Risk prediction for breast, endometrial, and ovarian cancer in white women aged 50 y or older: derivation and validation from population-based cohort studies.

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.

Maximizing DNA yield for epidemiologic studies: no more buffy coats?

Some molecular analyses require microgram quantities of DNA, yet many epidemiologic studies preserve only the buffy coat. In Frederick, Maryland, in 2010, we estimated DNA yields from 5 mL of whole blood and from equivalent amounts of all-cell-pellet (ACP) fraction, buffy coat, and residual blood cells from fresh blood (n = 10 volunteers) and from both fresh and frozen blood (n = 10). We extracted DNA with the QIAamp DNA Blood Midi Kit (Qiagen Sciences, Germantown, Maryland) for silica spin column capture and measured double-stranded DNA. Yields from frozen blood fractions were not statistically significantly different from those obtained from fresh fractions. ACP fractions yielded 80.6% (95% confidence interval: 66, 97) of the yield of frozen whole blood and 99.3% (95% confidence interval: 86, 100) of the yield of fresh blood. Frozen buffy coat and residual blood cells each yielded only half as much DNA as frozen ACP, and the yields were more variable. Assuming that DNA yield and quality from frozen ACP are stable, we recommend freezing plasma and ACP. Not only does ACP yield twice as much DNA as buffy coat but it is easier to process, and its yield is less variable from person to person. Long-term stability studies are needed. If one wishes to separate buffy coat before freezing, one should also save the residual blood cell fraction, which contains just as much DNA.

Robustness of risk-based allocation of resources for disease prevention.

Risk models for disease incidence can be useful for allocating resources for disease prevention if risk assessment is not too expensive. Assume there is a preventive intervention that should be given to everyone, but preventive resources are limited. We optimize risk-based prevention strategies and investigate robustness to modeling assumptions. The optimal strategy defines the proportion of the population to be given risk assessment and who should be offered intervention. The optimal strategy depends on the ratio of available resources to resources needed to intervene on everyone, and on the ratio of the costs of risk assessment to intervention. Risk assessment is not recommended if it is too expensive. Preventive efficiency decreases with decreasing compliance to risk assessment or intervention. Risk measurement error has little effect nor does misspecification of the risk distribution. Ignoring population substructure has small effects on optimal prevention strategy but can lead to modest over- or under-spending. We give conditions under which ignoring population substructure has no effect on optimal strategy. Thus, a simple one-population model offers robust guidance on prevention strategy but requires data on available resources, costs of risk assessment and intervention, population risk distribution, and probabilities of acceptance of risk assessment and intervention.

On combining family and case-control studies.

Studies to detect genetic association with disease can be family-based, often using families with multiple affected members, or population based, as in population-based case-control studies. If data on both study types are available from the same population, it is useful to combine them to improve power to detect genetic associations. Two aspects of the data need to be accommodated, the sampling scheme and potential residual correlations among family members. We propose two approaches for combining data from a case-control study and a family study that collected families with multiple cases. In the first approach, we view a family as the sampling unit and specify the joint likelihood for the family members using a two-level mixed effects model to account for random familial effects and for residual genetic correlations among family members. The ascertainment of the families is accommodated by conditioning on the ascertainment event. The individuals in the case-control study are treated as families of size one, and their unconditional likelihood is combined with the conditional likelihood for the families. This approach yields subject specific maximum likelihood estimates of covariate effects. In the second approach, we view an individual as the sampling unit. The sampling scheme is accommodated using two-phase sampling techniques, marginal covariate effects are estimated, and correlations among family members are accounted for in the variance calculations. The models are compared in simulations. Data from a case-control and a family study from north-eastern Italy on melanoma and a low-risk melanoma-susceptibility gene, MC1R, are used to illustrate the approaches.

Long-term garlic or micronutrient supplementation, but not anti-Helicobacter pylori therapy, increases serum folate or glutathione without affecting serum vitamin B-12 or homocysteine in a rural Chinese population.

