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Ross Prentice

Publications and source records attributed to Ross Prentice.

9 recordsLinked to original sources
PubMed2006

A comparison of two dietary instruments for evaluating the fat-breast cancer relationship.

BACKGROUND: Previous research suggests food diaries may be more efficient than food frequency questionnaires (FFQ) in detecting a dietary fat-breast cancer relationship. We assessed this further using 4 day food records (FRs) and FFQs in a large sample. METHODS: Participants were from the non-intervention group of the dietary modification component of the Women's Health Initiative Clinical Trial: 603 breast cancer cases and 1206 controls matched on age, clinic, and length of follow-up. Relative risks (RRs) were estimated using unconditional logistic regression, adjusted for confounders and for the selection into the trial of women with an FFQ report exceeding 32% calories from fat. Direct comparison of the statistical power of the two instruments used the standardized log RR. An alternative analysis after removing subjects with missing covariate data was also conducted. RESULTS: The RR estimate for breast cancer in the top quintile of total fat intake, adjusted for confounders and total energy, was 1.82 (P for trend 0.02) for the FR but 0.67 for the FFQ (P for trend 0.24). Following adjustment for selection, estimates were 2.09 (P for trend 0.008) for the FR (alternative: 2.54, P for trend 0.006) and 1.71 (P for trend 0.18) for the FFQ (alternative: 1.24, P for trend 0.41). Similar results were seen for fat subtypes, particularly unsaturated fats. Comparisons showed higher statistical power for the FR than the FFQ (e.g. total fat, P = 0.08: alternative P = 0.01). CONCLUSIONS: Alternative instruments, such as FRs, may be preferable to FFQs for evaluating diet-disease relationships in cohort studies. The results support a positive association between dietary fat and breast cancer.

Aged↗
PubMed2006

Conjugated equine estrogens and coronary heart disease: the Women's Health Initiative.

BACKGROUND: In recent randomized trials, conjugated equine estrogens (CEE) with continuous medroxyprogesterone acetate provided no protection against coronary heart disease in postmenopausal women and may have increased cardiac risk. These trials did not address the role of unopposed estrogen for coronary protection. METHODS: A total of 10 739 women aged 50 to 79 years at baseline (mean age, 63.6 years) who had previously undergone hysterectomy were randomized to receive CEE, 0.625 mg/d, or placebo at 40 US clinical centers beginning in 1993. The trial was terminated early after 6.8 years of follow-up (planned duration, 8.5 years). This report includes final, centrally adjudicated results for the primary efficacy outcome (myocardial infarction or coronary death), secondary coronary outcomes, and subgroup analyses. RESULTS: During the active intervention period, 201 coronary events were confirmed among women assigned to receive CEE compared with 217 events among women assigned to receive placebo (hazard ratio, 0.95; nominal 95% confidence interval, 0.79-1.16). Among women aged 50 to 59 years at baseline, the hazard ratio for the primary outcome was 0.63 (nominal 95% confidence interval, 0.36-1.08). In that age group, coronary revascularization was less frequent among women assigned to receive CEE (hazard ratio, 0.55; nominal 95% confidence interval, 0.35-0.86), as were several composite outcomes, which included the primary outcome and coronary revascularization (hazard ratio, 0.66; nominal 95% confidence interval, 0.44-0.97). CONCLUSIONS: Conjugated equine estrogens provided no overall protection against myocardial infarction or coronary death in generally healthy postmenopausal women during a 7-year period of use. There was a suggestion of lower coronary heart disease risk with CEE among women 50 to 59 years of age at baseline.

Age Distribution↗
PubMed2006

Low-fat dietary pattern and weight change over 7 years: the Women's Health Initiative Dietary Modification Trial.

