosis, with the possible exceptions of LSP1-rs3817198 and TNRC9-rs3803662. PMID:25611573

  10. Refining Breast Cancer Risk Stratification: Additional Genes, Additional Information.

    PubMed

    Kurian, Allison W; Antoniou, Antonis C; Domchek, Susan M

    2016-01-01

    Recent advances in genomic technology have enabled far more rapid, less expensive sequencing of multiple genes than was possible only a few years ago. Advances in bioinformatics also facilitate the interpretation of large amounts of genomic data. New strategies for cancer genetic risk assessment include multiplex sequencing panels of 5 to more than 100 genes (in which rare mutations are often associated with at least two times the average risk of developing breast cancer) and panels of common single-nucleotide polymorphisms (SNPs), combinations of which are generally associated with more modest cancer risks (more than twofold). Although these new multiple-gene panel tests are used in oncology practice, questions remain about the clinical validity and the clinical utility of their results. To translate this increasingly complex genetic information for clinical use, cancer risk prediction tools are under development that consider the joint effects of all susceptibility genes, together with other established breast cancer risk factors. Risk-adapted screening and prevention protocols are underway, with ongoing refinement as genetic knowledge grows. Priority areas for future research include the clinical validity and clinical utility of emerging genetic tests; the accuracy of developing cancer risk prediction models; and the long-term outcomes of risk-adapted screening and prevention protocols, in terms of patients' experiences and survival. PMID:27249685

  11. Sun Protection Motivational Stages and Behavior: Skin Cancer Risk Profiles

    ERIC Educational Resources Information Center

    Pagoto, Sherry L.; McChargue, Dennis E.; Schneider, Kristin; Cook, Jessica Werth

    2004-01-01

    Objective: To create skin cancer risk profiles that could be used to predict sun protection among Midwest beachgoers. Method: Cluster analysis was used with study participants (N=239), who provided information about sun protection motivation and behavior, perceived risk, burn potential, and tan importance. Participants were clustered according to…

  12. Development and Application of Chronic Disease Risk Prediction Models

    PubMed Central

    Oh, Sun Min; Stefani, Katherine M.

    2014-01-01

    Currently, non-communicable chronic diseases are a major cause of morbidity and mortality worldwide, and a large proportion of chronic diseases are preventable through risk factor management. However, the prevention efficacy at the individual level is not yet satisfactory. Chronic disease prediction models have been developed to assist physicians and individuals in clinical decision-making. A chronic disease prediction model assesses multiple risk factors together and estimates an absolute disease risk for the individual. Accurate prediction of an individual's future risk for a certain disease enables the comparison of benefits and risks of treatment, the costs of alternative prevention strategies, and selection of the most efficient strategy for the individual. A large number of chronic disease prediction models, especially targeting cardiovascular diseases and cancers, have been suggested, and some of them have been adopted in the clinical practice guidelines and recommendations of many countries. Although few chronic disease prediction tools have been suggested in the Korean population, their clinical utility is not as high as expected. This article reviews methodologies that are commonly used for developing and evaluating a chronic disease prediction model and discusses the current status of chronic disease prediction in Korea. PMID:24954311

  13. Fuzzy sets applications for cancer risk assessment.

    PubMed

    Molchanov, P A; Dudatiev, A V; Podobna, Y Y; Molchanova, O P

    2002-09-01

    The method of cancer risk assessment on the basis of the Fuzzy Set Theory is presented. The method is based on a multifactor risk assessment of cancer diseases. The individual risk of cancer disease is evaluated as the probability of disease multiplied by the value of an individual dose. An acupuncture method of cancer risk assessments was developed. The method is based on the analysis of changes of an electromagnetic field (biofield) of a person. The method allows to determine both cancer probability and probable location of the process. PMID:12298344

  14. Earthquake prediction decision and risk matrix

    NASA Astrophysics Data System (ADS)

    Zou, Qi-Jia

    1993-08-01

    The issuance of an earthquake prediction must cause widespread social responses. It is suggested and discussed in this paper that the comprehensive decision issue for earthquake prediction considering the factors of the social and economic cost. The method of matrix decision for earthquake prediction (MDEP) is proposed in this paper and it is based on the risk matrix. The goal of decision is that search the best manner issuing earthquake prediction so that minimize the total losses of economy. The establishment and calculation of the risk matrix is discussed, and the decision results taking account of economic factors and not considering the economic factors are compared by examples in this paper.

  15. Height and Prostate Cancer Risk

    PubMed Central

    Zuccolo, Luisa; Harris, Ross; Gunnell, David; Oliver, Steven; Lane, Jane Athene; Davis, Michael; Donovan, Jenny; Neal, David; Hamdy, Freddie; Beynon, Rebecca; Savovic, Jelena; Martin, Richard Michael

    2008-01-01

    Background Height, a marker of childhood environmental exposures, is positively associated with prostate cancer risk, perhaps through the insulin-like growth factor system. We investigated the relationship of prostate cancer with height and its components (leg and trunk length) in a nested case-control study and with height in a dose-response meta-analysis. Methods We nested a case-control study within a population-based randomized controlled trial evaluating treatments for localized prostate cancer in British men ages 50 to 69 years, including 1,357 cases detected through prostate-specific antigen testing and 7,990 controls (matched on age, general practice, assessment date). Nine bibliographic databases were searched systematically for studies on the height-prostate cancer association that were pooled in a meta-analysis. Results Based on the nested case-control, the odds ratio (OR) of prostate-specific antigen-detected prostate cancer per 10 cm increase in height was 1.06 [95% confidence interval (95% CI): 0.97-1.16; ptrend = 0.2]. There was stronger evidence of an association of height with high-grade prostate cancer (OR: 1.23; 95% CI: 1.06-1.43), mainly due to the leg component, but not with low-grade disease (OR: 0.99; 95% CI: 0.90-1.10). In general, associations with leg or trunk length were similar. A meta-analysis of 58 studies found evidence that height is positively associated with prostate cancer (random-effects OR per 10 cm: 1.06; 95% CI: 1.03-1.09), with a stronger effect for prospective studies of more advanced/aggressive cancers (random-effects OR: 1.12; 95% CI: 1.05-1.19). Conclusion These data indicate a limited role for childhood environmental exposures—as indexed by adult height—on prostate cancer incidence, while suggesting a greater role for progression, through mechanisms requiring further investigation. PMID:18768501

  16. Risks of Lung Cancer Screening

    MedlinePlus

    ... Cancer Treatment Small Cell Lung Cancer Treatment Lung cancer is the leading cause of cancer death in the United States. Lung cancer is ... non- skin cancer in the United States. Lung cancer is the leading cause of cancer death in men and in women. ...

