Potential bias in the indirect methods for extracting summary statistics in literature-based meta-analyses: an empirical evaluation

Background: In literature-based meta-analyses of cancer prognostic studies, methods for extracting summary statistics from published reports have been extensively employed. However, no assessment of the magnitude of bias produced by these methods or comparison of their influence on fixed vs. random effects models have been published previously. Therefore, the purpose of this study is to empirically assess the degree of bias produced by the methods used for extracting summary statistics and examine potential effects on fixed and random effects models. Methods: Using published data from cancer prognostic studies, systematic differences between reported statistics and those obtained indirectly using log-rank test p-values and total number of events were tested using paired t tests and the log-rank test of survival-agreement plots. The degree of disagreement between estimates was quantified using an information-based disagreement measure, which was also used to examine levels of disagreement between expressions obtained from fixed and random effects models. Results: Thirty-four studies provided a total of 65 estimates of lnHR and its variance. There was a significant difference between the means of the indirect lnHRs and the reported values (mean difference = -0.272, t = -4.652, p-value <0.0001), as well as between the means of the two estimates of variances (mean difference = -0.115, t = -4.5556, p-value <0.0001). Survival agreement plots illustrated a bias towards under-estimation by the indirect method for both lnHR (log-rank p-value = 0.031) and its variance (log-rank p-value = 0.0432). The magnitude of disagreement between estimates of lnHR based on the information-based measure was 0.298 (95% CI: 0.234 – 0.361) and, for the variances it was 0.406 (95% CI: 0.339 – 0.470). As the disagreement between variances was higher than that between lnHR estimates, this increased the level of disagreement between lnHRs weighted by the inverse of their variances in fixed effect models. In addition, results indicated that random effects meta-analyses could be more prone to bias than fixed effects meta-analyses as, in addition to bias in estimates of lnHRs and their variances, levels of disagreement as high as 0.487 (95% CI: 0.416 – 0.552) and 0.568 (95% CI: 0.496 – 0.635) were produced due to between-studies variance calculations. Conclusions: Extracting summary statistics from published studies could introduce bias in literature-based meta-analyses and undermine the validity of the evidence. These findings emphasise the importance of reporting sufficient statistical information in research articles and warrant further research into the influence of potential bias on random effects models.

Potential bias in the indirect methods for extracting summary statistics in literature-based meta-analyses: an empirical evaluation

10.7287/peerj.preprints.142 ◽

2013 ◽

Author(s):

Dima Y Abdallah

Keyword(s):

Random Effects ◽

Mean Difference ◽

Rank Test ◽

P Value ◽

Summary Statistics ◽

Potential Bias ◽

Random Effects Models ◽

Log Rank Test ◽

Leptin, adiponectin, and resistin blood adipokine levels in migraineurs: Systematic reviews and meta-analyses

Cephalalgia ◽

10.1177/0333102418807182 ◽

2019 ◽

Vol 39 (8) ◽

pp. 1010-1021 ◽

Cited By ~ 1

Author(s):

Milad Abbasi ◽

Ali Noori-Zadeh ◽

Ali Seidkhani-Nahal ◽

Mohammadreza Kaffashian ◽

Salar Bakhtiyari ◽

...

Keyword(s):

Confidence Interval ◽

Systematic Reviews ◽

Mean Difference ◽

Blood Levels ◽

P Value ◽

Case Control Studies ◽

Random Effects Models ◽

Standardized Mean Difference ◽

Migraine Pathophysiology ◽

Introduction Migraine comorbidity with obesity is not new and studies have focused on how adipose tissue-derived substances such as adipokines might be involved in the migraine pathophysiology. Quantification of the nature and magnitude of the association between each adipokine including leptin, adiponectin and resistin with migraine pathophysiology is the objective of the current study. Methods Using systematic reviews and meta-analyses and standardized mean difference as effect size, the levels of three adipokines, leptin, adiponectin and resistin, have been investigated in migraineur subjects in the case-control studies. Results Using random-effects models, the final analyses demonstrated the standardized mean differences of leptin, adiponectin and resistin as 0.534 (95% confidence interval, 0.169–0.898), 0.439 (95% confidence interval, 0.132–0.746) and 0.194 (95% confidence interval, −0.158–0.546), respectively. The p-value for test of significance for each pooled standardized mean difference was examined by the z-test and calculated as 0.004, 0.005 and 0.281 for leptin, adiponectin and resistin (clearly considered as statistically significant, significant and non-significant), respectively. Conclusion Based on the findings, the blood levels of leptin and adiponectin, but not resistin, of the migraineurs are associated with disease pathogenesis.

