ijsmr
Abstract : Association between Obesity, Race and Knee Osteoarthritis: The Multicenter Osteoarthritis Study
|
|
Abstract: On the basis of longitudinal Kellgren-Lawrence (KL) grades of knee radiographsobtained from the Multicenter Osteoarthritis Study (MOST), we examine the association of obesity and race with severity of knee osteoarthritis (OA). We use the proportional odds model with mixed effects to conduct the analysis. Repeated KL grades were modeled as ordinal longitudinal measures, and a random effect term was included to adjust for the within-subject correlation among the KL grades over time. We found that African Americans and more obese participants in MOST have a greater risk of developing severe knee OA. Keywords: Body mass index, Cumulative logits, Kellgren-Lawrence (KL) grade, Knee radiograph, Longitudinal ordinal data, Mixed effects model, Proportional odds model, Risk factors.Download Full Article |
Abstract : Comparative Risk-Benefit Analysis of Different Classes of Biologic Agents in Patients with Psoriasis: A Case Study on the Pros and Cons of Mixed Treatment Comparison in Synthesizing Complex Evidence Networks
|
|
Abstract: Background: Several classes of biologic agents are used for the management of moderate to severe psoriasis or psoriatic arthritis. However, there is uncertainty on which, if any, individual class of biologics is superior in terms of efficacy and safety in comparison to the other classes or placebo. We thus exploited the corresponding evidence network with suitable statistical methods (mixed treatment comparison and network meta-analysis) to formally address this issue. Methods: Randomized trials on biologic agents in psoriasis (including psoriatic arthritis) were systematically sought in several databases. We distinguished anti-tumor necrosis factor-α (TNF-α) agents, anti-T lymphocytes (T-cell) agents, anti-interleukin-12/23 (IL-12/23) agents, and anti-interleukin-17 (IL-17) agents. Endpoints of interest were the rates of ≥75% reduction in the Psoriasis Area and Severity Index (PASI75), of ≥20% improvement in the American College of Rheumatology core set of outcomes (ACR20), of serious adverse events (SAE), and of adverse events (AE) at the longest available non-cross-over follow-up. Random-effect methods were used to obtain network estimates for risk ratios (RR, with 95% credible intervals). Results: A total of 58 trials with 18,508 patients were included, with 51% affected by psoriatic arthritis. After a median of 17 weeks since randomization into parallel groups, several classes of biologic agents provided higher PASI75 rates than placebo, with anti-IL-17 agents yielding the most favorable results (RR=9.53 [5.55-13.80]). Accordingly, several classes of biologic agents provided higher ACR20 rates than placebo, with anti-TNF-α agents yielding the most favorable results (RR=2.58 [2.12-3.15]). Overall, rates of SAE and AE were higher for several but not all biologic agents versus placebo, with anti-T-cell agents being associated with the most favorable results for both SAE (RR=0.97 [0.30-3.35]), and AE (RR=1.00 [0.80-1.22]). Conclusions:Biologic agents provide significant clinical benefits in patients with moderate to severe psoriasis or psoriatic arthritis. There are differences in the efficacy and safety profile of each class, with anti-IL-17 and anti-TNF-α agents appearing most effective, and anti-T-cell agents appearing safest. Keywords: Biologic therapy, Biologics, Meta-analysis, Mixed treatment comparison, Network meta-analysis, Plaque psoriasis, Psoriasis, Psoriatic arthritis, Systematic review.Download Full Article |
Abstract : Predicting Risks of Increased Morbidity among Atrial Fibrillation Patients using Consumption Classes
|
|
Abstract: Background: Atrial fibrillation (AF) is the most common chronic cardiac arrhythmia. Predicting the risk of complications, or associated increases in healthcare costs, among AF patients is important for effective health care management. Methods: A bivariate regression model including a latent morbidity index is used to predict both risk of transition to higher health costs, and mortality risk over a single year. A risk scoring algorithm for predicting transition to higher cost levels is then set out which incorporates the most significant risk factors from the regression. Results: The regression analysis shows that in addition to age and comorbidities, baseline consumption category, ethnic group, metropolitan residence and Warfarin adherence are also significant influences on progression to increased health consumption, and relevant to assessing risk. The resulting risk scoring algorithm produces a higher AUC than the widely applied CHADS2 score. Conclusions: The utility of a bivariate regression method with a latent morbidity index for predicting transition to worsening health status among AF patients is demonstrated. A risk scoring system based on this method outperforms an established risk score. Keywords: Morbidity, Risk scores, Latent variable, Atrial fibrillation, Consumption class.Download Full Article |
Abstract : Improved Ridge Regression Estimators for Binary Choice Models: An Empirical Study
|
|
Abstract: This paper suggests some new estimators of the ridge parameter for binary choice models that may be applied in the presence of a multicollinearity problem. These new ridge parameters are functions of other estimators of the ridge parameter that have shown to work well in the previous research. Using a simulation study we investigate the mean square error (MSE) properties of these new ridge parameters and compare them with the best performing estimators from the previous research. The results indicate that we may improve the MSE properties of the ridge regression estimator by applying the proposed estimators in this paper, especially when there is a high multicollinearity between the explanatory variables and when many explanatory variables are included in the regression model. The benefit of this paper is then shown by a health related data where the effect of some risk factors on the probability of receiving diabetes is investigated. Keywords: Binary Choice Models, Estimation, MSE, Multicollinearity, Ridge Regression, Simulation.Download Full Article |
