Papers › Time-varying Bayesian Network Meta-Analysis
Time-varying Bayesian Network Meta-Analysis
Patrick M. LeBlanc, David Banks
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
The presence of methicillin-resistant \textit{Staphylococus Aureus} (MRSA) in complicated skin and soft structure infections (cSSSI) is associated with greater health risks and economic costs to patients. There is concern that MRSA is becoming resistant to other "gold standard" treatments such as vancomycin, and there is disagreement about the relative efficacy of vancocymin compared to linezolid. There are several review papers employing Bayesian Network Meta-Analyses (BNMAs) to investigate which treatments are best for MRSA related cSSSIs, but none address time-based design inconsistencies. This paper proposes a time-varying BNMA (tBNMA), which models time-varying treatment effects across studies using a Gaussian Process kernel. A dataset is compiled from nine existing MRSA cSSSI NMA review papers containing 58 studies comparing 19 treatments over 19 years. tBNMA finds evidence of a non-linear trend in the treatment effect of vancomycin - it became less effective than linezolid between 2002 and 2007, but has since recovered statistical equivalence.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections