Showing papers by "Ross L. Prentice published in 2010"

Estrogen plus progestin and breast cancer incidence and mortality in postmenopausal women

Abstract: Context In the Women's Health Initiative randomized, placebo-controlled trial of estrogen plus progestin, after a mean intervention time of 5.6 (SD, 1.3) years (range, 3.7-8.6 years) and a mean follow-up of 7.9 (SD, 1.4) years, breast cancer incidence was increased among women who received combined hormone therapy. Breast cancer mortality among participants in the trial has not been previously reported. Objective To determine the effects of therapy with estrogen plus progestin on cumulative breast cancer incidence and mortality after a total mean follow-up of 11.0 (SD, 2.7) years, through August 14, 2009. Design, Setting, and Participants A total of 16 608 postmenopausal women aged 50 to 79 years with no prior hysterectomy from 40 US clinical centers were randomly assigned to receive combined conjugated equine estrogens, 0.625 mg/d, plus medroxyprogesterone acetate, 2.5 mg/d, or placebo pill. After the original trial completion date (March 31, 2005), reconsent was required for continued follow-up for breast cancer incidence and was obtained from 12 788 (83%) of the surviving participants. Main Outcome Measures Invasive breast cancer incidence and breast cancer mortality. Results In intention-to-treat analyses including all randomized participants and censoring those not consenting to additional follow-up on March 31, 2005, estrogen plus progestin was associated with more invasive breast cancers compared with placebo (385 cases [0.42% per year] vs 293 cases [0.34% per year]; hazard ratio [HR], 1.25; 95% confidence interval [CI], 1.07-1.46; P = .004). Breast cancers in the estrogen-plus-progestin group were similar in histology and grade to breast cancers in the placebo group but were more likely to be node-positive (81 [23.7%] vs 43 [16.2%], respectively; HR, 1.78; 95% CI, 1.23-2.58; P = .03). There were more deaths directly attributed to breast cancer (25 deaths [0.03% per year] vs 12 deaths [0.01% per year]; HR, 1.96; 95% CI, 1.00-4.04; P = .049) as well as more deaths from all causes occurring after a breast cancer diagnosis (51 deaths [0.05% per year] vs 31 deaths [0.03% per year]; HR, 1.57; 95% CI, 1.01-2.48; P = .045) among women who received estrogen plus progestin compared with women in the placebo group. Conclusions Estrogen plus progestin was associated with greater breast cancer incidence, and the cancers are more commonly node-positive. Breast cancer mortality also appears to be increased with combined use of estrogen plus progestin. Trial Registration clinicaltrials.gov Identifier: NCT00000611

Performance of Common Genetic Variants in Breast-Cancer Risk Models

Abstract: Background Genomewide association studies have identified multiple genetic variants associated with breast cancer. The extent to which these variants add to existing risk-assessment models is unknown. Methods We used information on traditional risk factors and 10 common genetic variants associated with breast cancer in 5590 case subjects and 5998 control subjects, 50 to 79 years of age, from four U.S. cohort studies and one case–control study from Poland to fit models of the absolute risk of breast cancer. With the use of receiver-operating-characteristic curve analysis, we calculated the area under the curve (AUC) as a measure of discrimination. By definition, random classification of case and control subjects provides an AUC of 50%; perfect classification provides an AUC of 100%. We calculated the fraction of case subjects in quintiles of estimated absolute risk after the addition of genetic variants to the traditional risk model. Results The AUC for a risk model with age, study and entry year, and four...

Assessment of Clinical Validity of a Breast Cancer Risk Model Combining Genetic and Clinical Information

Abstract: Background The Gail model is widely used for the assessment of risk of invasive breast cancer based on recognized clinical risk factors. In recent years, a substantial number of single-nucleotide polymorphisms (SNPs) associated with breast cancer risk have been identified. However, it remains unclear how to effectively integrate clinical and genetic risk factors for risk assessment.