The effects of a 7.3-y supplementation with garlic and micronutrients and of anti-Helicobacter pylori treatment with amoxicillin (1 g twice daily) and omeprazole (20 mg twice daily) on serum folate, vitamin B-12, homocysteine, and glutathione concentrations were assessed in a rural Chinese population. A randomized, double-blind, placebo-controlled, factorial trial was conducted to compare the ability of 3 treatments to retard the development of precancerous gastric lesions in 3411 subjects. The treatments were: 1) anti-H. pylori treatment with amoxicillin and omeprazole; 2) 7.3-y supplementation with aged garlic and steam-distilled garlic oil; and 3) 7.3-y supplementation with vitamin C, vitamin E, and selenium. All 3 treatments were given in a 2(3) factorial design to subjects seropositive for H. pylori infection; only the garlic supplement and vitamin and selenium supplement were given in a 2(2) factorial design to the other subjects. Thirty-four subjects were randomly selected from each of the 12 treatment strata. Sera were analyzed after 7.3 y to measure effects on folate, vitamin B-12, homocysteine, and glutathione concentrations. Regression analyses adjusted for age, gender, and smoking indicated an increase of 10.2% (95%CI: 2.9-18.1%) in serum folate after garlic supplementation and an increase of 13.4% (95%CI: 5.3-22.2%) in serum glutathione after vitamin and selenium supplementation. The vitamin and selenium supplement did not affect other analytes and the amoxicillin and omeprazole therapy did not affect any of the variables tested. In this rural Chinese population, 7.3 y of garlic supplementation increased the serum folate concentration and the vitamin and selenium supplement increased that of glutathione, but neither affected serum concentrations of vitamin B-12 or homocysteine.

Projecting Individualized Absolute Invasive Breast Cancer Risk in US Hispanic Women.

Background: There is no model to estimate absolute invasive breast cancer risk for Hispanic women. Methods: The San Francisco Bay Area Breast Cancer Study (SFBCS) provided data on Hispanic breast cancer case patients (533 US-born, 553 foreign-born) and control participants (464 US-born, 947 foreign-born). These data yielded estimates of relative risk (RR) and attributable risk (AR) separately for US-born and foreign-born women. Nativity-specific absolute risks were estimated by combining RR and AR information with nativity-specific invasive breast cancer incidence and competing mortality rates from the California Cancer Registry and Surveillance, Epidemiology, and End Results program to develop the Hispanic risk model (HRM). In independent data, we assessed model calibration through observed/expected (O/E) ratios, and we estimated discriminatory accuracy with the area under the receiver operating characteristic curve (AUC) statistic. Results: The US-born HRM included age at first full-term pregnancy, biopsy for benign breast disease, and family history of breast cancer; the foreign-born HRM also included age at menarche. The HRM estimated lower risks than the National Cancer Institute's Breast Cancer Risk Assessment Tool (BCRAT) for US-born Hispanic women, but higher risks in foreign-born women. In independent data from the Women's Health Initiative, the HRM was well calibrated for US-born women (observed/expected [O/E] ratio = 1.07, 95% confidence interval [CI] = 0.81 to 1.40), but seemed to overestimate risk in foreign-born women (O/E ratio = 0.66, 95% CI = 0.41 to 1.07). The AUC was 0.564 (95% CI = 0.485 to 0.644) for US-born and 0.625 (95% CI = 0.487 to 0.764) for foreign-born women. Conclusions: The HRM is the first absolute risk model that is based entirely on data specific to Hispanic women by nativity. Further studies in Hispanic women are warranted to evaluate its validity.

Genetic polymorphisms of CYP2E1, GSTT1, GSTP1, GSTM1, ALDH2, and ODC and the risk of advanced precancerous gastric lesions in a Chinese population.

There have been few studies of the associations of genetic polymorphisms with precancerous gastric lesions. We conducted a cross-sectional study to compare the prevalences of several genetic polymorphisms in 302 subjects with mild chronic atrophic gastritis with prevalences in 606 subjects with deep intestinal metaplasia or dysplasia. This stratified random sample of 908 subjects was selected and analyzed for genetic polymorphisms from 2,628 individuals who had gastric biopsies with histopathology in 1989 in Linqu County, Shandong Province, China. In subjects with mild chronic atrophic gastritis, the frequencies of the variant (less common) alleles of CYP2E1 RsaI, CYP2E1 DraI, GSTP1, ALDH2, and ODC were, respectively, 0.156, 0.201, 0.189, 0.190, and 0.428. The frequencies of the null genotypes of GSTM1 and GSTT1 in the mild chronic atrophic gastritis group were 0.509 and 0.565, respectively. Comparing mild chronic atrophic gastritis with deep intestinal metaplasia or any degree of dysplasia, we found no statistically significant associations with any genotype from these loci for dominant, additive, or recessive inheritance models. There was no statistically significant evidence of multiplicative interactions between any pair of genotypes based on CYP2E1 RsaI, CYP2E1 DraI, GSTP1, GSTM1, or GSTT1; nor between Helicobacter pylori status and any of these five loci; nor between smoking status and GSTP1, GSTM1, or GSTT1; nor between alcohol consumption and ALDH2. Statistically significant interactions were noted between salt consumption and GSTP1 and between sour pancake consumption and CYP2E1 RsaI. There was, moreover, a statistically significant interaction (odds ratio, 1.78; 95% confidence interval, 1.03-3.08) between CYP2E1 DraI and smoking at least one cigarette per day. A positive but not statistically significant interaction was also seen between CYP2E1 RsaI and smoking status. These polymorphisms do not seem to govern progression from mild chronic atrophic gastritis to advanced precancerous gastric lesions, but the effects of smoking may be accentuated in individuals carrying variants of CYP2E1.

