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1.  Using multiple risk models with preventive interventions 
Statistics in medicine  2012;31(23):2687-2696.
An ideal preventive intervention would have negligible side effects and could be applied to the entire population, thus achieving maximal preventive impact. Unfortunately, many interventions have adverse effects as well as beneficial effects. For example, tamoxifen reduces the risk of breast cancer by about 50% and the risk of hip fracture by 45%, but increases the risk of stroke by about 60%; other serious adverse effects include endometrial cancer and pulmonary embolus. Hence, tamoxifen should only be given to the subset of the population with high enough risks of breast cancer and hip fracture such that the preventive benefits outweigh the risks. Recommendations for preventive use of tamoxifen have been based primarily on breast cancer risk. Age- and race-specific rates were considered for other health outcomes, but not risk models. In this paper, I investigate the extent to which modeling not only the risk of breast cancer, but also the risk of stroke, can improve the decision to take tamoxifen. These calculations also give insight into the relative benefits of improving the discriminatory accuracy of such risk models versus improving the preventive effectiveness or reducing the adverse risks of the intervention. Depending on the discriminatory accuracies of the risk models, there may be considerable advantage to modeling the risks of more than one health outcome.
doi:10.1002/sim.5443
PMCID: PMC3926659  PMID: 22733645
absolute risk models; breast cancer; disease prevention; modeling multiple risks; risk-based prevention strategy; risk versus benefit
3.  Feasibility of self-collection of fecal specimens by randomly sampled women for health-related studies of the gut microbiome 
BMC Research Notes  2014;7:204.
Background
The field of microbiome research is growing rapidly. We developed a method for self-collection of fecal specimens that can be used in population-based studies of the gut microbiome. We conducted a pilot study to test the feasibility of our methods among a random sample of healthy, postmenopausal women who are members of Kaiser Permanente Colorado (KPCO). We aimed to collect questionnaire data, fecal and urine specimens from 60 women, aged 55–69, who recently had a normal screening mammogram. We designed the study such that all questionnaire data and specimens could be collected at home.
Results
We mailed an invitation packet, consent form and opt-out postcard to 300 women, then recruited by telephone women who did not opt-out. Verbally consented women were mailed an enrollment package including a risk factor questionnaire, link to an online diet questionnaire, specimen collection kit, and instructions for collecting stool and urine. Specimens were shipped overnight to the biorepository. Of the 300 women mailed an invitation packet, 58 (19%) returned the opt-out postcard. Up to 3 attempts were made to telephone the remaining women, of whom 130 (43%) could not be contacted, 23 (8%) refused, and 12 (4%) were ineligible. Enrollment packages were mailed to 77 women, of whom 59 returned the risk factor questionnaire and specimens. We found no statistically significant differences between enrolled women and those who refused participation or could not be contacted.
Conclusions
We demonstrated that a representative sample of women can be successfully recruited for a gut microbiome study; however, significant personal contact and carefully timed follow-up from the study personnel are required. The methods employed by our study could successfully be applied to analytic studies of a wide range of clinical conditions that have been postulated to be influenced by the gut microbial population.
doi:10.1186/1756-0500-7-204
PMCID: PMC3974920  PMID: 24690120
Study design; Microbiome; Breast cancer
4.  Potential Usefulness of Single Nucleotide Polymorphisms to Identify Persons at High Cancer Risk: An Evaluation of Seven Common Cancers 
Journal of Clinical Oncology  2012;30(17):2157-2162.
Purpose
To estimate the likely number and predictive strength of cancer-associated single nucleotide polymorphisms (SNPs) that are yet to be discovered for seven common cancers.
Methods
From the statistical power of published genome-wide association studies, we estimated the number of undetected susceptibility loci and the distribution of effect sizes for all cancers. Assuming a log-normal model for risks and multiplicative relative risks for SNPs, family history (FH), and known risk factors, we estimated the area under the receiver operating characteristic curve (AUC) and the proportion of patients with risks above risk thresholds for screening. From additional prevalence data, we estimated the positive predictive value and the ratio of non–patient cases to patient cases (false-positive ratio) for various risk thresholds.
Results
Age-specific discriminatory accuracy (AUC) for models including FH and foreseeable SNPs ranged from 0.575 for ovarian cancer to 0.694 for prostate cancer. The proportions of patients in the highest decile of population risk ranged from 16.2% for ovarian cancer to 29.4% for prostate cancer. The corresponding false-positive ratios were 241 for colorectal cancer, 610 for ovarian cancer, and 138 or 280 for breast cancer in women age 50 to 54 or 40 to 44 years, respectively.
Conclusion
Foreseeable common SNP discoveries may not permit identification of small subsets of patients that contain most cancers. Usefulness of screening could be diminished by many false positives. Additional strong risk factors are needed to improve risk discrimination.
doi:10.1200/JCO.2011.40.1943
PMCID: PMC3397697  PMID: 22585702
5.  Fifteen-Year Effects of Helicobacter pylori, Garlic, and Vitamin Treatments on Gastric Cancer Incidence and Mortality 
In the Shandong Intervention Trial, 2 weeks of antibiotic treatment for Helicobacter pylori reduced the prevalence of precancerous gastric lesions, whereas 7.3 years of oral supplementation with garlic extract and oil (garlic treatment) or vitamin C, vitamin E, and selenium (vitamin treatment) did not. Here we report 14.7-year follow-up for gastric cancer incidence and cause-specific mortality among 3365 randomly assigned subjects in this masked factorial placebo-controlled trial. Conditional logistic regression was used to estimate the odds of gastric cancer incidence, and the Cox proportional hazards model was used to estimate the relative hazard of cause-specific mortality. All statistical tests were two-sided. Gastric cancer was diagnosed in 3.0% of subjects who received H pylori treatment and in 4.6% of those who received placebo (odds ratio = 0.61, 95% confidence interval = 0.38 to 0.96, P = .032). Gastric cancer deaths occurred among 1.5% of subjects assigned H pylori treatment and among 2.1% of those assigned placebo (hazard ratio [HR] of death = 0.67, 95% CI = 0.36 to 1.28). Garlic and vitamin treatments were associated with non-statistically significant reductions in gastric cancer incidence and mortality. Vitamin treatment was associated with statistically significantly fewer deaths from gastric or esophageal cancer, a secondary endpoint (HR = 0.51, 95% CI = 0.30 to 0.87; P = .014).
doi:10.1093/jnci/djs003
PMCID: PMC3309129  PMID: 22271764
6.  Evaluating breast cancer risk projections for Hispanic women 
Breast cancer research and treatment  2011;132(1):10.1007/s10549-011-1900-9.