INFLUENCE OF MARKET RETURN ON THE PORTFOLIO RETURNS OF COMPANIES IN THE MIMS AT NSE

International Journal of Finance ◽

10.47941/ijf.59 ◽

2017 ◽

Vol 2 (3) ◽

pp. 18

Author(s):

Emmanuel Otweyo ◽

Prof. Silas Onyango

Keyword(s):

Random Effects ◽

Panel Data Analysis ◽

P Value ◽

Random Effects Models ◽

Portfolio Returns ◽

Market Return ◽

Study Population ◽

Descriptive Survey ◽

Portfolio Return

Purpose: The purpose of this study was to determine the influence of market return on the Portfolio returns of companies in the MIMS at NSEMethodology: The study adopted descriptive survey. The study population study was composed of the forty seven firms within Main Investment Market Segment (MIMS), which form the four sectors of Nairobi Securities Exchange (NSE). A census was carried out and so the research covered 45 companies, listed in the MIMS of NSE for the period 1st January 2009 to 31st December 2013. The study used the panel data analysis where pooled OLS model was used and diagnostic tests carried out. Since the tests failed to meet the assumptions of OLS, the fixed and random effects models were used.Results: The study findings revealed that portfolio return and market return were positively (r= 0.565) and significantly (p-value<0.000) correlated and further the random effects panel regression results indicated a positive (β=3.38) and significantly (p-value<0.05) related to market return and portfolio return.Policy recommendation: The study recommended that the investors who would want to maximize the returns from their portfolios should invest when the market return is favorable. This would ensure that they derive maximum returns from their investments

Effects of dutasteride on prostate cancer incidence: A systematic review and meta-analysis

International Journal of Research in Pharmaceutical Sciences ◽

10.26452/ijrps.v11i4.3860 ◽

2020 ◽

Vol 11 (4) ◽

pp. 7266-7270

Author(s):

Gyeong-Eun Min ◽

Haesoo Kim ◽

Da Eun Lee ◽

Kisok Kim

Keyword(s):

Prostate Cancer ◽

Random Effects ◽

Fixed Effects ◽

Meta Analysis ◽

Adult Males ◽

Fixed Effects Model ◽

Random Effects Models ◽

Benign Prostate Hypertrophy ◽

5-Alpha-reductase inhibitors (5-ARIs) are used in the treatment of benign prostate hypertrophy (BPH). 5-ARIs, such as finasteride and dutasteride, suppress the biosynthesis of dihydrotestosterone (DHT), a precursor of androgen, which is closely related to the incidence of prostate cancer (PCa). A previous meta-analysis demonstrated a relationship between finasteride use and the incidence of PCA. However, there have been no meta-analyses on the relationship between PCa and dutasteride alone. This meta-analysis was performed to examine the prevalence of PCa in adult males taking dutasteride. We searched PubMed for reports regarding PCa risk and dutasteride use. The study was conducted according to the PRISMA guidelines for systematic reviews and meta-analyses. The analytic hierarchy process (AHP) method was used to weight the studies. Odds ratios (ORs), 95% confidence intervals (CIs), and P-values were calculated using fixed- and random-effects models. A total of eight articles were included in the meta-analysis. The overall OR for both the fixed- and random-effects models was 0.669 and the 95% CI for the random-effects model (0.526–0.851; P = 0.006) was wider than that for the fixed effects model (0.548–0.817; P < 0.001). This study confirmed that the incidence of PCa was significantly reduced by taking dutasteride.

