Back

A novel framework for quantifying the clinical impact of substandard and falsified antimicrobials: application to typhoid fever.

Cavany, S. M.; Adipo, L.; van Assche, K.; Caillet, C.; Dolecek, C.; Hauk, C.; Mendes, J.; Nanyonga, S.; Stoesser, N.; Newton, P. N.; Parry, C.; Cooper, B. S.

2025-07-11 infectious diseases
10.1101/2025.07.08.25331006 medRxiv
Show abstract

SynopsisO_ST_ABSObjectivesC_ST_ABSSubstandard and falsified (SF) medicines are a neglected public health threat, with an estimated 7% of antimicrobials in low- and middle-income countries SF. However, quantifying their clinical impact remains challenging. We developed a general framework for estimating population-level impacts of SF antimicrobials on patient outcomes and apply it to SF fluoroquinolones in typhoid treatment. Patients and methodsThe framework combines two data sources: published surveys of antimicrobial quality to characterize the distribution of active pharmaceutical ingredient (API) content and individual-level patient data to estimate dose-response relationships. These are synthesized to evaluate population-level impacts. We extracted data from surveys of fluoroquinolone quality and fitted generalized additive models to data from seven clinical trials to estimate the causal effect of ofloxacin dose on typhoid outcomes. ResultsApplication to typhoid demonstrated that while dose had negligible overall effect within trial dose ranges, lower doses worsened outcomes for non-susceptible strains. When the minimum inhibitory concentration was 1 mg/L, ofloxacin matching observed ofloxacin quality (mean %API=102.8%) improved fever clearance by 4.1 hours (90% CrI: 0.75-8.7) compared to 100% API. At the same minimum inhibitory concentration, ofloxacin whose %API instead matched the ciprofloxacin surveys (mean %API=93.6%) worsened fever clearance by 11 hours (90% CrI: 1.9- 25). ConclusionsThis framework can quantify the impact of SF antimicrobials on different pathogen- antimicrobial pairs. For typhoid, it demonstrates that SF fluoroquinolones likely have a substantial impact on treatment outcomes in settings like South Asia where non-susceptible strains are prevalent. Increased vigilance around antimicrobial quality is important in such settings.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.