A randomized design for repeated binary outcomes used to evaluate continued effectiveness of a breast cancer control intervention strategy.
The literature has not discussed in detail design and evaluation strategies for the assessment of continued effectiveness of intervention strategies. In this article we present an approach to evaluating continued effectiveness with two repeated binary outcomes that are related to the use of preventive services. We present a two-stage design with independent randomization procedures for each of two successive controlled trials and discuss the implications of the randomization plan for the statistical evaluation. Intervention effectiveness for each year is determined by an adjusted odds ratio that compares the odds of procedure use for those who received the intervention to those who did not. Changes in the two adjusted odds ratios between successive years are assessed within the context of a regressive logistic model. We demonstrate these methods by applying them to the Metropolitan Detroit Project to Reduce Avoidable Mortality from Breast Cancer. In this project, computer-generated physician mammography reminders placed prominently in medical records were used to promote mammography referrals among women visiting primary care clinics during a 2-year intervention period. An assessment of the change in intervention effectiveness as well as an adjusted estimate of the overall intervention effectiveness for the 2 years were obtained from a multivariate regressive logistic model. The advantage of this approach was its potential for reducing bias and producing a balanced comparison between intervention groups during the second year of intervention. This issue was important because previous work indicated that having had a mammogram had a significant impact on subsequent mammography use. An important component in the implementation of this design was an information management system that facilitated doing two randomization procedures efficiently. As information and computer technology advance, and as more sophisticated information systems are used for data management, designs such as these become reasonable alternatives to consider.
Gimotty
P A
PA
Barbara Ann Karmanos Cancer Institute and Department of Internal Medicine, School of Medicine, Wayne State University, Detroit, Michigan, USA.
Burack
R C
RC
George
J
J
D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000000981:diagnostic imaging / Q000517:prevention & control*; D015331:Cohort Studies; D005260:Female; D006293:Health Promotion; D006801:Humans; D016015:Logistic Models; D008327:Mammography; D008875:Middle Aged; D015233:Models, Statistical; D010818:Practice Patterns, Physicians'; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D017010:Reminder Systems; D012107:Research Design