Propensity score to detect baseline imbalance in cluster randomized trials: the role of the c-statistic.

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. CONCLUSION: The proposed tool could be useful in deciding whether covariate adjustment is required before performing statistical analyses of CRTs

Parent-Offspring Correlations in Pedometer-Assessed Physical Activity

Physical activity is a major component of a healthy lifestyle in youth and adults. To identify determinants of this complex behavior is an important research objective in the process of designing interventions to promote physical activity at population level. In addition to individual determinants, there is evidence documenting familial influences on physical activity. However, the few studies that have addressed this issue with objective measures did not provide data on parent-offspring physical activity relationships throughout childhood and adolescence. The purpose of this study was to assess familial correlations in pedometer-assessed physical activity.We measured ambulatory activity in 286 French nuclear families (283 mothers, 237 fathers, and 631 children aged 8-18 years) by pedometer recordings (Yamax Digiwalker DW 450) over a week. Correlations were computed with their 95% confidence intervals (CI) for spouse pairs, siblings, mother-offspring, and father-offspring. Data were expressed as steps per day and computed both for the full recording period and separately for weekdays and weekends.The correlations were the highest between siblings (r=0.28, 95%CI: 0.17-0.38). Parent-offspring correlations were significant in mothers (r=0.21, 95%CI: 0.12-0.30), especially between mothers and daughters (r=0.24, 95%CI: 0.12-0.36 vs. r=0.18, 95%CI: 0.05-0.31 for sons), but were almost nonexistent in fathers. Correlations were generally higher on weekend days compared to weekdays. Mother-offspring correlations did not decrease with increasing age of children (r=0.17, 95%CI: 0.00-0.34 in 8-11-year-olds, r=0.20, 95%CI: 0.07-0.33 in 12-15-year-olds, and r=0.25, 95%CI: 0.07-0.39 in ≥16-year-olds). Finally, between-spouse correlations were significant only during weekend days (r=0.14, 95%CI: 0.01-0.27).Ambulatory activity correlated within families, with a possible mother effect. Mother-offspring correlations remained significant through the transition from childhood to adolescence. Further studies are required to better understand the respective influences of shared activities, parental modeling and support as well as genetic factors on the familial aggregation of physical activity

Peer Review of Grant Applications: A Simple Method to Identify Proposals with Discordant Reviews

Grant proposals submitted for funding are usually selected by a peer-review rating process. Some proposals may result in discordant peer-review ratings and therefore require discussion by the selection committee members. The issue is which peer-review ratings are considered as discordant. We propose a simple method to identify such proposals. Our approach is based on the intraclass correlation coefficient, which is usually used in assessing agreement in studies with continuous ratings

Urinary Elimination of Coproporphyrins Is Dependent on ABCC2 Polymorphisms and Represents a Potential Biomarker of MRP2 Activity in Humans

MRP2 encoded by ABCC2 gene is involved in the secretion of numerous drugs and endogenous substrates. Patients with Dubin-Johnson syndrome due to mutation in ABCC2 gene have elevated urinary coproporphyrin ratio (UCP I/(I + III)). Here we investigated whether this ratio could serve as a biomarker of MRP2 function. Phenotype-genotype relationships were studied in 74 healthy subjects by measuring individual UCP I/(I + III) ratio obtained on 24-hour urine and by analyzing five common SNPs in ABCC2 gene. The UCP I/(I + III) ratio varied from 14.7% to 46.0% in our population. Subjects with 3972TT genotype had a higher ratio (P = .04) than those carrying the C allele. This higher UCP I/(I + III) ratio was correlated with a higher level of isomer I excretion. This study provides a proof of concept that UCP I/(I + III) ratio can be used as a biomarker of MRP2 function in clinical studies as it provides quantitative information about the in vivo activity of MRP2 in a given patient

A Comparison of Imputation Strategies in Cluster Randomized Trials with Missing Binary Outcomes

International audienceIn cluster randomized trials, clusters of subjects are randomized rather than subjects themselves, and missing outcomes are a concern as in individual randomized trials. We assessed strategies for handling missing data when analysing cluster randomized trials with a binary outcome; strategies included complete case, adjusted complete case, and simple and multiple imputation approaches. We performed a simulation study to assess bias and coverage rate of the population-averaged intervention-effect estimate. Both multiple imputation with a random-effects logistic regression model or classical logistic regression provided unbiased estimates of the intervention effect. Both strategies also showed good coverage properties, even slightly better for multiple imputation with a random-effects logistic regression approach. Finally, this latter approach led to a slightly negatively biased intracluster correlation coefficient estimate but less than that with a classical logistic regression model strategy. We applied these strategies to a real trial randomizing households and comparing ivermectin and malathion to treat head lice

Fallopian tube prolapse after hysterectomy: a systematic review.

