A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests

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A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests. / Simoneau, Gabrielle; Levis, Brooke; Cuijpers, Pim; Ioannidis, John P A; Patten, Scott B; Shrier, Ian; Bombardier, Charles H; de Lima Osório, Flavia; Fann, Jesse R; Gjerdingen, Dwenda; Lamers, Femke; Lotrakul, Manote; Löwe, Bernd; Shaaban, Juwita; Stafford, Lesley; van Weert, Henk C P M; Whooley, Mary A; Wittkampf, Karin A; Yeung, Albert S; Thombs, Brett D; Benedetti, Andrea.

In: BIOMETRICAL J, Vol. 59, No. 6, 11.2017, p. 1317-1338.

Research output: SCORING: Contribution to journalSCORING: Journal articleResearchpeer-review

Harvard

Simoneau, G, Levis, B, Cuijpers, P, Ioannidis, JPA, Patten, SB, Shrier, I, Bombardier, CH, de Lima Osório, F, Fann, JR, Gjerdingen, D, Lamers, F, Lotrakul, M, Löwe, B, Shaaban, J, Stafford, L, van Weert, HCPM, Whooley, MA, Wittkampf, KA, Yeung, AS, Thombs, BD & Benedetti, A 2017, 'A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests', BIOMETRICAL J, vol. 59, no. 6, pp. 1317-1338. https://doi.org/10.1002/bimj.201600184

APA

Simoneau, G., Levis, B., Cuijpers, P., Ioannidis, J. P. A., Patten, S. B., Shrier, I., Bombardier, C. H., de Lima Osório, F., Fann, J. R., Gjerdingen, D., Lamers, F., Lotrakul, M., Löwe, B., Shaaban, J., Stafford, L., van Weert, H. C. P. M., Whooley, M. A., Wittkampf, K. A., Yeung, A. S., ... Benedetti, A. (2017). A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests. BIOMETRICAL J, 59(6), 1317-1338. https://doi.org/10.1002/bimj.201600184

Vancouver

Bibtex

@article{2754fcd3e6514c619a8a0999e55d424b,
title = "A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests",
abstract = "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.",
keywords = "Journal Article",
author = "Gabrielle Simoneau and Brooke Levis and Pim Cuijpers and Ioannidis, {John P A} and Patten, {Scott B} and Ian Shrier and Bombardier, {Charles H} and {de Lima Os{\'o}rio}, Flavia and Fann, {Jesse R} and Dwenda Gjerdingen and Femke Lamers and Manote Lotrakul and Bernd L{\"o}we and Juwita Shaaban and Lesley Stafford and {van Weert}, {Henk C P M} and Whooley, {Mary A} and Wittkampf, {Karin A} and Yeung, {Albert S} and Thombs, {Brett D} and Andrea Benedetti",
note = "{\textcopyright} 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.",
year = "2017",
month = nov,
doi = "10.1002/bimj.201600184",
language = "English",
volume = "59",
pages = "1317--1338",
journal = "BIOMETRICAL J",
issn = "0323-3847",
publisher = "Wiley-VCH Verlag GmbH",
number = "6",

}

RIS

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

N1 - © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

PY - 2017/11

Y1 - 2017/11

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 - Journal Article

U2 - 10.1002/bimj.201600184

DO - 10.1002/bimj.201600184

M3 - SCORING: Journal article

C2 - 28692782

VL - 59

SP - 1317

EP - 1338

JO - BIOMETRICAL J

JF - BIOMETRICAL J

SN - 0323-3847

IS - 6

ER -