Evaluating antimalarial efficacy in single-armed and comparative drug trials using competing risk survival analysis:...

Area of Science:

• * Epidemiology
• * Biostatistics
• * Infectious Diseases

Background:

• * Antimalarial drug efficacy studies for Plasmodium falciparum are complicated by new infections, which act as competing risks that can obscure recrudescence events.
• * Current World Health Organization (WHO) guidelines recommend censoring these competing risks, potentially affecting the accuracy of efficacy estimates.

Purpose of the Study:

• * To investigate the impact of treating new infections as competing risks on antimalarial efficacy estimations.
• * To compare different statistical approaches in single-armed and comparative antimalarial drug trials.

Main Methods:

• * Two simulation studies were conducted to assess the influence of competing risks on efficacy estimates.
• * Study 1 compared the Kaplan-Meier (K-M) estimate complement with the Cumulative Incidence Function (CIF) across varying malaria transmission intensities.
• * Study 2 extended the comparison to a comparative drug trial setting, evaluating the log-rank test for K-M curves and Gray's k-sample test for CIFs.

Main Results:

• * The K-M complement method yielded higher cumulative treatment failure estimates than the CIF method, with overestimation increasing in higher transmission settings.
• * For a 90% drug efficacy, overestimation ranged from 0.3% in low to 3.1% in high transmission areas.
• * In comparative scenarios, the log-rank test demonstrated greater power than Gray's k-sample test for detecting treatment differences.

Conclusions:

• * The CIF approach is recommended for estimating antimalarial efficacy, particularly in high-transmission areas or when evaluating drugs with potential failures.
• * Comparative studies require careful selection of statistical tests based on whether the outcome of interest is the rate or cumulative risk of recrudescence.
• * Consideration of the differing prophylactic periods of compared antimalarials is crucial for accurate trial interpretation.