Individual participant data meta-analyses should not ignore clustering
Tài liệu tham khảo
Riley, 2010, Meta-analysis of individual participant data: conduct, rationale and reporting, BMJ, 340, c221, 10.1136/bmj.c221
Stewart, 1993, Meta-analysis of the literature or of individual patient data: is there a difference?, Lancet, 341, 418, 10.1016/0140-6736(93)93004-K
Stewart, 2002, To IPD or not to IPD? Advantages and disadvantages of systematic reviews using individual patient data, Eval Health Prof, 25, 76, 10.1177/0163278702025001006
Simmonds, 2005, Meta-analysis of individual patient data from randomized trials: a review of methods used in practice, Clin Trials, 2, 209, 10.1191/1740774505cn087oa
Turner, 2000, A multilevel model framework for meta-analysis of clinical trials with binary outcomes, Stat Med, 19, 3417, 10.1002/1097-0258(20001230)19:24<3417::AID-SIM614>3.0.CO;2-L
Higgins, 2001, Meta-analysis of continuous outcome data from individual patients, Stat Med, 20, 2219, 10.1002/sim.918
Whitehead, 2001, Meta-analysis of ordinal outcomes using individual patient data, Stat Med, 20, 2243, 10.1002/sim.919
Tudur-Smith, 2005, Investigating heterogeneity in an individual patient data meta-analysis of time to event outcomes, Stat Med, 24, 1307, 10.1002/sim.2050
Jones, 2009, Meta-analysis of individual patient data versus aggregate data from longitudinal clinical trials, Clin Trials, 6, 16, 10.1177/1740774508100984
Riley, 2008, Meta-analysis of continuous outcomes combining individual patient data and aggregate data, Stat Med, 27, 1870, 10.1002/sim.3165
Riley, 2008, Meta-analysis of diagnostic test studies using individual patient data and aggregate data, Stat Med, 27, 6111, 10.1002/sim.3441
Olkin, 1998, Comparison of meta-analysis versus analysis of variance of individual patient data, Biometrics, 54, 317, 10.2307/2534018
Mathew, 1999, On the equivalence of meta-analysis using literature and using individual patient data, Biometrics, 55, 1221, 10.1111/j.0006-341X.1999.01221.x
Tudur Smith, 2007, A comparison of methods for fixed effects meta-analysis of individual patient data with time to event outcomes, Clin Trials, 4, 621, 10.1177/1740774507085276
Matthew, 2010, Comparison of one-step and two-step meta-analysis models using individual patient data, Biometrical J, 52, 271
Stijnen, 2010, Random effects meta-analysis of event outcome in the framework of the generalized linear mixed model with applications in sparse data, Stat Med, 29, 3046, 10.1002/sim.4040
Hamza, 2008, The binomial distribution of meta-analysis was preferred to model within-study variability, J Clin Epidemiol, 61, 41, 10.1016/j.jclinepi.2007.03.016
Abo-Zaid, 2012, Individual participant data meta-analysis of prognostic factor studies: state of the art?, BMC Med Res Methodol, 12, 56, 10.1186/1471-2288-12-56
Whitehead, 2002
DerSimonian, 1986, Meta-analysis in clinical trials, Control Clin Trials, 7, 177, 10.1016/0197-2456(86)90046-2
Sterne, 2009
Bradburn, 2007, Much ado about nothing: a comparison of the performance of meta-analytical methods with rare events, Stat Med, 26, 53, 10.1002/sim.2528
Hukkelhoven, 2003, Patient age and outcome following severe traumatic brain injury: an analysis of 5600 patients, J Neurosurg, 99, 666, 10.3171/jns.2003.99.4.0666
Carlsson, 1968, Factors affecting the clinical course of patients with severe head injuries. 1. Influence of biological factors. 2. Significance of posttraumatic coma, J Neurosurg, 29, 242, 10.3171/jns.1968.29.3.0242
Kraaijenhagen, 2002, Simplification of the diagnostic management of suspected deep vein thrombosis, Arch Intern Med, 162, 907, 10.1001/archinte.162.8.907