Insights into Colon Cancer Etiology via a Regularized Approach to Gene Set Analysis of GWAS Data

Abstract: Genome-wide association studies (GWAS) have successfully identified susceptibility loci from marginal association analysis of SNPs. Valuable insight into genetic variation underlying complex diseases will likely be gained by considering functionally related sets of genes simultaneously. One approach is to further develop gene set enrichment analysis methods, which are initiated in gene expression studies, to account for the distinctive features of GWAS data. These features include the large number of SNPs per gene, the modest and sparse SNP associations, and the additional information provided by linkage disequilibrium (LD) patterns within genes. We propose a "gene set ridge regression in association studies (GRASS)" algorithm. GRASS summarizes the genetic structure for each gene as eigenSNPs and uses a novel form of regularized regression technique, termed group ridge regression, to select representative eigenSNPs for each gene and assess their joint association with disease risk. Compared with existing methods, the proposed algorithm greatly reduces the high dimensionality of GWAS data while still accounting for multiple hits and/or LD in the same gene. We show by simulation that this algorithm performs well in situations in which there are a large number of predictors compared to sample size. We applied the GRASS algorithm to a genome-wide association study of colon cancer and identified nicotinate and nicotinamide metabolism and transforming growth factor beta signaling as the top two significantly enriched pathways. Elucidating the role of variation in these pathways may enhance our understanding of colon cancer etiology.

Alcohol Consumption and Risk of Postmenopausal Breast Cancer by Subtype: The Women's Health Initiative Observational Study

Abstract: The study sponsor, National Heart, Lung, and Blood Institute (NHLBI), was not involved in the design of the analysis described here, in the interpretation of the data, in the writing of the article, or in the decision to submit this article for publication. The authors acknowledge the contributions of the following WHI investigators: Program Office: (NHLBI, Bethesda, MD) Elizabeth Nabel, Jacques Rossouw, Shari Ludlam, Joan McGowan, Leslie Ford, and Nancy Geller. Clinical Coordinating Center: Garnet Anderson, Andrea LaCroix, Charles L. Kooperberg, Ruth E. Patterson, and Anne McTiernan (Fred Hutchinson Cancer Research Center, Seattle, WA); Evan Stein (Medical Research Labs, Highland Heights, KY); Steven Cummings (University of California at San Francisco, San Francisco, CA). Clinical Centers: Sylvia Wassertheil-Smoller (Albert Einstein College of Medicine, Bronx, NY); Aleksandar Rajkovic (Baylor College of Medicine, Houston, TX); JoAnn E. Manson (Brigham and Women's Hospital, Harvard Medical School, Boston, MA); Charles B. Eaton (Brown University, Providence, RI); Lawrence Phillips (Emory University, Atlanta, GA); Shirley A. A. Beresford (Fred Hutchinson Cancer Research Center, Seattle, WA); Lisa Martin (George Washington University Medical Center, Washington, DC); Yvonne Michael (Kaiser Permanente Center for Health Research, Portland, OR); Bette Caan (Kaiser Permanente Division of Research, Oakland, CA); Jane Morley Kotchen (Medical College of Wisconsin, Milwaukee, WI); Barbara V. Howard (MedStar Research Institute and Howard University, Washington, DC); Linda Van Horn (Northwestern University, Chicago and Evanston, IL); Henry Black (Rush Medical Center, Chicago, IL); Marcia L. Stefanick (Stanford Prevention Research Center, Stanford, CA); Rebecca Jackson (Ohio State University, Columbus, OH); Cora E. Lewis (University of Alabama at Birmingham, Birmingham, AL); Cynthia A Thomson (University of Arizona, Tucson and Phoenix, AZ); John Robbins (University of California at Davis, Sacramento, CA); F. Allan Hubbell (University of California at Irvine, CA); Lauren Nathan (University of California at Los Angeles, Los Angeles, CA); Robert D. Langer (University of California at San Diego, LaJolla and Chula Vista, CA); Margery Gass (University of Cincinnati, Cincinnati, OH) ; Marian Limacher (University of Florida, Gainesville and Jacksonville, FL); J. David Curb (University of Hawaii, Honolulu, HI); Robert Wallace (University of Iowa, Iowa City/Davenport, IA); Judith Ockene (University of Massachusetts and Fallon Clinic, Worcester, MA); Norman Lasser (University of Medicine and Dentistry of New Jersey, Newark, NJ); Karen Margolis (University of Minnesota, Minneapolis, MN); Robert Brunner (University of Nevada, Reno, NV); Gerardo Heiss (University of North Carolina, Chapel Hill, NC); Robert Brzyski (University of Texas Health Science Center, San Antonio, TX); Gloria E. Sarto (University of Wisconsin, Madison, WI); Mara Vitolins (Wake Forest University School of Medicine, Winston-Salem, NC); Michael Simon (Wayne State University School of Medicine, Hutzel Hospital, Detroit, MI).

