Statistical methods in the analysis of multicentre HIV randomized controlled trials in the African region: a scoping review

BMC Med Res Methodol. 2025 Jan 8;25(1):3. doi: 10.1186/s12874-024-02441-w.

Abstract

Background: The majority of phase 3 clinical trials are implemented in multiple sites or centres, which inevitably leads to a correlation between observations from the same site or centre. This correlation must be carefully considered in both the design and the statistical analysis to ensure an accurate interpretation of the results and reduce the risk of biased results. This scoping review aims to provide a detailed statistical method used to analyze data collected from multicentre HIV randomized controlled trials in the African region.

Methods: This review followed the methodological framework proposed by Arksey and O'Malley. We searched four databases (PubMed, EBSCOhost, Scopus, and Web of Science) and retrieved 977 articles, 34 of which were included in the review.

Results: Data charting revealed that the most used statistical methods for analysing HIV endpoints in multicentre randomized controlled trials in Africa were standard survival analysis techniques (24 articles [71%]). Approximately 47% of the articles used stratified analysis methods to account for variations across different sites. Out of 34 articles reviewed, only 6 explicitly considered intra-site correlation in the analysis.

Conclusions: Our scoping review provides insights into the statistical methods used to analyse HIV data in multicentre randomized controlled trials in Africa and highlights the need for standardized reporting of statistical methods.

Keywords: HIV/AIDS trials; Multicentre trials; Randomized control trials; Scoping review.

Publication types

  • Review

MeSH terms

  • Africa / epidemiology
  • Data Interpretation, Statistical
  • HIV Infections* / drug therapy
  • Humans
  • Multicenter Studies as Topic* / methods
  • Randomized Controlled Trials as Topic* / methods
  • Randomized Controlled Trials as Topic* / statistics & numerical data
  • Research Design / statistics & numerical data