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Biomedical subjects

B Rockhill

Publications and source records attributed to B Rockhill.

At least 19 recordsLinked to original sources
PubMed2001

Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention.

BACKGROUND: Women and their clinicians are increasingly encouraged to use risk estimates derived from statistical models, primarily that of Gail et al., to aid decision making regarding potential prevention options for breast cancer, including chemoprevention with tamoxifen. METHODS: We evaluated both the goodness of fit of the Gail et al. model 2 that predicts the risk of developing invasive breast cancer specifically and its discriminatory accuracy at the individual level in the Nurses' Health Study. We began with a cohort of 82 109 white women aged 45-71 years in 1992 and applied the model of Gail et al. to these women over a 5-year follow-up period to estimate a 5-year risk of invasive breast cancer. All statistical tests were two-sided. RESULTS: The model fit well in the total sample (ratio of expected [E] to observed [O] numbers of cases = 0.94; 95% confidence interval [CI] = 0.89 to 0.99). Underprediction was slightly greater for younger women (<60 years), but in most age and risk factor strata, E/O ratios were close to 1.0. The model fit equally well (E/O ratio = 0.93; 95% CI = 0.87 to 0.99) in a subset of women reporting recent screening (i.e., within 1 year before the baseline); among women with an estimated 5-year risk of developing invasive breast cancer of 1.67% or greater, the E/O ratio was 1.04 (95% CI = 0.96 to 1.12). The concordance statistic, which indicates discriminatory accuracy, for the Gail et al. model 2 when used to estimate 5-year risk was 0.58 (95% CI = 0.56 to 0.60). Only 3.3% of the 1354 cases of breast cancer observed in the cohort arose among women who fell into age-risk strata expected to have statistically significant net health benefits from prophylactic tamoxifen use. CONCLUSIONS: The Gail et al. model 2 fit well in this sample in terms of predicting numbers of breast cancer cases in specific risk factor strata but had modest discriminatory accuracy at the individual level. This finding has implications for use of the model in clinical counseling of individual women.

Aged↗
PubMed2001

The privatization of risk.

The privatization, or individualization, of risk factor knowledge has been largely responsible for a rising tide of criticism of epidemiology. The current debate seems polarized into 2 sides, those who support and those who attack "risk factor" epidemiology. This commentary aims to reinvigorate some of Geoffrey Rose's central arguments and show that this debate may miss a key point: a risk factor is a probabilistic concept that applies to an aggregate of individuals, not to a specific individual. Risk factor knowledge compels those in public health to seek actions that shift population distributions of these factors and, to do so, to understand their social, economic, and political determinants. The author links Rose's qualitative distinction between the causes of cases and the causes of incidence to an examination of the conceptual and quantitative limits of "individual risk" estimation. The attempt to predict individuals' futures on the basis of risk factor profile is especially prominent now with breast cancer. The author suggests reasons why a policy promoting private decision making about risk, while likely ineffective from a population standpoint, is viewed as the only feasible primary prevention option against this disease.

Breast Neoplasms↗
PubMed2001

Physical activity and mortality: a prospective study among women.

OBJECTIVES: This study examined the association between recreational physical activity and mortality in middle-aged and older women and the possibility that physical activity serves as an important marker of health. METHODS: Analyses were conducted among participants in the Nurses' Health Study. Levels of physical activity were assessed by questionnaire in 1980 and updated every 2 to 4 years. RESULTS: Levels of physical activity were inversely associated with mortality risk; however, each activity level above the reference level had approximately the same level of risk reduction (20%-30%). The inverse association was stronger for cardiovascular deaths than for cancer deaths and was strongest for respiratory deaths. Women who died of noncardiovascular, noncancer causes were more likely to have reported that poor health limited their physical activity than were women who died of other causes or who remained alive. CONCLUSIONS: Part of the link between physical activity and mortality risk is probably spurious and difficult to remove analytically; however, on the basis of epidemiologic evidence, much of the health benefit of activity is real.

Adult↗
PubMed2000

Bias in breast cancer analyses due to error in age at menopause.

With the use of data from the Nurses' Health Study, the authors confirm the recent argument by Pike et al. (Am J Epidemiol 1998;147:718-21) that various ways of assigning ages at menopause to women with simple hysterectomy produce relative risks for the effect of hormone replacement therapy (HRT) that are biased downward. Different methods of including women with simple hysterectomy consistently produced relative risks for the association between a 1-year increase in duration of HRT use and breast cancer that were underestimates compared with the relative risk obtained when these women were excluded from analysis. The authors used longitudinal data on recalled age at menopause to demonstrate another source of error related to age at menopause: error in recall of age at menopause that increases with time since menopause.

Adult↗
PubMed1999

A prospective study of recreational physical activity and breast cancer risk.