For Hispanic women, the Breast Cancer Risk Assessment Tool (BCRAT; “Gail Model”) combines 1990–1996 breast cancer incidence for Hispanic women with relative risks for breast cancer risk factors from non-Hispanic white (NHW) women. BCRAT risk projections have never been comprehensively evaluated for Hispanic women. We compared the relative risks and calibration of BCRAT risk projections for 6,353 Hispanic to 128,976 NHW postmenopausal participants aged 50 and older in the Women’s Health Initiative (WHI). Calibration was assessed by the ratio of the number of breast cancers observed with that expected by the BCRAT (O/E). We re-evaluated calibration for an updated BCRAT that combined BCRAT relative risks with 1993–2007 breast cancer incidence that is contemporaneous with the WHI. Cox regression was used to estimate relative risks. Discriminatory accuracy was assessed using the concordance statistic (AUC). In the WHI Main Study, the BCRAT underestimated the number of breast cancers by 18% in both Hispanics (O/E = 1.18, P = 0.06) and NHWs (O/E = 1.18, P < 0.001). Updating the BCRAT improved calibration for Hispanic women (O/E = 1.08, P = 0.4) and NHW women (O/E = 0.98, P = 0.2). For Hispanic women, relative risks for number of breast biopsies (1.71 vs. 1.27, P = 0.03) and age at first birth (0.97 vs. 1.24, P = 0.02) differed between the WHI and BCRAT. The AUC was higher for Hispanic women than NHW women (0.63 vs. 0.58, P = 0.03). Updating the BCRAT with contemporaneous breast cancer incidence rates improved calibration in the WHI. The modest discriminatory accuracy of the BCRAT for Hispanic women might improve by using risk factor relative risks specific to Hispanic women.
doi:10.1007/s10549-011-1900-9
PMCID: PMC3827770  PMID: 22147080
Hispanic; Breast cancer; Risk prediction; Risk assessment; BCRAT
7.  Risk Factor Modification and Projections of Absolute Breast Cancer Risk 
Background
Although modifiable risk factors have been included in previous models that estimate or project breast cancer risk, there remains a need to estimate the effects of changes in modifiable risk factors on the absolute risk of breast cancer.
Methods
Using data from a case–control study of women in Italy (2569 case patients and 2588 control subjects studied from June 1, 1991, to April 1, 1994) and incidence and mortality data from the Florence Registries, we developed a model to predict the absolute risk of breast cancer that included five non-modifiable risk factors (reproductive characteristics, education, occupational activity, family history, and biopsy history) and three modifiable risk factors (alcohol consumption, leisure physical activity, and body mass index). The model was validated using independent data, and the percent risk reduction was calculated in high-risk subgroups identified by use of the Lorenz curve.
Results
The model was reasonably well calibrated (ratio of expected to observed cancers = 1.10, 95% confidence interval [CI] = 0.96 to 1.26), but the discriminatory accuracy was modest. The absolute risk reduction from exposure modifications was nearly proportional to the risk before modifying the risk factors and increased with age and risk projection time span. Mean 20-year reductions in absolute risk among women aged 65 years were 1.6% (95% CI = 0.9% to 2.3%) in the entire population, 3.2% (95% CI = 1.8% to 4.8%) among women with a positive family history of breast cancer, and 4.1% (95% CI = 2.5% to 6.8%) among women who accounted for the highest 10% of the total population risk, as determined from the Lorenz curve.
Conclusions
These data give perspective on the potential reductions in absolute breast cancer risk from preventative strategies based on lifestyle changes. Our methods are also useful for calculating sample sizes required for trials to test lifestyle interventions.
doi:10.1093/jnci/djr172
PMCID: PMC3131219  PMID: 21705679
8.  Projecting Individualized Absolute Invasive Breast Cancer Risk in Asian and Pacific Islander American Women 
Background
The Breast Cancer Risk Assessment Tool (BCRAT) of the National Cancer Institute is widely used for estimating absolute risk of invasive breast cancer. However, the absolute risk estimates for Asian and Pacific Islander American (APA) women are based on data from white women. We developed a model for projecting absolute invasive breast cancer risk in APA women and compared its projections to those from BCRAT.
Methods
Data from 589 women with breast cancer (case patients) and 952 women without breast cancer (control subjects) in the Asian American Breast Cancer Study were used to compute relative and attributable risks based on the age at menarche, number of affected mothers, sisters, and daughters, and number of previous benign biopsies. Absolute risks were obtained by combining this information with ethnicity-specific data from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) program and with US ethnicity-specific mortality data to create the Asian American Breast Cancer Study model (AABCS model). Independent data from APA women in the Women’s Health Initiative (WHI) were used to check the calibration and discriminatory accuracy of the AABCS model.
Results
The AABCS model estimated absolute risk separately for Chinese, Japanese, Filipino, Hawaiian, Other Pacific Islander, and Other Asian women. Relative and attributable risks for APA women were comparable to those in BCRAT, but the AABCS model usually estimated lower-risk projections than BCRAT in Chinese and Filipino, but not in Hawaiian women, and not in every age and ethnic subgroup. The AABCS model underestimated absolute risk by 17% (95% confidence interval = 1% to 38%) in independent data from WHI, but APA women in the WHI had incidence rates approximately 18% higher than those estimated from the SEER program.
Conclusions
The AABCS model was calibrated to ethnicity-specific incidence rates from the SEER program for projecting absolute invasive breast cancer risk and is preferable to BCRAT for counseling APA women.
doi:10.1093/jnci/djr154
PMCID: PMC3119648  PMID: 21562243
9.  Genome-wide association studies of gastric adenocarcinoma and esophageal squamous cell carcinoma identify a shared susceptibility locus in PLCE1 at 10q23 
Nature genetics  2012;44(10):1090-1097.
