TY - JOUR
T1 - A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests
AU - Simoneau, Gabrielle
AU - Levis, Brooke
AU - Cuijpers, Pim
AU - Ioannidis, John P.A.
AU - Patten, Scott B.
AU - Shrier, Ian
AU - Bombardier, Charles H.
AU - de Lima Osório, Flavia
AU - Fann, Jesse R.
AU - Gjerdingen, Dwenda
AU - Lamers, Femke
AU - Lotrakul, Manote
AU - Löwe, Bernd
AU - Shaaban, Juwita
AU - Stafford, Lesley
AU - van Weert, Henk C.P.M.
AU - Whooley, Mary A.
AU - Wittkampf, Karin A.
AU - Yeung, Albert S.
AU - Thombs, Brett D.
AU - Benedetti, Andrea
PY - 2017/11/1
Y1 - 2017/11/1
N2 - Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings.
AB - Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings.
KW - Individual patient data
KW - Meta-analysis
KW - Multiple thresholds
KW - Ordinal diagnostic test
KW - Poisson correlated frailty
UR - http://www.scopus.com/inward/record.url?scp=85022328420&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85022328420&partnerID=8YFLogxK
U2 - https://doi.org/10.1002/bimj.201600184
DO - https://doi.org/10.1002/bimj.201600184
M3 - Article
C2 - 28692782
SN - 0323-3847
VL - 59
SP - 1317
EP - 1338
JO - Biometrical Journal
JF - Biometrical Journal
IS - 6
ER -