Analysis of an ordinal outcome in a multicentric randomized controlled trial: application to a 3- arm anti- malarial drug trial in Cameroon

Abstract

BackgroundMalaria remains a burden in Sub-Saharan Countries. The strategy proposed by the World Health Organization (WHO) is to systematically compare the therapeutic efficacy of antimalarial drugs using as primary outcome for efficacy, a four-category ordered criterion. The objective of the present work was to analyze the treatment effects on this primary outcome taking into account both a center-effect and individual covariates. A three-arm, three-centre trial of Amodiaquine (AQ), sulfadoxine-pyrimethamine (SP) and their combination (AQ + SP), conducted by OCEAC-IRD in 2003, in 538 children with uncomplicated Plasmodium falciparum malaria, is used as an illustration.MethodsAnalyses were based on ordinal regression methods, assuming an underlying continuous latent variable, using either the proportional odds (PO) or the proportional hazards (PH) models. Different algorithms, corresponding to both frequentist- and bayesian-approaches, were implemented using the freely available softwares R and Winbugs, respectively. The performances of the different methods were evaluated on a simulated data set, and then they were applied on the trial data set.ResultsGood coverage probability and type-1 error for the treatment effect were achieved. When the methods were applied on the trial data set, results highlighted a significance decrease of SP efficacy when compared to AQ (PO, odds ratio [OR] 0.14, 95% confidence interval [CI] 0.04-0.57; hazard ratio [HR] 0.605, 95% CI 0.42-0.82), and an equal effectiveness between AQ + SP and AQ (PO, odds ratio [OR] 1.70, 95% confidence interval [CI] 0.25-11.44; hazard ratio [HR] 1.40, 95% CI 0.88-2.18). The body temperature was significantly related to the responses. The patient weights were marginally associated to the clinical response.ConclusionThe proposed analyses, based on usual statistical packages, appeared adapted to take into account the full information contained in the four categorical outcome in malaria trials, as defined by WHO, with the possibility of adjusting on individual and global covariates.

Methodological approaches for analysing data from therapeutic efficacy studies

“…This approach was applied to clinical studies conducted in Cameroon at the time when the WHO was recommending a 14-day follow-up for areas of intense transmission [5,9,10]. Individual patient data were available.…”

“…Categories can be ordered from the worst to the best or vice-versa. The odds ratio of comparison of drug A versus drug B is interpreted as either a progression towards success or progression towards failure [9]. Although the results of this retrospective study can no longer be of help for drug policy change since monotherapies are not used for the treatment of acute uncomplicated malaria, the application of the method illustrates the potential of alternative statistical methods.…”

“…This paper presents three approaches and areas of reflexion on how statistical analysis of existing database on anti-malarial drug efficacy can provide still unmined information. These approaches were presented in detail in previous works using data from therapeutic efficacy studies conducted in Cameroon [9][10][11]. They include (i) analysis of the ordinal outcome at a single time-point (day 14); (ii) analysis of the ordinal outcome over several time-points (day 14, day 21, and day 28); and (iii) network meta-analysis (NMA).…”

Model-based random forests for ordinal regression

“…Many disease stages or health conditions in clinical research are quantified by ordinal scores (Whegang, Basco, Gwét, and Thalabard, 2010, Roozenbeek, Lingsma, Perel, Edwards, Roberts, Murray, Maas, and Steyerberg, 2011, Tanadini, Steeves, Curt, and Hothorn, 2016, Peterson, Vock, Powers, Emery, Cruz, Hunsberger, Jain, Pett, Neaton, and Group, 2017, among many others). However, statistical methods commonly used for the analyses of ordinal score outcomes, most prominently approaches originally developed for continuous outcomes, seldom take into account the underlying structure of the outcome variable.…”

Multiple treatment comparisons in a series of anti-malarial trials with an ordinal primary outcome and repeated treatment evaluations

“…However, this previous work faced two limits: (i) a binary criterion was used instead of the recommended primary categorical outcome, and (ii) data were fitted separately on days 14 and 28, even though repeated measurements for each individual were available. A possible solution of the first limitation, concerning the use of a binary criterion instead of the primary categorical outcome, was proposed in a subsequent work [ 6 ], by analysing the data set on day 14 using the primary outcome as categorical. The second issue regarding repeated measurements on days 14, 21 and 28 of the primary outcome is considered in the present work with the aim to integrate the repeated measurements of the categorical outcome in a global meta-analysis approach.…”