We conducted a genome-wide association study of gastric cancer (GC) and esophageal squamous cell carcinoma (ESCC) in ethnic Chinese subjects in which we genotyped 551,152 single nucleotide polymorphisms (SNPs). We report a combined analysis of 2,240 GC cases, 2,115 ESCC cases, and 3,302 controls drawn from five studies. In logistic regression models adjusted for age, sex, and study, multiple variants at 10q23 had genome-wide significance for GC and ESCC independently. A notable signal was rs2274223, a nonsynonymous SNP located in PLCE1, for GC (P=8.40×1010; per allele odds ratio (OR) = 1.31) and ESCC (P=3.85×10−9; OR = 1.34). The association with GC differed by anatomic subsite. For tumors located in the cardia the association was stronger (P=4.19 × 10−15; OR= 1.57) and for those located in the noncardia stomach it was absent (P=0.44; OR=1.05). Our findings at 10q23 could provide insight into the high incidence rates of both cancers in China.
doi:10.1038/ng.2411
PMCID: PMC3513832  PMID: 22960999
10.  Personalized estimates of breast cancer risk in clinical practice and public health 
Statistics in medicine  2011;30(10):1090-1104.
This paper defines absolute risk and some of its properties, and presents applications in breast cancer counseling and prevention. For counseling, estimates of absolute risk give useful perspective and can be used in management decisions that require weighing risks and benefits, such as whether or not to take tamoxifen to prevent breast cancer. Absolute risk models are also useful in designing intervention trials to prevent breast cancer and in assessing the potential reductions in absolute risk of disease that might result from reducing exposures that are associated with breast cancer. In these applications, it is important that the risk model be well calibrated, namely that it accurately predict the numbers of women who will develop breast cancer in various subsets of the population. Absolute risk models are also needed to implement a “high risk” prevention strategy that identifies a high risk subset of the population and focuses intervention efforts on that subset. The limitations of the high risk strategy are discussed, including the need for risk models with high discriminatory accuracy, and the need for less toxic interventions that can reduce the threshold of risk above which the intervention provides a net benefit. I also discuss the potential use of risk models in allocating prevention resources under cost constraints. High discriminatory accuracy of the risk model, in addition to good calibration, is desirable in this application, and the risk assessment should not be expensive in comparison with the intervention.
doi:10.1002/sim.4187
PMCID: PMC3079423  PMID: 21337591
absolute risk; allocation of prevention resources; breast cancer; calibration; crude risk; cumulative incidence; discriminatory accuracy; disease prevention; designing disease prevention trials; high risk prevention strategy; risk versus benefit
11.  Beyond Recreational Physical Activity: Examining Occupational and Household Activity, Transportation Activity, and Sedentary Behavior in Relation to Postmenopausal Breast Cancer Risk 
American Journal of Public Health  2010;100(11):2288-2295.
Objectives
We prospectively examined nonrecreational physical activity and sedentary behavior in relation to breast cancer risk among 97039 postmenopausal women in the National Institutes of Health–AARP Diet and Health Study.
Methods
We identified 2866 invasive and 570 in situ breast cancer cases recorded between 1996 and 2003 and used Cox proportional hazards regression to estimate multivariate relative risks (RRs) and 95% confidence intervals (CIs).
Results
Routine activity during the day at work or at home that included heavy lifting or carrying versus mostly sitting was associated with reduced risk of invasive breast cancer (RR = 0.62; 95% CI = 0.42, 0.91; Ptrend = .024).
Conclusions
Routine activity during the day at work or home may be related to reduced invasive breast cancer risk. Domains outside of recreation time may be attractive targets for increasing physical activity and reducing sedentary behavior among postmenopausal women.
doi:10.2105/AJPH.2009.180828
PMCID: PMC2951936  PMID: 20864719
12.  Assessment of the human fecal microbiota: II. Reproducibility and associations of 16S rRNA pyrosequences 
Background
We conducted a pilot study of reproducibility and associations of microbial diversity and composition in fecal microbial DNA.
Methods and results
Participants (25 men, 26 women, ages 17–65 years) provided questionnaire data and multiple samples of one stool collected with two Polymedco and two Sarstedt devices pre-loaded with RNAlater. 16S rRNA genes in each fecal DNA aliquot were amplified, sequenced (Roche/454 Life Sciences), and assigned to taxa. Devices were compared for ease of use and reproducibility [intraclass correlation coefficient (ICC)] between duplicate aliquots on diversity and taxonomic assignment. Associations were tested by linear regression. Both collection devices were easy to use. Both alpha diversity (Shannon index) and beta diversity (UniFrac) were higher between than within duplicates (P≤10−8) and did not differ significantly by device (P≥0.62). Reproducibility was good (ICC ≥0.77) for alpha diversity and taxonomic assignment to the most abundant phyla, Firmicutes and Bacteroidetes (71.5% and 25.0% of sequences, respectively), but reproducibility was low (ICC≤0.48) for less abundant taxa. Alpha diversity was lower with non-antibiotic prescription medication (P=0.02), younger age (P=0.03) and marginally with higher body mass index (P=0.08).
Conclusions
With sampling from various parts of a stool, both devices provided good reproducibility on overall microbial diversity and classification for the major phyla, but not for minor phyla. Implementation of these methods should provide insights on how broad microbial parameters, but not necessarily rare microbes, affect risk for various conditions.
doi:10.1111/j.1365-2362.2012.02659.x
PMCID: PMC3369017  PMID: 22385292
Microbiome; alpha diversity; beta diversity; bacterial phylogenetics; medications; body mass index
13.  Assessment of the human fecal microbiota: I. Measurement and reproducibility of selected enzymatic activities 
Background
The intestinal microbial community has major effects on human health, but optimal research methods are unsettled. To facilitate epidemiologic and clinical research, we sought to optimize conditions and to assess reproducibility of selected core functions of the distal gut microbiota, β-glucuronidase and β-glucosidase bioactivities.
