Practical methods for incorporating summary time-to-event data into meta-analysis: updated guidance
Abstract Our previous guide to estimating hazard ratios (HRs) from published summary (aggregate) data has become very widely used, but many still have difficulties knowing when and how to apply the methods. Informed by our increased experience of applying them across a range of settings, the queries...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-04-01
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| Series: | Systematic Reviews |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13643-025-02752-z |
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| Summary: | Abstract Our previous guide to estimating hazard ratios (HRs) from published summary (aggregate) data has become very widely used, but many still have difficulties knowing when and how to apply the methods. Informed by our increased experience of applying them across a range of settings, the queries we have received and results of a survey of Cochrane editors on the methods, we have updated the guidance comprehensively. Previously, we described a range of scenarios for deriving a HR and logrank variance (V) from published time-to-event analyses. They are incorporated in this update, together with clarification of ambiguities and additional scenarios. We also provide further guidance on extracting and using data from publications and Kaplan–Meier (KM) curves, raise some of the challenges, and discuss recent alternatives to the “Parmar” KM methods. A new calculations spreadsheet will perform all possible calculations given the data that are entered and includes new features to enhance the user experience. This updated guidance and associated spreadsheet represent valuable additional tools for those conducting meta-analyses based on published, summary, time-to-event data. |
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| ISSN: | 2046-4053 |