Minimizing bias in randomized trials: the importance of blinding.

Abstract: IN 1992, HANSSON ET AL 1 PROPOSED A NOVEL DESIGN, THE prospective randomized open trial with blinded endpoint assessments. The lack of blinding of investigators and patients simplified the conduct of the trial, which would become more similar to routine medical practice than the blinded design. The use of blinding for the adjudication of outcomes would preserve the benefits of a fully blinded trial. A number of trials have used this design to evaluate antihypertensive agents and more recently antidiabetic agents. These trials were thought to produce valid and, perhaps, more generalizable results. Studies of trial results for specific classes of treatments support the importance of investigator blinding. In a crosssectional analysis of 192 trials that compared a statin drug with another statin or a nonstatin drug, the studies that described adequate blinding were much less likely to report findings that favored the test drug than studies that did not describe adequate blinding (odds ratio, 0.41; 95% confidence interval [CI], 0.23-0.73). Hence, it is important to evaluate whether the absence of investigator blinding may have influenced the results of specific important trials. The Rosiglitazone Evaluated for Cardiac Outcomes and Regulation of Glycemia in Diabetes (RECORD) trial, for instance, was an open-label trial that enrolled patients with type 2 diabetes who were taking either metformin or a sulfonylurea and randomized them to receive either rosiglitazone or the combination of metformin plus a sulfonylurea. The trial met the noninferiority criterion for the primary outcome of cardiovascular hospitalization or death. Moreover, rosiglitazone was not significantly associated with the risk of myocardial infarction (MI) (hazard ratio, 1.14; 95% CI, 0.80-1.63), a concern that had been raised by an earlier meta-analysis. However, event rates in the control group were unexpectedly low in this open trial with blinded end-point assessment. The independent review by the US Food and Drug Administration (FDA) of case-report forms from the RECORD trial by Marciniak has provided empirical estimates of the potential bias associated with an open-label design when, in an industry-sponsored trial setting, investigators were aware of the treatment assignment. Of the 2220 patients randomized to rosiglitazone, case-report forms were reviewed for 278 (12.5%). Of the 2227 patients randomized to control, case-report forms were reviewed for 271 (12.2%). The review included a random sample of 100 case-report forms plus others that were targeted because they might have represented problems. In general, the blinding of the eventrelated material sent to the end-points committee was good. Among the 549 case-report forms, however, Marciniak identified 70 problem cases (12.8%). These 70 problem cases included events that were missed (n=14), ascertained events that were not referred for adjudication (n=8), cases that had insufficient information (n=18), and other adjudication issues (n=22). Based on the random sample, he estimated that if all the case-report forms had been re-reviewed, a total of 283 problem cases would have been identified. The appendix of Marciniak’s report (see summary, page 92) provides details about the problem case-report forms in the RECORD trial. For instance, one patient had an MI that was not referred for adjudication (case A). Hospitalization of another patient for pulmonary edema was not adjudicated (case B). Another patient with intracerebral hematoma presented with a seizure, but information about the intracerebral hematoma was deleted from the case-report form and replaced with epilepsy; the dossier was not sent for adjudication (case C). Information was not obtained about a long hospitalization for a severe stroke (case D), and the event was labeled as noncardiovascular. Errors occur in all studies, and insofar as they are nondifferential between treatment groups, they may not systematically bias hazard ratios or other summary measures although precision will be reduced. The FDA review, however, provides evidence of differential outcome ascertainment by treatment group in the RECORD trial (TABLE). Among the 549 case-report forms, the prevalence of problem cases was higher in the rosiglitazone group (16.2%) than in the control group (9.2%). Marciniak also classified the problem cases according to the group that had been favored by the error

Improved Logrank-Type Tests for Survival Data Using Adaptive Weights

Abstract: For testing for treatment effects with time-to-event data, the logrank test is the most popular choice and has some optimality properties under proportional hazards alternatives. It may also be combined with other tests when a range of nonproportional alternatives are entertained. We introduce some versatile tests that use adaptively weighted logrank statistics. The adaptive weights utilize the hazard ratio obtained by fitting the model of Yang and Prentice (2005, Biometrika 92, 1-17). Extensive numerical studies have been performed under proportional and nonproportional alternatives, with a wide range of hazard ratios patterns. These studies show that these new tests typically improve the tests they are designed to modify. In particular, the adaptively weighted logrank test maintains optimality at the proportional alternatives, while improving the power over a wide range of nonproportional alternatives. The new tests are illustrated in several real data examples.

