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Meta-analysis 冒險

參考文獻

共 206 筆，依主題分組。每筆書目都以 PubMed、Crossref、arXiv 或 GitHub 實際查證過； 標「AI 章 [N]」者為第 12 關內文的引用編號。各章節內文另附該章使用的文獻連結。

總論與報告規範（15 筆）

  1. Moher D, Cook DJ, Eastwood S et al. Improving the quality of reports of meta-analyses of randomised controlled trials: the QUOROM statement. Quality of Reporting of Meta-analyses. Lancet. 1999.
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  2. Stroup DF, Berlin JA, Morton SC et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000.
    PubMed 10789670 ｜ DOI 10.1001/jama.283.15.2008
  3. Booth A, Clarke M, Ghersi D et al. An international registry of systematic-review protocols. Lancet. 2011.
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  4. Hutton B, Salanti G, Caldwell DM et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations. Ann Intern Med. 2015.
    PubMed 26030634 ｜ DOI 10.7326/m14-2385
  5. Shamseer L, Moher D, Clarke M et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ. 2015.
    PubMed 25555855 ｜ DOI 10.1136/bmj.g7647
  6. McGowan J, Sampson M, Salzwedel DM et al. PRESS Peer Review of Electronic Search Strategies: 2015 Guideline Statement. J Clin Epidemiol. 2016.
    PubMed 27005575 ｜ DOI 10.1016/j.jclinepi.2016.01.021
  7. Whiting P, Savović J, Higgins JP et al. ROBIS: A new tool to assess risk of bias in systematic reviews was developed. J Clin Epidemiol. 2016.
    PubMed 26092286 ｜ DOI 10.1016/j.jclinepi.2015.06.005
  8. Page MJ, Moher D Evaluations of the uptake and impact of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Statement and extensions: a scoping review. Syst Rev. 2017.
    PubMed 29258593 ｜ DOI 10.1186/s13643-017-0663-8
  9. McInnes MDF, Moher D, Thombs BD et al. Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies: The PRISMA-DTA Statement. JAMA. 2018.
    PubMed 29362800 ｜ DOI 10.1001/jama.2017.19163
  10. Cumpston M, Li T, Page MJ et al. Updated guidance for trusted systematic reviews: a new edition of the Cochrane Handbook for Systematic Reviews of Interventions. Cochrane Database Syst Rev. 2019.
    PubMed 31643080 ｜ DOI 10.1002/14651858.ed000142
  11. Higgins JPT, Thomas J, Chandler J, et al. (eds) Cochrane Handbook for Systematic Reviews of Interventions (version 6; living online version 6.5). Wiley / Cochrane (book). 2019.
    DOI 10.1002/9781119536604
  12. Page MJ, McKenzie JE, Bossuyt PM et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021.
    PubMed 33782057 ｜ DOI 10.1136/bmj.n71 ｜AI 章 [31]
  13. Page MJ, Moher D, Bossuyt PM et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. 2021.
    PubMed 33781993 ｜ DOI 10.1136/bmj.n160
  14. Rethlefsen ML, Kirtley S, Waffenschmidt S et al. PRISMA-S: an extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews. Syst Rev. 2021.
    PubMed 33499930 ｜ DOI 10.1186/s13643-020-01542-z
  15. Veroniki AA, Hutton B, Stevens A et al. Update to the PRISMA guidelines for network meta-analyses and scoping reviews and development of guidelines for rapid reviews: a scoping review protocol. JBI Evid Synth. 2025.
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問題形成與搜尋（5 筆）