BACKGROUND:Prolapse of the fallopian tube into the vaginal vault is a rarely reported complication that may occur after hysterectomy. Clinicians can miss the diagnosis of this disregarded complication when dealing with post-hysterectomy vaginal bleeding. OBJECTIVES:We performed a systematic review in order to describe the clinical presentation, therapeutic management and outcome of fallopian tube prolapse occurring after hysterectomy. SEARCH STRATEGY:A systematic search of MEDLINE and EMBASE references from January 1980 to December 2010 was performed. We included articles that reported cases of fallopian tube prolapse after hysterectomy. Data from eligible studies were independently extracted onto standardized forms by two reviewers. RESULTS:Twenty-eight articles including 51 cases of fallopian tube prolapse after hysterectomy were included in this systematic review. Clinical presentations included abdominal pain, dyspareunia, post- coital bleeding, and/or vaginal discharge. Two cases were asymptomatic and diagnosed at routine checkup. The surgical management reported comprised partial or total salpingectomy, with vaginal repair in some cases combined with oophorectomy using different approaches (vaginal approach, combined vaginal-laparoscopic approach, laparoscopic approach, or laparotomy). Six patients were initially treated by silver nitrate application without success. CONCLUSIONS:This systematic review provided a precise summary of the clinical characteristics and treatment of patients presenting with fallopian tube prolapse following hysterectomy published in the past 30 years. We anticipate that these results will help inform current investigations and treatment

A comparison of imputation strategies in cluster randomized trials with missing binary outcomes.

In cluster randomized trials, clusters of subjects are randomized rather than subjects themselves, and missing outcomes are a concern as in individual randomized trials. We assessed strategies for handling missing data when analysing cluster randomized trials with a binary outcome; strategies included complete case, adjusted complete case, and simple and multiple imputation approaches. We performed a simulation study to assess bias and coverage rate of the population-averaged intervention-effect estimate. Both multiple imputation with a random-effects logistic regression model or classical logistic regression provided unbiased estimates of the intervention effect. Both strategies also showed good coverage properties, even slightly better for multiple imputation with a random-effects logistic regression approach. Finally, this latter approach led to a slightly negatively biased intracluster correlation coefficient estimate but less than that with a classical logistic regression model strategy. We applied these strategies to a real trial randomizing households and comparing ivermectin and malathion to treat head lice

Dichotomizing a continuous outcome in cluster randomized trials: impact on power.

In cluster randomized trials (CRTs), clusters of individuals are randomized rather than the individuals themselves. For such trials, power depends in part on the degree of similarity among responses within a cluster, which is quantified by the intaclass correlation coefficient (ICC). Thus, for a fixed sample size, power decreases with increasing ICC. In reliability studies with two observers, dichotomizing a continuous outcome variable has been shown to reduce the ICC. We checked (by a simulation study) that this property still applies to CRTs, in which cluster sizes are variable and usually greater than in reliability studies and observations (within clusters) are exchangeable. Then, in a CRT, dichotomizing a continuous outcome actually induces two antagonistic effects: decreased power because of loss of information and increased power induced by attenuation of the ICC. Therefore, we aimed to assess the impact of dichotomizing a continuous outcome on power in a CRT. We derived an analytical formula for power based on a generalized estimating equation approach after dichotomizing a continuous outcome. This theoretical result was obtained by considering equal cluster sizes, and we then assessed its accuracy (by a simulation study) in the more realistic situation of varying cluster sizes. We showed that dichotomization is associated with decreased power: attenuation of the ICC does not compensate for the loss of power induced by loss of information. Loss of power is reduced with increased initial continuous-outcome ICC and/or prevalence of success for the dichotomized outcome approaching 50%