Get real in individual participant data (IPD) meta-analysis: a review of the methodology

被引：215

作者：

Debray, Thomas P. A. ^{[1
,2
]}

Moons, Karel G. M. ^{[1
,2
]}

van Valkenhoef, Gert ^{[3
]}

Efthimiou, Orestis ^{[4
]}

Hummel, Noemi ^{[5
]}

Groenwold, Rolf H. H. ^{[1
]}

Reitsma, Johannes B. ^{[1
,2
]}

机构：

[1] Univ Med Ctr Utrecht, Julius Ctr Hlth Sci & Primary Care, Utrecht, Netherlands

[2] Univ Med Ctr, Julius Ctr Hlth Sci & Primary Care, Dutch Cochrane Ctr, Utrecht, Netherlands

[3] Univ Groningen, Univ Med Ctr Groningen, Dept Epidemiol, Groningen, Netherlands

[4] Univ Ioannina, Sch Med, Dept Hyg & Epidemiol, GR-45110 Ioannina, Greece

[5] Univ Bern, Inst Social & Prevent Med, Bern, Switzerland

来源：

RESEARCH SYNTHESIS METHODS | 2015年 / 6卷 / 04期

关键词：

meta-analysis; IPD; evidence synthesis; review; RCT; non-randomized intervention studies; NRSI; cross-design; PATIENT DATA METAANALYSIS; ZERO-INFLATED POISSON; ADJUSTED INDIRECT COMPARISONS; RANDOM EFFECTS MODELS; CARE DECISION-MAKING; SURVIVAL-DATA; SYSTEMATIC REVIEWS; PROPORTIONAL-HAZARDS; AGGREGATE DATA; MULTIPLE IMPUTATION;

D O I：

10.1002/jrsm.1160

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Individual participant data (IPD) meta-analysis is an increasingly used approach for synthesizing and investigating treatment effect estimates. Over the past few years, numerous methods for conducting an IPD meta-analysis (IPD-MA) have been proposed, often making different assumptions and modeling choices while addressing a similar research question. We conducted a literature review to provide an overview of methods for performing an IPD-MA using evidence from clinical trials or non-randomized studies when investigating treatment efficacy. With this review, we aim to assist researchers in choosing the appropriate methods and provide recommendations on their implementation when planning and conducting an IPD-MA. (c) 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

引用

页码：293 / 309

页数：17

共 124 条

[1] Individual participant data meta-analyses should not ignore clustering [J].

Abo-Zaid, Ghada ;

Guo, Boliang ;

Deeks, Jonathan J. ;

Debray, Thomas P. A. ;

Steyerberg, Ewout W. ;

Moons, Karel G. M. ;

Riley, Richard David .

JOURNAL OF CLINICAL EPIDEMIOLOGY, 2013, 66 (08) :865-873

[2] Assessment of publication bias, selection bias, and unavailable data in meta-analyses using individual participant data: a database survey [J].

Ahmed, Ikhlaaq ;

Sutton, Alexander J. ;

Riley, Richard D. .

BMJ-BRITISH MEDICAL JOURNAL, 2012, 344

[3] The use of individual patient-level data (IPD) to quantify the impact of pretreatment predictors of response to treatment in chronic hepatitis B patients [J].

Ali, Shehzad ;

Mealing, Stuart ;

Hawkins, Neil ;

Lescrauwaet, Benedicte ;

Bjork, Stefan ;

Mantovani, Lorenzo ;

Lampertico, Pietro .

BMJ OPEN, 2013, 3 (01)

[4] Two-stage meta-analysis of survival data from individual participants using percentile ratios [J].

Barrett, Jessica K. ;

Farewell, Vern T. ;

Siannis, Fotios ;

Tierney, Jayne ;

Higgins, Julian P. T. .

STATISTICS IN MEDICINE, 2012, 31 (30) :4296-4308

[5] A Questionnaire to Assess the Relevance and Credibility of Observational Studies to Inform Health Care Decision Making: An ISPOR-AMCP-NPC Good Practice Task Force Report [J].

Berger, Marc L. ;

Martin, Bradley C. ;

Husereau, Don ;

Worley, Karen ;

Allen, J. Daniel ;

Yang, Winnie ;

Quon, Nicole C. ;

Mullins, C. Daniel ;

Kahler, Kristijan H. ;

Crown, William .

VALUE IN HEALTH, 2014, 17 (02) :143-156

[6] Individual patient- versus group-level data meta-regressions for the investigation of treatment effect modifiers: ecological bias rears its ugly head [J].

Berlin, JA ;

Santanna, J ;

Schmid, CH ;

Szczech, LA ;

Feldman, HI .

STATISTICS IN MEDICINE, 2002, 21 (03) :371-387

[7] Individual patient data meta-analysis of time-to-event outcomes: one-stage versus two-stage approaches for estimating the hazard ratio under a random effects model [J].

Bowden, Jack ;

Tierney, Jayne F. ;

Simmonds, Mark ;

Copas, Andrew J. ;

Higgins, Julian P. T. .

RESEARCH SYNTHESIS METHODS, 2011, 2 (03) :150-162

[8] Generalized linear models with clustered data: Fixed and random effects models [J].

Brostrom, Goran ;

Holmberg, Henrik .

COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2011, 55 (12) :3123-3134

[9] Use of Bayesian Multivariate Meta-Analysis to Estimate the HAQ for Mapping Onto the EQ-5D Questionnaire in Rheumatoid Arthritis [J].

Bujkiewicz, Sylwia ;

Thompson, John R. ;

Sutton, Alex J. ;

Cooper, Nicola J. ;

Harrison, Mark J. ;

Symmons, Deborah P. M. ;

Abrams, Keith R. .

VALUE IN HEALTH, 2014, 17 (01) :109-115

[10]

Burdett S, 2002, INT J TECHNOL ASSESS, V18, P619

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