Meta-analyses in systematic reviews of randomized controlled trials in perinatal medicine: comparison of fixed and random effects models

Statistics in Medicine ◽

10.1002/sim.1096 ◽

2001 ◽

Vol 20 (23) ◽

pp. 3635-3647 ◽

Cited By ~ 54

Author(s):

Jos� Villar ◽

Maria Eugenia Mackey ◽

Guillermo Carroli ◽

Allan Donner

Keyword(s):

Randomized Controlled Trials ◽

Random Effects ◽

Systematic Reviews ◽

Controlled Trials ◽

Perinatal Medicine ◽

Random Effects Models ◽

Randomized Controlled ◽

Generalized linear models with clustered data: Fixed and random effects models

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2011.06.011 ◽

2011 ◽

Vol 55 (12) ◽

pp. 3123-3134 ◽

Cited By ~ 42

Author(s):

Göran Broström ◽

Henrik Holmberg

Keyword(s):

Random Effects ◽

Generalized Linear Models ◽

Linear Models ◽

Clustered Data ◽

Random Effects Models ◽

Fixed And Random Effects

Meta-analysis of effect sizes reported at multiple time points: A multivariate approach

Clinical Trials ◽

10.1177/1740774512453218 ◽

2012 ◽

Vol 9 (5) ◽

pp. 610-620 ◽

Cited By ~ 28

Author(s):

Thomas A Trikalinos ◽

Ingram Olkin

Keyword(s):

Random Effects ◽

Treatment Effects ◽

Multivariate Analyses ◽

Meta Analysis ◽

Effect Sizes ◽

Multiple Time ◽

Time Points ◽

Multiple Time Points ◽

Background Many comparative studies report results at multiple time points. Such data are correlated because they pertain to the same patients, but are typically meta-analyzed as separate quantitative syntheses at each time point, ignoring the correlations between time points. Purpose To develop a meta-analytic approach that estimates treatment effects at successive time points and takes account of the stochastic dependencies of those effects. Methods We present both fixed and random effects methods for multivariate meta-analysis of effect sizes reported at multiple time points. We provide formulas for calculating the covariance (and correlations) of the effect sizes at successive time points for four common metrics (log odds ratio, log risk ratio, risk difference, and arcsine difference) based on data reported in the primary studies. We work through an example of a meta-analysis of 17 randomized trials of radiotherapy and chemotherapy versus radiotherapy alone for the postoperative treatment of patients with malignant gliomas, where in each trial survival is assessed at 6, 12, 18, and 24 months post randomization. We also provide software code for the main analyses described in the article. Results We discuss the estimation of fixed and random effects models and explore five options for the structure of the covariance matrix of the random effects. In the example, we compare separate (univariate) meta-analyses at each of the four time points with joint analyses across all four time points using the proposed methods. Although results of univariate and multivariate analyses are generally similar in the example, there are small differences in the magnitude of the effect sizes and the corresponding standard errors. We also discuss conditional multivariate analyses where one compares treatment effects at later time points given observed data at earlier time points. Limitations Simulation and empirical studies are needed to clarify the gains of multivariate analyses compared with separate meta-analyses under a variety of conditions. Conclusions Data reported at multiple time points are multivariate in nature and are efficiently analyzed using multivariate methods. The latter are an attractive alternative or complement to performing separate meta-analyses.

Fixed- and Random-Effects Models

Sensory Evaluation of Food ◽

10.1201/9780203739884-13 ◽

2017 ◽

pp. 247-258 ◽

Cited By ~ 1

Author(s):

Michael O’Mahony

Keyword(s):

Random Effects ◽

Random Effects Models ◽

Fixed And Random Effects

EFFICACY OF LATERAL WEDGING IN FOOTWEAR IN MEDIAL COMPARTMENT OSTEOARTHRITIS KNEE

10.36106/paripex/8300399 ◽

2019 ◽

pp. 1-3

Author(s):

Suman Badhal ◽

U. Singh ◽

S. L Yadav ◽

Gita Handa

Keyword(s):