Novel proteins associated with risk for coronary heart disease or stroke among postmenopausal women identified by in-depth plasma proteome profiling

Abstract: Coronary heart disease (CHD) and stroke were key outcomes in the Women's Health Initiative (WHI) randomized trials of postmenopausal estrogen and estrogen plus progestin therapy. We recently reported a large number of changes in blood protein concentrations in the first year following randomization in these trials using an in-depth quantitative proteomics approach. However, even though many affected proteins are in pathways relevant to the observed clinical effects, the relationships of these proteins to CHD and stroke risk among postmenopausal women remains substantially unknown. The same in-depth proteomics platform was applied to plasma samples, obtained at enrollment in the WHI Observational Study, from 800 women who developed CHD and 800 women who developed stroke during cohort follow-up, and from 1-1 matched controls. A plasma pooling strategy, followed by extensive fractionation prior to mass spectrometry, was used to identify proteins related to disease incidence, and the overlap of these proteins with those affected by hormone therapy was examined. Replication studies, using enzyme-linked-immunosorbent assay (ELISA), were carried out in the WHI hormone therapy trial cohorts. Case versus control concentration differences were suggested for 37 proteins (nominal P < 0.05) for CHD, with three proteins, beta-2 microglobulin (B2M), alpha-1-acid glycoprotein 1 (ORM1), and insulin-like growth factor binding protein acid labile subunit (IGFALS) having a false discovery rate < 0.05. Corresponding numbers for stroke were 47 proteins with nominal P < 0.05, three of which, apolipoprotein A-II precursor (APOA2), peptidyl-prolyl isomerase A (PPIA), and insulin-like growth factor binding protein 4 (IGFBP4), have a false discovery rate < 0.05. Other proteins involved in insulin-like growth factor signaling were also highly ranked. The associations of B2M with CHD (P < 0.001) and IGFBP4 with stroke (P = 0.005) were confirmed using ELISA in replication studies, and changes in these proteins following the initiation of hormone therapy use were shown to have potential to help explain hormone therapy effects on those diseases. In-depth proteomic discovery analysis of prediagnostic plasma samples identified B2M and IGFBP4 as risk markers for CHD and stroke respectively, and provided a number of candidate markers of disease risk and candidate mediators of hormone therapy effects on CHD and stroke. ClinicalTrials.gov identifier: NCT00000611

Characterization of the association between 8q24 and colon cancer: gene-environment exploration and meta-analysis

Abstract: Background Genome-wide association studies and subsequent replication studies have shown that single nucleotide polymorphisms (SNPs) in the chromosomal region 8q24 are associated with colorectal cancer susceptibility.

The effects of postmenopausal hormone therapy on serum estrogen, progesterone, and sex hormone-binding globulin levels in healthy postmenopausal women

Abstract: Objective Differences in disease outcomes between users and nonusers of hormone therapy (HT) and between users of estrogen therapy (ET) and users of estrogen + progesterone therapy (EPT) may relate to differences in serum hormone concentrations between these populations. In this study, we examined the response of serum hormone levels in healthy postmenopausal women after 1 year of HT. Methods A representative subsample of 200 healthy adherent participants from the active and placebo groups of the Women's Health Initiative randomized controlled clinical trials of ET (conjugated equine estrogens 0.625 mg daily) or EPT (ET plus medroxyprogesterone acetate 2.5 mg daily) were selected for the determination of selected sex hormone levels at baseline and 1 year after randomization. Results In participants receiving active ET intervention compared with placebo, estrogenic hormone levels increased from baseline to year 1 by 3.6-fold for total estrone, 2.7-fold for total estradiol, and 1.8-fold for bioavailable and free estradiol concentrations. Serum sex hormone-binding globulin concentrations also increased 2.5-fold. In contrast, progesterone levels decreased slightly in women taking exogenous EPT. The response of serum estrogens and sex hormone-binding globulin did not differ substantially with the addition of progesterone. In subgroup analyses, hormone response varied by age, ethnicity, body mass index, smoking status, vasomotor symptoms, and baseline hormone levels. Conclusions These data provide a reference point for the serum hormone response to HT and demonstrate that the response of serum estrogens is similar for ET and EPT. The implications of the slight decrease in serum progesterone levels with EPT therapy are uncertain. Potential treatment interactions for estrogenic hormones were identified, which suggest a larger response to HT in women with low endogenous levels.