  17. What Are the Risk Factors for Kidney Cancer?

    MedlinePlus

    ... kidney cancer? What are the risk factors for kidney cancer? A risk factor is anything that affects ... not cancer). Other risk factors Family history of kidney cancer People with a strong family history of ...

  18. Use of dose-dependent absorption into target tissues to more accurately predict cancer risk at low oral doses of hexavalent chromium.

    PubMed

    Haney, J

    2015-02-01

    The mouse dose at the lowest water concentration used in the National Toxicology Program hexavalent chromium (CrVI) drinking water study (NTP, 2008) is about 74,500 times higher than the approximate human dose corresponding to the 35-city geometric mean reported in EWG (2010) and over 1000 times higher than that based on the highest reported tap water concentration. With experimental and environmental doses differing greatly, it is a regulatory challenge to extrapolate high-dose results to environmental doses orders of magnitude lower in a meaningful and toxicologically predictive manner. This seems particularly true for the low-dose extrapolation of results for oral CrVI-induced carcinogenesis since dose-dependent differences in the dose fraction absorbed by mouse target tissues are apparent (Kirman et al., 2012). These data can be used for a straightforward adjustment of the USEPA (2010) draft oral slope factor (SFo) to be more predictive of risk at environmentally-relevant doses. More specifically, the evaluation of observed and modeled differences in the fraction of dose absorbed by target tissues at the point-of-departure for the draft SFo calculation versus lower doses suggests that the draft SFo be divided by a dose-specific adjustment factor of at least an order of magnitude to be less over-predictive of risk at more environmentally-relevant doses. PMID:25445295

  19. Resistin, Visfatin, Adiponectin, and Leptin: Risk of Breast Cancer in Pre- and Postmenopausal Saudi Females and Their Possible Diagnostic and Predictive Implications as Novel Biomarkers

    PubMed Central

    Assiri, Adel M. A.; Kamel, Hala F. M.; Hassanien, Mohamed F. R.

    2015-01-01

    The mechanisms of obesity-induced breast carcinogenesis are not clear. One hypothesis is that high levels of adipokines could promote breast cancer (BC) development. The aim of this study was to investigate the correlation of resistin, visfatin, adiponectin, and leptin with BC risk in pre- and postmenopausal females. A total of 82 BC newly diagnosed and histologically confirmed patients and 68 age and BMI matched healthy controls were enrolled. Both groups were subdivided into post- and premenopausal subgroups. Resistin, visfatin, adiponectin, and leptin were measured by ELISA. There were significantly higher levels of leptin, resistin, and visfatin in postmenopausal BC patients than their respective controls. Only in postmenopausal subgroups, leptin, resistin, and visfatin levels were positively correlated with TNM staging, tumor size, lymph node (LN) metastasis, and histological grading. In postmenopausal females, multivariate logistic regression analysis revealed that adiponectin, leptin, visfatin, and resistin were risk factors for BC. Our results suggested that serum resistin, leptin, adiponectin, and visfatin levels as risk factors for postmenopausal BC may provide a potential link with clinicopathological features and are promising to be novel biomarkers for postmenopausal BC. PMID:25838618

  20. Genetic testing and your cancer risk

    MedlinePlus

    ... this page: //medlineplus.gov/ency/patientinstructions/000842.htm Genetic testing and your cancer risk To use the ... before you get tested. Which Cancers May Be Genetic Today, we know specific gene mutations that can ...

  1. Risk Profiling May Improve Lung Cancer Screening

    Cancer.gov

    A new modeling study suggests that individualized, risk-based selection of ever-smokers for lung cancer screening may prevent more lung cancer deaths and improve the effectiveness and efficiency of screening compared with current screening recommendations

  2. The genetics of cancer risk.

    PubMed

    Pomerantz, Mark M; Freedman, Matthew L

    2011-01-01

    One hundred years ago, decades before the discovery of the structure of DNA, debate raged regarding how human traits were passed from one generation to the next. Phenotypes, including risk of disease, had long been recognized as having a familial component. Yet it was difficult to reconcile genetic segregation as described by Mendel with observations exhaustively documented by Karl Pearson and others regarding the normal distribution of human characteristics. In 1918, R. A. Fisher published his landmark article, "The Correlation Between Relatives on the Supposition of Mendelian Inheritance," bridging this divide and demonstrating that multiple alleles, all individually obeying Mendel's laws, account for the phenotypic variation observed in nature.Since that time, geneticists have sought to identify the link between genotype and phenotype. Trait-associated alleles vary in their frequency and degree of penetrance. Some minor alleles may approach a frequency of 50% in the human population, whereas others are present within only a few individuals. The spectrum for penetrance is similarly wide. These characteristics jointly determine the segregation pattern of a given trait, which, in turn, determine the method used to map the trait. Until recently, identification of rare, highly penetrant alleles was most practical. Revolutionary studies in genomics reported over the past decade have made interrogation of most of the spectrum of genetic variation feasible.The following article reviews recent discoveries in the genetic basis of inherited cancer risk and how these discoveries inform cancer biology and patient management. Although this article focuses on prostate cancer, the principles are generic for any cancer and, indeed, for any trait. PMID:22157285

  3. Risk-optimized proton therapy to minimize radiogenic second cancers

    NASA Astrophysics Data System (ADS)

    Rechner, Laura A.; Eley, John G.; Howell, Rebecca M.; Zhang, Rui; Mirkovic, Dragan; Newhauser, Wayne D.