Methods and results
A colorimetric kinetic method was optimized and used to quantify activities of β-glucuronidase and β-glucosidase in human feces. Enzyme detection was optimal with neutral pH, snap freezing in liquid nitrogen, and rapid thawing to 37°C before protein extraction. Enzymatic stability was assessed by delayed freezing for 2–48 hours to mimic field settings. Activities decayed approximately 20% within 2 hours and 40% within 4 hours at room temperature. To formally assess reproducibility, 51 volunteers (25 male; mean age 39) used two devices to self-collect and rapidly chill four replicates of a stool. Devices were compared for mean enzymatic activities and intraclass correlation coefficients (ICC) in paired replicates of the self-collected specimens. Reproducibility was excellent with both devices for β-glucuronidase (ICC 0.92). The larger collection device had significantly higher reproducibility for β-glucosidase (ICC 0.92 vs. 0.76, P<0.0001) and higher mean activities for both enzymes (P<0.0001).
Conclusions
Optimal measurement of these core activities of the microbiota required a sufficient quantity of rapidly chilled or frozen specimens collected in PBS at pH7.0. Application of these methods to clinical and epidemiologic research could provide insights on how the intestinal microbiota affects human health.
doi:10.1111/j.1365-2362.2012.02660.x
PMCID: PMC3399928  PMID: 22409163
β-glucuronidase activity; β-glucosidase activity; feces; reproducibility
14.  Association Between BRCA1 and BRCA2 Mutations and Survival in Women with Invasive Epithelial Ovarian Cancer 
Bolton, Kelly L. | Chenevix-Trench, Georgia | Goh, Cindy | Sadetzki, Siegal | Ramus, Susan J. | Karlan, Beth Y. | Lambrechts, Diether | Despierre, Evelyn | Barrowdale, Daniel | McGuffog, Lesley | Healey, Sue | Easton, Douglas F. | Sinilnikova, Olga | Benitez, Javier | García, María J. | Neuhausen, Susan | Gail, Mitchell H. | Hartge, Patricia | Peock, Susan | Frost, Debra | Evans, D. Gareth | Eeles, Ros | Godwin, Andrew K. | Daly, Mary B. | Kwong, Ava | Ma, Edmond SK | Lázaro, Conxi | Blanco, Ignacio | Montagna, Marco | D’Andrea, Emma | Nicoletto, Ornella | Investigators, kConFab | Johnatty, Sharon E. | Kjær, Susanne Krüger | Jensen, Allan | Høgdall, Estrid | Goode, Ellen L. | Fridley, Brooke L. | Loud, Jennifer T. | Greene, Mark H. | Mai, Phuong L. | Chetrit, Angela | Lubin, Flora | Hirsh-Yechezkel, Galit | Glendon, Gord | Andrulis, Irene L. | Toland, Amanda E. | Senter, Leigha | Gore, Martin E. | Gourley, Charlie | Michie, Caroline O | Song, Honglin | Tyrer, Jonathan | Whittemore, Alice S. | McGuire, Valerie | Sieh, Weiva | Kristoffersson, Ulf | Olsson, Håkan | Borg, Åke | Levine, Douglas A. | Steele, Linda | Beattie, Mary S. | Chan, Salina | Nussbaum, Robert | Moysich, Kirsten B. | Gross, Jenny | Cass, Ilana | Walsh, Christine | Li, Andrew J. | Leuchter, Ronald | Gordon, Ora | Garcia-Closas, Montserrat | Gayther, Simon A. | Chanock, Stephen J. | Antoniou, Antonis C. | Pharoah, Paul D.P.
Context
Approximately 10 percent of women with invasive epithelial ovarian cancer (EOC) carry deleterious germline mutations in BRCA1 or BRCA2. A recent report suggested that BRCA2 related EOC was associated with an improved prognosis, but the effect of BRCA1 remains unclear.
Objective
To characterize the survival of BRCA carriers with EOC compared to non-carriers and to determine whether BRCA1 and BRCA2 carriers show similar survival patterns.
Design, Setting, and Participants
We pooled data from 26 studies on the survival of women with ovarian cancer. This included data on 1,213 EOC cases with pathogenic germline mutations in BRCA1 (909) or BRCA2 (304) and 2,666 non-carriers recruited and followed for variable times between 1987 and 2010; the median year of diagnosis was 1998.
Main Outcome Measures
Five year overall mortality.
Results
The five-year overall survival was 36 percent (95% CI: 34–38) for non-carriers, 44 percent (95% CI: 40–48) for BRCA1 carriers and 52 percent (95% CI: 46–58) for BRCA2 carriers. After adjusting for study and year of diagnosis, BRCA1 and BRCA2 carriers showed a more favorable survival than non-carriers (BRCA1, HR=0.78; 95% CI=0.68–0.89, P=2×10−4; BRCA2, HR = 0.61; 95% CI=0.50–0.76, P=6×10−6). These survival differences remained after additional adjustment for stage, grade, histology and age at diagnosis (BRCA1, HR=0.73, 95% CI=0.64–0.84, P=2×10−5; BRCA2, HR = 0.49, 95% CI=0.39–0.61, P=3×10−10).
Conclusions
Among patients with invasive epithelial ovarian cancer, having a germline mutation in BRCA1 or BRCA2 was associated with improved 5-year overall survival.
doi:10.1001/jama.2012.20
PMCID: PMC3727895  PMID: 22274685
15.  Risk Prediction for Breast, Endometrial, and Ovarian Cancer in White Women Aged 50 y or Older: Derivation and Validation from Population-Based Cohort Studies 
PLoS Medicine  2013;10(7):e1001492.
Ruth Pfeiffer and colleagues describe models to calculate absolute risks for breast, endometrial, and ovarian cancers for white, non-Hispanic women over 50 years old using easily obtainable risk factors.