Migraine History and Breast Cancer Risk Among Postmenopausal Women

Abstract: Purpose Both migraine and breast cancer are hormonally mediated. Two recent reports indicate that women with a migraine history may have a lower risk of postmenopausal breast cancer than those who never suffered migraines. This finding requires confirmation; in particular, an assessment of the influence of use of nonsteroidal anti-inflammatory drugs (NSAID) is needed, because many studies indicate that NSAID use also may confer a reduction in breast cancer risk. Methods We assessed the relationship between self-reported history of migraine and incidence of postmenopausal breast cancer in 91,116 women enrolled on the Women's Health Initiative Observational Study prospective cohort from 1993 to 1998 at ages 50 to 79 years. Through September 15, 2005, there were 4,006 eligible patients with breast cancer diagnosed. Results Women with a history of migraine had a lower risk of breast cancer (hazard ratio [HR], 0.89; 95% CI, 0.80 to 98) than women without a migraine history. This risk did not vary by recent NSA...

Detection of Elevated Plasma Levels of Epidermal Growth Factor Receptor Before Breast Cancer Diagnosis among Hormone Therapy Users

Abstract: Applying advanced proteomic technologies to prospectively collected specimens from large studies is one means of identifying preclinical changes in plasma proteins that are potentially relevant to the early detection of diseases such as breast cancer. We conducted 14 independent quantitative proteomics experiments comparing pooled plasma samples collected from 420 estrogen receptor-positive (ER(+)) breast cancer patients ≤17 months before their diagnosis and matched controls. Based on the more than 3.4 million tandem mass spectra collected in the discovery set, 503 proteins were quantified, of which 57 differentiated cases from controls with a P value of <0.1. Seven of these proteins, for which quantitative ELISA assays were available, were assessed in an independent validation set. Of these candidates, epidermal growth factor receptor (EGFR) was validated as a predictor of breast cancer risk in an independent set of preclinical plasma samples for women overall [odds ratio (OR), 1.44; P = 0.0008] and particularly for current users of estrogen plus progestin (E + P) menopausal hormone therapy (OR, 2.49; P = 0.0001). Among current E + P users, the EGFR sensitivity for breast cancer risk was 31% with 90% specificity. Whereas the sensitivity and specificity of EGFR are insufficient for a clinically useful early detection biomarker, this study suggests that proteins that are elevated preclinically in women who go on to develop breast cancer can be discovered and validated using current proteomic technologies. Further studies are warranted to examine the role of EGFR and to discover and validate other proteins that could potentially be used for early detection of breast cancer.

Characterization of 9p24 risk locus and colorectal adenoma and cancer: gene-environment interaction and meta-analysis

