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Investigating heterogeneity in meta-analysis of studies with rare events

Investigating heterogeneity in meta-analysis of studies with rare events
Investigating heterogeneity in meta-analysis of studies with rare events
In many meta-analyses, the variable of interest is frequently a count outcome
reported in an intervention and a control group. Single- or double-zero studies
are often observed in this type of data. Given this setting, the well-known Cochran’s Q statistic for testing homogeneity becomes undefined. In this paper, we propose two statistics for testing homogeneity of the risk ratio, particularly for application in the case of rare events in meta-analysis. The first one is a chi-square type statistic. It is constructed based on information of the conditional probability of the number of events in the treatment group given the total number of events. The second one is a likelihood ratio statistic, derived from the logistic regression models allowing fixed and random effects for the risk ratio. Both proposed statistics are well defined even in the situation of single-zero studies. In a simulation study, the proposed tests show a performance better than the traditional test in terms of type I error and power of the test under common and rare event situations. However, as the performance of the two newly proposed tests is still unsatisfactory in the very rare events setting, we suggest a bootstrap approach that does not rely on asymptotic distributional theory and it is shown that the bootstrap approach performs well in terms of type I error. Furthermore, a number of empirical meta-analyses are used to illustrate the methods.
0026-1424
Bohning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Sangnawakij, Patarawan
e821a2a7-a89f-4172-9006-8a6c2db9add6
Holling, Heinz
88d46f56-77ca-4d0e-b035-a51aff735435
Böhning, Walailuck
e41681ae-1c18-42f9-96d2-e725d47dbeec
Bohning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Sangnawakij, Patarawan
e821a2a7-a89f-4172-9006-8a6c2db9add6
Holling, Heinz
88d46f56-77ca-4d0e-b035-a51aff735435
Böhning, Walailuck
e41681ae-1c18-42f9-96d2-e725d47dbeec

Bohning, Dankmar, Sangnawakij, Patarawan, Holling, Heinz and Böhning, Walailuck (2021) Investigating heterogeneity in meta-analysis of studies with rare events. Metron.

Record type: Article

Abstract

In many meta-analyses, the variable of interest is frequently a count outcome
reported in an intervention and a control group. Single- or double-zero studies
are often observed in this type of data. Given this setting, the well-known Cochran’s Q statistic for testing homogeneity becomes undefined. In this paper, we propose two statistics for testing homogeneity of the risk ratio, particularly for application in the case of rare events in meta-analysis. The first one is a chi-square type statistic. It is constructed based on information of the conditional probability of the number of events in the treatment group given the total number of events. The second one is a likelihood ratio statistic, derived from the logistic regression models allowing fixed and random effects for the risk ratio. Both proposed statistics are well defined even in the situation of single-zero studies. In a simulation study, the proposed tests show a performance better than the traditional test in terms of type I error and power of the test under common and rare event situations. However, as the performance of the two newly proposed tests is still unsatisfactory in the very rare events setting, we suggest a bootstrap approach that does not rely on asymptotic distributional theory and it is shown that the bootstrap approach performs well in terms of type I error. Furthermore, a number of empirical meta-analyses are used to illustrate the methods.

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More information

Accepted/In Press date: 3 May 2021
Published date: 2021

Identifiers

Local EPrints ID: 449058
URI: http://eprints.soton.ac.uk/id/eprint/449058
ISSN: 0026-1424
PURE UUID: 7956da80-ff70-4242-ae3b-bbfb6d9fb9c8
ORCID for Dankmar Bohning: ORCID iD orcid.org/0000-0003-0638-7106

Catalogue record

Date deposited: 14 May 2021 16:31
Last modified: 15 May 2021 01:44

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Contributors

Author: Dankmar Bohning ORCID iD
Author: Patarawan Sangnawakij
Author: Heinz Holling
Author: Walailuck Böhning

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