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Estimating risk and rate ratio in rare events meta-analysis with the Mantel-Haenszel estimator and assessing heterogeneity

Estimating risk and rate ratio in rare events meta-analysis with the Mantel-Haenszel estimator and assessing heterogeneity
Estimating risk and rate ratio in rare events meta-analysis with the Mantel-Haenszel estimator and assessing heterogeneity

Meta-analysis of binary outcome data faces often a situation where studies with a rare event are part of the set of studies to be considered. These studies have low occurrence of event counts to the extreme that no events occur in one or both groups to be compared. This raises issues how to estimate validly the summary risk or rate ratio across studies. A preferred choice is the Mantel-Haenszel estimator, which is still defined in the situation of zero studies unless all studies have zeros in one of the groups to be compared. For this situation, a modified Mantel-Haenszel estimator is suggested and shown to perform well by means of simulation work. Also, confidence interval estimation is discussed and evaluated in a simulation study. In a second part, heterogeneity of relative risk across studies is investigated with a new chi-square type statistic which is based on a conditional binomial distribution where the conditioning is on the event margin for each study. This is necessary as the conventional Q-statistic is undefined in the occurrence of zero studies. The null-distribution of the proposed Q-statistic is obtained by means of a parametric bootstrap as a chi-square approximation is not valid for rare events meta-analysis, as bootstrapping of the null-distribution shows. In addition, for the effect heterogeneity situation, confidence interval estimation is considered using a nonparametric bootstrap procedure. The proposed techniques are illustrated at hand of three meta-analytic data sets.

Mantel-Haenszel estimator, Q-statistic, heterogeneity, parametric bootstrap, rare events, single- and double-zero studies
1557-4679
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Sangnawakij, Patarawan
f37368bb-b1a1-4350-884c-bedfce646e1b
Holling, Heinz
d2c4b645-d04c-41f1-beea-d39bb8171482
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Sangnawakij, Patarawan
f37368bb-b1a1-4350-884c-bedfce646e1b
Holling, Heinz
d2c4b645-d04c-41f1-beea-d39bb8171482

Böhning, Dankmar, Sangnawakij, Patarawan and Holling, Heinz (2022) Estimating risk and rate ratio in rare events meta-analysis with the Mantel-Haenszel estimator and assessing heterogeneity. International Journal of Biostatistics. (doi:10.1515/ijb-2021-0087).

Record type: Article

Abstract

Meta-analysis of binary outcome data faces often a situation where studies with a rare event are part of the set of studies to be considered. These studies have low occurrence of event counts to the extreme that no events occur in one or both groups to be compared. This raises issues how to estimate validly the summary risk or rate ratio across studies. A preferred choice is the Mantel-Haenszel estimator, which is still defined in the situation of zero studies unless all studies have zeros in one of the groups to be compared. For this situation, a modified Mantel-Haenszel estimator is suggested and shown to perform well by means of simulation work. Also, confidence interval estimation is discussed and evaluated in a simulation study. In a second part, heterogeneity of relative risk across studies is investigated with a new chi-square type statistic which is based on a conditional binomial distribution where the conditioning is on the event margin for each study. This is necessary as the conventional Q-statistic is undefined in the occurrence of zero studies. The null-distribution of the proposed Q-statistic is obtained by means of a parametric bootstrap as a chi-square approximation is not valid for rare events meta-analysis, as bootstrapping of the null-distribution shows. In addition, for the effect heterogeneity situation, confidence interval estimation is considered using a nonparametric bootstrap procedure. The proposed techniques are illustrated at hand of three meta-analytic data sets.

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Accepted/In Press date: 7 July 2022
e-pub ahead of print date: 31 October 2022
Additional Information: Funding Information: The authors would like to thank the Editor and reviewers for all suggestions which lead to considerable improvements of the paper. This study was supported by Bualuang ASEAN Chair Professor Fund. Publisher Copyright: © 2022 Walter de Gruyter GmbH, Berlin/Boston 2022.
Keywords: Mantel-Haenszel estimator, Q-statistic, heterogeneity, parametric bootstrap, rare events, single- and double-zero studies

Identifiers

Local EPrints ID: 470411
URI: http://eprints.soton.ac.uk/id/eprint/470411
ISSN: 1557-4679
PURE UUID: de61f72d-2f89-4d58-a53b-0d7524354d32
ORCID for Dankmar Böhning: ORCID iD orcid.org/0000-0003-0638-7106

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Date deposited: 10 Oct 2022 16:52
Last modified: 31 Jan 2023 02:45

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Author: Patarawan Sangnawakij
Author: Heinz Holling

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