Uncertainty in the Bayesian meta-analysis of normally distributed surrogate endpoints

被引:18
作者
Bujkiewicz, Sylwia [1 ]
Thompson, John R. [2 ]
Spata, Enti [1 ]
Abrams, Keith R. [1 ]
机构
[1] Univ Leicester, Biostat Res Grp, Dept Hlth Sci, Univ Rd, Leicester LE1 7RH, Leics, England
[2] Univ Leicester, Genet Epidemiol Grp, Dept Hlth Sci, Univ Rd, Leicester, Leics, England
基金
英国医学研究理事会;
关键词
Meta-analysis; surrogate endpoints; Bayesian statistics; bivariate meta-analysis; meta-regression; PROGRESSION-FREE SURVIVAL; MULTIVARIATE METAANALYSIS; CLINICAL-TRIALS; OUTCOMES; VALIDATION; DISEASE; CANCER; REGRESSION; CRITERIA; WINBUGS;
D O I
10.1177/0962280215597260
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
We investigate the effect of the choice of parameterisation of meta-analytic models and related uncertainty on the validation of surrogate endpoints. Different meta-analytical approaches take into account different levels of uncertainty which may impact on the accuracy of the predictions of treatment effect on the target outcome from the treatment effect on a surrogate endpoint obtained from these models. A range of Bayesian as well as frequentist meta-analytical methods are implemented using illustrative examples in relapsing-remitting multiple sclerosis, where the treatment effect on disability worsening is the primary outcome of interest in healthcare evaluation, while the effect on relapse rate is considered as a potential surrogate to the effect on disability progression, and in gastric cancer, where the disease-free survival has been shown to be a good surrogate endpoint to the overall survival. Sensitivity analysis was carried out to assess the impact of distributional assumptions on the predictions. Also, sensitivity to modelling assumptions and performance of the models were investigated by simulation. Although different methods can predict mean true outcome almost equally well, inclusion of uncertainty around all relevant parameters of the model may lead to less certain and hence more conservative predictions. When investigating endpoints as candidate surrogate outcomes, a careful choice of the meta-analytical approach has to be made. Models underestimating the uncertainty of available evidence may lead to overoptimistic predictions which can then have an effect on decisions made based on such predictions.
引用
收藏
页码:2287 / 2318
页数:32
相关论文
共 43 条
[1]  
[Anonymous], 2011, STAT STAT SOFTW REL
[2]   Combining multiple outcome measures in a meta-analysis:: an application [J].
Arends, LR ;
Vokó, Z ;
Stijnen, T .
STATISTICS IN MEDICINE, 2003, 22 (08) :1335-1353
[3]  
Berkey CS, 1998, STAT MED, V17, P2537, DOI 10.1002/(SICI)1097-0258(19981130)17:22<2537::AID-SIM953>3.0.CO
[4]  
2-C
[5]  
Böhnig D, 2005, METHOD INFORM MED, V44, P127
[6]   Use of Bayesian Multivariate Meta-Analysis to Estimate the HAQ for Mapping Onto the EQ-5D Questionnaire in Rheumatoid Arthritis [J].
Bujkiewicz, Sylwia ;
Thompson, John R. ;
Sutton, Alex J. ;
Cooper, Nicola J. ;
Harrison, Mark J. ;
Symmons, Deborah P. M. ;
Abrams, Keith R. .
VALUE IN HEALTH, 2014, 17 (01) :109-115
[7]   Multivariate meta-analysis of mixed outcomes: a Bayesian approach [J].
Bujkiewicz, Sylwia ;
Thompson, John R. ;
Sutton, Alex J. ;
Cooper, Nicola J. ;
Harrison, Mark J. ;
Symmons, Deborah P. M. ;
Abrams, Keith R. .
STATISTICS IN MEDICINE, 2013, 32 (22) :3926-3943
[8]   A Bayesian semiparametric model for random-effects meta-analysis [J].
Burr, D ;
Doss, H .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2005, 100 (469) :242-251
[9]   A meta-analysis of studies on the association of the platelet PlA polymorphism of glycoprotein IIIa and risk of coronary heart disease [J].
Burr, D ;
Doss, H ;
Cooke, GE ;
Goldschmidt-Clermont, PJ .
STATISTICS IN MEDICINE, 2003, 22 (10) :1741-1760
[10]  
Burzykowski T., 2005, EVALUATION SURROGATE