Methodological standards for meta-analyses and qualitative systematic reviews of cardiac prevention and treatment studies a scientific statement from the American Heart Association

Circulation

Volumn 136, Issue 10, 2017, Pages e172-e194

  Rao, Goutham ^a   Lopez Jimenez, Francisco ^a   Boyd, Jack ^a   D'Amico, Frank ^a   Durant, Nefertiti H ^a   Hlatky, Mark A ^a   Howard, George ^a   Kirley, Katherine ^a   Masi, Christopher ^a   Powell Wiley, Tiffany M ^a   Solomonides, Anthony E ^a   West, Colin P ^a   Wessel, Jennifer ^a  

^a NONE

Author keywords

AHA scientific statements; Meta analysis as topic; Methodology; Prevention and control; Research; Review; Standards; Therapeutics

Indexed keywords

ARTICLE; BAYESIAN LEARNING; CARDIOVASCULAR DISEASE; CONSULTATION; DATA EXTRACTION; HUMAN; MEDICAL SOCIETY; META ANALYSIS (TOPIC); NETWORK META-ANALYSIS; PRIORITY JOURNAL; PUBLISHING; QUALITY CONTROL; REGISTRATION; SENSITIVITY ANALYSIS; STATISTICAL ANALYSIS; STUDY DESIGN; SYSTEMATIC REVIEW (TOPIC); FEMALE; HEART DISEASES; MALE; META ANALYSIS; UNITED STATES;

AMERICAN HEART ASSOCIATION; FEMALE; HEART DISEASES; HUMANS; MALE; UNITED STATES;

EID: 85030442176     PISSN: 00097322     EISSN: 15244539     Source Type: Journal    
DOI: 10.1161/CIR.0000000000000523     Document Type: Article

References (113)

1. Glass GV. Primary, secondary and meta-analysis of research. Educ Res. 1976;5:3-8.
2. Tebala GD. What is the future of biomedical research? Med Hypotheses. 2015;85:488-490. doi: 10.1016/j.mehy.2015.07.003.
3. Sackett DL, Rosenberg WM, Gray JA, Haynes RB, Richardson WS. Evidence based medicine: what it is and what it isn't. BMJ. 1996;312: 71-72.
4. Oxford Centre for Evidence-Based Medicine. Levels of evidence March 2009 http://www.cebm.net/oxford-centre-evidence-based-medicinelevels-evidence-march-2009/. Accessed October 2 2015.
5. Kristiansen IS. Evidence-based medicine: time for asking critical questions? ISPOR 9th Annual European Congress. http://www.ispor.org/news/articles/june07/ebmt.asp. Accessed March 25, 2016.
6. Concato J. Study design and "evidence" in patient-oriented research. Am J Respir Crit Care Med. 2013;187:1167-1172. doi: 10.1164/rccm.201303-0521OE.
7. Bero LA, Jadad AR. How consumers and policymakers can use systematic reviews for decision making. Ann Intern Med. 1997;127:37-42.
8. Bailar JC 3rd. The practice of meta-analysis. J Clin Epidemiol. 1995;48: 149-157.
9. Bailar JC 3rd. The promise and problems of meta-analysis. N Engl J Med. 1997;337:559-561. doi: 10.1056/NEJM199708213370810.
10. Berlin JA, Golub RM. Meta-analysis as evidence: building a better pyramid. JAMA. 2014;312:603-605. doi: 10.1001/jama.2014.8167.
11. Lundh A, Knijnenburg SL, Jørgensen AW, van Dalen EC, Kremer LC. Quality of systematic reviews in pediatric oncology: a systematic review. Cancer Treat Rev. 2009;35:645-652. doi: 10.1016/j.ctrv.2009.08.010.
12. Schroll JB, Moustgaard R, Gøtzsche PC. Dealing with substantial heterogeneity in Cochrane reviews. Cross-sectional study. BMC Med Res Methodol. 2011;11:22. doi: 10.1186/1471-2288-11-22.