CONTEXT: Obesity in the United States has increased dramatically during the past several decades. There is debate about optimum calorie balance for prevention of weight gain, and proponents of some low-carbohydrate diet regimens have suggested that the increasing obesity may be attributed, in part, to low-fat, high-carbohydrate diets. OBJECTIVES: To report data on body weight in a long-term, low-fat diet trial for which the primary end points were breast and colorectal cancer and to examine the relationships between weight changes and changes in dietary components. DESIGN, SETTING, AND PARTICIPANTS: Randomized intervention trial of 48,835 postmenopausal women in the United States who were of diverse backgrounds and ethnicities and participated in the Women's Health Initiative Dietary Modification Trial; 40% (19,541) were randomized to the intervention and 60% (29,294) to a control group. Study enrollment was between 1993 and 1998, and this analysis includes a mean follow-up of 7.5 years (through August 31, 2004). INTERVENTIONS: The intervention included group and individual sessions to promote a decrease in fat intake and increases in vegetable, fruit, and grain consumption and did not include weight loss or caloric restriction goals. The control group received diet-related education materials. MAIN OUTCOME MEASURE: Change in body weight from baseline to follow-up. RESULTS: Women in the intervention group lost weight in the first year (mean of 2.2 kg, P<.001) and maintained lower weight than control women during an average 7.5 years of follow-up (difference, 1.9 kg, P<.001 at 1 year and 0.4 kg, P = .01 at 7.5 years). No tendency toward weight gain was observed in intervention group women overall or when stratified by age, ethnicity, or body mass index. Weight loss was greatest among women in either group who decreased their percentage of energy from fat. A similar but lesser trend was observed with increases in vegetable and fruit servings, and a nonsignificant trend toward weight loss occurred with increasing intake of fiber. CONCLUSION: A low-fat eating pattern does not result in weight gain in postmenopausal women. Clinical Trial Registration ClinicalTrials.gov, NCT00000611.

Aged↗
PubMed2005

Ethnicity and breast cancer: factors influencing differences in incidence and outcome.

BACKGROUND: The lower breast cancer incidence in minority women and the higher breast cancer mortality in African American women than in white women are largely unexplained. The influence of breast cancer risk factors on these differences has received little attention. METHODS: Racial/ethnic differences in breast cancer incidence and outcome were examined in 156,570 postmenopausal women participating in the Women's Health Initiative. Detailed information on breast cancer risk factors including mammography was collected, and participants were followed prospectively for breast cancer incidence, pathological breast cancer characteristics, and breast cancer mortality. Comparisons of breast cancer incidence and mortality across racial/ethnic groups were estimated as hazard ratios (HRs) and 95% confidence intervals (CIs) from Cox proportional hazard models. Tumor characteristics were compared as odds ratios (ORs) and 95% confidence intervals in logistic regression models. RESULTS: After median follow-up of 6.3 years, 3938 breast cancers were diagnosed. Age-adjusted incidences for all minority groups (i.e., African American, Hispanic, American Indian/Alaskan Native, and Asian/Pacific Islander) were lower than for white women, but adjustment for breast cancer risk factors accounted for the differences for all but African Americans (HR = 0.75, 95% CI = 0.61 to 0.92) corresponding to 29 cases and 44 cases per 10,000 person years for African American and white women, respectively. Breast cancers in African American women had unfavorable characteristics; 32% of those in African Americans but only 10% in whites were both high grade and estrogen receptor negative (adjusted OR = 4.70, 95% CI = 3.12 to 7.09). Moreover, after adjustment for prognostic factors, African American women had higher mortality after breast cancer than white women (HR = 1.79, 95% CI = 1.05 to 3.05) corresponding to nine and six deaths per 10 000 person-years from diagnosis in African American and white women, respectively. CONCLUSION: Differences in breast cancer incidence rates between most racial/ethnic groups were largely explained by risk factor distribution except in African Americans. However, breast cancers in African American women more commonly had characteristics of poor prognosis, which may contribute to their increased mortality after diagnosis.

Adult↗
PubMed2005

Leukocyte count as a predictor of cardiovascular events and mortality in postmenopausal women: the Women's Health Initiative Observational Study.

BACKGROUND: Increasing evidence supports a role for inflammation in the atherosclerotic process. The role of the leukocyte count as an independent predictor of risk of a first cardiovascular disease (CVD) event remains uncertain. Our objective was to describe the relation between the baseline white blood cell (WBC) count and future CVD events and mortality in postmenopausal women. METHODS: In this prospective cohort study set in 40 US clinical centers, the study population comprised 72 242 postmenopausal women aged 50 to 79 years, free of CVD and cancer at baseline, enrolled in the Women's Health Initiative Observational Study. Main outcome measures included incident fatal coronary heart disease (CHD), nonfatal myocardial infarction, stroke, and total mortality. RESULTS: At baseline, the mean +/- SD age of the women was 63 +/- 7.3 years, 84% were white, 4% had diabetes, 35% had hypertension, and 6% were current smokers. The mean WBC count was 5.8 +/- 1.6 x 10(9) cells/L. During a mean of 6.1 years of follow-up, there were 187 CHD deaths, 701 nonfatal myocardial infarctions, 738 strokes, and 1919 deaths from all causes. Compared with women with WBC counts in the first quartile (2.5-4.7 x 10(9) cells/L), women in the fourth quartile (6.7-15.0 x 10(9) cells/L) had over a 2-fold elevated risk for CHD death (hazard ratio, 2.36; 95% confidence interval, 1.51-3.68), after multivariable adjustment for age, race, diabetes, hypertension, smoking, hypercholesterolemia, body mass index, alcohol intake, diet, physical activity, aspirin use, and hormone use. Women in the upper quartile of the WBC count also had a 40% higher risk for nonfatal myocardial infarction, a 46% higher risk for stroke, and a 50% higher risk for total mortality. In multivariable models adjusting for C-reactive protein, the WBC count was an independent predictor of CHD risk, comparable in magnitude to C-reactive protein. CONCLUSIONS: The WBC count, a stable, well-standardized, widely available and inexpensive measure of systemic inflammation, is an independent predictor of CVD events and all-cause mortality in postmenopausal women. A WBC count greater than 6.7 x 10(9) cells/L may identify high-risk individuals who are not currently identified by traditional CVD risk factors.

