Methods and Biostatistics in Oncology pp 287-305 | Cite as
Systematic Reviews and Meta-Analyses of Oncology Studies
Abstract
This chapter is intended principally for practicing clinicians who want to understand the concepts of and reasons for conducting systematic reviews and meta-analyses in oncology. Although there are a few striking examples of cancer treatments that really do work extremely well, most claims for efficacy turn out to be limited. Uncertainties coming from results obtained by different clinical studies need to be interpreted. Systematic reviews can define whether scientific findings are consistent and can be generalized across populations and treatment variations, or whether findings vary significantly by particular subsets. Meta-analyses can increase the power and precision of estimates of treatment effects and exposure risks. Explicit methods should be used to limit bias and improve the reliability and accuracy of conclusions. In the field of clinical oncology, there are several reasons for conducting a systematic review with meta-analyses. Here we discuss how to perform and interpret these studies, and present the main statistical concepts with examples from the literature.
Keywords
Systematic review Meta-analysis Oncology Cancer Individual patient data MetabiasReferences
- 1.Mulrow CD. Rationale for systematic reviews. BMJ. 1994;309(6954):597–9.CrossRefGoogle Scholar
- 2.Tebala GD. What is the future of biomedical research? Med Hypotheses. 2015;85(4):488–90.CrossRefGoogle Scholar
- 3.Pereira AA, Rego JF, Munhoz RR, Hoff PM, Sasse AD, Riechelmann RP. The impact of complete chemotherapy stop on the overall survival of patients with advanced colorectal cancer in first-line setting: a meta-analysis of randomized trials. Acta Oncol. 2015;54(10):1737–46.CrossRefGoogle Scholar
- 4.Sampson M, Barrowman NJ, Moher D, Klassen TP, Pham B, Platt R, et al. Should meta-analysts search EMBASE in addition to Medline? J Clin Epidemiol. 2003;56(10):943–55.CrossRefGoogle Scholar
- 5.Sasse AD, Santos L. Searching LILACS database is irrelevant in systematic reviews in oncology. In: Evidence in the era of globalisation. Abstracts of the 16th Cochrane colloquium. Freiburg, Germany. p. 2008.Google Scholar
- 6.Chan AW, Hrobjartsson A, Haahr MT, Gotzsche PC, Altman DG. Empirical evidence for selective reporting of outcomes in randomized trials: comparison of protocols to published articles. JAMA. 2004;291(20):2457–65.CrossRefGoogle Scholar
- 7.Lee K, Bacchetti P, Sim I. Publication of clinical trials supporting successful new drug applications: a literature analysis. PLoS Med. 2008;5(9):e191.CrossRefGoogle Scholar
- 8.Dwan K, Altman DG, Arnaiz JA, Bloom J, Chan AW, Cronin E, et al. Systematic review of the empirical evidence of study publication bias and outcome reporting bias. PLoS One. 2008;3(8):e3081.CrossRefGoogle Scholar
- 9.Kicinski M. Publication bias in recent meta-analyses. PLoS One. 2013;8(11):e81823.CrossRefGoogle Scholar
- 10.Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34.CrossRefGoogle Scholar
- 11.Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994;50(4):1088–101.CrossRefGoogle Scholar
- 12.Duval S, Tweedie R. Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics. 2000;56(2):455–63.CrossRefGoogle Scholar
- 13.Terrin N, Schmid CH, Lau J. In an empirical evaluation of the funnel plot, researchers could not visually identify publication bias. J Clin Epidemiol. 2005;58(9):894–901.CrossRefGoogle Scholar
- 14.Sterne JA, Sutton AJ, Ioannidis JP, Terrin N, Jones DR, Lau J, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ. 2011;343:d4002.CrossRefGoogle Scholar
- 15.Hopewell S, McDonald S, Clarke M, Egger M. Grey literature in meta-analyses of randomized trials of health care interventions. Cochrane Database Syst Rev. 2007;2. MR000010Google Scholar
- 16.McAuley L, Pham B, Tugwell P, Moher D. Does the inclusion of grey literature influence estimates of intervention effectiveness reported in meta-analyses? Lancet. 2000;356(9237):1228–31.CrossRefGoogle Scholar
- 17.Fergusson D, Laupacis A, Salmi LR, McAlister FA, Huet C. What should be included in meta-analyses? An exploration of methodological issues using the ISPOT meta-analyses. Int J Technol Assess Health Care. 2000;16(4):1109–19.CrossRefGoogle Scholar
- 18.Burdett S, Stewart LA, Tierney JF. Publication bias and meta-analyses: a practical example. Int J Technol Assess Health Care. 2003;19(1):129–34.CrossRefGoogle Scholar
- 19.Cook DJ, Guyatt GH, Ryan G, Clifton J, Buckingham L, Willan A, et al. Should unpublished data be included in meta-analyses? Current convictions and controversies. JAMA. 1993;269(21):2749–53.CrossRefGoogle Scholar
- 20.Tetzlaff J, Moher D, Pham B, Altman D, editors. Survey of views on including grey literature in systematic reviews. 14th Cochrane Colloquium; Dublin, Ireland. 2006.Google Scholar
- 21.Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009;339:b2700.CrossRefGoogle Scholar
- 22.Moher D, Liberati A, Tetzlaff J, Altman DG, Prisma Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol. 2009;62(10):1006–12.CrossRefGoogle Scholar
- 23.Shea BJ, Grimshaw JM, Wells GA, Boers M, Andersson N, Hamel C, et al. Development of AMSTAR: a measurement tool to assess the methodological quality of systematic reviews. BMC Med Res Methodol. 2007;7:10.CrossRefGoogle Scholar
- 24.Higgins JPT, Green S (editors). Cochrane handbook for systematic reviews of interventions version 5.1.0 [updated March 2011]. The cochrane collaboration, 2011. Available from http://handbook.cochrane.org.
