Multiple treatment comparison meta-analyses: A step forward into complexity

Clinical Epidemiology

Volumn 3, Issue 1, 2011, Pages 193-202

  Mills, Edward J ^a   Bansback, Nick ^b   Ghement, Isabella ^c   Thorlund, Kristian ^d   Kelly, Steven ^e   Puhan, Milo A ^f   Wright, James ^d  

^a UNIVERSITY OF OTTAWA   (Canada)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^c Ghement Statistical Consulting Company   (Canada)

^d MCMASTER UNIVERSITY   (Canada)

^e PFIZER GLOBAL RESEARCH AND DEVELOPMENT   (United Kingdom)

^f JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

Meta analysis; Mixed treatment comparison; Multiple treatment comparison; Network

Indexed keywords

ARTICLE; BAYES THEOREM; BREAST CANCER; CLINICAL TRIAL (TOPIC); COLORECTAL CANCER; HUMAN; LUNG NON SMALL CELL CANCER; MEDICAL DECISION MAKING; MEDICAL INFORMATION; METHODOLOGY; MULTIPLE TREATMENT COMPARISON META ANALYSIS; ONCOLOGY; OVARY CANCER; PREDICTION; RISK ASSESSMENT; STATISTICAL ANALYSIS; STATISTICAL MODEL;

EID: 79959276584     PISSN: None     EISSN: 11791349     Source Type: Journal    
DOI: 10.2147/CLEP.S16526     Document Type: Article

References (59)