BACKGROUND: Increased physical activity has been hypothesized to prevent breast cancer, largely by reducing cumulative lifetime exposure to circulating ovarian hormones. However, epidemiologic findings are inconsistent, and there is no consensus on the best way to quantify physical activity. We thus examined this issue in a large cohort of women, using several different measures of adult physical activity. METHODS: We analyzed data from the Nurses' Health Study, a prospective study of women aged 30 to 55 years in 1976. In 1980 and on subsequent surveys, women were asked about the average number of hours per week spent in various moderate and vigorous recreational physical activity during the past year. We computed a "baseline-only" (1980) measure of hours per week of physical activity, as well as a cumulative average measure that used updated reports on physical activity. During 16 years of follow-up, we identified 3137 cases of invasive breast cancer (1036 premenopausal and 2101 postmenopausal women). Data were analyzed by use of multivariate pooled logistic regression to produce relative risks of breast cancer, and the associated confidence intervals. RESULTS: Women who were more physically active in adulthood had a lower risk of breast cancer than those who were less physically active. Comparing those who reported engaging in moderate or vigorous physical activity for 7 or more hours per week with those who engaged in such physical activity for less than 1 hour per week, the relative risk was 0.82 (95% confidence interval, 0.70-0.97), using the cumulative average updating. The dose-response trend was statistically significant (P = .004). Using the baseline-only measure of physical activity produced slightly weaker relative risks. CONCLUSION: These results contribute to the body of evidence suggesting that higher levels of adult physical activity afford modest protection against breast cancer.

Adult↗
PubMed1998

Physical activity and breast cancer risk in a cohort of young women.

BACKGROUND: Increased physical activity has been hypothesized to be a means of breast cancer prevention. We examined the associations between physical activity at two different times in life and breast cancer risk. METHODS: We analyzed data from the Nurses' Health Study II, a prospective study of women aged 25-42 years in 1989. On the baseline survey, women were asked, "While in high school and between the ages 18 and 22 years, how often did you participate in strenuous physical activity at least twice a week?" We averaged answers to these two questions to develop a measure of late adolescent activity. Women were also asked at baseline to report the number of hours per week they currently spent in different nonoccupational activities. During 6 years of follow-up, we identified 372 cases of invasive breast cancer. Data were analyzed by use of multivariate pooled logistic regression to produce relative risk (RR) and confidence intervals (CIs) of being diagnosed with the disease. RESULTS: Women who were more active in late adolescence were not at reduced risk of breast cancer compared with less active women. For those women who reported engaging in strenuous activity at least twice per week for 10-12 months per year in late adolescence, the RR of cancer, compared with those who never engaged in such activity, was 1.1 (95% CI = 0.8-1.6). Similarly, higher levels of recent nonoccupational physical activity were not associated with reduced risk of breast cancer (RR for > or = 7 hours of activity/week relative to < 1 hour/week = 1.1; 95% CI = 0.8-1.5). CONCLUSION: Our findings do not support a link between physical activity, in late adolescence or in the recent past, and breast cancer risk among young adult women.

Adolescent↗
PubMed1998

Population attributable fraction estimation for established breast cancer risk factors: considering the issues of high prevalence and unmodifiability.

Established breast cancer risk factors, in addition to being relatively unmodifiable, are highly prevalent among US women. Previous reports of population attributable fraction for the established risk factors have used definitions that resulted in 75-100% of women in the source population labeled exposed. The practical value of such estimates has not been discussed; further, the estimates have frequently been misinterpreted. In the context of examining the interpretation and public health value of such estimates, the authors demonstrate the sensitivity of the population attributable fraction to changes in exposure cutpoints. They use data from the Carolina Breast Cancer Study, a case-control study of breast cancer conducted in North Carolina between 1993 and 1996. For the four established risk factors (menarche before age 14 years, first birth at age 20 years or later/nulliparity, family history of breast cancer, and history of benign breast biopsy), the estimated population attributable fraction was 0.25 (95% confidence interval 0.06-0.48). Over 98% of the source population was exposed to at least one of these risk factors. The population attributable fraction estimate was reduced to 0.15 when more restrictive definitions of early menarche (less than age 12 years) and late age at first full-term pregnancy (30 years or more) were used (proportion exposed, 0.62). Population attributable fractions for established breast cancer risk factors probably have little public health value because of both the high proportions exposed and the relative unmodifiability of the risk factor distributions.

Adolescent↗
PubMed1998

Age at menarche, time to regular cycling, and breast cancer (North Carolina, United States).