    2015-05-01

    Proton therapy confers substantially lower predicted risk of second cancer compared with photon therapy. However, no previous studies have used an algorithmic approach to optimize beam angle or fluence-modulation for proton therapy to minimize those risks. The objectives of this study were to demonstrate the feasibility of risk-optimized proton therapy and to determine the combination of beam angles and fluence weights that minimizes the risk of second cancer in the bladder and rectum for a prostate cancer patient. We used 6 risk models to predict excess relative risk of second cancer. Treatment planning utilized a combination of a commercial treatment planning system and an in-house risk-optimization algorithm. When normal-tissue dose constraints were incorporated in treatment planning, the risk model that incorporated the effects of fractionation, initiation, inactivation, repopulation and promotion selected a combination of anterior and lateral beams, which lowered the relative risk by 21% for the bladder and 30% for the rectum compared to the lateral-opposed beam arrangement. Other results were found for other risk models.

  4. Risk-optimized proton therapy to minimize radiogenic second cancers

    PubMed Central

    Rechner, Laura A.; Eley, John G.; Howell, Rebecca M.; Zhang, Rui; Mirkovic, Dragan; Newhauser, Wayne D.

    2015-01-01

    Proton therapy confers substantially lower predicted risk of second cancer compared with photon therapy. However, no previous studies have used an algorithmic approach to optimize beam angle or fluence-modulation for proton therapy to minimize those risks. The objectives of this study were to demonstrate the feasibility of risk-optimized proton therapy and to determine the combination of beam angles and fluence weights that minimize the risk of second cancer in the bladder and rectum for a prostate cancer patient. We used 6 risk models to predict excess relative risk of second cancer. Treatment planning utilized a combination of a commercial treatment planning system and an in-house risk-optimization algorithm. When normal-tissue dose constraints were incorporated in treatment planning, the risk model that incorporated the effects of fractionation, initiation, inactivation, and repopulation selected a combination of anterior and lateral beams, which lowered the relative risk by 21% for the bladder and 30% for the rectum compared to the lateral-opposed beam arrangement. Other results were found for other risk models. PMID:25919133

  5. Predictive and therapeutic markers in ovarian cancer

    DOEpatents

    Gray, Joe W.; Guan, Yinghui; Kuo, Wen-Lin; Fridlyand, Jane; Mills, Gordon B.

    2013-03-26

    Cancer markers may be developed to detect diseases characterized by increased expression of apoptosis-suppressing genes, such as aggressive cancers. Genes in the human chromosomal regions, 8q24, 11q13, 20q11-q13, were found to be amplified indicating in vivo drug resistance in diseases such as ovarian cancer. Diagnosis and assessment of amplification levels certain genes shown to be amplified, including PVT1, can be useful in prediction of poor outcome of patient's response and drug resistance in ovarian cancer patients with low survival rates. Certain genes were found to be high priority therapeutic targets by the identification of recurrent aberrations involving genome sequence, copy number and/or gene expression are associated with reduced survival duration in certain diseases and cancers, specifically ovarian cancer. Therapeutics to inhibit amplification and inhibitors of one of these genes, PVT1, target drug resistance in ovarian cancer patients with low survival rates is described.

  6. Overview of entry risk predictions

    NASA Astrophysics Data System (ADS)

    Mrozinski, R.; Mendeck, G.; Cutri-Kohart, R.

    Risk to people on the ground from uncontrolled entries of spacecraft is a primary concern when analyzing end-of-life disposal options for satellites. Countries must balance this risk with the need to mitigate an exponentially growing space debris population. Currently the United States does this via guidelines that call for a satellite to be disposed of in a controlled manner if an uncontrolled entry would be too risky to people on the ground. This risk is measured by a quantity called "casualty expectation", or E , where casualty expectation is defined as the expectedc number of people suffering death or injury due to a spacecraft entry event. If Ec exceeds 1 in 10,000, U. S. guidelines state that the entry should be controlled rather than uncontrolled. Since this guideline can have serious impacts on the cost, lifetime, and even the mission and functionality of a satellite, it is critical that this quantity be estimated well, and decision makers understand all assumptions and limitations inherent in the resulting value. This paper discusses several issues regarding estimates of casualty expectation, beginning with an overview of relevant United States policies and guidelines. The equation the space industry typically uses to estimate casualty expectation is presented, along with a look at the sensitivity of the results to the typical assumptions, models, and initial condition uncertainties. Differences in these modeling issues with respect to launch failure Ec estimates are included in the discussion. An alternate quantity to assess risks due to spacecraft entries is introduced. "Probability of casualty", or Pc , is defined as the probability of one or more instances of people suffering death or injury due to a spacecraft entry event. The equation to estimate Pc is derived, where the same assumptions, modeling, and initial condition issues for Ec apply. Several examples are then given of both Ec and Pc estimate calculations. Due to the difficult issues in

  7. Changing cancer risk pattern among Finnish hairdressers.

    PubMed

    Pukkala, E; Nokso-Koivisto, P; Roponen, P

    1992-01-01

    A cohort of 3637 female and 168 male hair-dressers in Finland was followed up for cancer through the Finnish Cancer Registry in 1970-1987. Compared with the total population, the women had a significantly elevated risk (standardized incidence ratio 1.7) during the first third of the observation period, but not thereafter. For the total follow-up period, the relative risks were highest for nonmelanoma skin cancer (2.0), lung cancer (1.7), ovarian cancer (1.6), cervical cancer (1.5), and cancer of the pancreas (1.5); only the risk of ovarian cancer was statistically significant. A decrease in relative risk with time was observed for many primary sites, e.g., pancreas, cervix uteri, central nervous system, and thyroid. The opposite was true for lung and skin: An increased risk was found only in 1982-1987. The excess was most prominent in the oldest age groups with the longest time span since the first employment as a hairdresser. Among men, too, the general cancer risk was highest (1.6) during the first third of the observation period. An excess of cancers of the lung and the pancreas was observed. The small numbers, however, did not allow any further conclusions. The changes in the cancer risk pattern over time may be associated with changes in working conditions in hairdressing salons. PMID:1399013