13. Ioannidis JP. The mass production of redundant, misleading, and conflicted systematic reviews and meta-analyses. Milbank Q. 2016;94:485-514. doi: 10.1111/1468-0009.12210.
14. Eden J, Levit L, Berg A, Mortin M, eds. Finding What Works in Health Care: Standards for Systematic Reviews. Washington, DC: Institute of Medicine; 2011.
15. Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097. doi: 10.1371/journal.pmed.1000097.
16. Shea BJ, Hamel C, Wells GA, Bouter LM, Kristjansson E, Grimshaw J, Henry DA, Boers M. AMSTAR is a reliable and valid measurement tool to assess the methodological quality of systematic reviews. J Clin Epidemiol. 2009;62:1013-1020. doi: 10.1016/j.jclinepi.2008.10.009.
17. Stawicki SPA. Research guide: guide to statistical software: meta-analysis applications. Opus 12 Scientist. 2011;5:4-5.
18. Schardt C, Adams MB, Owens T, Keitz S, Fontelo P. Utilization of the PICO framework to improve searching PubMed for clinical questions. BMC Med Inform Decis Mak. 2007;7:16. doi: 10.1186/1472-6947-7-16.
19. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, Clarke M, Devereaux PJ, Kleijnen J, Moher D. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol. 2009;62:e1-e34. doi: 10.1016/j.jclinepi.2009.06.006.
20. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA; PRISMA-P Group. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015;4:1. doi: 10.1186/2046-4053-4-1.
21. Page MJ, McKenzie JE, Kirkham J, Dwan K, Kramer S, Green S, Forbes A. Bias due to selective inclusion and reporting of outcomes and analyses in systematic reviews of randomised trials of healthcare interventions. Cochrane Database Syst Rev. 2014:MR000035.
22. Saini P, Loke YK, Gamble C, Altman DG, Williamson PR, Kirkham JJ. Selective reporting bias of harm outcomes within studies: findings from a cohort of systematic reviews. BMJ. 2014;349:g6501.
23. National Institute for Health Research. PROSPERO: International Prospective Register of Systematic Reviews http://www.crd.york.ac.uk/prospero/. Accessed July 10 2017.
24. Booth A, Clarke M, Dooley G, Ghersi D, Moher D, Petticrew M, Stewart L. The nuts and bolts of PROSPERO: an international prospective register of systematic reviews. Syst Rev. 2012;1:2. doi: 10.1186/2046-4053-1-2.
25. PLoS Medicine Editors. Best practice in systematic reviews: the importance of protocols and registration. PLoS Med. 2011;8:e1001009. doi: 10.1371/journal.pmed.1001009.
26. Suarez-Almazor ME, Belseck E, Homik J, Dorgan M, Ramos-Remus C. Identifying clinical trials in the medical literature with electronic databases: MEDLINE alone is not enough. Control Clin Trials. 2000;21:476-487.
27. Dickersin K, Scherer R, Lefebvre C. Identifying relevant studies for systematic reviews. BMJ. 1994;309:1286-1291.
28. McManus RJ, Wilson S, Delaney BC, Fitzmaurice DA, Hyde CJ, Tobias RS, Jowett S, Hobbs FD. Review of the usefulness of contacting other experts when conducting a literature search for systematic reviews. BMJ. 1998;317:1562-1563.
29. Petitti DB. Meta-Analysis, Decision Analysis, and Cost-Effectiveness Analysis: Methods for Quantitative Synthesis in Medicine. New York, NY: Oxford University Press; 1994.
30. McCrae N, Purssell E. Eligibility criteria in systematic reviews published in prominent medical journals: a methodological review. J Eval Clin Pract. 2015;21:1052-1058. doi: 10.1111/jep.12448.
31. Higgins JPT, Green S, Cochrane Collaboration. Cochrane Handbook for Systematic Reviews of Interventions. Chichester, UK: Wiley-Blackwell; 2008.