  1. McAuley L, Pham B, Tugwell P et al. Does the inclusion of grey literature influence estimates of intervention effectiveness reported in meta-analyses?. Lancet. 2000.
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  2. Hopewell S, McDonald S, Clarke M et al. Grey literature in meta-analyses of randomized trials of health care interventions. Cochrane Database Syst Rev. 2007.
    PubMed 17443631 ｜ DOI 10.1002/14651858.mr000010.pub3
  3. Methley AM, Campbell S, Chew-Graham C et al. PICO, PICOS and SPIDER: a comparison study of specificity and sensitivity in three search tools for qualitative systematic reviews. BMC Health Serv Res. 2014.
    PubMed 25413154 ｜ DOI 10.1186/s12913-014-0579-0
  4. Bramer WM, Rethlefsen ML, Kleijnen J et al. Optimal database combinations for literature searches in systematic reviews: a prospective exploratory study. Syst Rev. 2017.
    PubMed 29208034 ｜ DOI 10.1186/s13643-017-0644-y
  5. Paez A Gray literature: An important resource in systematic reviews. J Evid Based Med. 2017.
    PubMed 28857505 ｜ DOI 10.1111/jebm.12266

篩選與萃取（10 筆）

  1. Landis JR, Koch GG The measurement of observer agreement for categorical data. Biometrics. 1977.
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  2. Edwards P, Clarke M, DiGuiseppi C et al. Identification of randomized controlled trials in systematic reviews: accuracy and reliability of screening records. Stat Med. 2002.
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  3. Elbourne DR, Altman DG, Higgins JP et al. Meta-analyses involving cross-over trials: methodological issues. Int J Epidemiol. 2002.
    PubMed 11914310 ｜ DOI 10.1093/ije/31.1.140
  4. Hozo SP, Djulbegovic B, Hozo I. Estimating the mean and variance from the median, range, and the size of a sample. BMC Med Res Methodol. 2005.
    PubMed 15840177 ｜ DOI 10.1186/1471-2288-5-13
  5. Buscemi N, Hartling L, Vandermeer B et al. Single data extraction generated more errors than double data extraction in systematic reviews. J Clin Epidemiol. 2006.
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  6. Altman DG, Bland JM. How to obtain the confidence interval from a P value. BMJ. 2011.
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  7. McHugh ML Interrater reliability: the kappa statistic. Biochem Med (Zagreb). 2012.
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  8. Wan X, Wang W, Liu J et al. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol. 2014.
    PubMed 25524443 ｜ DOI 10.1186/1471-2288-14-135
  9. Luo D, Wan X, Liu J et al. Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range. Stat Methods Med Res. 2018.
    PubMed 27683581 ｜ DOI 10.1177/0962280216669183
  10. Waffenschmidt S, Knelangen M, Sieben W et al. Single screening versus conventional double screening for study selection in systematic reviews: a methodological systematic review. BMC Med Res Methodol. 2019.
    PubMed 31253092 ｜ DOI 10.1186/s12874-019-0782-0

Risk of bias（偏誤風險）評估（14 筆）

  1. Jüni P, Witschi A, Bloch R et al. The hazards of scoring the quality of clinical trials for meta-analysis. JAMA. 1999.
    PubMed 10493204 ｜ DOI 10.1001/jama.282.11.1054
  2. Jüni P, Altman DG, Egger M Systematic reviews in health care: Assessing the quality of controlled clinical trials. BMJ. 2001.
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  3. Hartling L, Ospina M, Liang Y et al. Risk of bias versus quality assessment of randomised controlled trials: cross sectional study. BMJ. 2009.
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  4. Stang A Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010.
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  5. Higgins JP, Altman DG, Gøtzsche PC et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ. 2011.
    PubMed 22008217 ｜ DOI 10.1136/bmj.d5928
  6. Whiting PF, Rutjes AW, Westwood ME et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011.
    PubMed 22007046 ｜ DOI 10.7326/0003-4819-155-8-201110180-00009
  7. Savović J, Jones HE, Altman DG et al. Influence of reported study design characteristics on intervention effect estimates from randomized, controlled trials. Ann Intern Med. 2012.
    PubMed 22945832 ｜ DOI 10.7326/0003-4819-157-6-201209180-00537
  8. Sterne JA, Hernán MA, Reeves BC et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ. 2016.
    PubMed 27733354 ｜ DOI 10.1136/bmj.i4919
  9. Shea BJ, Reeves BC, Wells G et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017.
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  10. Savovic J, Turner RM, Mawdsley D et al. Association Between Risk-of-Bias Assessments and Results of Randomized Trials in Cochrane Reviews: The ROBES Meta-Epidemiologic Study. Am J Epidemiol. 2018.
    PubMed 29126260 ｜ DOI 10.1093/aje/kwx344
  11. Sterne JAC, Savović J, Page MJ et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019.
    PubMed 31462531 ｜ DOI 10.1136/bmj.l4898
  12. Minozzi S, Dwan K, Borrelli F et al. Reliability of the revised Cochrane risk-of-bias tool for randomised trials (RoB2) improved with the use of implementation instruction. J Clin Epidemiol. 2022.
    PubMed 34537386 ｜ DOI 10.1016/j.jclinepi.2021.09.021
  13. Page MJ, Sterne JAC, Boutron I et al. ROB-ME: a tool for assessing risk of bias due to missing evidence in systematic reviews with meta-analysis. BMJ. 2023.
    PubMed 37984978 ｜ DOI 10.1136/bmj-2023-076754
  14. Higgins JPT, Morgan RL, Rooney AA et al. A tool to assess risk of bias in non-randomized follow-up studies of exposure effects (ROBINS-E). Environ Int. 2024.
    PubMed 38555664 ｜ DOI 10.1016/j.envint.2024.108602