Abstract: Background: A potential susceptibility locus for colorectal cancer on chromosome 9p24 (rs719725) was initially identified through a genome-wide association study, though replication attempts have been inconclusive. Methods:Wegenotypedthislocusandexploredinteractions withknownriskfactorsaspotential sourcesof heterogeneity, which may explain the previously inconsistent replication. We included Caucasians with colorectal adenoma or colorectal cancer and controls from 4 studies (total 3,891 cases, 4,490 controls): the Women’s Health Initiative (WHI); the Diet, Activity and Lifestyle Study (DALS); a Minnesota populationbased case–control study (MinnCCS); and the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO). We used logistic regression to evaluate the association and test for gene–environment interactions. Results: SNP rs719725 was statistically significantly associated with risk of colorectal cancer in WHI (OR perAallele 1.19; 95% CI, 1.01–1.40;Ptrend ¼0.04), marginally associated with adenoma risk in PLCO (OR perA allele 1.11; 95% CI, 0.99–1.25; Ptrend ¼ 0.07), and not associated in DALS and MinnCCS. Evaluating for gene– environment interactions yielded no consistent results across the studies. A meta-analysis of 17 studies (including these 4) gave an OR per A allele of 1.07 (95% CI, 1.03–1.12; Ptrend ¼ 0.001). Conclusions: Our results suggest the A allele for SNP rs719725 at locus 9p24 is positively associated with a small increase in risk for colorectal tumors. Environmental risk factors for colorectal cancer do not appear to explain heterogeneity across studies. Impact: If this finding is supported by further replication and functional studies, it may highlight new pathways underlying colorectal neoplasia. Cancer Epidemiol Biomarkers Prev; 19(12); 3131–9. � 2010 AACR.

Dietary Assessment and the Reliability of Nutritional Epidemiology Research Reports

Abstract: It is a pleasure to comment on the valuable article by Dahm et al. (1) in this issue of the Journal and to provide my perspective on research needs and opportunities for progress in the challenging nutritional epidemiology research area. In doing so, I would like to first offer a tribute to the late Dr Sheila Rodwell (Bingham), senior author of the article by Dahm et al. For some decades, Dr Bingham provided cutting-edge research on nutritional biomarkers and dietary assessment methodologies and on related epidemiological associations. Her diverse contributions have been vital to progress in the nutritional epidemiological research area, and her leadership will be much missed. Dahm et al. (1) revisit the association between dietary fiber and risk of colorectal cancer in the context of an analysis of data from seven prospective UK cohort studies, with the novel feature that fiber consumption estimates are available from food diaries (also referred to as food records [FRs]). Whereas dietary assessment in cohort studies of this and other nutritional epidemiology topics has almost universally been based on data obtained from food-frequency questionnaires (FFQs), a few cohorts have also collected dietary data by using FRs. The analysis of FRs for nutrient consumption and dietary pattern estimation is somewhat time-consuming and expensive so that some form of outcome-based sampling is needed for efficient association analyses. On the basis of data from 579 colorectal cancer case patients and 1996 matched control subjects, the authors report a statistically significant inverse association between intakes of either absolute fiber or fiber intake density (ie, the ratio of fiber to energy), as estimated from 4- to 7-day FRs, and the risk of colorectal cancer, particularly the risk of colon cancer. This inverse association was not apparent when fiber consumption, in the same case and control subjects, was estimated using an FFQ. This finding is consistent with earlier cohort study reports wherein risk of breast cancer was positively associated with fat consumption when assessment was based on FRs, whereas no association was apparent when assessment was based on FFQs (2,3). Dahm et al. comment that, “Although food diaries are probably better dietary assessment tools than FFQs, they do not completely eliminate measurement error.” In fact, the measurement properties of FRs, FFQs, and other dietary self-report procedures are largely unknown for most nutrients and dietary components, and uncertainty about such properties is the fundamental issue that separates the reliability of most reported nutritional epidemiological associations from that for many other well-established epidemiological risk factors and exposures. The fact that two conceptually different dietary assessment methods yielded results of differing interpretation does not, in itself, attest to the reliability of either. Rather, these findings point to the need to rigorously address the measurement error issue for progress in nutritional epidemiology. To support their assertion that FRs are probably better than FFQs for dietary assessment, Dahm et al. refer to their studies of protein, sodium, and potassium intakes in which FR estimates of these nutrients correlated more strongly with corresponding urinary recovery biomarkers than did FFQ estimates. This is valuable information, but there is no established biomarker for fiber consumption, obviating the ability to directly compare measurement properties for the two assessment procedures and precluding a compelling way to adjust fiber consumption odds ratios for measurement error. To address this limitation, Dahm et al. present “corrected” odds ratios for fiber consumption assuming a classical measurement error model, with little change in findings. Commendably, they also provide corrected sensitivity analyses that allow the measurement error to depend on the underlying (unobserved) fiber consumption while permitting the measurement errors for repeat application of the same assessment procedure to be correlated. These analyses also suggest little change in odds ratios for fiber consumption, using either FRs or FFQs. Although these measurement error provisions go beyond those typically presented in nutritional epidemiology reports, they still leave considerable uncertainty about the reliability and interpretation of the fiber and colorectal cancer association. This uncertainty is augmented by the absence of support from the cited intervention trials of colorectal adenoma recurrence [eg, (4,5)]. Although measurement error modeling issues in nutritional epidemiology may seem esoteric to some readers, these issues appear to be fundamental to the reliability of dietary association reports. Specifically, available information indicates that individuals tend to report dietary data quite differently depending on such characteristics as age, body mass index, and ethnicity, at least for FFQ assessments of energy and protein (6). These types of systematic assessment biases can play havoc with association studies: In one of the few nutritional epidemiology study published to date that made provision for these types of systematic biases, FFQ-assessed energy consumption among postmenopausal women was unrelated to the incidence of total invasive cancer or site-specific cancer, whereas after energy consumption was corrected using a doubly labeled water biomarker, strong positive associations were evident for total cancer and for various cancer sites, including breast, colon, endometrium, and kidney (7). Also, FFQ-assessed protein density was not associated with total invasive cancer incidence before biomarker calibration but inversely associated after biomarker calibration (7), with protein assessed by a urinary nitrogen biomarker. The fact that Dahm et al. could not correct the fiber consumption odds ratios for these types of systematic biases casts a shadow over the interpretation of their reported inverse association. Unfortunately, this shadow extends to virtually the entire body of the existing nutritional epidemiology literature and may well contribute to the fact that few associations between diet and cancer are regarded as established or probable (8). The explicit use of biomarkers to correct nutritional epidemiology associations for systematic and random measurement error in dietary assessment seems a logical next step in the nutritional epidemiology research agenda. Measurement error procedures that instead use one self-reported estimate to correct another are unlikely to be adequate because the availability of consumption estimates with measurement errors that are independent of those for the self-report estimates available for the study cohort is key to the correction procedure, and differing self-report assessment procedures can be expected to have some common sources of systematic bias. Instead, a major research effort is needed, using human feeding studies and other strategies, to develop suitable consumption biomarkers for additional nutrients and dietary components. The need for a vigorous and innovative research agenda to yield reliable information on diet and chronic disease risk seems imperative, given our ongoing epidemic of obesity and of obesity-related diseases.