  8. Diet and risk of breast cancer

    PubMed Central

    2016-01-01

    Diet may play a role in both promoting and inhibiting human breast cancer development. In this review, nutritional risk factors such as consumption of dietary fat, meat, fiber, and alcohol, and intake of phytoestrogen, vitamin D, iron, and folate associated with breast cancer are reviewed. These nutritional factors have a variety of associations with breast cancer risk. Type of fat consumed has different effects on risk of breast cancer: consumption of meat is associated with heterocyclic amine (HCA) exposure; different types of plant fiber have various effects on breast cancer risk; alcohol consumption may increase the risk of breast cancer by producing acetaldehyde and reactive oxygen species (ROS); intake of phytoestrogen may reduce risk of breast cancer through genomic and non-genomic action; vitamin D can reduce the risk of breast cancer by inhibiting the process of cancer invasion and metastasis; intake of dietary iron may lead to oxidative stress, DNA damage, and lipid peroxidation; and lower intake of folate may be linked to a higher risk of breast cancer. PMID:27095934

  9. Diet and risk of breast cancer.

    PubMed

    Kotepui, Manas

    2016-01-01

    Diet may play a role in both promoting and inhibiting human breast cancer development. In this review, nutritional risk factors such as consumption of dietary fat, meat, fiber, and alcohol, and intake of phytoestrogen, vitamin D, iron, and folate associated with breast cancer are reviewed. These nutritional factors have a variety of associations with breast cancer risk. Type of fat consumed has different effects on risk of breast cancer: consumption of meat is associated with heterocyclic amine (HCA) exposure; different types of plant fiber have various effects on breast cancer risk; alcohol consumption may increase the risk of breast cancer by producing acetaldehyde and reactive oxygen species (ROS); intake of phytoestrogen may reduce risk of breast cancer through genomic and non-genomic action; vitamin D can reduce the risk of breast cancer by inhibiting the process of cancer invasion and metastasis; intake of dietary iron may lead to oxidative stress, DNA damage, and lipid peroxidation; and lower intake of folate may be linked to a higher risk of breast cancer. PMID:27095934

  10. Bladder (ICRU) dose point does not predict urinary acute toxicity in adjuvant isolated vaginal vault high-dose-rate brachytherapy for intermediate-risk endometrial cancer

    PubMed Central

    Aiza, Antonio; Gomes, Maria José Leite; Chen, Michael Jenwei; Pellizzon, Antonio Cassio de Assis; Mansur, David B.; Baiocchi, Glauco

    2015-01-01

    Purpose High-dose-rate brachytherapy (HDR-BT) alone is an adjuvant treatment option for stage I intermediaterisk endometrial cancer after complete surgical resection. The aim of this study was to determine the value of the dose reported to ICRU bladder point in predicting acute urinary toxicity. Oncologic results are also presented. Material and methods One hundred twenty-six patients were treated with postoperative HDR-BT 24 Gy (4 × 6 Gy) per ICRU guidelines for dose reporting. Cox analysis was used to identify variables that affected local control. The mean bladder point dose was examined for its ability to predict acute urinary toxicity. Results Two patients (1.6%) developed grade 1 gastrointestinal toxicity and 12 patients (9.5%) developed grades 1-2 urinary toxicity. No grade 3 or greater toxicity was observed. The mean bladder point dose was 46.9% (11.256 Gy) and 49.8% (11.952 Gy) for the asymptomatic and symptomatic groups, respectively (p = 0.69). After a median follow-up of 36.8 months, the 3-year local failure and 5-year cancer-specific and overall survival rates were 2.1%, 100%, and 94.6%, respectively. No pelvic failure was seen in this cohort. Age over 60 years (p = 0.48), lymphatic invasion (p = 0.77), FIGO histological grade (p = 0.76), isthmus invasion (p = 0.68), and applicator type (cylinder × ovoid) (p = 0.82) did not significantly affect local control. Conclusions In this retrospective study, ICRU bladder point did not correlate with urinary toxicity. Four fractions of 6 Gy HDR-BT effected satisfactory local control, with acceptable urinary and gastrointestinal toxicity. PMID:26622241

  11. Improving Prediction of Prostate Cancer Recurrence using Chemical Imaging

    NASA Astrophysics Data System (ADS)

    Kwak, Jin Tae; Kajdacsy-Balla, André; Macias, Virgilia; Walsh, Michael; Sinha, Saurabh; Bhargava, Rohit

    2015-03-01

    Precise Outcome prediction is crucial to providing optimal cancer care across the spectrum of solid cancers. Clinically-useful tools to predict risk of adverse events (metastases, recurrence), however, remain deficient. Here, we report an approach to predict the risk of prostate cancer recurrence, at the time of initial diagnosis, using a combination of emerging chemical imaging, a diagnostic protocol that focuses simultaneously on the tumor and its microenvironment, and data analysis of frequent patterns in molecular expression. Fourier transform infrared (FT-IR) spectroscopic imaging was employed to record the structure and molecular content from tumors prostatectomy. We analyzed data from a patient cohort that is mid-grade dominant - which is the largest cohort of patients in the modern era and in whom prognostic methods are largely ineffective. Our approach outperforms the two widely used tools, Kattan nomogram and CAPRA-S score in a head-to-head comparison for predicting risk of recurrence. Importantly, the approach provides a histologic basis to the prediction that identifies chemical and morphologic features in the tumor microenvironment that is independent of conventional clinical information, opening the door to similar advances in other solid tumors.