Helicobacter pylori infection in rural China: demographic, lifestyle and environmental factors.

BACKGROUND: Although Helicobacter pylori is one of the most common human bacterial infections worldwide, its mode of transmission is unclear. METHODS: To investigate possible associations between H. pylori infection and demographic, lifestyle, and environmental factors in a rural Chinese population, a cross-sectional survey was administered to 3288 adults (1994 seropositive, 1019 seronegative, 275 indeterminate) from 13 villages in Linqu County, Shandong Province, China. RESULTS: Helicobacter pylori prevalence was elevated for: infrequent handwashing before meals (OR = 1.7, 95% CI: 1.0-3.0), crowding (i.e. sharing a bed with >2 people [OR = 2.3, 95% CI: 1.3-4.2]), washing/bathing in a pond or ditch (OR = 1.5, 95% CI: 1.0-2.4), and medium (OR = 1.6, 95% CI: 1.3-2.0) and low (OR = 2.3, 95% CI: 1.9-2.9) compared to high village education level, and reduced for never being married or divorced (OR = 0.4, 95% CI: 0.2-1.0). There was also a suggestion that source of drinking water, especially water from a shallow village well might be related to H. pylori seropositivity. There was no evidence of an association between H. pylori prevalence and alcohol or tobacco use, raw fruit and vegetable intake, or individual social class measures. CONCLUSIONS: The results of this study suggest that person-to-person transmission is the most plausible route of H. pylori infection in this rural Chinese population, but waterborne exposures deserve further investigation.

Effects of Helicobacter pylori treatment on gastric cancer incidence and mortality in subgroups.

Among 2258 Helicobacter pylori-seropositive subjects randomly assigned to receive one-time H. pylori treatment with amoxicillin-omeprazole or its placebo, we evaluated the 15-year effect of treatment on gastric cancer incidence and mortality in subgroups defined by age, baseline gastric histopathology, and post-treatment infection status. We used conditional logistic and Cox regressions for covariable adjustments in incidence and mortality analyses, respectively. Treatment was associated with a statistically significant decrease in gastric cancer incidence (odds ratio = 0.36; 95% confidence interval [CI] = 0.17 to 0.79) and mortality (hazard ratio = 0.26; 95% CI = 0.09 to 0.79) at ages 55 years and older and a statistically significant decrease in incidence among those with intestinal metaplasia or dysplasia at baseline (odds ratio = 0.56; 95% CI = 0.34 to 0.91). Treatment benefits for incidence and mortality among those with and without post-treatment infection were similar. Thus H. pylori treatment can benefit older members and those with advanced baseline histopathology, and benefits are present even with post-treatment infection, suggesting treatment can benefit an entire population, not just the young or those with mild histopathology.

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).

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.

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.

Effect of changing breast cancer incidence rates on the calibration of the Gail model.