32. Yoshii A, Plaut DA, McGraw KA, Anderson MJ, Wellik KE. Analysis of the reporting of search strategies in Cochrane systematic reviews. J Med Libr Assoc. 2009;97:21-29. doi: 10.3163/1536-5050.97.1.004.
33. Bratton DJ, Gaisl T, Wons AM, Kohler M. CPAP vs mandibular advancement devices and blood pressure in patients with obstructive sleep apnea: a systematic review and meta-analysis. JAMA. 2015;314:2280-2293. doi: 10.1001/jama.2015.16303.
34. Tan P, Wei S, Tang Z, Gao L, Zhang C, Nie P, Yang L, Wei Q. LDL-lowering therapy and the risk of prostate cancer: a meta-analysis of 6 randomized controlled trials and 36 observational studies. Sci Rep. 2016;6:24521. doi: 10.1038/srep24521.
35. Sanderson S, Tatt ID, Higgins JP. Tools for assessing quality and susceptibility to bias in observational studies in epidemiology: a systematic review and annotated bibliography. Int J Epidemiol. 2007;36:666-676. doi: 10.1093/ije/dym018.
36. Moher D, Jadad AR, Nichol G, Penman M, Tugwell P, Walsh S. Assessing the quality of randomized controlled trials: an annotated bibliography of scales and checklists. Control Clin Trials. 1995;16:62-73.
37. Jüni P, Witschi A, Bloch R, Egger M. The hazards of scoring the quality of clinical trials for meta-analysis. JAMA. 1999;282:1054-1060.
38. Hartling L, Ospina M, Liang Y, Dryden DM, Hooton N, Krebs Seida J, Klassen TP. Risk of bias versus quality assessment of randomised controlled trials: cross sectional study. BMJ. 2009;339:b4012.
39. Viswanathan M, Ansari MT, Berkman ND, Chang S, Hartling L, McPheeters LM, Santaguida PL, Shamliyan T, Singh K, Tsertsvadze A, Treadwell JR. Assessing the risk of bias of individual studies in systematic reviews of health care interventions: Agency for Healthcare Research and Quality Methods Guide for Comparative Effectiveness Reviews. March 2012. AHRQ Publication No. 12-EHC047-EF. http://www.effectivehealthcare.ahrq.gov/. Accessed June 8, 2016.
40. Olivo SA, Macedo LG, Gadotti IC, Fuentes J, Stanton T, Magee DJ. Scales to assess the quality of randomized controlled trials: a systematic review. Phys Ther. 2008;88:156-175. doi: 10.2522/ptj.20070147.
41. Cochrane Collaboration. Cochrane Handbook for Systematic Reviews of Interventions. http://handbook.cochrane.org/chapter-12/12-2-1-the-grade-approach.htm. Accessed January 17, 2017.
42. Mustafa RA, Santesso N, Brozek J, Akl EA, Walter SD, Norman G, Kulasegaram M, Christensen R, Guyatt GH, Falck-Ytter Y, Chang S, Murad MH, Vist GE, Lasserson T, Gartlehner G, Shukla V, Sun X, Whittington C, Post PN, Lang E, Thaler K, Kunnamo I, Alenius H, Meerpohl JJ, Alba AC, Nevis IF, Gentles S, Ethier MC, Carrasco-Labra A, Khatib R, Nesrallah G, Kroft J, Selk A, Brignardello-Petersen R, Schünemann HJ. The GRADE approach is reproducible in assessing the quality of evidence of quantitative evidence syntheses. J Clin Epidemiol. 2013;66:736-742; quiz 742.e1-742e-5. doi: 10.1016/j.jclinepi.2013.02.004.
43. Deeks JD, Higgins JPT, Altman D. Chapter 9: analyzing data and undertaking meta-analysis. In: Higgins JPT, Green S, eds. Cochrane Handbook of Systematic Reviews. 2011. http://handbook.cochrane.org/. Accessed February 20, 2016.
44. da Costa BR, Juni P. Systematic reviews and meta-analyses of randomized trials: principles and pitfalls. Eur Heart J. 2014;35:3336-3345.