效果量與合併模型（25 筆）

  1. MANTEL N, HAENSZEL W Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst. 1959.
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  2. Greenland S, Robins JM Estimation of a common effect parameter from sparse follow-up data. Biometrics. 1985.
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  3. DerSimonian R, Laird N Meta-analysis in clinical trials. Control Clin Trials. 1986.
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  4. Colditz GA, Brewer TF, Berkey CS et al. Efficacy of BCG vaccine in the prevention of tuberculosis. Meta-analysis of the published literature. JAMA. 1994.
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  5. Hackshaw AK, Law MR, Wald NJ. The accumulated evidence on lung cancer and environmental tobacco smoke. BMJ. 1997.
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  6. Davies HT, Crombie IK, Tavakoli M. When can odds ratios mislead?. BMJ. 1998.
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  7. Zhang J, Yu KF. What's the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA. 1998.
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  8. Normand SL. Meta-analysis: formulating, evaluating, combining, and reporting. Stat Med. 1999.
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  9. Chinn S. A simple method for converting an odds ratio to effect size for use in meta-analysis. Stat Med. 2000.
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  10. Hartung J, Knapp G A refined method for the meta-analysis of controlled clinical trials with binary outcome. Stat Med. 2001.
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  11. Altman DG, Deeks JJ. Meta-analysis, Simpson's paradox, and the number needed to treat. BMC Med Res Methodol. 2002.
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  12. Deeks JJ. Issues in the selection of a summary statistic for meta-analysis of clinical trials with binary outcomes. Stat Med. 2002.
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  13. Sidik K, Jonkman JN A simple confidence interval for meta-analysis. Stat Med. 2002.
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  14. Knapp G, Hartung J Improved tests for a random effects meta-regression with a single covariate. Stat Med. 2003.
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  15. Sweeting MJ, Sutton AJ, Lambert PC What to add to nothing? Use and avoidance of continuity corrections in meta-analysis of sparse data. Stat Med. 2004.
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  16. Bradburn MJ, Deeks JJ, Berlin JA et al. Much ado about nothing: a comparison of the performance of meta-analytical methods with rare events. Stat Med. 2007.
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  17. Tierney JF, Stewart LA, Ghersi D et al. Practical methods for incorporating summary time-to-event data into meta-analysis. Trials. 2007.
    PubMed 17555582 ｜ DOI 10.1186/1745-6215-8-16
  18. Higgins JP, Thompson SG, Spiegelhalter DJ A re-evaluation of random-effects meta-analysis. J R Stat Soc Ser A Stat Soc. 2009.
    PubMed 19381330 ｜ DOI 10.1111/j.1467-985x.2008.00552.x
  19. Borenstein M, Hedges LV, Higgins JP et al. A basic introduction to fixed-effect and random-effects models for meta-analysis. Res Synth Methods. 2010.
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  20. Riley RD, Higgins JP, Deeks JJ Interpretation of random effects meta-analyses. BMJ. 2011.
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  21. IntHout J, Ioannidis JP, Borm GF The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method. BMC Med Res Methodol. 2014.
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  22. IntHout J, Ioannidis JP, Rovers MM et al. Plea for routinely presenting prediction intervals in meta-analysis. BMJ Open. 2016.
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  23. Veroniki AA, Jackson D, Viechtbauer W et al. Methods to estimate the between-study variance and its uncertainty in meta-analysis. Res Synth Methods. 2016.
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  24. Page MJ, Altman DG, McKenzie JE et al. Flaws in the application and interpretation of statistical analyses in systematic reviews of therapeutic interventions were common: a cross-sectional analysis. J Clin Epidemiol. 2018.
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異質性（10 筆）