  12. Minimizing second cancer risk following radiotherapy: current perspectives.

    PubMed

    Ng, John; Shuryak, Igor

    2015-01-01

    Secondary cancer risk following radiotherapy is an increasingly important topic in clinical oncology with impact on treatment decision making and on patient management. Much of the evidence that underlies our understanding of secondary cancer risks and our risk estimates are derived from large epidemiologic studies and predictive models of earlier decades with large uncertainties. The modern era is characterized by more conformal radiotherapy technologies, molecular and genetic marker approaches, genome-wide studies and risk stratifications, and sophisticated biologically based predictive models of the carcinogenesis process. Four key areas that have strong evidence toward affecting secondary cancer risks are 1) the patient age at time of radiation treatment, 2) genetic risk factors, 3) the organ and tissue site receiving radiation, and 4) the dose and volume of tissue being irradiated by a particular radiation technology. This review attempts to summarize our current understanding on the impact on secondary cancer risks for each of these known risk factors. We review the recent advances in genetic studies and carcinogenesis models that are providing insight into the biologic processes that occur from tissue irradiation to the development of a secondary malignancy. Finally, we discuss current approaches toward minimizing the risk of radiation-associated secondary malignancies, an important goal of clinical radiation oncology. PMID:25565886

  13. Minimizing second cancer risk following radiotherapy: current perspectives

    PubMed Central

    Ng, John; Shuryak, Igor

    2015-01-01

    Secondary cancer risk following radiotherapy is an increasingly important topic in clinical oncology with impact on treatment decision making and on patient management. Much of the evidence that underlies our understanding of secondary cancer risks and our risk estimates are derived from large epidemiologic studies and predictive models of earlier decades with large uncertainties. The modern era is characterized by more conformal radiotherapy technologies, molecular and genetic marker approaches, genome-wide studies and risk stratifications, and sophisticated biologically based predictive models of the carcinogenesis process. Four key areas that have strong evidence toward affecting secondary cancer risks are 1) the patient age at time of radiation treatment, 2) genetic risk factors, 3) the organ and tissue site receiving radiation, and 4) the dose and volume of tissue being irradiated by a particular radiation technology. This review attempts to summarize our current understanding on the impact on secondary cancer risks for each of these known risk factors. We review the recent advances in genetic studies and carcinogenesis models that are providing insight into the biologic processes that occur from tissue irradiation to the development of a secondary malignancy. Finally, we discuss current approaches toward minimizing the risk of radiation-associated secondary malignancies, an important goal of clinical radiation oncology. PMID:25565886

  14. Northeast Regional Cancer Institute's Cancer Surveillance and Risk Factor Program

    SciTech Connect

    Lesko, Samuel M.

    2007-07-31

    OBJECTIVES The Northeast Regional Cancer Institute is conducting a program of ongoing epidemiologic research to address cancer disparities in northeast Pennsylvania. Of particular concern are disparities in the incidence of, stage at diagnosis, and mortality from colorectal cancer. In northeast Pennsylvania, age-adjusted incidence and mortality rates for colorectal cancer are higher, and a significantly smaller proportion of new colorectal cancer cases are diagnosed with local stage disease than is observed in comparable national data. Further, estimates of the prevalence of colorectal cancer screening in northeast Pennsylvania are lower than the US average. The Northeast Regional Cancer Institute’s research program supports surveillance of common cancers, investigations of cancer risk factors and screening behaviors, and the development of resources to further cancer research in this community. This project has the following specific objectives: I. To conduct cancer surveillance in northeast Pennsylvania. a. To monitor incidence and mortality for all common cancers, and colorectal cancer, in particular, and b. To document changes in the stage at diagnosis of colorectal cancer in this high-risk, underserved community. II. To conduct a population-based study of cancer risk factors and screening behavior in a six county region of northeast Pennsylvania. a. To monitor and document changes in colorectal cancer screening rates, and b. To document the prevalence of cancer risk factors (especially factors that increase the risk of colorectal cancer) and to identify those risk factors that are unusually common in this community. APPROACH Cancer surveillance was conducted using data from the Northeast Regional Cancer Institute’s population-based Regional Cancer Registry, the Pennsylvania Cancer Registry, and NCI’s SEER program. For common cancers, incidence and mortality were examined by county within the region and compared to data for similar populations in the US

  15. Machine learning applications in cancer prognosis and prediction.

    PubMed

    Kourou, Konstantina; Exarchos, Themis P; Exarchos, Konstantinos P; Karamouzis, Michalis V; Fotiadis, Dimitrios I

    2015-01-01

    Cancer has been characterized as a heterogeneous disease consisting of many different subtypes. The early diagnosis and prognosis of a cancer type have become a necessity in cancer research, as it can facilitate the subsequent clinical management of patients. The importance of classifying cancer patients into high or low risk groups has led many research teams, from the biomedical and the bioinformatics field, to study the application of machine learning (ML) methods. Therefore, these techniques have been utilized as an aim to model the progression and treatment of cancerous conditions. In addition, the ability of ML tools to detect key features from complex datasets reveals their importance. A variety of these techniques, including Artificial Neural Networks (ANNs), Bayesian Networks (BNs), Support Vector Machines (SVMs) and Decision Trees (DTs) have been widely applied in cancer research for the development of predictive models, resulting in effective and accurate decision making. Even though it is evident that the use of ML methods can improve our understanding of cancer progression, an appropriate level of validation is needed in order for these methods to be considered in the everyday clinical practice. In this work, we present a review of recent ML approaches employed in the modeling of cancer progression. The predictive models discussed here are based on various supervised ML techniques as well as on different input features and data samples. Given the growing trend on the application of ML methods in cancer research, we present here the most recent publications that employ these techniques as an aim to model cancer risk or patient outcomes. PMID:25750696

  16. Machine learning applications in cancer prognosis and prediction

    PubMed Central

    Kourou, Konstantina; Exarchos, Themis P.; Exarchos, Konstantinos P.; Karamouzis, Michalis V.; Fotiadis, Dimitrios I.

