Relative contributions of baseline patient characteristics and the choice of statistical methods to the variability of genotypic resistance scores: the example of didanosine

Abstract

Background: Our aim was to investigate the respective role of statistical methodology and patients' baseline characteristics in the selection of mutations included in genotypic resistance scores.

Methods: As an example, the FORUM database on didanosine including 1453 patients was used. We split this population into four samples based on countries of enrolment (France n = 474, Italy n = 440, USA/Canada n = 219, others n = 320). We used both a continuous outcome measure (the viral load reduction at week 8) and a binary outcome measure (viral load decline at week 8 <0.6 log(10) or > or =0.6 log(10)) and both parametric and non-parametric methods for each outcome.

Results: Overall, 61 distinct mutations were selected by at least one method in at least one data set. The variability due to baseline characteristics varies from 79% to 88%, i.e. for a given method applied to the four data sets >80% of the mutations are selected only once. The variability induced by the methodology varies from 49% to 56%, i.e. for a given data set approximately 50% of the mutations are selected by at least two methods.

Conclusions: Baseline patient characteristics contribute more than the choice of statistical method to the variability of the mutations to be included in the genotypic resistance scores.