Please see later in the article for the Editors' Summary
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 ovarian cancers from easily obtainable risk factors and may assist in clinical decision-making. Limitations are the modest discriminatory ability of the breast and ovarian models and that these models may not generalize to women of other races.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
In 2008, just three types of cancer accounted for 10% of global cancer-related deaths. That year, about 460,000 women died from breast cancer (the most frequently diagnosed cancer among women and the fifth most common cause of cancer-related death). Another 140,000 women died from ovarian cancer, and 74,000 died from endometrial (womb) cancer (the 14th and 20th most common causes of cancer-related death, respectively). Although these three cancers originate in different tissues, they nevertheless share many risk factors. For example, current age, age at menarche (first period), and parity (the number of children a woman has had) are all strongly associated with breast, ovarian, and endometrial cancer risk. Because these cancers share many hormonal and epidemiological risk factors, a woman with a high breast cancer risk is also likely to have an above-average risk of developing ovarian or endometrial cancer.
Why Was This Study Done?
Several statistical models (for example, the Breast Cancer Risk Assessment Tool) have been developed that estimate a woman's absolute risk (probability) of developing breast cancer over the next few years or over her lifetime. Absolute risk prediction models are useful in the design of cancer prevention trials and can also help women make informed decisions about cancer prevention and treatment options. For example, a woman at high risk of breast cancer might decide to take tamoxifen for breast cancer prevention, but ideally she needs to know her absolute endometrial cancer risk before doing so because tamoxifen increases the risk of this cancer. Similarly, knowledge of her ovarian cancer risk might influence a woman's decision regarding prophylactic removal of her ovaries to reduce her breast cancer risk. There are few absolute risk prediction models for ovarian cancer, and none for endometrial cancer, so here the researchers develop models to predict the risk of these cancers and of breast cancer.
What Did the Researchers Do and Find?
Absolute risk prediction models are constructed by combining estimates for risk factors from cohorts with population-based incidence rates from cancer registries. Models are validated in an independent cohort by testing their ability to identify people with the disease in an independent cohort and their ability to predict the observed numbers of incident cases. The researchers used data on white, non-Hispanic women aged 50 years or older that were collected during two large prospective US cohort studies of cancer screening and of diet and health, and US cancer incidence and mortality rates provided by the Surveillance, Epidemiology, and End Results Program to build their models. The models all included parity as a risk factor, as well as other factors. The model for endometrial cancer, for example, also included menopausal status, age at menopause, body mass index (an indicator of the amount of body fat), oral contraceptive use, menopausal hormone therapy use, and an interaction term between menopausal hormone therapy use and body mass index. Individual women's risk for endometrial cancer calculated using this model ranged from 1.22% to 17.8% over the next 20 years depending on their exposure to various risk factors. Validation of the models using data from the US Nurses' Health Study indicated that the endometrial cancer model overestimated the risk of endometrial cancer but that the breast and ovarian cancer models were well calibrated—the predicted and observed risks for these cancers in the validation cohort agreed closely. Finally, the discriminatory power of the models (a measure of how well a model separates people who have a disease from people who do not have the disease) was modest for the breast and ovarian cancer models but somewhat better for the endometrial cancer model.
What Do These Findings Mean?
These findings show that breast, ovarian, and endometrial cancer can all be predicted using information on known risk factors for these cancers that is easily obtainable. Because these models were constructed and validated using data from white, non-Hispanic women aged 50 years or older, they may not accurately predict absolute risk for these cancers for women of other races or ethnicities. Moreover, the modest discriminatory power of the breast and ovarian cancer models means they cannot be used to decide which women should be routinely screened for these cancers. Importantly, however, these well-calibrated models should provide realistic information about an individual's risk of developing breast, ovarian, or endometrial cancer that can be used in clinical decision-making and that may assist in the identification of potential participants for research studies.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001492.
This study is further discussed in a PLOS Medicine Perspective by Lars Holmberg and Andrew Vickers
The US National Cancer Institute provides comprehensive information about cancer (in English and Spanish), including detailed information about breast cancer, ovarian cancer, and endometrial cancer;
Information on the Breast Cancer Risk Assessment Tool, the Surveillance, Epidemiology, and End Results Program, and on the prospective cohort study of screening and the diet and health study that provided the data used to build the models is also available on the NCI site
Cancer Research UK, a not-for-profit organization, provides information about cancer, including detailed information on breast cancer, ovarian cancer, and endometrial cancer
The UK National Health Service Choices website has information and personal stories about breast cancer, ovarian cancer, and endometrial cancer; the not-for-profit organization Healthtalkonline also provides personal stories about dealing with breast cancer and ovarian cancer
doi:10.1371/journal.pmed.1001492
PMCID: PMC3728034  PMID: 23935463
16.  Value of Adding Single-Nucleotide Polymorphism Genotypes to a Breast Cancer Risk Model 
Background
Adding genotypes from seven single-nucleotide polymorphisms (SNPs), which had previously been associated with breast cancer, to the National Cancer Institute's Breast Cancer Risk Assessment Tool (BCRAT) increases the area under the receiver operating characteristic curve from 0.607 to 0.632.
Methods
Criteria that are based on four clinical or public health applications were used to compare BCRAT with BCRATplus7, which includes the seven genotypes. Criteria included number of expected life-threatening events for the decision to take tamoxifen, expected decision losses (in units of the loss from giving a mammogram to a woman without detectable breast cancer) for the decision to have a mammogram, rates of risk reclassification, and number of lives saved by risk-based allocation of screening mammography. For all calculations, the following assumptions were made: Hardy–Weinberg equilibrium, linkage equilibrium across SNPs, additive effects of alleles at each locus, no interactions on the logistic scale among SNPs or with factors in BCRAT, and independence of SNPs from factors in BCRAT.
Results
Improvements in expected numbers of life-threatening events were only 0.07% and 0.81% for deciding whether to take tamoxifen to prevent breast cancer for women aged 50–59 and 40–49 years, respectively. For deciding whether to recommend screening mammograms to women aged 50–54 years, the reduction in expected losses was 0.86% if the ideal breast cancer prevalence threshold for recommending mammography was that of women aged 50–54 years. Cross-classification of risks indicated that some women classified by BCRAT would have different classifications with BCRATplus7, which might be useful if BCRATplus7 was well calibrated. Improvements from BCRATplus7 were small for risk-based allocation of mammograms under costs constraints.
