BackgroundAutomatic stepwise subset selection methods in linear regression often perform poorly, both in terms of variable selection and estimation of coefficients and standard errors, especially when number of independent variables is large and multicollinearity is present. Yet, stepwise algorithms remain the dominant method in medical and epidemiological research.MethodsPerformance of stepwise (backward elimination and forward selection algorithms using AIC, BIC, and Likelihood Ratio Test, p = 0.05 (LRT)) and alternative subset selection methods in linear regression, including Bayesian model averaging (BMA) and penalized regression (lasso, adaptive lasso, and adaptive elastic net) was investigated in a dataset from a cross-sectional study of drug users in St. Petersburg, Russia in 2012–2013. Dependent variable measured health-related quality of life, and independent correlates included 44 variables measuring demographics, behavioral, and structural factors.ResultsIn our case study all methods returned models of different size and composition varying from 41 to 11 variables. The percentage of significant variables among those selected in final model varied from 100 % to 27 %. Model selection with stepwise methods was highly unstable, with most (and all in case of backward elimination: BIC, forward selection: BIC, and backward elimination: LRT) of the selected variables being significant (95 % confidence interval for coefficient did not include zero). Adaptive elastic net demonstrated improved stability and more conservative estimates of coefficients and standard errors compared to stepwise. By incorporating model uncertainty into subset selection and estimation of coefficients and their standard deviations, BMA returned a parsimonious model with the most conservative results in terms of covariates significance.ConclusionsBMA and adaptive elastic net performed best in our analysis. Based on our results and previous theoretical studies the use of stepwise methods in medical and epidemiological research may be outperformed by alternative methods in cases such as ours. In situations of high uncertainty it is beneficial to apply different methodologically sound subset selection methods, and explore where their outputs do and do not agree. We recommend that researchers, at a minimum, should explore model uncertainty and stability as part of their analyses, and report these details in epidemiological papers.Electronic supplementary materialThe online version of this article (doi:10.1186/s12874-015-0066-2) contains supplementary material, which is available to authorized users.
Background. Placing the left ventricular (LV) lead in a viable segment with the latest mechanical activation (vSOLA) may be associated with optimal cardiac resynchronization therapy (CRT) response. We assessed the role of gated SPECT myocardial perfusion imaging (gSPECT MPI) in predicting clinical outcomes at 6 months in patients submitted to CRT.
Background Ukraine’s volatile syndemics of tuberculosis (TB) and HIV among people who inject drugs (PWIDs) introduces numerous treatment challenges for each condition, including high mortality and development of multi-drug resistant TB (MDR-TB). Methods A prospective, non-randomized 90-day observational study was conducted in six Ukrainian TB treatment sites to assess the effectiveness of integrating methadone maintenance (MMT) with TB treatment using: (1) 90-day TB treatment retention; (2) time to treatment discontinuation; (3) TB medication adherence; and (4) subject disposition, including mortality. Of the 110 participants enrolled, 57 received MMT and 53 did not (non-MMT). Results All of the primary outcomes were significantly better in MMT versus non-MMT groups, including 90-day TB treatment completion (89.5% versus 73.6%; p = 0.031), time to TB treatment discontinuation (p = 0.039) and TB medication adherence (97.1% versus 86.2%; p<0.001) after controlling for death. The major reasons for treatment non-completion in the non-MMT group included death (N=3), administrative discharge from the clinic (N =5), loss to follow-up (N =2), and arrest (N=4). Overall, 90-day mortality was high (8.2%). After controlling for covariates differing between the two groups at baseline, the only independent predictor of completing 90 days of TB treatment was receipt of MMT in an integrated treatment setting (AOR = 3.05; 95% CI 1.08–8.66). Conclusions MMT integrated into inpatient TB treatment significantly improves retention in TB treatment and TB medication adherence among PWIDs. These findings call for policy change to increase the number of MMT sites in TB facilities and make MMT a low-threshold treatment option for opioid dependence in Ukraine.
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