To assist in medical counseling, we present a method to estimate the chance that a woman with given age and risk factors will develop breast cancer over a specified interval. The risk factors used were age at menarche, age at first live birth, number of previous biopsies, and number of first-degree relatives with breast cancer. A model of relative risks for various combinations of these factors was developed from case-control data from the Breast Cancer Detection Demonstration Project (BCDDP). The model allowed for the fact that relative risks associated with previous breast biopsies were smaller for women aged 50 or more than for younger women. Thus, the proportional hazards models for those under age 50 and for those of age 50 or more. The baseline age-specific hazard rate, which is the rate for a patient without identified risk factors, is computed as the product of the observed age-specific composite hazard rate times the quantity 1 minus the attributable risk. We calculated individualized breast cancer probabilities from information on relative risks and the baseline hazard rate. These calculations take competing risks and the interval of risk into account. Our data were derived from women who participated in the BCDDP and who tended to return for periodic examinations. For this reason, the risk projections given are probably most reliable for counseling women who plan to be examined about once a year.

A straightforward and unified approach is presented for the calculation of the population attributable risk per cent (etiologic fraction) in the general multivariate setting, with emphasis on using data from case-control studies. The summary attributable risk for multiple factors can be estimated, with or without adjustment for other (confounding) risk factors. The relation of this approach to procedures in the literature is discussed. Given values of the relative risks for various combinations of factors, all that is required is the distribution of these factors among the cases only. The required information can often be estimated solely from case-control data, and in some situations relative risk estimates from one population can be applied to calculation of attributable risk for another population. The authors emphasize the benefits to be obtained from logistic regression models, so that risks need not be estimated separately in a large number of strata, some of which may contain inadequate numbers of individuals. This approach allows incorporation of important interactions between factors, but does not require that all possible interactions be included. The approach is illustrated with data on four risk factors from a pair-matched case-control study of participants in a multicenter breast cancer screening project.

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The problem considered is how to compare time-to-response data for different groups when the group membership of an individual can be arbitrarily varied during a study. Modified life tables can be constructed which reflect such changes in an individual's status, and associated measures of relative risk and statistical significance calculated. This is illustrated with survival data for heart-transplant patients, for which a patient can transfer from the nontransplanted to the transplanted group. Alternative procedures are given in which distinctive groups are defined for each transplant day.

The results of these clinical trials over the past 12 years have revealed an unsuspected toxicity of DES used in treating patients with cancer of the prostate when given in a dose of 5.0 mg daily. The first VA study did not show that orchiectomy was superior to estrogen in treating cancer of the prostate or that the combination orchiectomy plus estrogen had much to offer beyond the benefits of estrogen alone when indicated. The preponderance of evidence from the second study shows that 1.0 mg of DES appears to be about as effective as the 5.0 mg dose in treating cancer of the prostate but does not carry the excess hazard of cardiovascular deaths. Our overall recommendation at present is that patients with prostatic cancer should not be treated until their symptoms require relief, and at that time we recommend starting treatment with 1.0 mg DES daily. These recommendations may change as we continue to analyze our data.

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