Conclusions
The gains from BCRATplus7 are small in the applications examined. Models with SNPs, such as BCRATplus7, have not been validated for calibration in independent cohort data. Additional studies are needed to validate a model with SNPs and justify its use.
doi:10.1093/jnci/djp130
PMCID: PMC2704229  PMID: 19535781
17.  Estrogen Metabolism and Risk of Breast Cancer in Postmenopausal Women 
Background
Estrogens are recognized causal factors in breast cancer. Interindividual variation in estrogen metabolism may also influence the risk of breast cancer and could provide clues to mechanisms of breast carcinogenesis. Long-standing hypotheses about how estrogen metabolism might influence breast cancer have not been adequately evaluated in epidemiological studies because of the lack of accurate, reproducible, and high-throughput assays for estrogen metabolites.
Methods
We conducted a prospective case–control study nested within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). Participants included 277 women who developed invasive breast cancer (case subjects) and 423 matched control subjects; at PLCO baseline, all subjects were aged 55–74 years, postmenopausal and not using hormone therapy, and provided a blood sample. Liquid chromatography–tandem mass spectrometry was used to measure serum concentrations of 15 estrogens and estrogen metabolites, in unconjugated and conjugated forms, including the parent estrogens, estrone and estradiol, and estrogen metabolites in pathways defined by irreversible hydroxylation at the C-2, C-4, or C-16 positions of the steroid ring. We calculated hazard ratios (HRs) approximating risk in highest vs lowest deciles of individual estrogens and estrogen metabolites, estrogens and estrogen metabolites grouped by metabolic pathways, and metabolic pathway ratios using multivariable Cox proportional hazards models. All statistical tests were two-sided.
Results
Nearly all estrogens, estrogen metabolites, and metabolic pathway groups were associated with an increased risk of breast cancer; the serum concentration of unconjugated estradiol was strongly associated with the risk of breast cancer (HR = 2.07, 95% confidence interval [CI] = 1.19 to 3.62). No estrogen, estrogen metabolite, or metabolic pathway group remained statistically significantly associated with the risk of breast cancer after adjusting for unconjugated estradiol. The ratio of the 2-hydroxylation pathway to parent estrogens (HR = 0.66, 95% CI = 0.51 to 0.87) and the ratio of 4-hydroxylation pathway catechols to 4-hydroxylation pathway methylated catechols (HR = 1.34, 95% CI = 1.04 to 1.72) were statistically significantly associated with the risk of breast cancer and remained so after adjustment for unconjugated estradiol.
Conclusions
More extensive 2-hydroxylation of parent estrogens is associated with lower risk, and less extensive methylation of potentially genotoxic 4-hydroxylation pathway catechols is associated with higher risk of postmenopausal breast cancer.
doi:10.1093/jnci/djr531
PMCID: PMC3283536  PMID: 22232133
18.  Discriminatory Accuracy From Single-Nucleotide Polymorphisms in Models to Predict Breast Cancer Risk 
One purpose for seeking common alleles that are associated with disease is to use them to improve models for projecting individualized disease risk. Two genome-wide association studies and a study of candidate genes recently identified seven common single-nucleotide polymorphisms (SNPs) that were associated with breast cancer risk in independent samples. These seven SNPs were located in FGFR2, TNRC9 (now known as TOX3), MAP3K1, LSP1, CASP8, chromosomal region 8q, and chromosomal region 2q35. I used estimates of relative risks and allele frequencies from these studies to estimate how much these SNPs could improve discriminatory accuracy measured as the area under the receiver operating characteristic curve (AUC). A model with these seven SNPs (AUC = 0.574) and a hypothetical model with 14 such SNPs (AUC = 0.604) have less discriminatory accuracy than a model, the National Cancer Institute’s Breast Cancer Risk Assessment Tool (BCRAT), that is based on ages at menarche and at first live birth, family history of breast cancer, and history of breast biopsy examinations (AUC = 0.607). Adding the seven SNPs to BCRAT improved discriminatory accuracy to an AUC of 0.632, which was, however, less than the improvement from adding mammographic density. Thus, these seven common alleles provide less discriminatory accuracy than BCRAT but have the potential to improve the discriminatory accuracy of BCRAT modestly. Experience to date and quantitative arguments indicate that a huge increase in the numbers of case patients with breast cancer and control subjects would be required in genome-wide association studies to find enough SNPs to achieve high discriminatory accuracy.
doi:10.1093/jnci/djn180
PMCID: PMC2528005  PMID: 18612136
19.  Discriminatory Accuracy from Single-Nucleotide Polymorphisms in Models to Predict Breast Cancer Risk 
One purpose for seeking common alleles that are associated with disease is to use them to improve models for projecting individualized disease risk. Two genome-wide association studies and a study of candidate genes recently identified seven common single-nucleotide polymorphisms (SNPs) that were associated with breast cancer risk in independent samples. These seven SNPs were located in FGFR2, TNRC9, MAP3K1, LSP1, CASP8, chromosomal region 8q, and chromosomal region 2q35. I used estimates of relative risks and allele frequencies from these studies to estimate how much these SNPs could improve discriminatory accuracy measured as the area under the receiver operating characteristic curve (AUC). A model with these seven SNPs (AUC = 0.574) and a hypothetical model with 14 such SNPs (AUC = 0.604) have less discriminatory accuracy than a model, the National Cancer Institute's Breast Cancer Risk Assessment Tool (BCRAT), which is based on ages at menarche and at first live birth, family history of breast cancer, and history of breast biopsy examinations (AUC = 0.607). Adding the seven SNPs to BCRAT improved discriminatory accuracy to an AUC of 0.632, which was, however, less than the improvement from adding mammographic density. Thus, these seven common alleles provide less discriminatory accuracy than BCRAT but have the potential to improve the discriminatory accuracy of BCRAT modestly. Experience to date and quantitative arguments indicate that a huge increase in the numbers of case patients with breast cancer and control subjects would be required in genome-wide association studies to find enough SNPs to achieve high discriminatory accuracy.
doi:10.1093/jnci/djn180
PMCID: PMC2528005  PMID: 18612136
20.  Fecal microbial determinants of fecal and systemic estrogens and estrogen metabolites: a cross-sectional study 
Background
High systemic estrogen levels contribute to breast cancer risk for postmenopausal women, whereas low levels contribute to osteoporosis risk. Except for obesity, determinants of non-ovarian systemic estrogen levels are undefined. We sought to identify members and functions of the intestinal microbial community associated with estrogen levels via enterohepatic recirculation.