Aged↗
PubMed2004

Estrogen plus progestin and risk of venous thrombosis.

CONTEXT: Postmenopausal hormone therapy increases the risk of venous thrombosis. It is not known whether other factors influencing thrombosis add to this risk. OBJECTIVE: To report final data on incidence of venous thrombosis in the Women's Health Initiative Estrogen Plus Progestin clinical trial and the association of hormone therapy with venous thrombosis in the setting of other thrombosis risk factors. DESIGN, SETTING, AND PARTICIPANTS: Double-blind randomized controlled trial of 16,608 postmenopausal women between the ages of 50 and 79 years, who were enrolled in 1993 through 1998 at 40 US clinical centers with 5.6 years of follow up; and a nested case-control study. Baseline gene variants related to thrombosis risk were measured in the first 147 women who developed thrombosis and in 513 controls. INTERVENTION: Random assignment to 0.625 mg/d of conjugated equine estrogen plus 2.5 mg/d of medroxyprogesterone acetate, or placebo. MAIN OUTCOME MEASURES: Centrally validated deep vein thrombosis and pulmonary embolus. RESULTS: Venous thrombosis occurred in 167 women taking estrogen plus progestin (3.5 per 1000 person-years) and in 76 taking placebo (1.7 per 1000 person-years); hazard ratio (HR), 2.06 (95% confidence interval [CI], 1.57-2.70). Compared with women between the ages of 50 and 59 years who were taking placebo, the risk associated with hormone therapy was higher with age: HR of 4.28 (95% CI, 2.38-7.72) for women aged 60 to 69 years and 7.46 (95% CI, 4.32-14.38) for women aged 70 to 79 years. Compared with women who were of normal weight and taking placebo, the risk associated with taking estrogen plus progestin was increased among overweight and obese women: HR of 3.80 (95% CI, 2.08-6.94) and 5.61 (95% CI, 3.12-10.11), respectively. Factor V Leiden enhanced the hormone-associated risk of thrombosis with a 6.69-fold increased risk compared with women in the placebo group without the mutation (95% CI, 3.09-14.49). Other genetic variants (prothrombin 20210A, methylenetetrahydrofolate reductase C677T, factor XIII Val34Leu, PAI-1 4G/5G, and factor V HR2) did not modify the association of hormone therapy with venous thrombosis. CONCLUSIONS: Estrogen plus progestin was associated with doubling the risk of venous thrombosis. Estrogen plus progestin therapy increased the risks associated with age, overweight or obesity, and factor V Leiden.

Age Factors↗
PubMed2004

Research issues and strategies for genomic and proteomic biomarker discovery and validation: a statistical perspective.

The development and validation of clinically useful biomarkers from high-dimensional genomic and proteomic information pose great research challenges. Present bottlenecks include: that few of the biomarkers showing promise in initial discovery were found to warrant subsequent validation; and biomarker validation is expensive and time consuming. Biomarker evaluation should proceed in an orderly fashion to enhance rigor and efficiency. A molecular profiling approach, although promising, has a high chance of yielding biased results and overfitted models. Specimens from cohorts or intervention trials are essential to eliminate biases. The high cost for biomarker validation motivates some novel study design features, including sequential filtering and DNA pooling. For data analysis, logistic regression (in particular, boosting logistic regression) has features of robustness against model misspecification, and has resistance to model overfitting. Model assessment and cross-validation are critical components of data analysis. Having an independent test set is a vital feature of study design.

Biomarkers, Tumor↗