Adjusting for publication bias in meta-analysis via inverse probability weighting using clinical trial registries.
clinical trial registry
missing not at random
propensity score
sensitivity analysis
systematic review
Journal
Biometrics
ISSN: 1541-0420
Titre abrégé: Biometrics
Pays: United States
ID NLM: 0370625
Informations de publication
Date de publication:
09 2023
09 2023
Historique:
received:
28
09
2021
accepted:
15
12
2022
medline:
13
9
2023
pubmed:
6
1
2023
entrez:
5
1
2023
Statut:
ppublish
Résumé
Publication bias is a major concern in conducting systematic reviews and meta-analyses. Various sensitivity analysis or bias-correction methods have been developed based on selection models, and they have some advantages over the widely used trim-and-fill bias-correction method. However, likelihood methods based on selection models may have difficulty in obtaining precise estimates and reasonable confidence intervals, or require a rather complicated sensitivity analysis process. Herein, we develop a simple publication bias adjustment method by utilizing the information on conducted but still unpublished trials from clinical trial registries. We introduce an estimating equation for parameter estimation in the selection function by regarding the publication bias issue as a missing data problem under the missing not at random assumption. With the estimated selection function, we introduce the inverse probability weighting (IPW) method to estimate the overall mean across studies. Furthermore, the IPW versions of heterogeneity measures such as the between-study variance and the I
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2089-2102Informations de copyright
© 2023 The International Biometric Society.
Références
Baudard, M., Yavchitz, A., Ravaud, P., Perrodeau, E. & Boutron, I. (2017) Impact of searching clinical trial registries in systematic reviews of pharmaceutical treatments: methodological systematic review and reanalysis of meta-analyses. BMJ, 356, j448.
Borenstein, M., Hedges, L.V., Higgins, J.P. & Rothstein, H.R. (2010) A basic introduction to fixed-effect and random-effects models for meta-analysis. Research Synthesis Methods, 1(2), 97-111.
Carpenter, J.R., Schwarzer, G., Rücker, G. & Künstler, R. (2009) Empirical evaluation showed that the Copas selection model provided a useful summary in 80% of meta-analyses. Journal of Clinical Epidemiology, 62(6), 624-631.
Chen, Y., Zhang, Y., Tang, Y., Huang, X. & Xie, Y. (2013) High-maintenance-dose clopidogrel in patients undergoing percutaneous coronary intervention: a systematic review and meta-analysis. PloS ONE, 8(10), e78549.
Cochran, W.G. (1954) The combination of estimates from different experiments. Biometrics, 10(1), 101-129.
Copas, J. (1999) What works: selectivity models and meta-analysis. Journal of the Royal Statistical Society: Series A (Statistics in Society), 162(1), 95-109.
Copas, J. & Shi, J.Q. (2000) Meta-analysis, funnel plots and sensitivity analysis. Biostatistics, 1(3), 247-262.
Copas, J.B. (2013) A likelihood-based sensitivity analysis for publication bias in meta-analysis. Journal of the Royal Statistical Society: Series C (Applied Statistics), 62(1), 47-66.
DeAngelis, C.D., Drazen, J.M., Frizelle, F.A., Haug, C., Hoey, J., Horton, R., et al. (2005) Clinical trial registration: a statement from the international committee of medical journal editors. Archives of Dermatology, 141(1), 76-77.
DerSimonian, R. & Laird, N. (1986) Meta-analysis in clinical trials. Controlled Clinical Trials, 7(3), 177-188.
Duval, S. & Tweedie, R. (2000) Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56(2), 455-463.
Egger, M., Smith, G.D., Schneider, M. & Minder, C. (1997) Bias in meta-analysis detected by a simple, graphical test. BMJ, 315(7109), 629-634.
Follmann, D.A. & Proschan, M.A. (1999) Valid inference in random effects meta-analysis. Biometrics, 55(3), 732-737.
Friede, T., Röver, C., Wandel, S. & Neuenschwander, B. (2017) Meta-analysis of few small studies in orphan diseases. Research Synthesis Methods, 8(1), 79-91.
Gopalakrishnan, S. & Ganeshkumar, P. (2013) Systematic reviews and meta-analysis: understanding the best evidence in primary healthcare. Journal of Family Medicine and Primary Care, 2(1), 9-14.
Günhan, B.K., Röver, C. & Friede, T. (2020) Random-effects meta-analysis of few studies involving rare events. Research Synthesis Methods, 11(1), 74-90.
Hart, B., Lundh, A. & Bero, L. (2012) Effect of reporting bias on meta-analyses of drug trials: reanalysis of meta-analyses. BMJ, 344, d7202.