PURPOSE: The Gail model combines relative risks (RRs) for five breast cancer risk factors with age-specific breast cancer incidence rates and competing mortality rates from the Surveillance, Epidemiology, and End Results (SEER) program from 1983 to 1987 to predict risk of invasive breast cancer over a given time period. Motivated by changes in breast cancer incidence during the 1990s, we evaluated the model's calibration in two recent cohorts. METHODS: We included white, postmenopausal women from the National Institutes of Health (NIH) -AARP Diet and Health Study (NIH-AARP, 1995 to 2003), and the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO, 1993 to 2006). Calibration was assessed by comparing the number of breast cancers expected from the Gail model with that observed. We then evaluated calibration by using an updated model that combined Gail model RRs with 1995 to 2003 SEER invasive breast cancer incidence rates. RESULTS: Overall, the Gail model significantly underpredicted the number of invasive breast cancers in NIH-AARP, with an expected-to-observed ratio of 0.87 (95% CI, 0.85 to 0.89), and in PLCO, with an expected-to-observed ratio of 0.86 (95% CI, 0.82 to 0.90). The updated model was well-calibrated overall, with an expected-to-observed ratio of 1.03 (95% CI, 1.00 to 1.05) in NIH-AARP and an expected-to-observed ratio of 1.01 (95% CI: 0.97 to 1.06) in PLCO. Of women age 50 to 55 years at baseline, 13% to 14% had a projected Gail model 5-year risk lower than the recommended threshold of 1.66% for use of tamoxifen or raloxifene but >or= 1.66% when using the updated model. The Gail model was well calibrated in PLCO when the prediction period was restricted to 2003 to 2006. CONCLUSION: This study highlights that model calibration is important to ensure the usefulness of risk prediction models for clinical decision making.

Validation of a colorectal cancer risk prediction model among white patients age 50 years and older.

PURPOSE: Validation of an absolute risk prediction model for colorectal cancer (CRC) by using a large, population-based cohort. PATIENTS AND METHODS: The National Institutes of Health (NIH) -American Association of Retired Persons (AARP) diet and health study, a prospective cohort study, was used to validate the model. Men and women age 50 to 71 years at baseline answered self-administered questionnaires that asked about demographic characteristics, diet, lifestyle, and medical histories. We compared expected numbers of CRC patient cases predicted by the model to the observed numbers of CRC patient cases identified in the NIH-AARP study overall and in subgroups defined by risk factor combinations. The discriminatory power was measured by the area under the receiver-operating characteristic curve (AUC). RESULTS: During an average of 6.9 years of follow-up, we identified 2,092 and 832 incident CRC patient cases in men and women, respectively. The overall expected/observed ratio was 0.99 (95% CI, 0.95 to 1.04) in men and 1.05 (95% CI, 0.98 to 1.11) in women. Agreement between the expected and the observed number of cases was good in most risk factor categories, except for in subgroups defined by CRC screening and polyp history. This discrepancy may be caused by differences in the question on screening and polyp history between two studies. The AUC was 0.61 (95% CI, 0.60 to 0.62) for men and 0.61 (95% CI, 0.59 to 0.62) for women, which was similar to other risk prediction models. CONCLUSION: The absolute risk model for CRC was well calibrated in a large prospective cohort study. This prediction model, which estimates an individual's risk of CRC given age and risk factors, may be a useful tool for physicians, researchers, and policy makers.

Colorectal cancer risk prediction tool for white men and women without known susceptibility.

PURPOSE: Given the high incidence of colorectal cancer (CRC), and the availability of procedures that can detect disease and remove precancerous lesions, there is a need for a model that estimates the probability of developing CRC across various age intervals and risk factor profiles. METHODS: The development of separate CRC absolute risk models for men and women included estimating relative risks and attributable risk parameters from population-based case-control data separately for proximal, distal, and rectal cancer and combining these estimates with baseline age-specific cancer hazard rates based on Surveillance, Epidemiology, and End Results (SEER) incidence rates and competing mortality risks. RESULTS: For men, the model included a cancer-negative sigmoidoscopy/colonoscopy in the last 10 years, polyp history in the last 10 years, history of CRC in first-degree relatives, aspirin and nonsteroidal anti-inflammatory drug (NSAID) use, cigarette smoking, body mass index (BMI), current leisure-time vigorous activity, and vegetable consumption. For women, the model included sigmoidoscopy/colonoscopy, polyp history, history of CRC in first-degree relatives, aspirin and NSAID use, BMI, leisure-time vigorous activity, vegetable consumption, hormone-replacement therapy (HRT), and estrogen exposure on the basis of menopausal status. For men and women, relative risks differed slightly by tumor site. A validation study in independent data indicates that the models for men and women are well calibrated. CONCLUSION: We developed absolute risk prediction models for CRC from population-based data, and a simple questionnaire suitable for self-administration. This model is potentially useful for counseling, for designing research intervention studies, and for other applications.

Probability of detecting disease-associated single nucleotide polymorphisms in case-control genome-wide association studies.