    2014-01-01

    Cancer has been characterized as a heterogeneous disease consisting of many different subtypes. The early diagnosis and prognosis of a cancer type have become a necessity in cancer research, as it can facilitate the subsequent clinical management of patients. The importance of classifying cancer patients into high or low risk groups has led many research teams, from the biomedical and the bioinformatics field, to study the application of machine learning (ML) methods. Therefore, these techniques have been utilized as an aim to model the progression and treatment of cancerous conditions. In addition, the ability of ML tools to detect key features from complex datasets reveals their importance. A variety of these techniques, including Artificial Neural Networks (ANNs), Bayesian Networks (BNs), Support Vector Machines (SVMs) and Decision Trees (DTs) have been widely applied in cancer research for the development of predictive models, resulting in effective and accurate decision making. Even though it is evident that the use of ML methods can improve our understanding of cancer progression, an appropriate level of validation is needed in order for these methods to be considered in the everyday clinical practice. In this work, we present a review of recent ML approaches employed in the modeling of cancer progression. The predictive models discussed here are based on various supervised ML techniques as well as on different input features and data samples. Given the growing trend on the application of ML methods in cancer research, we present here the most recent publications that employ these techniques as an aim to model cancer risk or patient outcomes. PMID:25750696

  17. Predictive features of breast cancer on Mexican screening mammography patients

    NASA Astrophysics Data System (ADS)

    Rodriguez-Rojas, Juan; Garza-Montemayor, Margarita; Trevino-Alvarado, Victor; Tamez-Pena, José Gerardo

    2013-02-01

    Breast cancer is the most common type of cancer worldwide. In response, breast cancer screening programs are becoming common around the world and public programs now serve millions of women worldwide. These programs are expensive, requiring many specialized radiologists to examine all images. Nevertheless, there is a lack of trained radiologists in many countries as in Mexico, which is a barrier towards decreasing breast cancer mortality, pointing at the need of a triaging system that prioritizes high risk cases for prompt interpretation. Therefore we explored in an image database of Mexican patients whether high risk cases can be distinguished using image features. We collected a set of 200 digital screening mammography cases from a hospital in Mexico, and assigned low or high risk labels according to its BIRADS score. Breast tissue segmentation was performed using an automatic procedure. Image features were obtained considering only the segmented region on each view and comparing the bilateral di erences of the obtained features. Predictive combinations of features were chosen using a genetic algorithms based feature selection procedure. The best model found was able to classify low-risk and high-risk cases with an area under the ROC curve of 0.88 on a 150-fold cross-validation test. The features selected were associated to the differences of signal distribution and tissue shape on bilateral views. The model found can be used to automatically identify high risk cases and trigger the necessary measures to provide prompt treatment.

  18. A prediction model for colon cancer surveillance data.

    PubMed

    Good, Norm M; Suresh, Krithika; Young, Graeme P; Lockett, Trevor J; Macrae, Finlay A; Taylor, Jeremy M G

    2015-08-15

    Dynamic prediction models make use of patient-specific longitudinal data to update individualized survival probability predictions based on current and past information. Colonoscopy (COL) and fecal occult blood test (FOBT) results were collected from two Australian surveillance studies on individuals characterized as high-risk based on a personal or family history of colorectal cancer. Motivated by a Poisson process, this paper proposes a generalized nonlinear model with a complementary log-log link as a dynamic prediction tool that produces individualized probabilities for the risk of developing advanced adenoma or colorectal cancer (AAC). This model allows predicted risk to depend on a patient's baseline characteristics and time-dependent covariates. Information on the dates and results of COLs and FOBTs were incorporated using time-dependent covariates that contributed to patient risk of AAC for a specified period following the test result. These covariates serve to update a person's risk as additional COL, and FOBT test information becomes available. Model selection was conducted systematically through the comparison of Akaike information criterion. Goodness-of-fit was assessed with the use of calibration plots to compare the predicted probability of event occurrence with the proportion of events observed. Abnormal COL results were found to significantly increase risk of AAC for 1 year following the test. Positive FOBTs were found to significantly increase the risk of AAC for 3 months following the result. The covariates that incorporated the updated test results were of greater significance and had a larger effect on risk than the baseline variables. PMID:25851283

  19. Molecular classification and prediction in gastric cancer

    PubMed Central

    Lin, Xiandong; Zhao, Yongzhong; Song, Won-min; Zhang, Bin

    2015-01-01

    Gastric cancer, a highly heterogeneous disease, is the second leading cause of cancer death and the fourth most common cancer globally, with East Asia accounting for more than half of cases annually. Alongside TNM staging, gastric cancer clinic has two well-recognized classification systems, the Lauren classification that subdivides gastric adenocarcinoma into intestinal and diffuse types and the alternative World Health Organization system that divides gastric cancer into papillary, tubular, mucinous (colloid), and poorly cohesive carcinomas. Both classification systems enable a better understanding of the histogenesis and the biology of gastric cancer yet have a limited clinical utility in guiding patient therapy due to the molecular heterogeneity of gastric cancer. Unprecedented whole-genome-scale data have been catalyzing and advancing the molecular subtyping approach. Here we cataloged and compared those published gene expression profiling signatures in gastric cancer. We summarized recent integrated genomic characterization of gastric cancer based on additional data of somatic mutation, chromosomal instability, EBV virus infection, and DNA methylation. We identified the consensus patterns across these signatures and identified the underlying molecular pathways and biological functions. The identification of molecular subtyping of gastric adenocarcinoma and the development of integrated genomics approaches for clinical applications such as prediction of clinical intervening emerge as an essential phase toward personalized medicine in treating gastric cancer. PMID:26380657

