Using multiple risk models with preventive interventions

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 and 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-specific and race-specific rates were considered for other health outcomes, but not risk models. In this paper, we 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.

Efficient adaptively weighted analysis of secondary phenotypes in case-control genome-wide association studies

We propose and compare methods of analysis for detecting associations between genotypes of a single nucleotide polymorphism (SNP) and a dichotomous secondary phenotype (X), when the data arise from a case-control study of a primary dichotomous phenotype (D), which is not rare. We considered both a dichotomous genotype (G) as in recessive or dominant models and an additive genetic model based on the number of minor alleles present. To estimate the log odds ratio β(1) relating X to G in the general population, one needs to understand the conditional distribution [D ∣ X, G] in the general population. For the most general model, [D ∣ X, G], one needs external data on P(D = 1) to estimate β(1). We show that for this 'full model', the maximum likelihood (FM) corresponds to a previously proposed weighted logistic regression (WL) approach if G is dichotomous. For the additive model, WL yields results numerically close, but not identical, to those of the maximum likelihood FM. Efficiency can be gained by assuming that [D ∣ X, G] is a logistic model with no interaction between X and G (the 'reduced model'). However, the resulting maximum likelihood (RM) can be misleading in the presence of interactions. We therefore propose an adaptively weighted approach (AW) that captures the efficiency of RM but is robust to the occasional SNP that might interact with the secondary phenotype to affect the risk of the primary disease. We study the robustness of FM, WL, RM and AW to misspecification of P(D = 1). In principle, one should be able to estimate β(1) without external information on P(D = 1) under the reduced model. However, our simulations show that the resulting inference is unreliable. Therefore, in practice one needs to introduce external information on P(D = 1), even in the absence of interactions between X and G.

Potential usefulness of single nucleotide polymorphisms to identify persons at high cancer risk: an evaluation of seven common cancers

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.

Abstract 5489: Feasibility study of gut microbiome collection in randomly sampled women

Systemic estrogen level strongly determines risk for postmenopausal breast cancer (BC). We hypothesize that differences in hormone metabolism by the gut microbiota may contribute to BC risk by modulating enterohepatic circulation of estrogens. We conducted a study to determine the feasibility of enrolling healthy postmenopausal members of Kaiser Permanente Colorado (KPCO) in a fecal microbiome study. With electronic medical records, we created a pool of potentially eligible women aged 55-69 who recently had a negative screening mammogram. We excluded those with any hormone prescription in the prior 12 months, an antibiotic prescription in the prior 6 months, or history of cancer, inflammatory bowel disease or other conditions likely to affect fecal microbiota. A packet (invitation letter, informed consent form, information pamphlet, and opt-out postcard) was sent to 250 randomly sampled women. Women who have not returned the postcard are contacted by KPCO research staff to determine interest in participating, verify eligibility, and obtain verbal informed consent. Consented participants were mailed a second packet with a self-administered risk factor questionnaire, link to an on-line diet questionnaire, collection kit for urine (to measure 15 estrogens) and stool specimens, and shipping instructions to the laboratory. Enrollees have spent an estimated 1-2 hours completing all recruitment and data collection components. To date, 60 (24%) have enrolled, 70 (28%) refused (most via the opt-out card), and the remainder are pending phone contact. As shown in the table, the enrolled women are similar to the total sample; slightly more of them are non-Hispanic white, and they are more likely to have a history of breast biopsy. These data demonstrate that we can successfully recruit an apparently representative sample of women into a microbiome study.

Piecewise exponential survival times and analysis of case-cohort data

Case-cohort designs select a random sample of a cohort to be used as control with cases arising from the follow-up of the cohort. Analyses of case-cohort studies with time-varying exposures that use Cox partial likelihood methods can be computer intensive. We propose a piecewise-exponential approach where Poisson regression model parameters are estimated from a pseudolikelihood and the corresponding variances are derived by applying Taylor linearization methods that are used in survey research. The proposed approach is evaluated using Monte Carlo simulations. An illustration is provided using data from the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study of male smokers in Finland, where a case-cohort study of serum glucose level and pancreatic cancer was analyzed.

Association between BRCA1 and BRCA2 mutations and survival in women with invasive epithelial ovarian cancer

CONTEXT

Approximately 10% of women with invasive epithelial ovarian cancer (EOC) carry deleterious germline mutations in BRCA1 or BRCA2. A recent article 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 with noncarriers and to determine whether BRCA1 and BRCA2 carriers show similar survival patterns.

DESIGN, SETTING, AND PARTICIPANTS

A pooled analysis of 26 observational studies on the survival of women with ovarian cancer, which included data from 1213 EOC cases with pathogenic germline mutations in BRCA1 (n = 909) or BRCA2 (n = 304) and from 2666 noncarriers recruited and followed up at variable times between 1987 and 2010 (the median year of diagnosis was 1998).

MAIN OUTCOME MEASURE

Five-year overall mortality.