1. Sutton AJ, Higgins JP. Recent developments in meta-analysis. Stat Med. 2008;27:625-650.
2. Glenny AM, Altman DG, Song F, et al. Indirect comparisons of competing interventions. Health Technol Assess. 2005;9:1-134, iii-iv.
3. Stampfer MJ, Goldhaber SZ, Yusuf S, et al. Effect of intravenous streptokinase on acute myocardial infarction: pooled results from randomized trials. N Engl J Med. 1982;307:1180-1182.
4. Yusuf S, Peto R, Lewis J, et al. Beta blockade during and after myocardial infarction: an overview of the randomized trials. Prog Cardiovasc Dis. 1985;27:335-371.
5. Chalmers I. The Cochrane Collaboration: preparing, maintaining, and disseminating systematic reviews of the effects of health care. Ann N Y Acad Sci. 1993;703:156-163; discussion 63-65.
6. Bucher HC, Guyatt GH, Griffith LE, Walter SD. The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials. J Clin Epidemiol. 1997;50:683-691.
7. Lu G, Ades AE. Combination of direct and indirect evidence in mixed treatment comparisons. Stat Med. 2004;23:3105-3124.
8. Cooper NJ, Sutton AJ, Morris D, et al. Addressing between-study heterogeneity and inconsistency in mixed treatment comparisons: application to stroke prevention treatments in individuals with non-rheumatic atrial fibrillation. Stat Med. 2009;28:1861-1881.
9. Lumley T. Network meta-analysis for indirect treatment comparisons. Stat Med. 2002;21:2313-2324.
10. Song F, Loke YK, Walsh T, et al. Methodological problems in the use of indirect comparisons for evaluating healthcare interventions: survey of published systematic reviews. BMJ. 2009;338:b1147.
11. O'Regan C, Ghement I, Eyawo O, et al. Incorporating multiple interventions in meta-analysis: an evaluation of the mixed treatment comparison with the adjusted indirect comparison. Trials. 2009;10:86.
12. Higgins JP, Whitehead A. Borrowing strength from external trials in a meta-analysis. Stat Med. 1996;15:2733-2749.
13. Salanti G, Kavvoura FK, Ioannidis JP. Exploring the geometry of treatment networks. Ann Intern Med. 2008;148:544-553.
14. Borenstein M, Hedges L, Higgins JP, Rothstein H. Introduction to Meta-analysis. Chichester: John Wiley & Sons, 2009.
15. Sanchez-Meca J, Marin-Martinez F. Confidence intervals for the overall effect size in random-effects meta-analysis. Psychol Methods. 2008;13: 31-48.
16. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7:177-188.
17. Golfinopoulos V, Pentheroudakis G, Salanti G, et al. Comparative survival with diverse chemotherapy regimens for cancer of unknown primary site: multiple-treatments meta-analysis. Cancer Treat Rev. 2009;35:570-573.
18. Kyrgiou M, Salanti G, Pavlidis N, et al. Survival benefits with diverse chemotherapy regimens for ovarian cancer: meta-analysis of multiple treatments. J Natl Cancer Inst. 2006;98:1655-1663.
19. Mauri D, Polyzos NP, Salanti G, et al. Multiple-treatments meta-analysis of chemotherapy and targeted therapies in advanced breast cancer. J Natl Cancer Inst. 2008;100:1780-1791.
20. Cardoso F, Bedard PL, Winer EP, et al. International guidelines for management of metastatic breast cancer: combination vs sequential singleagent chemotherapy. J Natl Cancer Inst. 2009;101:1174-1181.
21. Wilcox RA, Djulbegovic B, Moffitt HL, et al. Randomized trials in oncology stopped early for benefit. J Clin Oncol. 2008;26:18-19.
22. Montori VM, Devereaux PJ, Adhikari NK, et al. Randomized trials stopped early for benefit: a systematic review. JAMA. 2005;294: 2203-2209.
23. Bassler D, Ferreira-Gonzalez I, Briel M, et al. Systematic reviewers neglect bias that results from trials stopped early for benefit. J Clin Epidemiol. 2007;60:869-873.
24. Ioannidis JP. Indirect comparisons: the mesh and mess of clinical trials. Lancet. 2006;368:1470-1472.
25. Song F, Harvey I, Lilford R. Adjusted indirect comparison may be less biased than direct comparison for evaluating new pharmaceutical interventions. J Clin Epidemiol. 2008;61:455-463.
26. Mills EJ, Wu P, Spurden D, et al. Efficacy of pharmacotherapies for short-term smoking abstinance: a systematic review and meta-analysis. Harm Reduct J. 2009;6:25.
27. Mills EJ, Ghement I, O'Regan C, Thorlund K. Estimating the power of indirect comparisons: a simulation study. PLOS One. 2011;6: e16237.
28. Ioannidis JP. Integration of evidence from multiple meta-analyses: a primer on umbrella reviews, treatment networks and multiple treatments meta-analyses. CMAJ. 2009;181:488-493.
29. Dias S, Welton NJ, Caldwell DM, Ades AE. Checking consistency in mixed treatment comparison meta-analysis. Stat Med. 2010;29: 932-944.
30. Thorlund K, Anema A, Mills E. Interpreting meta-analysis according to the adequacy of sample size. An example using isoniazid chemoprophylaxis for tuberculosis in purified protein derivative negative HIV-infected individuals. Clinical Epidemiology. 2010;2:1-10.
31. Thorlund K, Devereaux PJ, Wetterslev J, et al. Can trial sequential monitoring boundaries reduce spurious inferences from meta-analyses? Int J Epidemiol. 2009;38:276-286.
32. Trikalinos TA, Churchill R, Ferri M, et al. Effect sizes in cumulative meta-analyses of mental health randomized trials evolved over time. J Clin Epidemiol. 2004;57:1124-1130.