Some case-control genome-wide association studies (CCGWASs) select promising single nucleotide polymorphisms (SNPs) by ranking corresponding p-values, rather than by applying the same p-value threshold to each SNP. For such a study, we define the detection probability (DP) for a specific disease-associated SNP as the probability that the SNP will be "T-selected," namely have one of the top T largest chi-square values (or smallest p-values) for trend tests of association. The corresponding proportion positive (PP) is the fraction of selected SNPs that are true disease-associated SNPs. We study DP and PP analytically and via simulations, both for fixed and for random effects models of genetic risk, that allow for heterogeneity in genetic risk. DP increases with genetic effect size and case-control sample size and decreases with the number of nondisease-associated SNPs, mainly through the ratio of T to N, the total number of SNPs. We show that DP increases very slowly with T, and the increment in DP per unit increase in T declines rapidly with T. DP is also diminished if the number of true disease SNPs exceeds T. For a genetic odds ratio per minor disease allele of 1.2 or less, even a CCGWAS with 1000 cases and 1000 controls requires T to be impractically large to achieve an acceptable DP, leading to PP values so low as to make the study futile and misleading. We further calculate the sample size of the initial CCGWAS that is required to minimize the total cost of a research program that also includes follow-up studies to examine the T-selected SNPs. A large initial CCGWAS is desirable if genetic effects are small or if the cost of a follow-up study is large.

Projecting individualized absolute invasive breast cancer risk in African American women.

BACKGROUND: The Breast Cancer Risk Assessment Tool of the National Cancer Institute (NCI) is widely used for counseling and determining eligibility for breast cancer prevention trials, although its validity for projecting risk in African American women is uncertain. We developed a model for projecting absolute risk of invasive breast cancer in African American women and compared its projections with those from the Breast Cancer Risk Assessment Tool. METHODS: Data from 1607 African American women with invasive breast cancer and 1647 African American control subjects in the Women's Contraceptive and Reproductive Experiences (CARE) Study were used to compute relative and attributable risks that were based on age at menarche, number of affected mother or sisters, and number of previous benign biopsy examinations. Absolute risks were obtained by combining this information with data on invasive breast cancer incidence in African American women from the NCI's Surveillance, Epidemiology and End Results Program and with national mortality data. Eligibility screening data from the Study of Tamoxifen and Raloxifene (STAR) trial were used to determine how the new model would affect eligibility, and independent data from the Women's Health Initiative (WHI) were used to assess how well numbers of invasive breast cancers predicted by the new model agreed with observed cancers. RESULTS: Tables and graphs for estimating relative risks and projecting absolute invasive breast cancer risk with confidence intervals were developed for African American women. Relative risks for family history and number of biopsies and attributable risks estimated from the CARE population were lower than those from the Breast Cancer Risk Assessment Tool, as was the discriminatory accuracy (i.e., concordance). Using eligibility screening data from the STAR trial, we estimated that 30.3% of African American women would have had 5-year invasive breast cancer risks of at least 1.66% by use of the CARE model, compared with only 14.5% by use of the Breast Cancer Risk Assessment Tool. The numbers of cancers predicted by the CARE model agreed well with observed numbers of cancers (i.e., it was well calibrated) in data from the WHI, except that it underestimated risk in African American women with breast biopsy examinations. CONCLUSIONS: The CARE model usually gave higher risk estimates for African American women than the Breast Cancer Risk Assessment Tool and is recommended for counseling African American women regarding their risk of breast cancer.

Projecting absolute invasive breast cancer risk in white women with a model that includes mammographic density.

BACKGROUND: To improve the discriminatory power of the Gail model for predicting absolute risk of invasive breast cancer, we previously developed a relative risk model that incorporated mammographic density (DENSITY) from data on white women in the Breast Cancer Detection Demonstration Project (BCDDP). That model also included the variables age at birth of first live child (AGEFLB), number of affected mother or sisters (NUMREL), number of previous benign breast biopsy examinations (NBIOPS), and weight (WEIGHT). In this study, we developed the corresponding model for absolute risk. METHODS: We combined the relative risk model with data on the distribution of the variables AGEFLB, NUMREL, NBIOPS, and WEIGHT from the 2000 National Health Interview Survey, with data on the conditional distribution of DENSITY given other risk factors in BCDDP, with breast cancer incidence rates from the Surveillance, Epidemiology, and End Results program of the National Cancer Institute, and with national mortality rates. Confidence intervals (CIs) accounted for variability of estimates of relative risks and of risk factor distributions. We compared the absolute 5-year risk projections from the new model with those from the Gail model on 1744 white women. RESULTS: Attributable risks of breast cancer associated with DENSITY, AGEFLB, NUMREL, NBIOPS, and WEIGHT were 0.779 (95% CI = 0.733 to 0.819) and 0.747 (95% CI = 0.702 to 0.788) for women younger than 50 years and 50 years or older, respectively. The model predicted higher risks than the Gail model for women with a high percentage of dense breast area. However, the average risk projections from the new model in various age groups were similar to those from the Gail model, suggesting that the new model is well calibrated. CONCLUSIONS: This new model for absolute invasive breast cancer risk in white women promises modest improvements in discriminatory power compared with the Gail model but needs to be validated with independent data.