Variation in the FGFR2 gene and the effect of a low-fat dietary pattern on invasive breast cancer.

Abstract: Background: The Women's Health Initiative dietary modification (DM) trial provided suggestive evidence of a benefit of a low-fat dietary pattern on breast cancer risk, with stronger evidence among women whose baseline diet was high in fat. Single nucleotide polymorphisms (SNP) in the FGFR2 gene relate strongly to breast cancer risk and could influence intervention effects. Methods: All 48,835 trial participants were postmenopausal and ages 50 to 79 years at enrollment (1993-1998). We interrogated eight SNPs in intron 2 of the FGFR2 gene for 1,676 women who developed breast cancer during trial follow-up (1993-2005). Case-only analyses were used to estimate odds ratios for the DM intervention in relation to SNP genotype. Results: Odds ratios for the DM intervention did not vary significantly with the genotype for any of the eight FGFR2 SNPs ( P ≥ 0.18). However, odds ratios varied ( P < 0.05) with the genotype of six of these SNPs, among women having baseline percent of energy from fat in the upper quartile (≥36.8%). This variation is most evident for SNP rs3750817, with odds ratios for the DM intervention at 0, 1, and 2 minor SNP alleles of 1.06 [95% confidence intervals (95% CI), 0.80-1.41], 0.53 (95% CI, 0.38-0.74), and 0.62 (95% CI, 0.33-1.15). The nominal significance level for this interaction is P = 0.005, and P = 0.03 following multiple testing adjustment, with most evidence deriving from hormone receptor–positive tumors. Conclusion: Invasive breast cancer odds ratios for a low-fat dietary pattern, among women whose usual diets are high in fat, seem to vary with SNP rs3750817 in the FGFR2 gene. Cancer Epidemiol Biomarkers Prev; 19(1); 74–9

Pooled versus individual genotyping in a breast cancer genome-wide association study.