33. Berkey CS, Mosteller F, Lau J, Antman EM. Uncertainty of the time of first significance in random effects cumulative meta-analysis. Control Clin Trials. 1996;17:357-371.
34. Brok J, Thorlund K, Wetterslev J, Gluud C. Apparently conclusive metaanalyses may be inconclusive: trial sequential analysis adjustment of random error risk due to repetitive testing of accumulating data in apparently conclusive neonatal meta-analyses. Int J Epidemiol. 2009;38:287-298.
35. Saad ED, Katz A, Hoff PM, Buyse M. Progression-free survival as surrogate and as true end point: insights from the breast and colorectal cancer literature. Ann Oncol. 2009;21:7-12.
36. Di Leo A, Bleiberg H, Buyse M. Overall survival is not a realistic end point for clinical trials of new drugs in advanced solid tumors: a critical assessment based on recently reported phase III trials in colorectal and breast cancer. J Clin Oncol. 2003;21:2045-2047.
37. Di Leo A, Buyse M, Bleiberg H. Is overall survival a realistic primary end point in advanced colorectal cancer studies? A critical assessment based on four clinical trials comparing fluorouracil plus leucovorin with the same treatment combined either with oxaliplatin or with CPT-11. Ann Oncol. 2004;15:545-549.
38. Thomsen IM, Crawford ED. Adjuvant radiotherapy for pathological T3N0M0 prostate cancer. J Urol. 2009;181:956.
39. Mouridsen H, Gershanovich M, Sun Y, et al. Superior efficacy of letrozole versus tamoxifen as first-line therapy for postmenopausal women with advanced breast cancer: results of a phase III study of the International Letrozole Breast Cancer Group. J Clin Oncol. 2001;19:2596-2606.
40. Mouridsen H, Gershanovich M, Sun Y, et al. Phase III study of letrozole versus tamoxifen as first-line therapy of advanced breast cancer in postmenopausal women: analysis of survival and update of efficacy from the International Letrozole Breast Cancer Group. J Clin Oncol. 2003;21:2101-2109.
41. Fleming TR, Rothmann MD, Lu HL. Issues in using progression-free survival when evaluating oncology products. J Clin Oncol. 2009;27: 2874-2880.
42. Fergusson D, Aaron SD, Guyatt G, Hebert P. Post-randomisation exclusions: the intention to treat principle and excluding patients from analysis. BMJ. 2002;325:652-654.
43. Mills EJ, Chan AW, Wu P, et al. Design, analysis, and presentation of crossover trials. Trials. 2009;10:27.
44. Carroll KJ. Analysis of progression-free survival in oncology trials: some common statistical issues. Pharm Stat. 2007;6:99-113.
45. Akl EA, Briel M, You JJ, et al. LOST to follow-up Information in Trials (LOST-IT): a protocol on the potential impact. Trials. 2009;10:40.
46. Tuma R. Progression-free survival remains debatable endpoint in cancer trials. J Natl Cancer Inst. 2009;101:1439-1441.
47. Davey-Smith G, Egger M, Going beyond the grand mean: subgroup analysis in meta-analysis of randomised trials. Systematic Reviews in Health Care: Meta-analysis in Context. 2nd ed. London, England: BMJ Publishing Group. 2001:143-156.
48. Thompson SG, Higgins JP. How should meta-regression analyses be undertaken and interpreted? Stat Med. 2002;21:1559-1573.
49. Nixon RM, Bansback N, Brennan A. Using mixed treatment comparisons and meta-regression to perform indirect comparisons to estimate the efficacy of biologic treatments in rheumatoid arthritis. Stat Med. 2007;26:1237-1254.
50. Cristofanilli M, Hayes DF, Budd GT, et al. Circulating tumor cells: a novel prognostic factor for newly diagnosed metastatic breast cancer. J Clin Oncol. 2005;23:1420-1430.
51. Bucher HC, Guyatt GH, Griffith LE, Walter SD. The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials. J Clin Epidemiol. 1997;50:683-691.
52. Spiegelhalter DJ, Myles JP, Jones DR, Abrams KR. Bayesian methods in health technology assessment: a review. Health Technol Assess. 2000;4:1-130.
53. Ades AE, Sculpher M, Sutton A, et al. Bayesian methods for evidence synthesis in cost-effectiveness analysis. Pharmacoeconomics. 2006; 24:1-19.
54. Miksad RA, Gonen M, Lynch TJ, Roberts TG Jr. Interpreting trial results in light of conflicting evidence: a Bayesian analysis of adjuvant chemotherapy for non-small-cell lung cancer. J Clin Oncol. 2009;27: 2245-2252.
55. Atkins D, Best D, Briss PA, et al. Grading quality of evidence and strength of recommendations. BMJ. 2004;328:1490.
56. Guyatt GH, Oxman AD, Vist GE, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336:924-926.
57. Golfinopoulos V, Salanti G, Pavlidis N, Ioannidis JP. Survival and disease-progression benefits with treatment regimens for advanced colorectal cancer: a meta-analysis. Lancet Oncol. 2007;8:898-911.
58. Hawkins N, Scott DA, Woods BS, Thatcher N. No study left behind: a network meta-analysis in non-small-cell lung cancer demonstrating the importance of considering all relevant data. Value Health. 2009;12: 996-1003.
59. Griffin S, Bojke L, Main C, Palmer S. Incorporating direct and indirect evidence using Bayesian methods: an applied case study in ovarian cancer. Value Health. 2006;9:123-131.