A systematic comparison of software dedicated to meta-analysis of causal studies

<p>Abstract</p> <p>Background</p> <p>Our objective was to systematically assess the differences in features, results, and usability of currently available meta-analysis programs.</p> <p>Methods</p> <p>Systematic review of software. We did an extensive search on the internet (Google, Yahoo, Altavista, and MSN) for specialized meta-analysis software. We included six programs in our review: Comprehensive Meta-analysis (CMA), MetAnalysis, MetaWin, MIX, RevMan, and WEasyMA. Two investigators compared the features of the software and their results. Thirty independent researchers evaluated the programs on their usability while analyzing one data set.</p> <p>Results</p> <p>The programs differed substantially in features, ease-of-use, and price. Although most results from the programs were identical, we did find some minor numerical inconsistencies. CMA and MIX scored highest on usability and these programs also have the most complete set of analytical features.</p> <p>Conclusion</p> <p>In consideration of differences in numerical results, we believe the user community would benefit from openly available and systematically updated information about the procedures and results of each program's validation. The most suitable program for a meta-analysis will depend on the user's needs and preferences and this report provides an overview that should be helpful in making a substantiated choice.</p

Health Related Quality of Life among Patients with Tuberculosis and HIV in Thailand

INTRODUCTION: Health utilities of tuberculosis (TB) patients may be diminished by side effects from medication, prolonged treatment duration, physical effects of the disease itself, and social stigma attached to the disease. METHODS: We collected health utility data from Thai patients who were on TB treatment or had been successfully treated for TB for the purpose of economic modeling. Structured questionnaire and EuroQol (EQ-5D) and EuroQol visual analog scale (EQ-VAS) instruments were used as data collection tools. We compared utility of patients with two co-morbidities calculated using multiplicative model (U(CAL)) with the direct measures and fitted Tobit regression models to examine factors predictive of health utility and to assess difference in health utilities of patients in various medical conditions. RESULTS: Of 222 patients analyzed, 138 (62%) were male; median age at enrollment was 40 years (interquartile range [IQR], 35-47). Median monthly household income was 6,000 Baht (187 US$; IQR, 4,000-15,000 Baht [125-469 US$]). Concordance correlation coefficient between utilities measured using EQ-5D and EQ-VAS (U(EQ-5D) and U(VAS), respectively) was 0.6. U(CAL) for HIV-infected TB patients was statistically different from the measured U(EQ-5D) (p-value<0.01) and U(VAS) (p-value<0.01). In tobit regression analysis, factors independently predictive of U(EQ-5D) included age and monthly household income. Patients aged ≥40 years old rated U(EQ-5D) significantly lower than younger persons. Higher U(EQ-5D) was significantly associated with higher monthly household income in a dose response fashion. The median U(EQ-5D) was highest among patients who had been successfully treated for TB and lowest among multi-drug resistant TB (MDR-TB) patients who were on treatment. CONCLUSIONS: U(CAL) of patients with two co-morbidities overestimated the measured utilities, warranting further research of how best to estimate utilities of patients with such conditions. TB and MDR-TB treatments impacted on patients' self perceived health status. This effect diminished after successful treatment

Improved hospital-level risk adjustment for surveillance of healthcare-associated bloodstream infections: a retrospective cohort study

Background: To allow direct comparison of bloodstream infection (BSI) rates between hospitals for performance measurement, observed rates need to be risk adjusted according to the types of patients cared for by the hospital. However, attribute data on all individual patients are often unavailable and hospital-level risk adjustment needs to be done using indirect indicator variables of patient case mix, such as hospital level. We aimed to identify medical services associated with high or low BSI rates, and to evaluate the services provided by the hospital as indicators that can be used for more objective hospital-level risk adjustment

Assessment of regression-based methods to adjust for publication bias through a comprehensive simulation study

<p>Abstract</p> <p>Background</p> <p>In meta-analysis, the presence of funnel plot asymmetry is attributed to publication or other small-study effects, which causes larger effects to be observed in the smaller studies. This issue potentially mean inappropriate conclusions are drawn from a meta-analysis. If meta-analysis is to be used to inform decision-making, a reliable way to adjust pooled estimates for potential funnel plot asymmetry is required.</p> <p>Methods</p> <p>A comprehensive simulation study is presented to assess the performance of different adjustment methods including the novel application of several regression-based methods (which are commonly applied to detect publication bias rather than adjust for it) and the popular Trim & Fill algorithm. Meta-analyses with binary outcomes, analysed on the log odds ratio scale, were simulated by considering scenarios with and without i) publication bias and; ii) heterogeneity. Publication bias was induced through two underlying mechanisms assuming the probability of publication depends on i) the study effect size; or ii) the p-value.</p> <p>Results</p> <p>The performance of all methods tended to worsen as unexplained heterogeneity increased and the number of studies in the meta-analysis decreased. Applying the methods conditional on an initial test for the presence of funnel plot asymmetry generally provided poorer performance than the unconditional use of the adjustment method. Several of the regression based methods consistently outperformed the Trim & Fill estimators.</p> <p>Conclusion</p> <p>Regression-based adjustments for publication bias and other small study effects are easy to conduct and outperformed more established methods over a wide range of simulation scenarios.</p

Excision Repair Cross-Complementation Group 1 (ERCC1) Status and Lung Cancer Outcomes: A Meta-Analysis of Published Studies and Recommendations

Despite discrepant results on clinical utility, several trials are already prospectively randomizing non-small cell lung cancer (NSCLC) patients by ERCC1 status. We aimed to characterize the prognostic and predictive effect of ERCC1 by systematic review and meta-analysis.Eligible studies assessed survival and/or chemotherapy response in NSCLC or SCLC by ERCC1 status. Effect measures of interest were hazard ratio (HR) for survival or relative risk (RR) for chemotherapy response. Random-effects meta-analyses were used to account for between-study heterogeneity, with unadjusted/adjusted effect estimates considered separately.23 eligible studies provided survival results in 2,726 patients. Substantial heterogeneity was observed in all meta-analyses (I(2) always >30%), partly due to variability in thresholds defining 'low' and 'high' ERCC1. Meta-analysis of unadjusted estimates showed high ERCC1 was associated with significantly worse overall survival in platinum-treated NSCLC (average unadjusted HR = 1.61, 95%CI:1.23-2.1, p = 0.014), but not in NSCLC untreated with chemotherapy (average unadjusted HR = 0.82, 95%CI:0.51-1.31). Meta-analysis of adjusted estimates was limited by variable choice of adjustment factors and potential publication bias (Egger's p<0.0001). There was evidence that high ERCC1 was associated with reduced response to platinum (average RR = 0.80; 95%CI:0.64-0.99). SCLC data were inadequate to draw firm conclusions.Current evidence suggests high ERCC1 may adversely influence survival and response in platinum-treated NSCLC patients, but not in non-platinum treated, although definitive evidence of a predictive influence is lacking. International consensus is urgently required to provide consistent, validated ERCC1 assessment methodology. ERCC1 assessment for treatment selection should currently be restricted to, and evaluated within, clinical trials