  20. Cancer associated thrombosis: risk factors and outcomes.

    PubMed

    Eichinger, Sabine

    2016-04-01

    Deep vein thrombosis of the leg and pulmonary embolism are frequent diseases and cancer is one of their most important risk factors. Patients with cancer also have a higher prevalence of venous thrombosis located in other parts than in the legs and/or in unusual sites including upper extremity, splanchnic or cerebral veins. Cancer also affects the risk of arterial thrombotic events particularly in patients with myeloproliferative neoplasms and in vascular endothelial growth factor receptor inhibitor recipients. Several risk factors need to interact to trigger thrombosis. In addition to common risk factors such as surgery, hospitalisation, infection and genetic coagulation disorders, the thrombotic risk is also driven and modified by cancer-specific factors including type, histology, and stage of the malignancy, cancer treatment and certain biomarkers. A venous thrombotic event in a cancer patient has serious consequences as the risk of recurrent thrombosis, the risk of bleeding during anticoagulation and hospitalisation rates are all increased. Survival of cancer patients with thrombosis is worse compared to that of cancer patients without thrombosis, and thrombosis is a leading direct cause of death in cancer patients. PMID:27067965

  1. The potential of large studies for building genetic risk prediction models

    Cancer.gov

    NCI scientists have developed a new paradigm to assess hereditary risk prediction in common diseases, such as prostate cancer. This genetic risk prediction concept is based on polygenic analysis—the study of a group of common DNA sequences, known as singl

  2. Predictive Assay For Cancer Targets

    SciTech Connect

    Suess, A; Nguyen, C; Sorensen, K; Montgomery, J; Souza, B; Kulp, K; Dugan, L; Christian, A

    2005-09-19

    Early detection of cancer is a key element in successful treatment of the disease. Understanding the particular type of cancer involved, its origins and probable course, is also important. PhIP (2-amino-1-methyl-6 phenylimidazo [4,5-b]pyridine), a heterocyclic amine produced during the cooking of meat at elevated temperatures, has been shown to induce mammary cancer in female, Sprague-Dawley rats. Tumors induced by PhIP have been shown to contain discreet cytogenetic signature patterns of gains and losses using comparative genomic hybridization (CGH). To determine if a protein signature exists for these tumors, we are analyzing expression levels of the protein products of the above-mentioned tumors in combination with a new bulk protein subtractive assay. This assay produces a panel of antibodies against proteins that are either on or off in the tumor. Hybridization of the antibody panel onto a 2-D gel of tumor or control protein will allow for identification of a distinct protein signature in the tumor. Analysis of several gene databases has identified a number of rat homologs of human cancer genes located in these regions of gain and loss. These genes include the oncogenes c-MYK, ERBB2/NEU, THRA and tumor suppressor genes EGR1 and HDAC3. The listed genes have been shown to be estrogen-responsive, suggesting a possible link between delivery of bio-activated PhIP to the cell nucleus via estrogen receptors and gene-specific PhIP-induced DNA damage, leading to cell transformation. All three tumors showed similar silver staining patterns compared to each other, while they all were different than the control tissue. Subsequent screening of these genes against those from tumors know to be caused by other agents may produce a protein signature unique to PhIP, which can be used as a diagnostic to augment optical and radiation-based detection schemes.

  3. The Distinct Role of Comparative Risk Perceptions in a Breast Cancer Prevention Program

    PubMed Central

    Dillard, Amanda J.; Ubel, Peter A.; Smith, Dylan M.; Zikmund-Fisher, Brian J.; Nair, Vijay; Derry, Holly A.; Zhang, Aijun; Pitsch, Rosemarie K.; Alford, Sharon Hensley; McClure, Jennifer B.; Fagerlin, Angela

    2013-01-01

    Background Comparative risk perceptions may rival other types of information in terms of effects on health behavior decisions. Purpose We examined associations between comparative risk perceptions, affect, and behavior while controlling for absolute risk perceptions and actual risk. Methods Women at an increased risk of breast cancer participated in a program to learn about tamoxifen which can reduce the risk of breast cancer. Women reported comparative risk perceptions of breast cancer and completed measures of anxiety, knowledge, and tamoxifen-related behavior intentions. Three months later, women reported their behavior. Results Comparative risk perceptions were positively correlated with anxiety, knowledge, intentions, and behavior three months later. After controlling for participants’ actual risk of breast cancer and absolute risk perceptions, comparative risk perceptions predicted anxiety and knowledge, but not intentions or behavior. Conclusions Comparative risk perceptions can affect patient outcomes like anxiety and knowledge independently of absolute risk perceptions and actual risk information. PMID:21698518

  4. Cancer risk-reduction behaviors of breast cancer survivors.

    PubMed

    Lindsey, Ada M; Waltman, Nancy; Gross, Gloria; Ott, Carol D; Twiss, Jan

    2004-12-01

    Using secondary data analysis, the aim was to determine if postmenopausal women, who have survived breast cancer, have adopted healthy nutritional and physical activity behaviors recommended in the American Cancer Society guidelines as cancer risk-reduction strategies, and in guidelines for prevention of other chronic diseases or for improving general health. From their personal health history, women who have survived breast cancer would be likely candidates to adopt healthy behaviors recommended as cancer risk-reduction strategies or for prevention of other chronic diseases. A secondary aim was to determine the perceived general health and affective state of these women. These breast cancer survivors had a high perception of their general health, a positive affective state, and have adopted some healthy lifestyle behaviors, but they are not fully adhering to the ACS nutrition and physical activity guidelines or other health related guidelines for cancer risk reduction or prevention of other chronic diseases. PMID:15539533

  5. Risk of radiogenic second cancers following volumetric modulated arc therapy and proton arc therapy for prostate cancer

    PubMed Central

    Rechner, Laura A.; Howell, Rebecca M.; Zhang, Rui; Etzel, Carol; Lee, Andrew K.; Newhauser, Wayne D.

