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 lion with only two legs

International audienceA lion with only two legsIn the randomized controlled trial reported by Harter et al. [1] 647 women with IIB-IV International Federation of Gynecology and Obstetrics stage ovarian cancer who had undergone macroscopically complete resection and whose lymph nodes were normal before and during surgery were enrolled. Patients were randomized to undergo lymphadenectomy (n = 323 patients) or not (n = 324 patients). The primary outcome was overall survival. Analysis was performed with a two-sided stratified log-rank test. For sample size calculation, the authors, based on previous studies, assumed a 3-year overall survival rate of 76 % in the no lymphadenectomy group and hypothesized a hazard ratio of 0.7, corresponding to a 3-year overall survival rate of 82.5 % in the lymphadenectomy group. With a planned enrolment period of 3 years and 6 years follow-up phase, and accounting for potential dropout rate of 10 %, they reported a needed sample size of 640 patients to ensure a power of 80 %.We re-calculated the required sample size calculation using nQuery Advisor 3.0. This trial would actually have necessitated the inclusion of 612 patients per group to observe 247 deaths, and, after taking into account a potential dropout rate of 10 %, the sample size would have been 680 patients per group and thus 1360 patients in total.It seems that the total required sample size reported for this trial was actually the per-group required sample size. Keeping the same hypothesis of a 0.7 hazard ratio, the nominal power of the trials was actually 52 %. Surprisingly, such an error was missed when the project was selected for funding, during regulatory and ethical approvals and finally during the reviewing process.Such a situation raises a major issue regarding this trial, although nothing can no longer be changed. Two comments can be made. The first one is that according to the overall survival curves presented in their article (The median overall survival was 65.5 months in the lymphadenectomy group and 69.2 months in the nolymphadenectomy group, hazard ratio for death in the lymphadenectomy group, 1.06; 95 % CI, 0.83-1.34; P = 0.65), we can assume that even with an adequate sample size of 1360, the results would have been qualitatively the same. Things would have been much more troublesome in case a clinically relevant difference would have been observed without being statistically significant.Second, results of underpowered trial are better than none and could further be included in a future meta-analysis.</div

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

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