OBJECTIVES: Later menarche, and a longer time until onset of regular cycling, are considered markers of lower lifetime exposure to circulating ovarian hormones. While later age at menarche is associated with reduced breast cancer risk, evidence for the relationship between time until onset of regular cycles and breast cancer is inconsistent. We evaluated both associations with breast cancer risk. METHODS: We used data from the Carolina Breast Cancer Study, a population-based case-control study of breast cancer among White and Black women aged 20 to 74 years, residing in central and eastern North Carolina (United States). Cases were diagnosed between May 1993 and June 1996. Unconditional logistic regression models were limited to women with complete data for the risk factors considered (n = 830 cases, 758 controls). RESULTS: We observed an inverse relationship between age at menarche and breast cancer risk, but found little support for the hypothesis that a longer time until onset of regular menstrual cycling was associated with reduced risk of breast cancer (odds ratios = 1.0 [95 percent confidence interval (CI) = 0.7-1.5], and 1.2 [CI = 0.8-1.6], respectively, for 1-4 years and < 1 year until onset of regular cycling, relative to 5+ years). There was little relationship between age at menarche and time until regular cycling. We found strong evidence that delays in onset of regular cycling were associated with increased frequency of irregular cycles throughout young adulthood. CONCLUSIONS: Given the inconsistent findings regarding the links between menstrual cycle characteristics and breast cancer, and recent recommendations to delay menarche and alter the patterns of cycles of young women in order to reduce breast cancer risk, this topic calls for further, innovative study.

Adolescent↗
PubMed1998

Cigarette smoking, N-acetyltransferases 1 and 2, and breast cancer risk.

To examine the effects of smoking and N-acetylation genetics on breast cancer risk, we analyzed data from an ongoing, population-based, case-control study of invasive breast cancer in North Carolina. The study population consisted of 498 cases and 473 controls, with approximately equal numbers of African-American and white women, and women under the age of 50 and age 50 years or older. Among premenopausal women, there was no association between current smoking [odds ratio (OR), 0.9; 95% confidence interval (CI), 0.5-1.5] or past smoking (OR, 1.0; 95% CI, 0.6-1.6) and breast cancer risk. Among postmenopausal women, there was also no association with current smoking (OR, 1.2; 95% CI, 0.7-2.0); however, a small increase in risk was observed for past smoking (OR, 1.5; 95% CI, 1.0-2.4). For postmenopausal women who smoked in the past, ORs and 95% CIs were 3.4 (1.4-8.1) for smoking within the past 3 years, 3.0 (1.3-6.7) for smoking 4-9 years ago, and 0.6 (0.3-1.4) for smoking 10-19 years ago. Neither N-acetyltransferase 1 (NAT1) nor N-acetyltransferase 2 (NAT2) genotype alone was associated with increased breast cancer risk. There was little evidence for modification of smoking effects according to genotype, except among postmenopausal women. Among postmenopausal women, ORs for smoking within the past 3 years were greater for women with the NAT1*10 genotype (OR, 9.0; 95% CI, 1.9-41.8) than NAT1-non*10 (OR, 2.5; 95% CI, 0.9-7.2) and greater for NAT2-rapid genotype (OR, 7.4; 95% CI, 1.6-32.6) than NAT2-slow (OR, 2.8; 95% CI, 0.4-8.0). Future studies of NAT genotypes and breast cancer should investigate the effects of environmental tobacco smoke, diet, and other exposures.

Acetyltransferases↗
PubMed1997

Validity and efficiency of approximation methods for tied survival times in Cox regression.

Survival-time studies sometimes do not yield distinct failure times. Several methods have been proposed to handle the resulting ties. The goal of this paper is to compare these methods. Simulations were conducted, in which failure times were generated for a two-sample problem with an exponential hazard, a constant hazard ratio, and no censoring. Failure times were grouped to produce heavy, moderate, and light ties, corresponding to a mean of 10.0, 5.0, and 2.5 failures per interval. Cox proportional hazards models were fit using each of three approximations for handling ties with each interval size for sample sizes of n = 25, 50, 250, and 500 in each group. The Breslow (1974, Biometrics 30, 89-99) approximation tends to underestimate the true beta, while the Kalbfleisch-Prentice (1973, Biometrika 60, 267-279) approximation tends to overestimate beta. As the ties become heavier, the bias of these approximations increases. The Efron (1977, Journal of the American Statistical Association 72, 557-565) approximation performs far better than the other two, particularly with moderate or heavy ties; even with n = 25 in each group, the bias is under 2%, and for sample sizes larger than 50 per group, it is less than 1%. Except for the heaviest ties in the smallest sample, confidence interval coverage for all three estimators fell in the range of 94-96%. However, the tail probabilities were asymmetric with the Breslow and Kalbfleisch-Prentice formulas; using the Efron approximation, they were closer to the nominal 2.5%. Although the Breslow approximation is the default in many standard software packages, the Efron method for handling ties is to be preferred, particularly when the sample size is small either from the outset or due to heavy censoring.

Bias↗