45. Lau J, Antman EM, Jimenez-Silva J, Kupelnick B, Mosteller F, Chalmers TC. Cumulative meta-analysis of therapeutic trials for myocardial infarction. N Engl J Med. 1992;327:248-254. doi: 10.1056/NEJM199207233270406.
46. Clarke M, Brice A, Chalmers I. Accumulating research: a systematic account of how cumulative meta-analyses would have provided knowledge, improved health, reduced harm and saved resources. PLoS One. 2014;9:e102670. doi: 10.1371/journal.pone.0102670.
47. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Part 4: heterogeneity. In: Introduction to Meta-Analysis. Chichester, UK: John Wiley and Sons; 2009:105-125.
48. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557-560. doi: 10.1136/bmj.327. 7414.557.
49. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21:1539-1558. doi: 10.1002/sim.1186.
50. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Identifying and quantifying heterogeneity. Introduction to Meta-Analysis. Chichester, UK: Wiley & Sons; 2009:107-125.
51. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Fixed-effect versus random effects models. In: Introduction to Meta-Analysis. Chichester, UK: John Wiley and Sons; 2009:84.
52. Borenstein M, Higgins JP. Meta-analysis and subgroups. Prev Sci. 2013;14:134-143. doi: 10.1007/s11121-013-0377-7.
53. Sedgwick P. Meta-analyses: heterogeneity and subgroup analysis. BMJ 2013;346:f4040 doi: 10.1136/bmj.f4040.
54. Song F, Sheldon TA, Sutton AJ, Abrams KR, Jones DR. Methods for exploring heterogeneity in meta-analysis. Eval Health Prof. 2001;24:126-151. doi: 10.1177/016327870102400203.
55. Briasoulis A, Agarwal V, Tousoulis D, Stefanadis C. Effects of antihypertensive treatment in patients over 65 years of age: a meta-analysis of randomised controlled studies. Heart. 2014;100:317-323. doi: 10.1136/heartjnl-2013-304111.
56. Gan Y, Gong Y, Tong X, Sun H, Cong Y, Dong X, Wang Y, Xu X, Yin X, Deng J, Li L, Cao S, Lu Z. Depression and the risk of coronary heart disease: a meta-analysis of prospective cohort studies. BMC Psychiatry. 2014;14:371. doi: 10.1186/s12888-014-0371-z.
57. Kunz LM, Normand SL, Sedrakyan A. Meta-analysis of rate ratios with differential follow-up by treatment arm: inferring comparative effectiveness of medical devices. Stat Med. 2015;34:2913-2925. doi: 10.1002/sim.6530.
58. Crippa A, Orsini N. Dose-response meta-analysis of differences in means. BMC Med Res Methodol 2016;16:91. doi: 10.1186/s12874-016-0189-0.
59. Rücker G, Schumacher M. Simpson's paradox visualized: the example of the rosiglitazone meta-analysis. BMC Med Res Methodol. 2008;8:34. doi: 10.1186/1471-2288-8-34.
60. Baker WL, White CM, Cappelleri JC, Kluger J, Coleman CI; Health Outcomes, Policy, and Economics (HOPE) Collaborative Group. Understanding heterogeneity in meta-analysis: the role of meta-regression. Int J Clin Pract. 2009;63:1426-1434. doi: 10.1111/j.1742-1241.2009. 02168.x.
61. Barria Perez AE, Rao SV, Jolly SJ, Pancholy SB, Plourde G, Rimac G, Poirier Y, Costerousse O, Bertrand OF. Meta-analysis of effects of bivalirudin versus heparin on myocardial ischemic and bleeding outcomes after percutaneous coronary intervention. Am J Cardiol. 2016;117:1256-1266. doi: 10.1016/j.amjcard.2016.01.015.
62. Lambert PC, Sutton AJ, Abrams KR, Jones DR. A comparison of summary patient-level covariates in meta-regression with individual patient data meta-analysis. J Clin Epidemiol. 2002;55:86-94.