RESULTS

The 5-year overall survival was 36% (95% CI, 34%-38%) for noncarriers, 44% (95% CI, 40%-48%) for BRCA1 carriers, and 52% (95% CI, 46%-58%) for BRCA2 carriers. After adjusting for study and year of diagnosis, BRCA1 and BRCA2 mutation carriers showed a more favorable survival than noncarriers (for BRCA1: hazard ratio [HR], 0.78; 95% CI, 0.68-0.89; P < .001; and for BRCA2: HR, 0.61; 95% CI, 0.50-0.76; P < .001). These survival differences remained after additional adjustment for stage, grade, histology, and age at diagnosis (for BRCA1: HR, 0.73; 95% CI, 0.64-0.84; P < .001; and for BRCA2: HR, 0.49; 95% CI, 0.39-0.61; P < .001). The BRCA1 HR estimate was significantly different from the HR estimated in the adjusted model (P for heterogeneity = .003).

CONCLUSION

Among patients with invasive EOC, having a germline mutation in BRCA1 or BRCA2 was associated with improved 5-year overall survival. BRCA2 carriers had the best prognosis.

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).

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.

Predicting the absolute risk of dying from colorectal cancer and from other causes using population-based cancer registry data

This paper describes how population cancer registry data from the Surveillance, Epidemiology, and End Results program of the National Cancer Institute can be used to develop a prognostic model to predict the absolute risk of mortality from cancer and from other causes for an individual with specific covariates. It incorporates previously developed methods for competing risk modeling along with an imputation method to address missing cause of death information. We illustrate these approaches with colorectal cancer and evaluate the model discriminatory and calibration accuracy by time-dependent area under the receiver operating characteristic curve and calibration plot.

Evaluating breast cancer risk projections for Hispanic women

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.

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.

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.

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.

Personalized estimates of breast cancer risk in clinical practice and public health

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 predicts 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.

Benefit/risk assessment for breast cancer chemoprevention with raloxifene or tamoxifen for women age 50 years or older

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.

Abstract 3717: Evaluation and comparison of breast cancer risk prediction models for Hispanic and non-Hispanic white women in the Women's Health Initiative

Introduction: The National Cancer Institute (NCI) Breast Cancer Risk Assessment Tool (BCRAT) has not been previously validated for use in Hispanic women. We evaluated and compared BCRAT risk projections for Hispanic and non-Hispanic White (NHW) participants in the Women's Health Initiative (WHI).

Methods: We used data on 6,248 Hispanic and 127,426 NHW post-menopausal WHI participants aged 50 years and older. Absolute risks of developing invasive breast cancer over the WHI main and extension studies were calculated using the BCRAT and an updated BCRAT using 1993-2007 SEER breast cancer incidence rates. We assessed model calibration by the ratio of observed to expected number of breast cancers (O/E ratio) and discriminatory accuracy with the concordance statistic (c-statistic).

Results: In the WHI main study, the BCRAT underestimated the number of breast cancers in Hispanics (O/E ratio=1.18, 95% CI = 0.99, 1.40) and NHWs (O/E ratio=1.18, 95% CI = 1.14, 1.21). The updated BCRAT was well calibrated for Hispanics (O/E ratio=1.08, 95% CI = 0.91, 1.28) and NHWs (O/E ratio=0.98, 95% CI = 0.96, 1.01). The c-statistic was 0.629 (95% CI = 0.582, 0.676) for Hispanics and 0.575 (95%CI = 0.566, 0.583] for NHWs. In the WHI extension study, where women reported being screened less frequently, BCRAT overestimated risk in both Hispanics and NHWs.

Conclusion: Underestimation of breast cancer risk by the BCRAT in Hispanic and NHW women was corrected by using updated SEER breast cancer incidence rates. Recalibrating the BCRAT with current SEER incidence rates and racial/ethnic specific relative risk estimates may improve the predictive accuracy for Hispanic women.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3717. doi:10.1158/1538-7445.AM2011-3717

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; P(trend) < .001), whereas non-AIDS-defining cancers increased by approximately threefold (3193 to 10,059 cancers; P(trend) < .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.

Postdiagnosis diet quality, the combination of diet quality and recreational physical activity, and prognosis after early-stage breast cancer

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 (HR(Q4:Q1): 0.40, 95% CI: 0.17, 0.94) and an 88% reduced risk of death from breast cancer (HR(Q4: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.

Two criteria for evaluating risk prediction models

We propose and study two criteria to assess the usefulness of models that predict risk of disease incidence for screening and prevention, or the usefulness of prognostic models for management following disease diagnosis. The first criterion, the proportion of cases followed PCF (q), is the proportion of individuals who will develop disease who are included in the proportion q of individuals in the population at highest risk. The second criterion is the proportion needed to follow-up, PNF (p), namely the proportion of the general population at highest risk that one needs to follow in order that a proportion p of those destined to become cases will be followed. PCF (q) assesses the effectiveness of a program that follows 100q% of the population at highest risk. PNF (p) assess the feasibility of covering 100p% of cases by indicating how much of the population at highest risk must be followed. We show the relationship of those two criteria to the Lorenz curve and its inverse, and present distribution theory for estimates of PCF and PNF. We develop new methods, based on influence functions, for inference for a single risk model, and also for comparing the PCFs and PNFs of two risk models, both of which were evaluated in the same validation data.