- 25.Buscemi N, Hartling L, Vandermeer B, Tjosvold L, Klassen TP. Single data extraction generated more errors than double data extraction in systematic reviews. J Clin Epidemiol. 2006;59(7):697–703.CrossRefGoogle Scholar
- 26.Keene ON. Alternatives to the hazard ratio in summarizing efficacy in time-to-event studies: an example from influenza trials. Stat Med. 2002;21(23):3687–700.CrossRefGoogle Scholar
- 27.Tierney JF, Stewart LA, Ghersi D, Burdett S, Sydes MR. Practical methods for incorporating summary time-to-event data into meta-analysis. Trials. 2007;8:16.CrossRefGoogle Scholar
- 28.Moher D, Pham B, Jones A, Cook DJ, Jadad AR, Moher M, et al. Does quality of reports of randomised trials affect estimates of intervention efficacy reported in meta-analyses? Lancet. 1998;352(9128):609–13.CrossRefGoogle Scholar
- 29.Higgins JP, Altman DG, Gotzsche PC, Juni P, Moher D, Oxman AD, et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928.CrossRefGoogle Scholar
- 30.Jadad AR, Moore RA, Carroll D, Jenkinson C, Reynolds DJ, Gavaghan DJ, et al. Assessing the quality of reports of randomized clinical trials: is blinding necessary? Control Clin Trials. 1996;17(1):1–12.CrossRefGoogle Scholar
- 31.Verhagen AP, de Vet HC, de Bie RA, Kessels AG, Boers M, Bouter LM, et al. The Delphi list: a criteria list for quality assessment of randomized clinical trials for conducting systematic reviews developed by Delphi consensus. J Clin Epidemiol. 1998;51(12):1235–41.CrossRefGoogle Scholar
- 32.Pildal J, Hrobjartsson A, Jorgensen KJ, Hilden J, Altman DG, Gotzsche PC. Impact of allocation concealment on conclusions drawn from meta-analyses of randomized trials. Int J Epidemiol. 2007;36(4):847–57.CrossRefGoogle Scholar
- 33.Wood L, Egger M, Gluud LL, Schulz KF, Juni P, Altman DG, et al. Empirical evidence of bias in treatment effect estimates in controlled trials with different interventions and outcomes: meta-epidemiological study. BMJ. 2008;336(7644):601–5.CrossRefGoogle Scholar
- 34.Holmes J, Herrmann D, Koller C, Khan S, Umberham B, Worley JA, et al. Heterogeneity of systematic reviews in oncology. Proc (Bayl Univ Med Cent). 2017;30(2):163–6.CrossRefGoogle Scholar
- 35.Borenstein M, Hedges LV, Higgins JP, Rothstein HR. A basic introduction to fixed-effect and random-effects models for meta-analysis. Res Synth Methods. 2010;1(2):97–111.CrossRefGoogle Scholar
- 36.Higgins J, Thompson S, Deeks J, Altman D. Statistical heterogeneity in systematic reviews of clinical trials: a critical appraisal of guidelines and practice. J Health Serv Res Policy. 2002;7(1):51–61.CrossRefGoogle Scholar
- 37.Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–60.CrossRefGoogle Scholar
- 38.Munhoz RR, Pereira AA, Sasse AD, Hoff PM, Traina TA, Hudis CA, et al. Gonadotropin-releasing hormone agonists for ovarian function preservation in premenopausal women undergoing chemotherapy for early-stage breast cancer: a systematic review and meta-analysis. JAMA Oncol. 2016;2(1):65–73.CrossRefGoogle Scholar
- 39.Stewart LA, Tierney JF. To IPD or not to IPD? Advantages and disadvantages of systematic reviews using individual patient data. Eval Health Prof. 2002;25(1):76–97.CrossRefGoogle Scholar
- 40.Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336(7650):924–6.CrossRefGoogle Scholar
- 41.Hultcrantz M, Rind D, Akl EA, Treweek S, Mustafa RA, Iorio A, et al. The GRADE Working Group clarifies the construct of certainty of evidence. J Clin Epidemiol. 2017;87:4–13.CrossRefGoogle Scholar
- 42.Guyatt GH, Haynes RB, Jaeschke RZ, Cook DJ, Green L, Naylor CD, et al. Users' guides to the medical literature: XXV. Evidence-based medicine: principles for applying the users' guides to patient care. Evidence-Based Medicine Working Group. JAMA. 2000;284(10):1290–6.CrossRefGoogle Scholar
- 43.Villar J, Carroli G, Belizan JM. Predictive ability of meta-analyses of randomised controlled trials. Lancet. 1995;345(8952):772–6.CrossRefGoogle Scholar
- 44.Cappelleri JC, Ioannidis JP, Schmid CH, de Ferranti SD, Aubert M, Chalmers TC, et al. Large trials vs meta-analysis of smaller trials: how do their results compare? JAMA. 1996;276(16):1332–8.CrossRefGoogle Scholar
- 45.LeLorier J, Gregoire G, Benhaddad A, Lapierre J, Derderian F. Discrepancies between meta-analyses and subsequent large randomized, controlled trials. N Engl J Med. 1997;337(8):536–42.CrossRefGoogle Scholar