Randomized double-blind factorial trial of three treatments to reduce the prevalence of precancerous gastric lesions.

BACKGROUND: Randomized trials have yielded mixed results on the effects of treatment for Helicobacter pylori and little information on the effects of vitamins or garlic supplements on precancerous gastric lesions. We conducted a randomized trial to test the effects of one-time H. pylori treatment and long-term vitamin or garlic supplements in reducing the prevalence of advanced precancerous gastric lesions. METHODS: Most of the adults aged 35-64 years in 13 randomly selected villages in Linqu County, Shandong Province, China, were identified and given baseline endoscopies in 1994. In 1995, 3365 eligible subjects were randomly assigned in a factorial design to three interventions or placebos: amoxicillin and omeprazole for 2 weeks in 1995 (H. pylori treatment); vitamin C, vitamin E, and selenium for 7.3 years (vitamin supplement); and aged garlic extract and steam-distilled garlic oil for 7.3 years (garlic supplement). Subjects underwent endoscopies with biopsies in 1999 and 2003, and the prevalence of precancerous gastric lesions was determined by histopathologic examination of seven standard biopsy sites. The 3365 eligible randomized subjects represented 93.5% of those with baseline endoscopy and included all baseline histologic categories except gastric cancer. Only 0.18% had normal gastric mucosa. Logistic regression was used to estimate the intervention effects on the odds of advanced precancerous gastric lesions, and t-tests were used to assess effects on histologic severity. All statistical tests were two-sided. RESULTS: H. pylori treatment resulted in statistically significant decreases in the combined prevalence of severe chronic atrophic gastritis, intestinal metaplasia, dysplasia, or gastric cancer in 1999 (odds ratio [OR] = 0.77; 95% confidence interval [CI] = 0.62 to 0.95) and in 2003 (OR = 0.60; 95% CI = 0.47 to 0.75), and had favorable effects on the average histopathologic severity and on progression and regression of precancerous gastric lesions in 2003. H. pylori treatment did not reduce the combined prevalence of dysplasia or gastric cancer. However, fewer subjects receiving H. pylori treatment (19/1130; 1.7%) than receiving placebo (27/1128; 2.4%) developed gastric cancer (adjusted P = .14). No statistically significant favorable effects were seen for garlic or vitamin supplements. CONCLUSION: H. pylori treatment reduces the prevalence of precancerous gastric lesions and may reduce gastric cancer incidence, but further data are needed to prove the latter point. Long-term vitamin or garlic supplementation had no beneficial effects on the prevalence of precancerous gastric lesions or on gastric cancer incidence.

A case-cohort design for assessing covariate effects in longitudinal studies.

The case-cohort design for longitudinal data consists of a subcohort sampled at the beginning of the study that is followed repeatedly over time, and a case sample that is ascertained through the course of the study. Although some members in the subcohort may experience events over the study period, we refer to it as the "control-cohort." The case sample is a random sample of subjects not in the control-cohort, who have experienced at least one event during the study period. Different correlations among repeated observations on the same individual are accommodated by a two-level random-effects model. This design allows consistent estimation of all parameters estimable in a cohort design and is a cost-effective way to study the effects of covariates on repeated observations of relatively rare binary outcomes when exposure assessment is expensive. It is an extension of the case-cohort design (Prentice, 1986, Biometrika73, 1-11) and the bidirectional case-crossover design (Navidi, 1998, Biometrics54, 596-605). A simulation study compares the efficiency of the longitudinal case-cohort design to a full cohort analysis, and we find that in certain situations up to 90% efficiency can be obtained with half the sample size required for a full cohort analysis. A bootstrap method is presented that permits testing for intra-subject homogeneity in the presence of unidentifiable nuisance parameters in the two-level random-effects model. As an illustration we apply the design to data from an ongoing study of childhood asthma.