Quantifying, displaying and accounting for heterogeneity in the meta-analysis of RCTs using standard and generalised Q statistics

BMC Medical Research Methodology

Volumn 11, Issue , 2011, Pages

  Bowden, Jack ^a,b   Tierney, Jayne F ^a   Copas, Andrew J ^a   Burdett, Sarah ^a  

^a MRC CLINICAL TRIALS UNIT   (United Kingdom)

^b MRC BIOSTATISTICS UNIT   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYSIS OF VARIANCE; ARTICLE; CLINICAL TRIAL (TOPIC); HUMAN; META ANALYSIS (TOPIC); NEOPLASM; RANDOMIZED CONTROLLED TRIAL (TOPIC); STATISTICAL ANALYSIS; STATISTICS;

ANALYSIS OF VARIANCE; CLINICAL TRIALS AS TOPIC; DATA INTERPRETATION, STATISTICAL; HUMANS; META-ANALYSIS AS TOPIC; NEOPLASMS; RANDOMIZED CONTROLLED TRIALS AS TOPIC; STATISTICS AS TOPIC;

EID: 79953689306     PISSN: None     EISSN: 14712288     Source Type: Journal    
DOI: 10.1186/1471-2288-11-41     Document Type: Article

References (44)

1. Meta analysis of individual patient data from randomized trials: a review of methods used in practice. M Simmonds J Higgins L Stewart J Tierney M Clarke S Thompson, Clinical Trials 2005 2 209 217 10.1191/1740774505cn087oa 16279144 (Pubitemid 40910470)
2. Bias in the analysis and reporting of randomized controlled trials. L Stewart M Parmar, International Journal of Technology Assessment in Health Care 1996 12 264 275 10.1017/S0266462300009612 8707499 (Pubitemid 26195524)
3. Meta-analysis in clinical trials. R DerSimonian N Laird, Controlled Clinical Trials 1986 7 177 188 10.1016/0197-2456(86)90046-2 3802833 (Pubitemid 17189972)
4. Quantifying heterogeneity in a meta-analysis. J Higgins S Thompson, Statistics in Medicine 2002 21 1539 1558 10.1002/sim.1186 12111919 (Pubitemid 34746062)
5. Measuring inconsistency in meta-analyses. J Higgins S Thompson J Deeks D Altman, BMJ 2003 327 557 560 12958120 10.1136/bmj.327.7414.557 (Pubitemid 37088507)
6. J Higgins S Green, Cochrane Handbook for Systematic Reviews of Interventions Version 5.0.2 The Cochrane Collaboration 2009 http://www.cochrane- handbook.org
7. Chemotherapy in advanced ovarian cancer: an overview of randomised clinical trials. Advanced Ovarian Cancer Trials Group. AOCTG, British Medical Journal 1991 303 884 893 1834291 10.1136/bmj.303.6807.884
8. Chemotherapy in non-small cell lung cancer: a meta-analysis using updated data on individual patients from 52 randomised trials. Non-Small cell Lung cancer Collaborative group. NSCLC, British Medical Journal 1995 311 899 909 7580546
9. Adjuvant chemotherapy for localised resectable soft tissue sarcoma of adults: meta-analysis of individual data. Sarcoma Meta-analysis Collaboration. SMC, Lancet 1997 350 1647 1654 10.1016/S0140-6736(97)08165-8 9400508
10. Chemotherapy in advanced ovarian cancer: for systematic meta-analyses of individual patient data from 37 randomized trials. Advanced Ovarian Cancer Trials Group. AOCTG, British Journal of Cancer 1998 78 1479 1487 9836481 10.1038/bjc.1998.710
11. Postoperative radiotherapy in non-small-cell lung cancer: systematic review and meta-analysis of individual patient data from nine-randomised controlled trials. PORT Meta-analysis Trialists Group. PMTG, Lancet 1998 352 257 263 10.1016/S0140-6736(98)06341-7 9690404
12. Preoperative radiotherapy in esophageal carcinoma: A meta-analysis using individual patient data. Oesophageal Cancer Collaborative Group. OCCG, Int J Radiation Oncology Biol Phys 1998 41 579 583 10.1016/S0360-3016(97)00569-5 (Pubitemid 28275087)
13. Chemotherapy in adult high-grade glioma: a systematic review and meta-analysis of individual patient data from 12 randomised trials. Glioma Meta-analysis Trialists Group. GMTG, Lancet 2002 359 1011 1018 10.1016/S0140-6736(02)08091-1 11937180
14. Neoadjuvant chemotherapy in invasive bladder cancer: a systematic review and meta-analysis. Advanced Bladder Cancer Meta-analysis Collaboration. ABCMC, Lancet 2003 361 1927 1934 10.1016/S0140-6736(03)13580-5 12801735
15. Neoadjuvant chemotherapy for locally advanced cervical cancer: A systematic review and meta-analysis of individual patient data from 21 randomised trials. Neoadjuvant Chemotherapy for Cervix Cancer Meta-analysis Collaboration. NACCCMA, European Journal of Cancer 2003 39 2470 2486 10.1016/S0959-8049(03)00425-8 14602133
16. Adjuvant chemotherapy in invasive bladder cancer: a systematic review and meta-analysis of individual patient data. Advanced Bladder Cancer Meta-analysis Collaboration. ABCMC, European Urology 2005 48 189 201 10.1016/j.eururo.2005. 04.005 15939530
17. Reducing uncertainties about the effects of chemoradiotherapy for cervical cancer: a systematic review and meta-analysis of individual patient data from 18 randomized trials. Chemoradiotherapy for Cervical Cancer Meta-analysis Collaboration. CCCMC, Journal of Clinical Oncology 2008 26 5802 5812 19001332 10.1200/JCO.2008.16.4368
