Analysis of combined data from heterogeneous study designs: an applied example from the patient navigation research program.

BACKGROUND: The Patient Navigation Research Program (PNRP) is a cooperative effort of nine research projects, with similar clinical criteria but with different study designs. To evaluate projects such as PNRP, it is desirable to perform a pooled analysis to increase power relative to the individual projects. There is no agreed-upon prospective methodology, however, for analyzing combined data arising from different study designs. Expert opinions were thus solicited from the members of the PNRP Design and Analysis Committee. PURPOSE: To review possible methodologies for analyzing combined data arising from heterogeneous study designs. METHODS: The Design and Analysis Committee critically reviewed the pros and cons of five potential methods for analyzing combined PNRP project data. The conclusions were based on simple consensus. The five approaches reviewed included the following: (1) analyzing and reporting each project separately, (2) combining data from all projects and performing an individual-level analysis, (3) pooling data from projects having similar study designs, (4) analyzing pooled data using a prospective meta-analytic technique, and (5) analyzing pooled data utilizing a novel simulated group-randomized design. RESULTS: Methodologies varied in their ability to incorporate data from all PNRP projects, to appropriately account for differing study designs, and to accommodate differing project sample sizes. LIMITATIONS: The conclusions reached were based on expert opinion and not derived from actual analyses performed. CONCLUSIONS: The ability to analyze pooled data arising from differing study designs may provide pertinent information to inform programmatic, budgetary, and policy perspectives. Multisite community-based research may not lend itself well to the more stringent explanatory and pragmatic standards of a randomized controlled trial design. Given our growing interest in community-based population research, the challenges inherent in the analysis of heterogeneous study design are likely to become more salient. Discussion of the analytic issues faced by the PNRP and the methodological approaches we considered may be of value to other prospective community-based research programs.

Time to definitive diagnosis of breast cancer in Latina and non-Hispanic white women: the six cities study.

Time delay after an abnormal screening mammogram may have a critical impact on tumor size, stage at diagnosis, treatment, prognosis, and survival of subsequent breast cancer. This study was undertaken to evaluate disparities between Latina and non-Hispanic white (NHW) women in time to definitive diagnosis of breast cancer after an abnormal screening mammogram, as well as factors contributing to such disparities. As part of the activities of the National Cancer Institute (NCI)-funded Redes En Acción research network, clinical records of 186 Latinas and 74 NHWs who received abnormal screening mammogram results were reviewed to determine the time to obtain a definitive diagnosis. Data was obtained from participating clinics in six U.S. cities and included demographics, clinical history, and mammogram characteristics. Kaplan-Meier estimates and Cox proportional hazards models were used to test differences in median time to definitive diagnosis by ethnicity after adjusting for clinic site, demographics, and clinical characteristics. Time-to-event analysis showed that Latinas took 2.2 times longer to reach 50% definitively diagnosed with breast cancer relative to NHWs, and three times longer to reach 80% diagnosed (p=0.001). Latinas' median time to definitive diagnosis was 60 days compared to 27 for NHWs, a 59% gap in diagnosis rates (adjusted Hazard Ratio [aHR] = 1.59, 95% CI = 1.09, 2.31; p=0.015). BI-RADS-4/5 women's diagnosis rate was more than twice that of BI-RADS-3 (aHR = 2.11, 95% CI = 1.18, 3.78; p=0.011). Disparities in time between receipt of abnormal screening result and definitive diagnosis adversely affect Latinas compared to NHWs, and remain significant after adjusting for demographic and clinical variables. With cancer now the leading cause of mortality among Latinos, a greater need exists for ethnically and culturally appropriate interventions like patient navigation to facilitate Latinas' successful entry into, and progression through, the cancer care system.