Background
Individual-patient data meta-analysis (IPD-MA) is an increasingly popular approach because of its analytical benefits. IPD-MA of observational studies must overcome the problem of confounding, otherwise biased estimates of treatment effect may be obtained. One approach to reducing confounding bias could be the use of propensity score matching (PSM). IPD-MA can be considered as two-stage clustered data (patients within studies) and propensity score matching can be implemented within studies, across studies, and combining both.
Methods
This article focuses on implementation of four PSM-based approaches for the analysis of data structure that exploit IPD-MA in two ways: (i) estimation of propensity score model using single-level or random-effects logistic regression; and (ii) matching of propensity scores (PS) across studies, within studies or preferential-within studies. We investigated the performance of these approaches through a simulation study, which considers an IPD-MA that examined the success of different treatments for multidrug-resistant tuberculosis (MDR-TB). The simulation parameters were varied according to three treatment prevalences (according to studies, 50% and 30%), three levels of heterogeneity between studies (low, moderate and high) and three levels of pooled odds ratio (1, 1.5, 3).
Results
All approaches showed greater biases at the higher levels of heterogeneity regardless of the choices of treatment prevalences. However, matching of propensity scores using within-study and preferential-within study reported better performance compared to matching across studies when treatment prevalence varied across-studies. For fixed prevalences, a random-effect propensity score model to estimate propensity scores followed by matching of propensity scores across-studies achieved lower biases compared to other PSM-based approaches.
Conclusions
Propensity score matching has wide application in health research while only limited literature is available on the implementation of PSM methods in IPD-MA, and until now methodological performance of PSM methods have not been examined. We believe, this work offers an intuition to the applied researcher for the choice of the PSM-based approaches.
Ciprofloxacin (200 mg) was infused to seven patients at the beginning of elective colorectal surgery. Thirty minutes after the end of infusion (i.e. 60 min after the start of the operation) ciprofloxacin reached concentrations of 1.60 mg/l in serum and of 3.42-6.07 mg/kg fresh weight in the ileum and colon. During the next 30 min (90 min after the start of operation) the concentration of ciprofloxacin in serum decreased to 86% of its initial level, but this decrease was less rapid than that observed in the ileal (to 56.8%) or colonic (to 74.8%) mucosa. Three metabolites could be identified (desethylen-, sulpho-, oxociprofloxacin). Initially, at 60 min the amount of these metabolites was about 15% of the total drug concentration in serum, but only 2-3% of that in the gut tissues. At 90 min the relative amount of metabolites was increased in serum as well as in the gut tissues. It is concluded that transintestinal elimination of ciprofloxacin is a general feature of the whole gut. Obviously, the elimination process is not due to degradation of ciprofloxacin within the gut wall.
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