Empirical comparison of subgroup effects in conventional and individual patient data meta-analyses

2008 ◽  
Vol 24 (03) ◽  
pp. 358-361 ◽  
Author(s):  
Laura Koopman ◽  
Geert J. M. G. van der Heijden ◽  
Arno W. Hoes ◽  
Diederick E. Grobbee ◽  
Maroeska M. Rovers

Objectives:Individual patient data (IPD) meta-analyses have been proposed as a major improvement in meta-analytic methods to study subgroup effects. Subgroup effects of conventional and IPD meta-analyses using identical data have not been compared. Our objective is to compare such subgroup effects using the data of six trials (n= 1,643) on the effectiveness of antibiotics in children with acute otitis media (AOM).Methods:Effects (relative risks, risk differences [RD], and their confidence intervals [CI]) of antibiotics in subgroups of children with AOM resulting from (i) conventional meta-analysis using summary statistics derived from published data (CMA), (ii) two-stage approach to IPD meta-analysis using summary statistics derived from IPD (IPDMA-2), and (iii) one-stage approach to IPD meta-analysis where IPD is pooled into a single data set (IPDMA-1) were compared.Results:In the conventional meta-analysis, only two of the six studies were included, because only these reported on relevant subgroup effects. The conventional meta-analysis showed larger (age < 2 years) or smaller (age ≥ 2 years) subgroup effects and wider CIs than both IPD meta-analyses (age < 2 years: RDCMA-21 percent, RDIPDMA-1-16 percent, RDIPDMA-2-15 percent; age ≥2 years: RDCMA-5 percent, RDIPDMA-1-11 percent, RDIPDMA-2-11 percent). The most important reason for these discrepant results is that the two studies included in the conventional meta-analysis reported outcomes that were different both from each other and from the IPD meta-analyses.Conclusions:This empirical example shows that conventional meta-analyses do not allow proper subgroup analyses, whereas IPD meta-analyses produce more accurate subgroup effects. We also found no differences between the one- and two-stage meta-analytic approaches.

BMJ Open ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. e026925 ◽  
Author(s):  
Beth Stuart ◽  
Hilda Hounkpatin ◽  
Taeko Becque ◽  
Guiqing Yao ◽  
Shihua Zhu ◽  
...  

IntroductionDelayed prescribing can be a useful strategy to reduce antibiotic prescribing, but it is not clear for whom delayed prescribing might be effective. This protocol outlines an individual patient data (IPD) meta-analysis of randomised controlled trials (RCTs) and observational cohort studies to explore the overall effect of delayed prescribing and identify key patient characteristics that are associated with efficacy of delayed prescribing.Methods and analysisA systematic search of the databases Cochrane Central Register of Controlled Trials, Ovid MEDLINE, Ovid Embase, EBSCO CINAHL Plus and Web of Science was conducted to identify relevant studies from inception to October 2017. Outcomes of interest include duration of illness, severity of illness, complication, reconsultation and patient satisfaction. Study authors of eligible papers will be contacted and invited to contribute raw IPD data. IPD data will be checked against published data, harmonised and aggregated to create one large IPD database. Multilevel regression will be performed to explore interaction effects between treatment allocation and patient characteristics. The economic evaluation will be conducted based on IPD from the combined trial and observational studies to estimate the differences in costs and effectiveness for delayed prescribing compared with normal practice. A decision model will be developed to assess potential savings and cost-effectiveness in terms of reduced antibiotic usage of delayed prescribing and quality-adjusted life years.Ethics and disseminationEthical approval was obtained from the University of Southampton Faculty of Medicine Research Ethics Committee (Reference number: 30068). Findings of this study will be published in peer-reviewed academic journals as well as General Practice trade journals and will be presented at national and international conferences. The results will have important public health implications, shaping the way in which antibiotics are prescribed in the future and to whom delayed prescriptions are issued.PROSPERO registration numberCRD42018079400.


2021 ◽  
Vol 108 (Supplement_4) ◽  
Author(s):  
P Probst ◽  
U Klaiber ◽  
S Seide ◽  
M Kawai ◽  
I Matsumoto ◽  
...  

Abstract Objective Some studies have indicated that resecting the pylorus during partial pancreatoduodenectomy (PD) may lead to reduced delayed gastric emptying (DGE). Randomized controlled trials (RCTs) showed conflicting results regarding superiority of pylorus-resecting PD (prPD) compared to the pylorus-preserving procedure (ppPD). The aim of this individual patient data meta-analysis was to investigate risk factors on an individual patient level which may explain the observed differences between the existing RCTs. Methods RCTs comparing ppPD and prPD were searched systematically in MEDLINE, Web of Science and CENTRAL. Individual patient data (IPD) from existing RCTs were included. The primary endpoint was DGE according to the International Study Group of Pancreatic Surgery (ISGPS) adjusted for age, sex and body-mass-index (BMI). The meta-regression model was applied to the IPD of the RCTs. Mixed effects models were applied to perform meta-analyses. Results IPD from 418 patients (three RCTs) were used for quantitative synthesis. There was no significant statistical difference between ppPD and prPD regarding DGE adjusted for age, sex and BMI (OR 0.72; 95%-CI: 0.41 to 1.22) and DGE grade (RR 1.01; 95%-CI: 0.64 to 1.57). Regarding other relevant perioperative and postoperative outcome parameters, there were also no significant differences among the two techniques. Conclusion This IPD meta-analysis comparing preservation and resection of the pylorus during PD confirmed that the resection of the pylorus is not superior to the pylorus-preserving procedure regarding DGE. The pylorus should therefore be preserved whenever possible. Further RCT are futile, because their results are unlikely to change the pooled estimate for DGE.


Author(s):  
Janet L. Peacock ◽  
Sally M. Kerry ◽  
Raymond R. Balise

Chapter 13 introduces systematic reviews and meta-analyses, describing the use of aggregate or individual patient data. It describes how bias can arise in meta-analyses. It describes and demonstrates the use of the PRISMA guidelines statement.


2000 ◽  
Vol 16 (2) ◽  
pp. 657-667 ◽  
Author(s):  
Jayne F. Tierney ◽  
Mike Clarke ◽  
Lesley A. Stewart

Objective: There is increasing empirical evidence for the existence of bias in the publication of primary clinical research, with statistically significant results being published more readily, more quickly, and in higher impact journals. Meta-analysis of individual patient data (IPD) may represent a gold standard of “secondary” clinical research, giving the best possible summary of current evidence for a particular question, but publication of these may also be subject to bias. This study aimed to explore which factors might be associated with publication of IPD meta-analyses and to identify potential sources of bias.Methods: For all known IPD meta-analysis projects in cancer, the responsible investigator was surveyed by means of a questionnaire to determine descriptive characteristics of the meta-analysis, the nature of the results, and details of the publication history.Results: There is no good evidence that overall publication status of meta-analyses in cancer is dependent on the statistical or clinical significance of the results. However, those meta-analyses with nonsignificant results did seem to take longer to publish and were published in lower impact journals compared with those with more striking results.Conclusions: Based on the current data, there seems to be no strong association between the results of IPD meta-analyses in cancer and publication.


The Lancet ◽  
2006 ◽  
Vol 368 (9545) ◽  
pp. 1429-1435 ◽  
Author(s):  
Maroeska M Rovers ◽  
Paul Glasziou ◽  
Cees L Appelman ◽  
Peter Burke ◽  
David P McCormick ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document