Abstract

BackgroundDrug safety assessments in clinical trials present unique analytical challenges. Some of these include adjusting for individual follow-up time, repeated measurements of multiple outcomes and missing data among others. Furthermore, pre-specifying appropriate analysis becomes difficult as some safety endpoints are unexpected. Although existing guidelines such as CONSORT encourage thorough reporting of adverse events (AEs) in clinical trials, they provide limited details for safety data analysis. The limited guidelines may influence suboptimal analysis by failing to account for some analysis challenges above. A typical example where such challenges exist are trials of anti-malarial drugs for malaria prevention during pregnancy. Lack of proper standardized evaluation of the safety of antimalarial drugs has limited the ability to draw conclusions about safety. Therefore, a systematic review was conducted to establish the current practice in statistical analysis for preventive antimalarial drug safety in pregnancy.MethodsThe search included five databases (PubMed, Embase, Scopus, Malaria in Pregnancy Library and Cochrane Central Register of Controlled Trials) to identify original English articles reporting Phase III randomized controlled trials (RCTs) on anti-malarial drugs for malaria prevention in pregnancy published from January 2010 to July 2019.ResultsEighteen trials were included in this review that collected multiple longitudinal safety outcomes including AEs. Statistical analysis and reporting of the safety outcomes in all the trials used descriptive statistics; proportions/counts (n = 18, 100%) and mean/median (n = 2, 11.1%). Results presentation included tabular (n = 16, 88.9%) and text description (n = 2, 11.1%). Univariate inferential methods were reported in most trials (n = 16, 88.9%); including Chi square/Fisher’s exact test (n = 12, 66.7%), t test (n = 2, 11.1%) and Mann–Whitney/Wilcoxon test (n = 1, 5.6%). Multivariable methods, including Poisson and negative binomial were reported in few trials (n = 3, 16.7%). Assessment of a potential link between missing efficacy data and safety outcomes was not reported in any of the trials that reported efficacy missing data (n = 7, 38.9%).ConclusionThe review demonstrated that statistical analysis of safety data in anti-malarial drugs for malarial chemoprevention in pregnancy RCTs is inadequate. The analyses insufficiently account for multiple safety outcomes potential dependence, follow-up time and informative missing data which can compromise anti-malarial drug safety evidence development, based on the available data.

Highlights

  • Drug safety assessments in clinical trials present unique analytical challenges

  • There exist some general regulatory guidelines on safety data analysis, such as International Conference on Harmonization which recommend descriptive statistical methods supplemented by confidence intervals [3, 4], the proposed statistical methods rarely account for the complexity of the collected safety data, e.g., recurrent adverse events (AEs)

  • This review focused on Phase III Randomized clinical trial (RCT), because they have the largest sample size among pre-marketing trials and accommodates multidisciplinary support in safety evaluation

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Summary

Introduction

Drug safety assessments in clinical trials present unique analytical challenges Some of these include adjusting for individual follow-up time, repeated measurements of multiple outcomes and missing data among others. Pre-specifying appropriate analysis becomes difficult as some safety endpoints are unexpected Existing guidelines such as CONSORT encourage thorough reporting of adverse events (AEs) in clinical trials, they provide limited details for safety data analysis. Absence of standardized guidelines for safety data analysis in specific settings may limit the ability to draw rich conclusions about the safety of the investigational product, based on collected data. Standardized guidelines can simplify integration of safety information from multiple outcomes across RCTs [5] and would ensure optimal use of data in developing the safety profile of the investigational product

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