Journal of clinical epidemiology
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To assess whether nominally statistically significant effects in meta-analyses of clinical trials are true and whether their magnitude is inflated. ⋯ Most meta-analyses with nominally significant results pertain to truly nonnull effects, but exceptions are not uncommon. The magnitude of observed effects, especially in meta-analyses with limited evidence, is often inflated.
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Rare diseases may be difficult to study through conventional research methods, but are amenable to study through certain uncommonly used designs. We sought to explain these designs and to provide a framework to assist researchers in identifying the most appropriate design for a given research question. ⋯ These techniques may facilitate research in rare diseases.
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Analyses comparing randomized to nonrandomized clinical trials suffer from the fact that the study populations are usually different. We aimed for a comparison of randomized clinical trials (RCTs) and propensity score (PS) analyses in similar populations. ⋯ In our example, treatment effects of off-pump versus on-pump surgery from RCTs and PS analyses were very similar in a "meta-matched" population of studies, indicating that only a small remaining bias is present in PS analyses.