Methods
Fifty-one epidemiologists at the National Institutes of Health, including 25 men, 7 postmenopausal women, and 19 premenopausal women, provided urine and aliquots of feces, using methods proven to yield accurate and reproducible results. Estradiol, estrone, 13 estrogen metabolites (EM), and their sum (total estrogens) were quantified in urine and feces by liquid chromatography/tandem mass spectrometry. In feces, β-glucuronidase and β-glucosidase activities were determined by realtime kinetics, and microbiome diversity and taxonomy were estimated by pyrosequencing 16S rRNA amplicons. Pearson correlations were computed for each loge estrogen level, loge enzymatic activity level, and microbiome alpha diversity estimate. For the 55 taxa with mean relative abundance of at least 0.1%, ordinal levels were created [zero, low (below median of detected sequences), high] and compared to loge estrogens, β-glucuronidase and β-glucosidase enzymatic activity levels by linear regression. Significance was based on two-sided tests with α=0.05.
Results
In men and postmenopausal women, levels of total urinary estrogens (as well as most individual EM) were very strongly and directly associated with all measures of fecal microbiome richness and alpha diversity (R≥0.50, P≤0.003). These non-ovarian systemic estrogens also were strongly and significantly associated with fecal Clostridia taxa, including non-Clostridiales and three genera in the Ruminococcaceae family (R=0.57−0.70, P=0.03−0.002). Estrone, but not other EM, in urine correlated significantly with functional activity of fecal β-glucuronidase (R=0.36, P=0.04). In contrast, fecal β-glucuronidase correlated inversely with fecal total estrogens, both conjugated and deconjugated (R≤-0.47, P≤0.01). Premenopausal female estrogen levels, which were collected across menstrual cycles and thus highly variable, were completely unrelated to fecal microbiome and enzyme parameters (P≥0.6).
Conclusions
Intestinal microbial richness and functions, including but not limited to β-glucuronidase, influence levels of non-ovarian estrogens via enterohepatic circulation. Thus, the gut microbial community likely affects the risk for estrogen-related conditions in older adults. Understanding how Clostridia taxa relate to systemic estrogens may identify targets for interventions.
Trial registration
Not applicable.
doi:10.1186/1479-5876-10-253
PMCID: PMC3552825  PMID: 23259758
Microbiome; Feces; Enterohepatic circulation; β-glucuronidase; β-glucosidase; Postmenopausal estrogens; Fecal estrogens; Estrogen metabolites
21.  Association of Fecal Microbial Diversity and Taxonomy with Selected Enzymatic Functions 
PLoS ONE  2012;7(6):e39745.
Few microbial functions have been compared to a comprehensive survey of the human fecal microbiome. We evaluated determinants of fecal microbial β-glucuronidase and β-glucosidase activities, focusing especially on associations with microbial alpha and beta diversity and taxonomy. We enrolled 51 healthy volunteers (26 female, mean age 39) who provided questionnaire data and multiple aliquots of a stool, from which proteins were extracted to quantify β-glucuronidase and β-glucosidase activities, and DNA was extracted to amplify and pyrosequence 16S rRNA gene sequences to classify and quantify microbiome diversity and taxonomy. Fecal β-glucuronidase was elevated with weight loss of at least 5 lb. (P = 0.03), whereas β-glucosidase was marginally reduced in the four vegetarians (P = 0.06). Both enzymes were correlated directly with microbiome richness and alpha diversity measures, directly with the abundance of four Firmicutes Clostridia genera, and inversely with the abundance of two other genera (Firmicutes Lactobacillales Streptococcus and Bacteroidetes Rikenellaceae Alistipes) (all P = 0.05–0.0001). Beta diversity reflected the taxonomic associations. These observations suggest that these enzymatic functions are performed by particular taxa and that diversity indices may serve as surrogates of bacterial functions. Independent validation and deeper understanding of these associations are needed, particularly to characterize functions and pathways that may be amenable to manipulation.
doi:10.1371/journal.pone.0039745
PMCID: PMC3386201  PMID: 22761886
22.  Benefit/Risk Assessment for Breast Cancer Chemoprevention With Raloxifene or Tamoxifen for Women Age 50 Years or Older 
Journal of Clinical Oncology  2011;29(17):2327-2333.
Purpose
The Study of Tamoxifen and Raloxifene (STAR) demonstrated that raloxifene was as effective as tamoxifen in reducing the risk of invasive breast cancer (IBC) in postmenopausal women and had lower risks of thromboembolic events, endometrial cancer, and cataracts but had a nonstatistically significant higher risk of noninvasive breast cancer. There is a need to summarize the risks and benefits of these agents.
Patients and Methods
Baseline incidence rates of IBC and other health outcomes, absent raloxifene and tamoxifen, were estimated from breast cancer chemoprevention trials; the Surveillance, Epidemiology and End Results Program; and the Women's Health Initiative. Effects of raloxifene and tamoxifen were estimated from STAR and the Breast Cancer Prevention Trial. We assigned weights to health outcomes to calculate the net benefit from raloxifene compared with placebo and tamoxifen compared with placebo.
Results
Risks and benefits of treatment with raloxifene or tamoxifen depend on age, race, breast cancer risk, and history of hysterectomy. Over a 5-year period, postmenopausal women with an intact uterus had a better benefit/risk index for raloxifene than for tamoxifen. For postmenopausal women without a uterus, the benefit/risk ratio was similar. The benefits and risks of raloxifene and tamoxifen are described in tables that can help identify groups of women for whom the benefits outweigh the risks.
Conclusion
We developed a benefit/risk index to quantify benefits from chemoprevention with tamoxifen or raloxifene. This index can complement clinical evaluation in deciding whether to initiate chemoprevention and in comparing the benefits and risks of raloxifene versus tamoxifen.
doi:10.1200/JCO.2010.33.0258
PMCID: PMC3107748  PMID: 21537036
23.  Confirmation of Family Cancer History Reported in a Population-Based Survey 
Background
Knowledge of family cancer history is essential for estimating an individual’s cancer risk and making clinical recommendations regarding screening and referral to a specialty cancer genetics clinic. However, it is not clear if reported family cancer history is sufficiently accurate for this purpose.