Toll, 2006, Excluding deep vein thrombosis safely in primary care, J Fam Pract, 55, 613
Anderson, 2003, Combined use of clinical assessment and d-dimer to improve the management of patients presenting to the emergency department with suspected deep vein thrombosis (the EDITED Study), J Thromb Haemost, 1, 645, 10.1046/j.1538-7836.2003.00131.x
Stevens, 2004, Withholding anticoagulation after a negative result on duplex ultrasonography for suspected symptomatic deep venous thrombosis, Ann Intern Med, 140, 985, 10.7326/0003-4819-140-12-200406150-00007
Wells, 2003, Evaluation of D-dimer in the diagnosis of suspected deep-vein thrombosis, N Engl J Med, 349, 1227, 10.1056/NEJMoa023153
Toll, 2008, A new diagnostic rule for deep vein thrombosis: safety and efficiency in clinically relevant subgroups, Fam Pract, 25, 3, 10.1093/fampra/cmm075
Rice, 2001, Nursing interventions for smoking cessation, Cochrane Database Syst Rev (Complete Reviews), CD001188
Altman, 2002, Meta-analysis, Simpson's paradox, and the number needed to treat, BMC Med Res Methodol, 2, 3, 10.1186/1471-2288-2-3
Peters, 2003, Comparison of methods for analysing cluster randomized trials: an example involving a factorial design, Int J Epidemiol, 32, 840, 10.1093/ije/dyg228
Bland, 2004, Cluster randomised trials in the medical literature: two bibliometric surveys, BMC Med Res Methodol, 4, 21, 10.1186/1471-2288-4-21
Lee, 2005, The use of random effects models to allow for clustering in individually randomized trials, Clin Trials, 2, 163, 10.1191/1740774505cn082oa
Steyerberg, 2000, Clinical trials in acute myocardial infarction: should we adjust for baseline characteristics?, Am Heart J, 139, 745, 10.1016/S0002-8703(00)90001-2
Hernández, 2004, Covariate adjustment in randomized controlled trials with dichotomous outcomes increases statistical power and reduces sample size requirements, J Clin Epidemiol, 57, 454, 10.1016/j.jclinepi.2003.09.014
Turner, 2012, Covariate adjustment increased power in randomized controlled trials: an example in traumatic brain injury, J Clin Epidemiol, 65, 474, 10.1016/j.jclinepi.2011.08.012
Robinson, 1991, Some surprising results about covariate adjustment in logistic regression models, Int Stat Rev, 58, 227, 10.2307/1403444
Greenland, 1999, Confounding and collapsibility in causal inference, Stat Sci, 14, 29, 10.1214/ss/1009211805
Gail, 1984, Biased estimates of treatment effect in randomized experiments with nonlinear regressions and omitted covariates, Biometrika, 71, 431, 10.1093/biomet/71.3.431
Mantel, 1959, Statistical aspects of the analysis of data from retrospective studies of disease, J Natl Cancer Inst, 22, 719
Yusuf, 1985, Beta blockade during and after myocardial infarction: an overview of the randomized trials, Prog Cardiovasc Dis, 17, 335, 10.1016/S0033-0620(85)80003-7
Chu, 2006, Bivariate meta-analysis of sensitivity and specificity with sparse data: a generalized linear mixed model approach, J Clin Epidemiol, 59, 1331, 10.1016/j.jclinepi.2006.06.011
Ahmed, 2012, Assessment of publication bias, selection bias and unavailable data in meta-analyses using individual participant data: a database survey, BMJ, 344, d7762, 10.1136/bmj.d7762
Riley, 2007, Evidence synthesis combining individual patient data and aggregate data: a systematic review identified current practice and possible methods, J Clin Epidemiol, 60, 431, 10.1016/j.jclinepi.2006.09.009
Jackson, 2009, Systematically missing confounders in individual participant data meta-analysis of observational cohort studies, Stat Med, 28, 1218, 10.1002/sim.3540