Recent journal publications

  1. Evrenoglou T, Boutron I, Seitidis G, Ghosn L, Chaimani A. metaCOVID: A web‐application for living meta‐analyses of COVID‐19 trials. Research Synthesis Methods 2023. Full text.
  2. Leucht S*, Chaimani A*, Krause M, Schneider-Thoma J, Wang D, Dong S, Samara M, Peter N, Huhn M, Priller J, Davis JM. The response of subgroups of patients with schizophrenia to different antipsychotic drugs: a systematic review and meta-analysis. Lancet Psychiatry 2022; 9(11):884-993. Full text.
  3. Evrenoglou T, White IR, Afach S, Mavridis D, Chaimani A. Network meta-analysis of rare events using penalized likelihood regression. Statistics in Medicine 2022. Full text
  4. Charitakis E, Metelli S, Karlsson LO, Antoniadis AP, Rizas K, Liuba I, Almroth H, Jönsson AH, Schweiler J, Tsartsalis D, Sideris S, Dragioti E, Fragakis N, Chaimani A. Comparing efficacy and safety in catheter ablation strategies for atrial fibrillation: a network meta-analysis of randomized controlled trials. BMC Medicine 2022; 20(1):1-13. Full text
  5. Davidson M, Menon S, Chaimani A, Evrenoglou T, Ghosn L, Grana C, et al. Interleukin‐1 blocking agents for treating COVID‐19. Cochrane Database of Systematic Reviews 2022;1(1):CD015308. Full text
  6. Guelimi R, Metelli S, Sbidian E, van Zuuren EJ, Flohr C, Leonardi-Bee J, Le Cleach L. Network meta-analysis: methodological points for readers, authors and reviewers. British Journal of Dermatology 2022;186(6):917-918. Full text
  7. Chaimani A, Porcher R, Sbidian E, Mavridis D. A Markov chain approach for ranking treatments in network meta‐analysis. Stat Med 2021; 40 (2), 451-464. Full text

New pre-prints

  1. Evrenoglou T, Metelli S, Thomas JS, Siafis S, Turner RM, Leucht S, Chaimani A. Sharing information across patient subgroups to draw conclusions from sparse treatment networks. arXiv:2301.09442. Full text.
  2. Metelli S, Chaimani A. NMAstudio web-application: A brief tutorial. Research Square 2002. Full text.
  3. Bouvier FB, Chaimani A, Gueyffier F, Grenet G, Porcher R. Estimating individualized treatment effects using individual participant data meta-analysis. HAL Open Science 2022. Full text.
  4. Metelli S, Mavridis D, Créquit P, Chaimani A. Bayesian model-based outlier detection in network meta-analysis. arXiv:2109.06559. Full text