Methods
In the population-based 2001 Connecticut Family Health Study, 1019 participants reported on 20 578 first-degree relatives (FDR) and second-degree relatives (SDR). Of those, 2605 relatives were sampled for confirmation of cancer reports on breast, colorectal, prostate, and lung cancer. Confirmation sources included state cancer registries, Medicare databases, the National Death Index, death certificates, and health-care facility records. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated for reports on lung, colorectal, breast, and prostate cancer and after stratification by sex, age, education, and degree of relatedness and used to estimate report accuracy. Pairwise t tests were used to evaluate differences between the two strata in each stratified analysis. All statistical tests were two-sided.
Results
Overall, sensitivity and positive predictive value were low to moderate and varied by cancer type: 60.2% and 40.0%, respectively, for lung cancer reports, 27.3% and 53.5% for colorectal cancer reports, 61.1% and 61.3% for breast cancer reports, and 32.0% and 53.4% for prostate cancer reports. Specificity and negative predictive value were more than 95% for all four cancer types. Cancer history reports on FDR were more accurate than reports on SDR, with reports on FDR having statistically significantly higher sensitivity for prostate cancer than reports on SDR (58.9% vs 21.5%, P = .002) and higher positive predictive value for lung (78.1% vs 31.7%, P < .001), colorectal (85.8% vs 43.5%, P = .004), and breast cancer (79.9% vs 53.6%, P = .02).
Conclusions
General population reports on family history for the four major adult cancers were not highly accurate. Efforts to improve accuracy are needed in primary care and other health-care settings in which family history is collected to ensure appropriate risk assessment and clinical care recommendations.
doi:10.1093/jnci/djr114
PMCID: PMC3096799  PMID: 21562245
24.  Cancer Burden in the HIV-Infected Population in the United States 
Background
Effective antiretroviral therapy has reduced the risk of AIDS and dramatically prolonged the survival of HIV-infected people in the United States. Consequently, an increasing number of HIV-infected people are at risk of non-AIDS-defining cancers that typically occur at older ages. We estimated the annual number of cancers in the HIV-infected population, both with and without AIDS, in the United States.
Methods
Incidence rates for individual cancer types were obtained from the HIV/AIDS Cancer Match Study by linking 15 HIV and cancer registries in the United States. Estimated counts of the US HIV-infected and AIDS populations were obtained from Centers for Disease Control and Prevention surveillance data. We obtained estimated counts of AIDS-defining (ie, Kaposi sarcoma, non-Hodgkin lymphoma, and cervical cancer) and non-AIDS-defining cancers in the US AIDS population during 1991–2005 by multiplying cancer incidence rates and AIDS population counts, stratified by year, age, sex, race and ethnicity, transmission category, and AIDS-relative time. We tested trends in counts and standardized incidence rates using linear regression models. We multiplied overall cancer rates and HIV-only (HIV infected, without AIDS) population counts, available from 34 US states during 2004–2007, to estimate cancers in the HIV-only population. All statistical tests were two-sided.
Results
The US AIDS population expanded fourfold from 1991 to 2005 (96 179 to 413 080) largely because of an increase in the number of people aged 40 years or older. During 1991–2005, an estimated 79 656 cancers occurred in the AIDS population. From 1991–1995 to 2001–2005, the estimated number of AIDS-defining cancers decreased by greater than threefold (34 587 to 10 325 cancers; Ptrend < .001), whereas non-AIDS-defining cancers increased by approximately threefold (3193 to 10 059 cancers; Ptrend < .001). From 1991–1995 to 2001–2005, estimated counts increased for anal (206 to 1564 cancers), liver (116 to 583 cancers), prostate (87 to 759 cancers), and lung cancers (875 to 1882 cancers), and Hodgkin lymphoma (426 to 897 cancers). In the HIV-only population in 34 US states, an estimated 2191 non-AIDS-defining cancers occurred during 2004–2007, including 454 lung, 166 breast, and 154 anal cancers.
Conclusions
Over a 15-year period (1991–2005), increases in non-AIDS-defining cancers were mainly driven by growth and aging of the AIDS population. This growing burden requires targeted cancer prevention and treatment strategies.
doi:10.1093/jnci/djr076
PMCID: PMC3086877  PMID: 21483021
25.  Postdiagnosis diet quality, the combination of diet quality and recreational physical activity, and prognosis after early-stage breast cancer 
Cancer causes & control : CCC  2011;22(4):589-598.
Objective
To investigate, among women with breast cancer, how postdiagnosis diet quality and the combination of diet quality and recreational physical activity are associated with prognosis.
Methods
This multiethnic, prospective observational cohort included 670 women diagnosed with local or regional breast cancer. Thirty months after diagnosis, women completed self-report assessments on diet and physical activity and were followed for 6 years. Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals for death from any cause and breast cancer death.
Results
Women consuming better-quality diets, as defined by higher Healthy Eating Index-2005 scores, had a 60% reduced risk of death from any cause (HRQ4:Q1: 0.40, 95% CI: 0.17, 0.94) and an 88% reduced risk of death from breast cancer (HRQ4:Q1: 0.12, 95% CI: 0.02, 0.99). Compared with inactive survivors consuming poor-quality diets, survivors engaging in any recreational physical activity and consuming better-quality diets had an 89% reduced risk of death from any cause (HR: 0.11, 95% CI: 0.04, 0.36) and a 91% reduced risk of death from breast cancer (HR: 0.09, 95% CI: 0.01, 0.89). Associations observed were independent of obesity status.
Conclusion
Women diagnosed with localized or regional breast cancer may improve prognosis by adopting better-quality dietary patterns and regular recreational physical activity. Lifestyle interventions emphasizing postdiagnosis behavior changes are advisable in breast cancer survivors.
doi:10.1007/s10552-011-9732-9
PMCID: PMC3091887  PMID: 21340493
Diet; Exercise; Breast neoplasm; Prognosis

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