  1. Thompson SG, Sharp SJ Explaining heterogeneity in meta-analysis: a comparison of methods. Stat Med. 1999.
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  2. Higgins JP, Thompson SG Quantifying heterogeneity in a meta-analysis. Stat Med. 2002.
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  3. Thompson SG, Higgins JP How should meta-regression analyses be undertaken and interpreted?. Stat Med. 2002.
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  4. Higgins JP, Thompson SG, Deeks JJ et al. Measuring inconsistency in meta-analyses. BMJ. 2003.
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  5. Viechtbauer W Confidence intervals for the amount of heterogeneity in meta-analysis. Stat Med. 2007.
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  6. Higgins JP Commentary: Heterogeneity in meta-analysis should be expected and appropriately quantified. Int J Epidemiol. 2008.
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  7. Rücker G, Schwarzer G, Carpenter JR et al. Undue reliance on I(2) in assessing heterogeneity may mislead. BMC Med Res Methodol. 2008.
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  8. Viechtbauer W, Cheung MW Outlier and influence diagnostics for meta-analysis. Res Synth Methods. 2010.
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  9. von Hippel PT The heterogeneity statistic I(2) can be biased in small meta-analyses. BMC Med Res Methodol. 2015.
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  10. Borenstein M, Higgins JP, Hedges LV et al. Basics of meta-analysis: I(2) is not an absolute measure of heterogeneity. Res Synth Methods. 2017.
    PubMed 28058794 ｜ DOI 10.1002/jrsm.1230

Publication bias 與 small-study effects（14 筆）

  1. Dickersin K The existence of publication bias and risk factors for its occurrence. JAMA. 1990.
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  2. Begg CB, Mazumdar M Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994.
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  3. Egger M, Davey Smith G, Schneider M et al. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997.
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  4. 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.
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  5. Sutton AJ, Duval SJ, Tweedie RL et al. Empirical assessment of effect of publication bias on meta-analyses. BMJ. 2000.
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  6. Terrin N, Schmid CH, Lau J et al. Adjusting for publication bias in the presence of heterogeneity. Stat Med. 2003.
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  7. Lau J, Ioannidis JP, Terrin N et al. The case of the misleading funnel plot. BMJ. 2006.
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  8. Peters JL, Sutton AJ, Jones DR et al. Comparison of two methods to detect publication bias in meta-analysis. JAMA. 2006.
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  9. Ioannidis JP, Trikalinos TA The appropriateness of asymmetry tests for publication bias in meta-analyses: a large survey. CMAJ. 2007.
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  10. Peters JL, Sutton AJ, Jones DR et al. Contour-enhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry. J Clin Epidemiol. 2008.
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  11. Rücker G, Schwarzer G, Carpenter J Arcsine test for publication bias in meta-analyses with binary outcomes. Stat Med. 2008.
    PubMed 17592831 ｜ DOI 10.1002/sim.2971
  12. Sterne JA, Sutton AJ, Ioannidis JP et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ. 2011.
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  13. Lin L, Chu H Quantifying publication bias in meta-analysis. Biometrics. 2018.
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  14. Page MJ, Sterne JAC, Higgins JPT et al. Investigating and dealing with publication bias and other reporting biases in meta-analyses of health research: A review. Res Synth Methods. 2021.
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Certainty of evidence：GRADE（15 筆）