Using cases to strengthen inference on the association between single nucleotide polymorphisms and a secondary phenotype in genome-wide association studies

Case-control genome-wide association studies provide a vast amount of genetic information that may be used to investigate secondary phenotypes. We study the situation in which the primary disease is rare and the secondary phenotype and genetic markers are dichotomous. An analysis of the association between a genetic marker and the secondary phenotype based on controls only (CO) is valid, whereas standard methods that also use cases result in biased estimates and highly inflated type I error if there is an interaction between the secondary phenotype and the genetic marker on the risk of the primary disease. Here we present an adaptively weighted (AW) method that combines the case and control data to study the association, while reducing to the CO analysis if there is strong evidence of an interaction. The possibility of such an interaction and the misleading results for standard methods, but not for the AW or CO approaches, are illustrated by data from a case-control study of colorectal adenoma. Simulations and asymptotic theory indicate that the AW method can reduce the mean square error for estimation with a prespecified SNP and increase the power to discover a new association in a genome-wide study, compared to CO analysis. Further experience with genome-wide studies is needed to determine when methods that assume no interaction gain precision and power, thereby can be recommended, and when methods such as the AW or CO approaches are needed to guard against the possibility of nonzero interactions.

Long-term survival among patients with Hodgkin's lymphoma who developed breast cancer: a population-based study

PURPOSE

The increased risk of breast cancer (BC) among women receiving chest radiotherapy for Hodgkin's lymphoma (HL) is well-established. However, there are no large population-based studies that describe overall survival (OS) and cause-specific survival (CSS) compared with women with first primary BC.

METHODS

For 298 HL survivors who developed BC (HL-BC group) and 405,223 women with a first or only BC (BC-1 group), actuarial OS and CSS were compared, accounting for age, BC stage, hormone receptor status, sociodemographic status, radiation for HL, and other variables. All patients were derived from the population-based Surveillance, Epidemiology, and End Results program.

RESULTS

OS among patients with HL-BC was significantly inferior that of to patients with BC-1: 15-year OS was 48% versus 69% (P < .0001) for localized BC, and 33% versus 43% (P < .0001) for regional/distant BC. Patients with HL-BC had a significantly increased seven-fold risk (P < .0001) of death from other cancers (ie, not HL or BC) compared with patients with BC-1. Mortality from heart disease among patients with HL-BC with either localized or regional/distant disease was also significantly increased (hazard ratio = 2.22, P = .04; and hazard ratio = 4.28, P = .02, respectively) compared with patients with BC-1. Although 10-year BC-CSS was similar for patients with HL-BC and BC-1 with regional/distant disease, it was inferior for patients with localized BC (82% v 88%, respectively; P = .002).

CONCLUSION

Women with HL may survive a subsequent diagnosis of BC, only to experience significant excesses of death from other primary cancers and cardiac disease. Greater awareness of screening for cardiac disease and subsequent primary cancers in patients with HL-BC is warranted.

Five-year and lifetime risk of breast cancer among U.S. subpopulations: implications for magnetic resonance imaging screening

BACKGROUND

Guidelines from the American Cancer Society recommend annual breast magnetic resonance imaging (MRI) screening for women with a projected lifetime risk of ≥20% based on risk models that use family history. Because MRI screening is costly and has limited specificity, estimates of the numbers of U.S. women with ≥20% breast cancer risk would be useful.

METHODS

We used data from the 2000 and 2005 National Health Interview Survey and the National Cancer Institute (NCI) Breast Cancer Risk Assessment Tool (i.e., Gail model 2 with a revision for African Americans) to calculate estimates of U.S. women by age and race/ethnicity categories with a lifetime absolute breast cancer risk of ≥20%. Distributions of 5-year and lifetime absolute risk of breast cancer were compared across demographic groups.

RESULTS

We estimated that 1.09% (95% confidence interval, 0.95-1.24%) of women age 30 to 84 years have a lifetime absolute breast cancer risk of ≥20%, which translates to 880,063 U.S. women eligible for MRI screening. The 5-year risks are highest for white non-Hispanics and lowest for Hispanics. The lifetime risks decrease with age and are generally highest for white non-Hispanics, lower for African American non-Hispanic, and lowest for Hispanics.

CONCLUSION

We provide national estimates of the number of U.S. women who would be eligible for MRI breast screening and distributions of 5-year and lifetime risks of breast cancer using the NCI Breast Cancer Risk Assessment Tool.

IMPACT

These estimates inform the potential resources and public health demand for MRI screening and chemopreventive interventions that might be required for U.S. women.