63. Higgins JP, Lane PW, Anagnostelis B, Anzures-Cabrera J, Baker NF, Cappelleri JC, Haughie S, Hollis S, Lewis SC, Moneuse P, Whitehead A. A tool to assess the quality of a meta-analysis. Res Synth Methods. 2013;4:351-366. doi: 10.1002/jrsm.1092.
64. 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;1:97-111. doi: 10.1002/jrsm.12.
65. Higgins JPT, Green S, eds. Section 9.4, summarizing effects across studies. Cochrane Handbook for Systematic Reviews of Interventions. The Cochrane Collaboration. March 2011. http://www.cochrane-handbook.org. Accessed June 8, 2016.
66. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7:177-188.
67. Greenland S, Salvan A. Bias in the one-step method for pooling study results. Stat Med. 1990;9:247-252.
68. Sweeting MJ, Sutton AJ, Lambert PC. What to add to nothing? Use and avoidance of continuity corrections in meta-analysis of sparse data [published correction appears in Stat Med. 2006;25:2700]. Stat Med. 2004;23:1351-1375. doi: 10.1002/sim.1761.
69. van Houwelingen HC, Arends LR, Stijnen T. Advanced methods in meta-analysis: multivariate approach and meta-regression. Stat Med. 2002;21:589-624.
70. Guolo A, Varin C. Random-effects meta-analysis: the number of studies matters. Stat Methods Med Res. 2017;26:1500-1518. doi: 10.1177/0962280215583568.
71. Jüni P, Holenstein F, Sterne J, Bartlett C, Egger M. Direction and impact of language bias in meta-analyses of controlled trials: empirical study. Int J Epidemiol. 2002;31:115-123.
72. Morrison A, Polisena J, Husereau D, Moulton K, Clark M, Fiander M, Mierzwinski-Urban M, Clifford T, Hutton B, Rabb D. The effect of English-language restriction on systematic review-based meta-analyses: a systematic review of empirical studies. Int J Technol Assess Health Care. 2012;28:138-144. doi: 10.1017/S0266462312000086.
73. Kicinski M. Publication bias in recent meta-analyses [published correction appears in PLoS One. 2014;9]. PLoS One. 2013;8:e81823. doi: 10.1371/journal.pone.0081823.
74. US National Institutes of Health. History, policies, and laws https://clinicaltrials.gov/ct2/about-site/history. Accessed June 5 2016
75. Ghersi D, Pang T. En route to international clinical trial transparency. Lancet. 2008;372:1531-1532. doi: 10.1016/S0140-6736(08)61635-9.
76. Anderson ML, Chiswell K, Peterson ED, Tasneem A, Topping J, Califf RM. Compliance with results reporting at clinicaltrials.gov. N Engl J Med. 2015;372:1031-1039. doi: 10.1056/NEJMsa1409364.
77. Richie ML, Romanuk TN. A meta-analysis of probiotic efficacy for gastrointestinal diseases. PLoS One. 2012;7:e34938. doi: 10.1371/journal. pone.0034938.
78. Liyanage SS, Rahman B, Ridda I, Newall AT, Tabrizi SN, Garland SM, Segelov E, Seale H, Crowe PJ, Moa A, Macintyre CR. The aetiological role of human papillomavirus in oesophageal squamous cell carcinoma: a meta-analysis. PLoS One. 2013;8:e69238. doi: 10.1371/journal. pone.0069238.
79. Stuck, AE, Rubenstein LZ, Wieland D, Bias in meta-analysis detected by a simple, graphical test: asymmetry detected in funnel plot was probably due to true heterogeneity. BMJ. 1998;316:469; author reply 470-471.
80. Sterne JA, Gavaghan D, Egger M. Publication and related bias in metaanalysis: power of statistical tests and prevalence in the literature. J Clin Epidemiol. 2000;53:1119-1129.
81. Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994;50:1088-1101.
82. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315:629-634.
83. Rücker G, Schwarzer G, Carpenter J. Arcsine test for publication bias in meta-analyses with binary outcomes. Stat Med. 2008;27:746-763. doi: 10.1002/sim.2971.
