title: Propensity score to detect baseline imbalance in cluster randomized trials: the role of the c-statistic.
abstract: BACKGROUND
  Despite randomization, baseline imbalance and confounding bias may occur in cluster randomized trials (CRTs). Covariate imbalance may jeopardize the validity of statistical inferences if they occur on prognostic factors. Thus, the diagnosis of a such imbalance is essential to adjust statistical analysis if required.
  
  
  METHODS
  We developed a tool based on the c-statistic of the propensity score (PS) model to detect global baseline covariate imbalance in CRTs and assess the risk of confounding bias. We performed a simulation study to assess the performance of the proposed tool and applied this method to analyze the data from 2 published CRTs.
  
  
  RESULTS
  The proposed method had good performance for large sample sizes (n =500 per arm) and when the number of unbalanced covariates was not too small as compared with the total number of baseline covariates (≥40% of unbalanced covariates). We also provide a strategy for pre selection of the covariates needed to be included in the PS model to enhance imbalance detection.
  
  
  CONCLUSIONS
  The proposed tool could be useful in deciding whether covariate adjustment is required before performing statistical analyses of CRTs.
authors.affiliation: INSERM U1153, Paris, France. clemence.leyrat@lshtm.ac.uk.|INSERM CIC 1415, Tours, France. clemence.leyrat@lshtm.ac.uk.|CHRU de Tours, Tours, France. clemence.leyrat@lshtm.ac.uk.|Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom. clemence.leyrat@lshtm.ac.uk.
authors.forename: Clémence
authors.initials: C
authors.lastname: Leyrat
authors.affiliation: INSERM U1153, Paris, France.|INSERM CIC 1415, Tours, France.|CHRU de Tours, Tours, France.|Université François-Rabelais, PRES Centre-Val de Loire Université, Tours, France.
authors.forename: Agnès
authors.initials: A
authors.lastname: Caille
authors.affiliation: SPHERE (EA 4275): Biostatistics, Clinical Research and Subjective Measures in Health Sciences, Université de Nantes, Nantes, France.
authors.forename: Yohann
authors.initials: Y
authors.lastname: Foucher
authors.affiliation: INSERM U1153, Paris, France.|INSERM CIC 1415, Tours, France.|CHRU de Tours, Tours, France.|Université François-Rabelais, PRES Centre-Val de Loire Université, Tours, France.
authors.forename: Bruno
authors.initials: B
authors.lastname: Giraudeau
mesh_terms: D000368:Aged; D000465:Algorithms; D019295:Computational Biology / Q000379:methods* / Q000706:statistics & numerical data; D003198:Computer Simulation; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D020370:Osteoarthritis, Knee / Q000175:diagnosis / Q000628:therapy; D010147:Pain Measurement / Q000379:methods / Q000592:standards; D057216:Propensity Score; D016032:Randomized Controlled Trials as Topic / Q000379:methods / Q000592:standards*; D015203:Reproducibility of Results; D012107:Research Design / Q000592:standards*; D012680:Sensitivity and Specificity; D013223:Statistics as Topic / Q000379:methods