Multiply adjusted comparisons: A meta-analysis method to compare single-arm clinical-trial data to literature results regarding a competitor. (March 2019)

• Record Type: Journal Article
• Authors: Boethig, Dietmar; Hecker, Hartmut
• Is Part Of: Statistical methods in medical research. Volume 28:Number 3(2019)
• Page Start: 644
• Page End: 669
• Publication Date: 2019-03
• Subjects: Meta-analysis -- evidence-based medicine -- non-randomized controlled trials -- statistical model; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280217733776
• Languages: English
• ISSNs: 0962-2802

Abstract

Prospective randomized controlled trials are difficult to obtain if a promising new therapy has to be tested against seemingly obsolete alternatives. One method to address this problem is to compare the results of (multicentre) trials to literature results. However, previous treatment-era changes and population-dependent results complicate objective comparisons. The presented approach describes a method to objectify such comparisons in cases in which individual raw data regarding a new therapy have to be compared to summary results regarding a conventional alternative published in the literature. The chosen example is the introduction of bovine neck veins as a substitute for dysfunctional human pulmonary valves, and the conventional therapeutic alternative is pulmonary-artery homografts. Literature research, subgroup identification, filtering, endpoint remodelling, weighting and, if necessary, confidence-limit calculation yield adjusted comparisons. These individual comparisons are then aggregated, first by article and then over several articles (similar to meta-analyses), resulting in a differentiated panel of answers (Multiply Adjusted Comparisons). In situations in which extensive raw data regarding a new therapeutic alternative but no randomized controlled trials and no raw data from previous studies using the conventional therapeutic alternative are available, the proposed method identifies the best evidence and is by far superior to unadjusted direct comparisons or gut feelings.