Hartung, J. & Knapp, G. (2001a) On tests of the overall treatment effect in meta-analysis with normally distributed responses. Statistics in Medicine, 20(12), 1771-1782.
Hartung, J. & Knapp, G. (2001b) A refined method for the meta-analysis of controlled clinical trials with binary outcome. Statistics in Medicine, 20(24), 3875-3889.
Hattori, S. & Zhou, X.H. (2018) Sensitivity analysis for publication bias in meta-analysis of diagnostic studies for a continuous biomarker. Statistics in Medicine, 37(3), 327-342.
Higgins, J.P. & Thompson, S.G. (2002) Quantifying heterogeneity in a meta-analysis. Statistics in Medicine, 21(11), 1539-1558.
Huang, A., Komukai, S., Friede, T. & Hattori, S. (2021) Using clinical trial registries to inform Copas selection model for publication bias in meta-analysis. Research Synthesis Methods, 12(5), 658-673.
Kott, P.S. & Chang, T. (2010) Using calibration weighting to adjust for nonignorable unit nonresponse. Journal of the American Statistical Association, 105(491), 1265-1275.
Kuss, O. (2015) Statistical methods for meta-analyses including information from studies without any events-add nothing to nothing and succeed nevertheless. Statistics in Medicine, 34(7), 1097-1116.
Marks-Anglin, A., Luo, C., Piao, J., Gibbons, M. B.C., Schmid, C.H., Ning, J. & Chen, Y. (2022) Embrace: an em-based bias reduction approach through copas-model estimation for quantifying the evidence of selective publishing in network meta-analysis. Biometrics, 78(2), 754-765.
Mathur, M.B. & VanderWeele, T.J. (2020) Sensitivity analysis for publication bias in meta-analyses. Journal of the Royal Statistical Society: Series C (Applied Statistics), 69(5), 1091-1119.
Matsuoka, N., Hasegawa, C. & Hamada, C. (2007) A practical method adjusting for publication bias in meta-analysis based on p-value. Japanese Journal of Biometrics, 28(1), 19-36.
Mavridis, D., Sutton, A., Cipriani, A. & Salanti, G. (2013) A fully Bayesian application of the Copas selection model for publication bias extended to network meta-analysis. Statistics in Medicine, 32(1), 51-66.
Miao, W. & Tchetgen Tchetgen, E.J. (2016) On varieties of doubly robust estimators under missingness not at random with a shadow variable. Biometrika, 103(2), 475-482.
Morikawa, K. & Kim, J.K. (2021) Semiparametric optimal estimation with nonignorable nonresponse data. The Annals of Statistics, 49(5), 2991-3014.
Peters, J.L., Sutton, A.J., Jones, D.R., Abrams, K.R. & Rushton, L. (2007) Performance of the trim and fill method in the presence of publication bias and between-study heterogeneity. Statistics in Medicine, 26(25), 4544-4562.
Piao, J., Liu, Y., Chen, Y. & Ning, J. (2019) Copas-like selection model to correct publication bias in systematic review of diagnostic test studies. Statistical Methods in Medical Research, 28(10-11), 2912-2923.
Preston, C., Ashby, D. & Smyth, R. (2004) Adjusting for publication bias: modelling the selection process. Journal of Evaluation in Clinical Practice, 10(2), 313-322.
Schwarzer, G., Carpenter, J. & Rücker, G. (2010) Empirical evaluation suggests Copas selection model preferable to trim-and-fill method for selection bias in meta-analysis. Journal of Clinical Epidemiology, 63(3), 282-288.
Terrin, N., Schmid, C.H., Lau, J. & Olkin, I. (2003) Adjusting for publication bias in the presence of heterogeneity. Statistics in Medicine, 22(13), 2113-2126.
Thornton, A. & Lee, P. (2000) Publication bias in meta-analysis: its causes and consequences. Journal of Clinical Epidemiology, 53(2), 207-216.
Turner, E.H., Matthews, A.M., Linardatos, E., Tell, R.A. & Rosenthal, R. (2008) Selective publication of antidepressant trials and its influence on apparent efficacy. New England Journal of Medicine, 358(3), 252-260.
Turner, R.M., Omar, R.Z., Yang, M., Goldstein, H. & Thompson, S.G. (2000) A multilevel model framework for meta-analysis of clinical trials with binary outcomes. Statistics in Medicine, 19(24), 3417-3432.
Van der Vaart, A.W. (2000) Asymptotic statistics. Cambridge University Press.
Viechtbauer, W. (2007) Confidence intervals for the amount of heterogeneity in meta-analysis. Statistics in Medicine, 26(1), 37-52.