84. Schwarzer G, Antes G, Schumacher M. A test for publication bias in meta-analysis with sparse binary data. Stat Med. 2007;26:721-733. doi: 10.1002/sim.2588.
85. Harbord RM, Egger M, Sterne JA. A modified test for small-study effects in meta-analyses of controlled trials with binary endpoints. Stat Med. 2006;25:3443-3457. doi: 10.1002/sim.2380.
86. Macaskill P, Walter SD, Irwig L. A comparison of methods to detect publication bias in meta-analysis. Stat Med. 2001;20:641-654. doi: 10.1002/sim.698.
87. Thompson SG, Sharp SJ. Explaining heterogeneity in meta-analysis: a comparison of methods. Stat Med. 1999;18:2693-2708.
88. Jin ZC, Zhou XH, He J. Statistical methods for dealing with publication bias in meta-analysis. Stat Med. 2015;34:343-360. doi: 10.1002/sim.6342.
89. Thornton A, Lee P. Publication bias in meta-analysis: its causes and consequences. J Clin Epidemiol. 2000;53:207-216.
90. Davey J, Turner RM, Clarke MJ, Higgins JP. Characteristics of meta-analyses and their component studies in the Cochrane Database of Systematic Reviews: a cross-sectional, descriptive analysis. BMC Med Res Methodol. 2011;11:160. doi: 10.1186/1471-2288-11-160.
91. Copas JB, Shi JQ. A sensitivity analysis for publication bias in systematic reviews. Stat Methods Med Res. 2001;10:251-265. doi: 10.1177/096228020101000402.
92. Taylor J, Tibshirani RJ. Statistical learning and selective inference. Proc Natl Acad Sci U S A. 2015;112:7629-7634. doi: 10.1073/pnas. 1507583112.
93. Greenhouse JB, Iyengar S. Sensitivity analysis and diagnostics. In: Cooper H, Hedges LV, Valentine JC, eds. The Handbook of Research Synthesis and Meta-Analysis. New York, NY: Russel Sage Foundation; 2009:418.
94. Higgins JPT, Green S, eds. Section 9.7, sensitivity analysis. Cochrane Handbook for Systematic Reviews of Interventions. The Cochrane Collaboration. March 2011. http://www.cochrane-handbook.org. Accessed June 6, 2016.
95. Cipriani A, Higgins JP, Geddes JR, Salanti G. Conceptual and technical challenges in network meta-analysis. Ann Intern Med. 2013;159:130-137. doi: 10.7326/0003-4819-159-2-201307160-00008.
96. Caldwell DM. An overview of conducting systematic reviews with network meta-analysis. Syst Rev. 2014;3:109. doi: 10.1186/2046-4053-3-109.
97. Biondi-Zoccai G, Abbate A, Benedetto U, Palmerini T, D'Ascenzo F, Frati G. Network meta-analysis for evidence synthesis: what is it and why is it posed to dominate cardiovascular decision making? Int J Cardiol. 2015;182:309-314. doi: 10.1016/j.ijcard.2015.01.023.
98. Caldwell DM, Ades AE, Higgins JP. Simultaneous comparison of multiple treatments: combining direct and indirect evidence. BMJ. 2005;331:897-900. doi: 10.1136/bmj.331.7521.897.
99. Palmerini T, Biondi-Zoccai G, Della Riva D, Stettler C, Sangiorgi D, D'Ascenzo F, Kimura T, Briguori C, Sabatè M, Kim HS, De Waha A, Kedhi E, Smits PC, Kaiser C, Sardella G, Marullo A, Kirtane AJ, Leon MB, Stone GW. Stent thrombosis with drug-eluting and bare-metal stents: evidence from a comprehensive network meta-analysis. Lancet. 2012;379:1393-1402. doi: 10.1016/S0140-6736(12)60324-9.
