Validation of a model predicting enrollment status in a chemoprevention trial for breast cancer.

We evaluated the performance of a regression model in predicting enrollment status in a chemoprevention trial for breast cancer using a population independent of that from which the model was derived. In years 1 and 2 of recruitment, questionnaires were completed by eligible participants following attendance at informational meetings about the Breast Cancer Prevention Trial. The variables in the original model, based on women recruited in year 1, included not being able to take estrogen replacement therapy (ERT), concern about the side effects of tamoxifen, the possibility of getting a placebo, the out-of-pocket expenses associated with the trial, and disagreement with the statement "significant others would be reassured if the respondent was taking tamoxifen." These variables were used to predict enrollment status of women newly recruited to the trial in year 2. Among the 89 women in the study population who responded to the questionnaire, 66% did not enroll in the trial. By applying the original logistic regression model, enrollment status in the trial was correctly predicted for 72% of year 2 questionnaire respondents. Age and risk scores, as binary variables, were used in a derived logistic model to determine whether they provided additional predictive information on enrollment status. The resulting four-factor model, which predicted nonenrollment, included: age of > or = 50 years, not being able to take ERT, expressed concern that significant others would not be reassured if the respondent was taking tamoxifen, and concern about out-of-pocket expenses associated with the trial. This model correctly classified 76% of the respondents. The logistic regression models performed reasonably well in predicting enrollment status. Not being able to take ERT remained the strongest factor predicting nonenrollment. More research is needed to evaluate factors that motivate persons to seek participation in primary chemoprevention trials in culturally diverse populations.

Factors related to enrollment in the breast cancer prevention trial at a comprehensive cancer center during the first year of recruitment.

BACKGROUND: Using an a priori theoretic model of behavior change, factors predicting enrollment in a randomized chemoprevention trial during the first year of recruitment were assessed prospectively. METHODS: Eligible participants were asked to complete a 90-item semistructured questionnaire after attendance at an informational meeting. Components of the Health Belief Model (including perceived susceptibility, perceived severity, perceived benefits and barriers, cues to action, and health motivation), health status, preventive health behaviors, and social influence were assessed in relation to enrollment. RESULTS: Overall, 331 women attended one of the meetings, and 73% completed a questionnaire; 45% enrolled on the trial and 55% did not. In bivariate analyses, all but one of the perceived barriers were associated negatively with enrollment; however, items assessing perceived susceptibility, perceived severity, and perceived benefits were not. Nonparticipants also were more likely to be over 49 years of age, to be currently or to have been on estrogen replacement therapy, and to have had hot flashes. In logistic regression analysis, not being able to take estrogen replacement therapy was the strongest predictor of nonparticipation (odds ratio [OR], 12.13, 95% confidence interval [CI], 3.63, 40.60). Other factors associated with nonparticipation were concern about side effects of tamoxifen (OR, 5.06; CI, 2.37, 10.80); the possibility of getting a placebo (OR, 7.75; CI, 1.51, 39.67); the costs associated with the trial (OR, 3.21; CI, 1.12, 9.24); and absence of concern that significant others would be reassured if the respondent was taking tamoxifen (OR, 2.58; CI, 1.04, 6.41). CONCLUSIONS: These findings support the view that recruitment efforts for chemoprevention trials should address barriers specific to their circumstances. In addition, increasing the support available from personal social networks may enhance recruitment to chemoprevention trials for breast cancer.