    2013-01-01

    Prostate cancer patients who undergo radiotherapy are at an increased risk to develop a radiogenic second cancer. Proton therapy has been shown to reduce the predicted risk of second cancer when compared to intensity modulated radiotherapy. However, it is unknown if this is also true for the rotational therapies proton arc therapy and volumetric modulated arc therapy (VMAT). The objective of this study was to compare the predicted risk of cancer following proton arc therapy and VMAT for prostate cancer. Proton arc therapy and VMAT plans were created for 3 patients. Various risk models were combined with the dosimetric data (therapeutic and stray dose) to predict the excess relative risk (ERR) of cancer in the bladder and rectum. Ratios of ERR values (RRR) from proton arc therapy and VMAT were calculated. RRR values ranged from 0.74 to 0.99, and all RRR values were shown to be statistically less than 1, except for the value calculated with the linear-non-threshold risk model. We conclude that the predicted risk of cancer in the bladder or rectum following proton arc therapy for prostate cancer is either less than or approximately equal to the risk following VMAT, depending on which risk model is applied. PMID:23051714

  6. Risks of Colorectal Cancer Screening

    MedlinePlus

    ... Genetics of Colorectal Cancer Colorectal cancer is the second leading cause of death from cancer in the ... professional versions have detailed information written in technical language. The patient versions are written in easy-to- ...

  7. What Are the Risk Factors for Breast Cancer in Men?

    MedlinePlus

    ... in men? What are the risk factors for breast cancer in men? A risk factor is anything that ... old when they are diagnosed. Family history of breast cancer Breast cancer risk is increased if other members ...

  8. Breast cancer susceptibility polymorphisms and endometrial cancer risk: a Collaborative Endometrial Cancer Study

    PubMed Central

    Ahmed, Shahana; O’Mara, Tracy A.; Ferguson, Kaltin; Lambrechts, Diether; Garcia-Dios, Diego A.; Vergote, Ignace; Amant, Frederic; Howarth, Kimberley; Gorman, Maggie; Hodgson, Shirley; Tomlinson, Ian; Yang, Hannah P.; Lissowska, Jolanta; Brinton, Louise A.; Chanock, Stephen; Garcia-Closas, Montserrat; Hall, Per; Liu, Jianjun; Shah, Mitul; Pharoah, Paul D.P.; Thompson, Deborah J.; Rebbeck, Timothy R.; Strom, Brian L.; Dunning, Alison M.; Easton, Douglas F.; Spurdle, Amanda B.

    2011-01-01

    Recent large--scale association studies, both of genome-wide and candidate gene design, have revealed several single-nucleotide polymorphisms (SNPs) which are significantly associated with risk of developing breast cancer. As both breast and endometrial cancers are considered to be hormonally driven and share multiple risk factors, we investigated whether breast cancer risk alleles are also associated with endometrial cancer risk. We genotyped nine breast cancer risk SNPs in up to 4188 endometrial cases and 11 928 controls, from between three and seven Caucasian populations. None of the tested SNPs showed significant evidence of association with risk of endometrial cancer. PMID:21965274

  9. Breast cancer susceptibility polymorphisms and endometrial cancer risk: a Collaborative Endometrial Cancer Study.

    PubMed

    Healey, Catherine S; Ahmed, Shahana; O'Mara, Tracy A; Ferguson, Kaltin; Lambrechts, Diether; Garcia-Dios, Diego A; Vergote, Ignace; Amant, Frederic; Howarth, Kimberley; Gorman, Maggie; Hodgson, Shirley; Tomlinson, Ian; Yang, Hannah P; Lissowska, Jolanta; Brinton, Louise A; Chanock, Stephen; Garcia-Closas, Montserrat; Hall, Per; Liu, Jianjun; Shah, Mitul; Pharoah, Paul D P; Thompson, Deborah J; Rebbeck, Timothy R; Strom, Brian L; Dunning, Alison M; Easton, Douglas F; Spurdle, Amanda B

    2011-12-01

    Recent large--scale association studies, both of genome-wide and candidate gene design, have revealed several single-nucleotide polymorphisms (SNPs) which are significantly associated with risk of developing breast cancer. As both breast and endometrial cancers are considered to be hormonally driven and share multiple risk factors, we investigated whether breast cancer risk alleles are also associated with endometrial cancer risk. We genotyped nine breast cancer risk SNPs in up to 4188 endometrial cases and 11,928 controls, from between three and seven Caucasian populations. None of the tested SNPs showed significant evidence of association with risk of endometrial cancer. PMID:21965274

  10. Birth Weight and Subsequent Risk of Cancer

    PubMed Central

    Spracklen, Cassandra N; Wallace, Robert B; Sealy-Jefferson, Shawnita; Robinson, Jennifer G; Freudenheim, Jo L; Wellons, Melissa F; Saftlas, Audrey F; Snetselaar, Linda G; Manson, JoAnn E; Hou, Lifang; Qi, Lihong; Chlebowski, Rowan T; Ryckman, Kelli K

    2014-01-01

    Background We aimed to determine the association between self-reported birth weight and incident cancer in the Women’s Health Initiative Observational Study cohort, a large multiethnic cohort of postmenopausal women. Methods 65,850 women reported their birth weight by category (<6 lbs., 6 lbs.–7 lbs. 15 oz., 8 lbs.–9 lbs. 15 oz., and ≥10 lbs.). All self-reported, incident cancers were adjudicated by study staff. We used Cox proportional hazards regression to estimate crude and adjusted hazard ratios (aHR) for associations between birth weight and: 1) all cancer sites combined, 2) gynecologic cancers, and 3) several site-specific cancer sites. Results After adjustments, birth weight was positively associated with the risk of lung cancer (p=0.01), and colon cancer (p=0.04). An inverse trend was observed between birth weight and risk for leukemia (p=0.04). A significant trend was not observed with breast cancer risk (p=0.67); however, women born weighing ≥10 lbs. were less likely to develop breast cancer compared to women born between 6 lbs.–7 lbs. 15 oz (aHR 0.77, 95% CI 0.63, 0.94). Conclusion Birth weight category appears to be significantly associated with the risk of any postmenopausal incident cancer, though the direction of the association varies by cancer type. PMID:25096278