  1. Guyatt GH, Oxman AD, Vist GE et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008.
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  2. Balshem H, Helfand M, Schünemann HJ et al. GRADE guidelines: 3. Rating the quality of evidence. J Clin Epidemiol. 2011.
    PubMed 21208779 ｜ DOI 10.1016/j.jclinepi.2010.07.015
  3. Guyatt G, Oxman AD, Akl EA et al. GRADE guidelines: 1. Introduction-GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. 2011.
    PubMed 21195583 ｜ DOI 10.1016/j.jclinepi.2010.04.026
  4. Guyatt GH, Oxman AD, Kunz R et al. GRADE guidelines 6. Rating the quality of evidence--imprecision. J Clin Epidemiol. 2011.
    PubMed 21839614 ｜ DOI 10.1016/j.jclinepi.2011.01.012
  5. Guyatt GH, Oxman AD, Kunz R et al. GRADE guidelines: 2. Framing the question and deciding on important outcomes. J Clin Epidemiol. 2011.
    PubMed 21194891 ｜ DOI 10.1016/j.jclinepi.2010.09.012
  6. Guyatt GH, Oxman AD, Kunz R et al. GRADE guidelines: 7. Rating the quality of evidence--inconsistency. J Clin Epidemiol. 2011.
    PubMed 21803546 ｜ DOI 10.1016/j.jclinepi.2011.03.017
  7. Guyatt GH, Oxman AD, Kunz R et al. GRADE guidelines: 8. Rating the quality of evidence--indirectness. J Clin Epidemiol. 2011.
    PubMed 21802903 ｜ DOI 10.1016/j.jclinepi.2011.04.014
  8. Guyatt GH, Oxman AD, Montori V et al. GRADE guidelines: 5. Rating the quality of evidence--publication bias. J Clin Epidemiol. 2011.
    PubMed 21802904 ｜ DOI 10.1016/j.jclinepi.2011.01.011
  9. Guyatt GH, Oxman AD, Sultan S et al. GRADE guidelines: 9. Rating up the quality of evidence. J Clin Epidemiol. 2011.
    PubMed 21802902 ｜ DOI 10.1016/j.jclinepi.2011.06.004
  10. Guyatt GH, Oxman AD, Vist G et al. GRADE guidelines: 4. Rating the quality of evidence--study limitations (risk of bias). J Clin Epidemiol. 2011.
    PubMed 21247734 ｜ DOI 10.1016/j.jclinepi.2010.07.017
  11. Brunetti M, Shemilt I, Pregno S et al. GRADE guidelines: 10. Considering resource use and rating the quality of economic evidence. J Clin Epidemiol. 2013.
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  12. Guyatt GH, Oxman AD, Santesso N et al. GRADE guidelines: 12. Preparing summary of findings tables-binary outcomes. J Clin Epidemiol. 2013.
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  13. Guyatt GH, Thorlund K, Oxman AD et al. GRADE guidelines: 13. Preparing summary of findings tables and evidence profiles-continuous outcomes. J Clin Epidemiol. 2013.
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  14. Schünemann HJ, Cuello C, Akl EA et al. GRADE guidelines: 18. How ROBINS-I and other tools to assess risk of bias in nonrandomized studies should be used to rate the certainty of a body of evidence. J Clin Epidemiol. 2019.
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  15. Zhang Y, Coello PA, Guyatt GH et al. GRADE guidelines: 20. Assessing the certainty of evidence in the importance of outcomes or values and preferences-inconsistency, imprecision, and other domains. J Clin Epidemiol. 2019.
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進階主題：NMA、DTA、IPD、TSA、Bayesian（26 筆）

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  6. Lu G, Ades AE Combination of direct and indirect evidence in mixed treatment comparisons. Stat Med. 2004.
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  7. Deeks JJ, Macaskill P, Irwig L The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol. 2005.
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