Intervention Group ◽

Cost Effective ◽

Mean Difference ◽

Medial Compartment ◽

Treatment Modalities ◽

Rank Test ◽

P Value ◽

Knee Oa ◽

The Mean ◽

Group B

INTRODUCTION: In Knee osteoarthritis (OA) Shoe modifications, such as lateral-wedge insoles or shock absorbing shoes with insoles, have been recommended for conservative therapy of mild knee OA but with little objective data on Indian patients. OBJECTIVE : this prospective study was done to study the effect of lateral heel sole wedging (insole) in the patients of OA of knee (medial compartment) and its relation to function,pain and stiffness parameters status on VAS and WOMAC scale and to see the requirement of the number of Aceclofenac tablets. METHODS: 60 patients fulfilling the inclusion criteria were enrolled and divided into intervention group A (30) and nonintervention Group B (30) with random allocation.Paired t-test,Wilcoxon sign rank test and Man Whitney U test were applied at significant p-value of <0.05%. RESULTS: the reduction of mean difference in pain on VAS and WOMAC scale, improvement in Mean difference in function parameters the mean reduction of pain in standing/ walking,bending and ascending/descending at WOMAC scale was significantly higher in intervention group. Also the mean reduction in the need for aceclofenac was significantly lower in intervention group evident from fourth week onward to fifth and sixth week.Conclusion:The lateral wedging in shoes in medial joint osteoarthritis is beneficial and it can be cost-effective conservative treatment modalities in early osteoarthritis patients, particularly in developing countries as it can reduces the requirement of NSAIDS and improve functional level of patients by reducing pain in various activities.

Effect of Using a Safety Checklist on Patient Complications after Surgery

Anesthesiology ◽

10.1097/aln.0000000000000232 ◽

2014 ◽

Vol 120 (6) ◽

pp. 1380-1389 ◽

Cited By ~ 63

Author(s):

Brigid M. Gillespie ◽

Wendy Chaboyer ◽

Lukman Thalib ◽

Melinda John ◽

Nicole Fairweather ◽

...

Keyword(s):

Absolute Risk ◽

Absolute Risk Reduction ◽

Cochrane Library ◽

Number Needed To Treat ◽

Complication Rates ◽

Random Effects Models ◽

Before And After ◽

Meta Analyses ◽

The Cochrane Library

Abstract Background: Previous before-and-after studies indicate that the use of safety checklists in surgery reduces complication rates in patients. Methods: A systematic review of studies was undertaken using MEDLINE, CINAHL, Proquest, and the Cochrane Library to identify studies that evaluated the effects of checklist use in surgery on complication rates. Study quality was assessed using the Methodological Index for Nonrandomized Studies. The pooled risk ratio (RR) was estimated using both fixed and random effects models. For each outcome, the number needed to treat (NNT) and the absolute risk reduction (ARR) were also computed. Results: Of the 207 intervention studies identified, 7 representing 37,339 patients were included in meta-analyses, and all were cohort studies. Results indicated that the use of checklists in surgery compared with standard practice led to a reduction in any complication (RR, 0.63; 95% CI, 0.58 to 0.72; P < 0.0001; ARR, 3.7%; NNT, 27) and wound infection (RR, 0.54; 95% CI, 0.40 to 0.72; P = 0.0001; ARR, 2.9%; NNT, 34) and also reduction in blood loss (RR, 0.56; 95% CI, 0.45 to 0.70; P = 0.0001; ARR, 3.8%; NNT, 33). There were no significant reductions in mortality (RR, 0.79; 95% CI, 0.57 to 1.11; P = 0.191; ARR, 0.44%; NNT, 229), pneumonia (RR, 1.03; 95% CI, 0.73 to 1.4; P = 0.857; ARR, 0.04%; NNT, 2,512), or unplanned return to operating room (RR, 0.75; 95% CI, 0.56 to 1.02; P = 0.068; ARR, 0.52%; NNT, 192). Conclusion: Notwithstanding the lack of randomized controlled trials, synthesis of the existing body of evidence suggests a relationship between checklist use in surgery and fewer postoperative complications.