Clinical trials in diet and cancer

Physical activity and cancer: lessons learned from nutritional epidemiology

Convincing epidemiologic evidence currently exists for an association between physical activity and the prevention of colon and breast cancer Physical activity may also reduce the risk of cancer at several other sites. With increasing research on this topic, it is apparent that studies of physical activity and cancer have numerous methodological similarities with studies of nutrition and cancer Lessons learned from nutritional epidemiology that can be applied to studies of physical activity and cancer prevention and recommendations for future research are discussed in this review.

Fat, caloric intake, and obesity: lifestyle risk factors for breast cancer

Dietary fat is a likely important determinant of postmenopausal breast cancer as part of an intricate and inseparable interaction of lifestyle cancer risk factors that include dietary fat, type of fat, energy intake and expenditure, and obesity. These factors possibly build upon individual susceptibilities derived from a complex array of polygenetic risk determinants. Epidemiologic studies have not provided conclusive evidence for a dietary fat-breast cancer association, partly because studies that focus on a single nutrient cannot always evaluate readily the interactive effects of other lifestyle factors. Further, persons generally underestimate their usual dietary intake, measured by either food frequency questionnaires (FFQs) or diet records. A dietary measurement model that accounts for this underreporting demonstrated that FFQs and diet records may not be able to detect a dietary fat-breast cancer association because of measurement error biases. Although meta-analysis of epidemiologic data across individual studies suggests only a week association between breast cancer and dietary fat, this result is compatible with the dietary measurement model and does not rule out a contributing role for dietary fat, either alone or with other causative factors. Research is needed that focuses on a comprehensive approach to dietary lifestyle choices and breast cancer risk and that emphasizes a fat-caloric intake-obesity linkage. The best hope for a definitive answer may rest with randomized, controlled clinical trials. Two such trials, the Women's Health Initiative and the Women's Intervention Nutrition Study, are under way.

Dave Byar's contribution to epidemiology

Some of Dave Byar's personal qualities and his scientific approach are described. His work on substantive epidemiologic projects is mentioned briefly. There follows a review of his work on theoretical issues, including extentions of the Mantel-Haenszel procedure and other contingency table methods, confounding, and estimation of attributable and absolute risk from case-control data.

On the role, design, and analysis of disease prevention trials

Some differences between prevention and therapeutic trials are reviewed, as are some of David Byar's contributions to the methodology and practice of prevention trials. This leads to a more detailed discussion of three more technical topics pertinent to prevention trials: (i) the role that aggregate data studies may be able to play to complement analytic epidemiologic studies and prevention trials in the identification of disease prevention strategies; (ii) the methods for analysis of correlated response data, as may arise in group randomized trials; and (iii) the importance of emphasizing overall benefits vs. risks in the design and conduct of disease prevention trials.

New directions in dietary studies in cancer: the National Cancer Institute

Through an orderly sequence incorporating epidemiologic and laboratory research, human clinical/metabolic studies, and clinical intervention trials, the NCI develops and maintains cancer prevention and control programs that are directed toward the overall goal to reduce cancer incidence, morbidity, and mortality. Epidemiologic studies have shown correlations between consumption of numerous dietary constituents and cancer risk. Results of in vitro and animal studies have reinforced many of these epidemiologic associations and data from clinical/metabolic studies are being used to evaluate the relevance of these associations in humans. Although much remains to be learned about the influence of specific dietary constituents and dietary patterns on cancer risk, it is clear that diet can have a significant impact in cancer prevention and control. Investigations on the cellular and molecular effects of dietary constituents, as well as their metabolic and physiologic effects should provide better insight on the mechanisms of action of these dietary constituents. There also is a need to develop biomarkers of dietary intake that could be used to monitor compliance in intervention studies, as well as biomarkers as clinical trial endpoints that can be used to predict the emergence and progression of cancer. Working with other agencies and the private sector, the NCI will continue to design and implement information programs that translate the knowledge gained from these diet and cancer prevention studies to help Americans adopt dietary patterns that may reduce cancer risk. Continued emphasis will be placed on intervention programs targeted toward high-risk and underserved segments of the U.S. population in an effort to reduce the high incidence of cancers in these groups.

Collinearity diagnosis for a relative risk regression analysis: an application to assessment of diet-cancer relationship in epidemiological studies

In epidemiologic studies, two forms of collinear relationships between the intake of major nutrients, high correlations, and the relative homogeneity of the diet, can yield unstable and not easily interpreted regression estimates for the effect of diet on disease risk. This paper presents tools for assessing the magnitude and source of the corresponding collinear relationships among the estimated coefficients for relative risk regression models. I show how to extend three tools (condition indices, variance decomposition proportions, and standard inflation factors) for diagnosing collinearity in standard regression models to likelihood and partial likelihood estimation for logistic and proportional hazards models. This extension is based on the analogue role of the information matrix in such analyses and the cross-product matrix in the standard linear model. I apply the methodology to relative risk models that relate crude intakes (on the log scale) and nutrient densities to breast cancer cases in the NHANES-I follow-up study. The three diagnostic tools provide complementary evidence of the existence of a strong collinearity in all models that is due largely to homogeneity of the population with respect to our risk scale for the crude intakes. The analysis suggests that the non-significant relative risks for the crude intakes in these models may be due to their involvement in collinear relationships, while the nonsignificant relative risks for the nutrient densities are far less affected by multicollinearity.

The effect of partial noncompliance on the power of a clinical trial

Noncompliance is an important concern in randomized trials and must be taken into account when calculating sample sizes. The effect of noncompliance is usually assessed through a simple binary model that assumes that the patient either does or does not comply with the allocated treatment. In this article I present an example from cancer prevention, and show that different time courses of noncompliance can have different effects on the power, with widely varying estimates of the sample size required. The time course as well as the level of noncompliance should be considered when planning trials with long-term treatments.

Strengths and limitations of methodologic approaches to the study of diet and cancer: summary and future perspectives with emphasis on dietary fat and breast cancer

For many years, scientists have been studying the relationship between diet and certain cancers in animal and human population studies. With the exception of leukemia, nine of the leading cancers in humans may be associated positively or negatively with diet. Extensive literature reviewed by an expert group convened by the National Academy of Sciences concluded that the strongest evidence of an association between the incidence of certain cancers and dietary components is that for dietary fat, particularly for breast cancer (Committee on Diet, Nutrition and Cancer, National Research Council, National Academy of Sciences; Diet, Nutrition and Cancer; Washington, DC: National Academy Press, 1982). The conclusions reached by this group and the consensus of other advisory experts provided the rationale for the National Cancer Institute (NCI) to sponsor a multi-institutional breast cancer prevention trial. This trial was designed to test whether a diet containing 20% of calories from fat compared with the usual diet containing twice that amount would reduce breast cancer incidence in 45- to 69-year-old women. Ensuing controversies about the nature of the research evidence and methodologic issues related to the conduct of this trial led NCI, on advice of its counselors, to discontinue the full-scale implementation. It is clear from these debates that experts have looked at the same data and differed both in their interpretation and in their conception of what constitutes convincing evidence.