100. Palmerini T, Biondi-Zoccai G, Della Riva D, Mariani A, Sabaté M, Valgimigli M, Frati G, Kedhi E, Smits PC, Kaiser C, Genereux P, Galatius S, Kirtane AJ, Stone GW. Clinical outcomes with drug-eluting and bare-metal stents in patients with ST-segment elevation myocardial infarction: evidence from a comprehensive network meta-analysis. J Am Coll Cardiol. 2013;62:496-504. doi: 10.1016/j.jacc.2013.05.022.
101. Palmerini T, Biondi-Zoccai G, Della Riva D, Mariani A, Sabaté M, Smits PC, Kaiser C, D'Ascenzo F, Frati G, Mancone M, Genereux P, Stone GW. Clinical outcomes with bioabsorbable polymer-versus durable polymerbased drug-eluting and bare-metal stents: evidence from a comprehensive network meta-analysis. J Am Coll Cardiol. 2014;63:299-307. doi: 10.1016/j.jacc.2013.09.061.
102. Mills EJ, Thorlund K, Eapen S, Wu P, Prochaska JJ. Cardiovascular events associated with smoking cessation pharmacotherapies: a network metaanalysis. Circulation. 2014;129:28-41. doi: 10.1161/CIRCULATIONAHA.113.003961.
103. Bafeta A, Trinquart L, Seror R, Ravaud P. Reporting of results from network meta-analyses: methodological systematic review. BMJ. 2014; 348:g1741.
104. Veroniki AA, Vasiliadis HS, Higgins JP, Salanti G. Evaluation of inconsistency in networks of interventions [published correction appears in Int J Epidemiol. 2013;42:919]. Int J Epidemiol. 2013;42:332-345. doi: 10.1093/ije/dys222.
105. Kibret T, Richer D, Beyene J. Bias in identification of the best treatment in a bayesian network meta-analysis for binary outcome: a simulation study. Clin Epidemiol. 2014;6:451-460. doi: 10.2147/CLEP.S69660.
106. Trinquart L, Attiche N, Bafeta A, Porcher R, Ravaud P. Uncertainty in treatment rankings: reanalysis of network meta-analyses of randomized trials. Ann Intern Med. 2016;164:666-673. doi: 10.7326/M15-2521.
107. Sutton AJ, Abrams KR. Bayesian methods in meta-analysis and evidence synthesis. Stat Methods Med Res. 2001;10:277-303. doi: 10.1177/096228020101000404.
108. Higgins JP, Thompson SG, Spiegelhalter DJ. A re-evaluation of randomeffects meta-analysis. J R Stat Soc Ser A Stat Soc. 2009;172:137-159. doi: 10.1111/j.1467-985X.2008.00552.x.
109. Stewart LA, Clarke MJ. Practical methodology of meta-analyses (overviews) using updated individual patient data: Cochrane Working Group. Stat Med. 1995;14:2057-2079.
110. Simmonds MC, Higgins JP, Stewart LA, Tierney JF, Clarke MJ, Thompson SG. Meta-analysis of individual patient data from randomized trials: a review of methods used in practice. Clin Trials. 2005;2:209-217. doi: 10.1191/1740774505cn087oa.
111. Thompson S, Kaptoge S, White I, Wood A, Perry P, Danesh J; Emerging Risk Factors Collaboration. Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies. Int J Epidemiol. 2010;39:1345-1359. doi: 10.1093/ije/dyq063.
112. Cholesterol Treatment Trialists' (CTT) Collaboration, Fulcher J, O'Connell R, Voysey M, Emberson J, Blackwell L, Mihaylova B, Simes J, Collins R, Kirby A. Colhoun H, Braunwald E, LaRosa J, Pedersen TR, Tonkin A, Davis B, Sleight P, Franzosi MG, Baigent C, Keech A. Efficacy and safety of LDL-lowering therapy among men and women: meta-analysis of individual data from 174,000 participants in 27 randomised trials. Lancet. 2015;385:1397-1405.
113. Cohen AM, Stavri PZ, Hersh WR. A categorization and analysis of the criticisms of evidence-based medicine. Int J Med Inform. 2004;73:35-43. doi: 10.1016/j.ijmedinf.2003.11.002.