Two-Stage Meta-Regression Framework for Precision Medicine Using Data from Clinical Data Research [Methods Study], United States, 2018-2023 (ICPSR 39739)

Version Date: Mar 23, 2026 View help for published

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Yong Chen, University of Pennsylvania

https://doi.org/10.3886/ICPSR39739.v1

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Network meta-analysis, or NMA, is a statistical method that researchers use to combine results from many clinical trials done within a research network. A research network is a group of scientists and doctors from different places, like hospitals and research centers, who do studies together and share data. Researchers can use NMA to compare how well different treatments work for a specific health problem. But current NMA methods don't work well when comparing three or more treatments across many health outcomes.

In this study, the research team developed new NMA methods to compare three or more treatments that bring on labor to start the process of childbirth across many health outcomes using research network data.

Chen, Yong. Two-Stage Meta-Regression Framework for Precision Medicine Using Data from Clinical Data Research [Methods Study], United States, 2018-2023. Inter-university Consortium for Political and Social Research [distributor], 2026-03-23. https://doi.org/10.3886/ICPSR39739.v1

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Patient-Centered Outcomes Research Institute (PCORI) (ME-2018C3-14899)
Inter-university Consortium for Political and Social Research
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2018 -- 2023
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To develop new network meta-analysis (NMA) methods for comparing three or more treatments at the same time across multiple health outcomes using research network data

The research team developed new methods, called PAtient-centered treatment ranking via Large-scale Multivariate network meta-analysis (PALM), for comparing multiple treatments. PALM consists of three parts: (1) a framework that accounts for multiple outcomes and treatment comparisons, (2) an algorithm that calculates the model's parameter values, and (3) plots to visually compare treatments.

The research team tested the methods with existing data from completed clinical trials for labor induction treatments among pregnant people. First, the team used PALM to estimate the effects of eight treatment options on five labor induction outcomes. Using the visualization plots, the team ranked the treatments based on the likelihood that each treatment would result in each of the outcomes compared with a placebo. Then they compared the eight treatments to each other based on each treatment's combined risk for two outcomes: cesarean section and serious neonatal morbidity.

To test the likelihood of errors with the new methods, the research team also conducted simulation studies under equal and unequal variance assumptions between individual studies. Equal variance assumes trials results are similar, whereas unequal variance assumes trial results are different.

Patients and clinicians helped design the study.

NMA data set with data from 48,068 women in 280 randomized clinical trials on prostaglandin treatments in the Cochrane Pregnancy and Childbirth Database

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2026-03-23

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