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Abstract: Objective: To compare statistical models for the analysis of two-state disease processes. Study Design and Setting: A two-armed randomized trial of patients with early rheumatoid arthritis (RA) treated by either combination therapy (sulfasazaline, methotrextate, prednisolone) or monotherapy (sulfasazaline). Disease activity (remission or relapse) was analyzed with the logistic regression model, the proportional hazards regression model, and the continuous-time Markov process model for panel data. The dependence among the switching times was studied by (1) including correlated normal random patient effects for the relapse–remission and remission–relapse switching probabilities; (2) assuming the population to be a mixture of patients responsive and nonresponsive to therapy; (3) including separate parameters for the first and subsequent relapse–remission switch; and (4) combining (1) and (3). The four approaches were compared using parametric bootstrap checks. Results: The logistic regression model, the proportional hazards regression model, and the continuous-time Markov process model for panel data yielded similar combination therapy effects. The inclusion of random patient effects (approaches 1 and 4) gave the best fit to the observed disease activity pattern. Conclusion: Models with correlated random effects can provide a satisfactory fit to two-state disease patterns. [Copyright &y& Elsevier]

Abstract: Objective: Our purpose was to measure the agreement, reliability, construct validity, and feasibility of a measurement tool to assess systematic reviews (AMSTAR). Study Design and Setting: We randomly selected 30 systematic reviews from a database. Each was assessed by two reviewers using: (1) the enhanced quality assessment questionnaire (Overview of Quality Assessment Questionnaire [OQAQ]); (2) Sacks'' instrument; and (3) our newly developed measurement tool (AMSTAR). We report on reliability (interobserver kappas of the 11 AMSTAR items), intraclass correlation coefficients (ICCs) of the sum scores, construct validity (ICCs of the sum scores of AMSTAR compared with those of other instruments), and completion times. Results: The interrater agreement of the individual items of AMSTAR was substantial with a mean kappa of 0.70 (95% confidence interval [CI]: 0.57, 0.83) (range: 0.38–1.0). Kappas recorded for the other instruments were 0.63 (95% CI: 0.38, 0.78) for enhanced OQAQ and 0.40 (95% CI: 0.29, 0.50) for the Sacks'' instrument. The ICC of the total score for AMSTAR was 0.84 (95% CI: 0.65, 0.92) compared with 0.91 (95% CI: 0.82, 0.96) for OQAQ and 0.86 (95% CI: 0.71, 0.94) for the Sacks'' instrument. AMSTAR proved easy to apply, each review taking about 15 minutes to complete. Conclusions: AMSTAR has good agreement, reliability, construct validity, and feasibility. These findings need confirmation by a broader range of assessors and a more diverse range of reviews. [Copyright &y& Elsevier]