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Abstract : Adjusting Complex Heterogeneity in Treatment Assignment in Observational Studies
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Abstract: Treatment assignment in observational studies is complex and can be influenced by many factors that include patient characteristics, physician practices, and health care systems. These influences can present heterogeneity or clustering effects in the treatment assignment. If those heterogeneity or clustering effects are not appropriately adjusted, the estimated treatment effect may be severely biased. Through a series of models that mimic various level of heterogeneity in treatment assignment in observational studies, we evaluate, through simulation study, the performance of several estimators under the impact of different types of heterogeneity. These estimators include propensity score stratification, propensity score inverse probability weighting, propensity score regression and the partial least squares method. Our results suggest that the partial least squares method is most robust while the dummy variable adjustment method in propensity regression also performs fairly consistently. We use the proposed method to analyze a data set from the German Breast Cancer Study Group study. Keywords: Heterogeneity, partial least squares, propensity score.Download Full Article |
Abstract : Biologic Therapy for Psoriatic Arthritis or Moderate to Severe Plaque Psoriasis: Systematic Review with Pairwise and Network Meta-Analysis
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Background: A comprehensive assessment of the risk-benefit profile of biologic agents in psoriasis is lacking. We conducted a network meta-analysis of randomized trials on biologic agents in psoriasis. Methods: Trials on biologic agents in psoriasis (including psoriatic arthritis) were sought in several databases. Endpoints were ≥75% Reduction in the Psoriasis Area and Severity Index (PASI75), ≥20% improvement in the American College of Rheumatology core set of outcomes (ACR20), serious adverse events (SAE), and adverse events (AE) at the longest available non-cross-over follow-up. Random-effect methods were used to obtain pairwise and network pooled estimates. Results: A total of 52 trials with 17,617 patients and 9 different biologic agents included, with 52% affected by psoriatic arthritis. After an average follow-up of 18 weeks, treatment with placebo was associated with a 5.9% (5.2%-6.6%) rate of PASI75, 17.4% (15.1%-19.6%) of ACR20, 2.4% (1.9%-2.8%) of SAE, and 51.8% (50.2%-53.4%) of AE. Several biologic agents provided higher PASI75 rates than placebo, with golimumab yielding the most favorable results (relative risk [RR]=14.02 [6.85-17.11]). Accordingly, several agents provided higher ACR20 rates than placebo, with infliximab yielding the most favorable results (RR=3.02 [1.67-4.55]). Overall, rates of SAE and AE were higher for several but not all biologic agents versus placebo, with golimumab being associated with the most favorable results for SAE (RR=0.40 [0.11-1.41]), and abatacept for AE (RR=1.00 [0.79-1.22]). Conclusions: Efficacy and safety of biologic agents for psoriasis differ, and clinicians should bear in mind these features to maximize safety and efficacy in the individual patient. Keywords: Meta-analysis, Mixed treatment comparison, Network meta-analysis, Plaque psoriasis, Psoriasis, Psoriatic arthritis, Systematic review. Download Full Article |
Abstract : The Bivariate Erlang and its Application in Modeling Recurrence Times of Kidney Dialysis Data
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Abstract: Recent advances in computer modeling allows us to find closer fits to data. Our emphasis is on the interdependence between occurrence at kidney dialysis. The interdependence between kidney dialysis occurrences is modelled by a bivariate exponential that we propose in this article. The application is shown on the McGilchrist and Aisbett kidney data set with the use of the exponential distribution. The proposed bivariate exponential model has exponential marginal densities, correlated via a latent random variables and with finite probability of simultaneous occurrence. Extension of the model to a bivariate Erlang type distribution with same shape parameter is presented. Keywords: Bivariate models, Erlang, exponential, Dirac delta. Download Full Article |
Abstract : Deployment of Six Sigma Methodology in Pars Plana Vitrectomy
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Abstract: Purpose:To show how a Turkish public eye care centre in Turkey initiated Six Sigma principles to reduce the number of complications occurring during and after pars plana vitreoretctomy surgeries. Method: Data were collected for two years. To analyse the complications among 2272 patients, main tools of Six Sigma’s Define-Measure-Analyse-Improve-Control (DMAIC) improvement cycle such as SIPOC table, Fishbone Diagram and, Failure, Mode and Effect Analysis were implemented. Sources and root causes of twenty-two types of complications were identified and reported. Results: For a successful pars plana vitrectomy procedure, experience of vitreoretinal surgeon, attention of vitreoretinal surgeon, patient’s anatomy were determined to be the “critical few” factors whereas, sterilization and hygiene, amount of silicone oil and amount of gas were found to be the “trivial many” factors. The most frequently occurring complication was found to be subconjunctival haemorrhage. Conclusion:The sigma level of the overall process was measured to be 3.8559. The surgical team concluded that twelve of the complications should be significantly reduced by taking the necessary preventive measures. Institutional ethics committee approval has been taken due to retrospective nature of this study. Keywords: Six Sigma, ophthalmology, pars plana vitrectomy, complications. |