Abstract: We examine the measurement properties of pooled DNA odds ratio estimates for 7357 single nucleotide polymorphisms (SNPs) genotyped in a genome-wide association study of postmenopausal breast cancer. This study involved DNA pools formed from 125 cases or 125 matched controls. Individual genotyping for these SNPs subsequently came available for a substantial majority of women included in seven pool pairs, providing the opportunity for a comparison of pooled DNA and individual odds ratio estimates and their variances. We find that the ‘per minor allele’ odds ratio estimates from the pooled DNA comparisons agree fairly well with those from individual genotyping. Furthermore, the log-odds ratio variance estimates support a pooled DNA measurement model that we previously described, though with somewhat greater extra-binomial variation than was hypothesized in project design. Implications for the role of pooled DNA comparisons in the future genetic epidemiology research agenda are discussed.

Chronic Disease Prevention Research Methods and Their Reliability, With Illustrations From the Women's Health Initiative

Abstract: This article reviews the status of statistical methods for chronic disease prevention research, with emphasis on the reliability of findings and on future methodological needs and opportunities. Observational studies, especially cohort studies, play a major role in disease prevention research, but depend on adequate confounding control methods for a useful interpretation. Stratification and regression methods that are commonly used to control confounding are described, and comparative findings from the Women’s Health Initiative (WHI) randomized controlled trial and companion cohort study of the benefits and risk of postmenopausal hormone therapy are used to illustrate the success of these methods. Measurement error in exposure assessment may be a potentially dominating source of bias in such important prevention research areas as nutrition and physical activity epidemiology. Statistical methods to correct for measurement error are briefly reviewed, and the need for methods to accommodate systematic bias i...

Breast cancer outcome and estrogen plus progestin use in postmenopausal women.

Abstract: 1507 Background: During a mean (SD) 5.6 years (1.3) of intervention, use of estrogen plus progestin in the Women's Health Initiative (WHI) randomized clinical trial increased breast cancer incidence (Chlebowski et al JAMA 2003;289;3243) but breast cancer mortality was not reported. Therefore, we determined combined hormone therapy effects on breast cancer incidence and mortality in the WHI trial over the entire follow-up period (mean [SD] 11.0 [2.7] years) and also in the WHI observational study cohort. Methods: In the clinical trial, 16,608 postmenopausal women with no prior hysterectomy were randomized to conjugated equine estrogens (0.625 mg/d) plus medroxyprogesterone acetate (2.5 mg/d) (estrogen plus progestin) or placebo. In the observational study, 41,449 postmenopausal women with characteristics similar to clinical trial participants were identified at entry as estrogen plus progestin users (n = 16,121) or not users (n = 25,328). Main outcome measures included invasive breast cancer incidence and ...

Clinical validity assessment of a breast cancer risk model combining genetic and clinical information

Abstract: The extent to which common genetic variation can assist in breast cancer (BCa) risk assessment is unclear. We assessed the addition of risk information from a panel of BCa-associated single nucleotide polymorphisms (SNPs) on risk stratification offered by the Gail Model.Methods: We selected 7 validated SNPs from the literature and genotyped them among white women in a nested case-control study within the Women’s Health Initiative Clinical Trial. To model SNP risk, previously published odds ratios were combined multiplicatively. To produce a combined clinical/genetic risk, Gail Model risk estimates were multiplied by combined SNP odds ratios. We assessed classification performance using reclassification tables and receiver operating characteristic (ROC) curves. Results: The SNP risk score was well calibrated and nearly independent of Gail risk, and the combined predictor was more predictive than either Gail risk or SNP risk alone. In ROC curve analysis, the combined score had an area under the curve (AUC) of 0.594 compared to 0.557 for Gail risk alone. For reclassification with 5-year risk thresholds at 1.5% and 2%, the net reclassification index (NRI) was 0.085 (Z = 4.3, P = 1.0 × 10^-5^). Focusing on women with Gail 5-year risk of 1.5-2% results in an NRI of 0.195 (Z = 3.8, P = 8.6 × 10^−5^). Combining clinical risk factors and validated common genetic risk factors results in improvement in classification of BCa risks in white, postmenopausal women. This may have implications for informing primary prevention and/or screening strategies. Future research should assess the clinical utility of such strategies.