18. Beta blockade during and after myocardial infarction: an overview of the randomised trials. S Yusef R Peto, Prog Cardio Dis 1985 27 335 371 10.1016/S0033-0620(85)80003-7 (Pubitemid 15107153)
19. A re-evaluation of random-effects meta-analysis. J Higgins S Thompson D Spiegelhalter, J Royal Statistical Soc Series A 2009 172 137 159
20. A likelihood approach to meta-analysis with random effects. R Hardy S Thompson, Statistics in Medicine 1999 15 619 629 10.1002/(SICI)1097- 0258(19960330)15:6<619::AID-SIM188>3.0.CO;2-A
21. Bayesian meta-analysis, with application to studies of ETS and lung cancer. R Tweedie D Scott B Biggerstaff K Mengersen, Lung Cancer 1996 14 171 S194 10.1016/S0169-5002(96)90222-6 8785662
22. Random-effects models for meta-analysis of clinical trials: An update. R DerSimonian R Kacker, Contemporary Clinical Trials 2007 28 105 114 10.1016/j.cct.2006.04.004 16807131 (Pubitemid 44937874)
23. Consensus values and weighting factors. R Paule J Mandel, J Res Natl Bur Stand 1982 87 377 385
24. Restricted maximum likelihood estimation of a common mean and the Mandel-Paule algorithm. A Ruhkin B Biggerstaff M Vangel, Journal of Statistical Planning and Inference 2000 83 319 330 10.1016/S0378-3758(99)00098-1
25. Confidence intervals for the amount of heterogeneity in meta-analysis. W Viechtbauer, Statistics in Medicine 2007 26 37 52 10.1002/sim.2514 16463355 (Pubitemid 46099416)
26. Incorporating variability in estimates of heterogeneity in the random effect smodel in meta-analysis. B Biggerstaff R Tweedie, Statistics in Medicine 1997 16 753 768 10.1002/(SICI)1097-0258(19970415)16:7<753::AID-SIM494>3.0. CO;2-G 9131763 (Pubitemid 27165681)
27. Simple heterogeneity variance estimation for meta-analysis. K Sidik J Jonkman, J Royal Statistical Soc Series C 2005 54 367 384 10.1111/j.1467-9876. 2005.00489.x (Pubitemid 40306660)
28. 2 Index? T Huedo-Medina J Sanchez-Meca F Marin-Martinez J Botella, Psychological Methods 2006 11 193 206 10.1037/1082-989X.11.2.193 16784338 (Pubitemid 44001277)
29. R Light D Pillemer, Summing up: The Science of Reviewing Research Cambridge: Harvard University Press 1984
30. Bias in meta-analysis detected by a simple graphical test. M Egger G Davey-Smith M Schneider C Minder, British Medical Journal 1997 315 629 634 9310563 (Pubitemid 27387172)
31. A robust P-value for treatment effect in meta-analysis with publication bias. J Copas P Malley, Statistics in Medicine 2008 27 4267 4278 10.1002/sim.3284 18384185
32. A graphical method for exploring heterogeneity in meta-analyses: application to a meta-analysis of 65 trials. B Baujat C Mahe J Pignon C Hill, Statistics in Medicine 2002 21 2641 2652 10.1002/sim.1221 12228882
33. Graphical displays for meta-analysis: An overview with suggestions for practice. J Anzures-Cabrera J Higgins, Research Synthesis Methods 2010 1 66 80 10.1002/jrsm.6
34. Invited Commentary: A Critical Look at Some Popular Meta-Analytic Methods. S Greenland, American Journal of Epidemiology 1994 140 291 296
35. Meta-regression methods for detecting and estimating empirical effects in the presence of publication selection. T Stanley, Oxford Bulletin of Economics and Statistics 2008 70 103 127
36. Assessment of regression-based methods to adjust for publication bias through a comprehensive simulation study. S Moreno A Sutton A Ades T Stanley K Abrams J Peters N Cooper, BMC Medical Research Methodology 2009 9 2 19138428 10.1186/1471-2288-9-2
37. Treatment-effect estimates adjusted for small study effects via a limit meta-analysis. G Rücker G Schwarzer J Carpenter H Binder M Shumacher, Biostatistics 2011 12 122 142 10.1093/biostatistics/kxq046 20656692
38. Confidence intervals for random effects meta-analysis and robustness to publication bias. M Henmi J Copas, Statistics in Medicine 2010 29 2969 2983 10.1002/sim.4029 20963748
39. A new approach to outliers in meta-analysis. R Baker D Jackson, Health Care Management Science 2008 11 121 131 10.1007/s10729-007-9041-8 18581818
40. How does the DerSimonian and Laird procedure for random effects meta-analysis compare with its more efficient but harder to compute counterparts. D Jackson J Bowden R Baker, Journal of Statistical Planning and Inference 2010 140 961 970 10.1016/j.jspi.2009.09.017
41. 2 in assessing heterogeneity may mislead. G Rücker G Schwarzer J Carpenter M Shumacher, BMC Medical Research Methodology 2008 8 79 19036172 10.1186/1471-2288-8-79
42. Sequential meta-analysis: an efficient decision-making tool. I Van der Tweel C Bollen, Clinical Trials 2010 7 136 146 10.1177/1740774509360994 20338906
43. Why sources of heterogeneity in meta-analysis should be investigated. S Thompson, British Medical Journal 1994 309 1351 1355 7866085 (Pubitemid 24345976)
44. Comments on "Empirical vs natural weighting in random effects meta-analysis" by JJ Shuster, Statistics in Medicine 2009. G Rücker G Schwarzer J Carpenter M Shumacher, Statistics in Medicine 2010 29 2963 2965 10.1002/sim.3957 21104939