Estimating reference intervals from an IPD meta-analysis using quantile regression
Abstract Background Reference intervals, which define an interval in which a specific proportion of measurements from a healthy population are expected to fall, are commonly used in medical practice. Synthesizing information from multiple studies through meta-analysis can provide a more precise and...
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BMC
2024-10-01
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| Series: | BMC Medical Research Methodology |
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| Online Access: | https://doi.org/10.1186/s12874-024-02378-0 |
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| author | Ziren Jiang Haitao Chu Zhen Wang M. Hassan Murad Lianne K. Siegel |
| author_facet | Ziren Jiang Haitao Chu Zhen Wang M. Hassan Murad Lianne K. Siegel |
| author_sort | Ziren Jiang |
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| description | Abstract Background Reference intervals, which define an interval in which a specific proportion of measurements from a healthy population are expected to fall, are commonly used in medical practice. Synthesizing information from multiple studies through meta-analysis can provide a more precise and representative reference interval than one derived from a single study. However, the current approaches for estimating the reference interval from a meta-analysis mainly rely on aggregate data and require parametric distributional assumptions that cannot always be checked. Methods With the availability of individual participant data (IPD), non-parametric methods can be used to estimate reference intervals without any distributional assumptions. Furthermore, patient-level covariates can be introduced to estimate personalized reference intervals that may be more applicable to specific patients. This paper introduces quantile regression as a method to estimate the reference interval from an IPD meta-analysis under the fixed effects model. Results We compared several non-parametric bootstrap methods through simulation studies to account for within-study correlation. Under fixed effects model, we recommend keeping the studies fixed and only randomly sampling subjects with replacement within each study. Conclusion We proposed to use the quantile regression in the IPD meta-analysis to estimate the reference interval. Based on the simulation results, we identify an optimal bootstrap strategy for estimating the uncertainty of the estimated reference interval. An example of liver stiffness measurements, a clinically important diagnostic test without explicitly established reference range in children, is provided to demonstrate the use of quantile regression in estimating both overall and subject-specific reference intervals. |
| format | Article |
| id | doaj-art-3031ba3880f04e2b9c3ff06b4bd4470b |
| institution | OA Journals |
| issn | 1471-2288 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | BMC |
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| series | BMC Medical Research Methodology |
| spelling | doaj-art-3031ba3880f04e2b9c3ff06b4bd4470b2025-08-20T02:11:17ZengBMCBMC Medical Research Methodology1471-22882024-10-012411910.1186/s12874-024-02378-0Estimating reference intervals from an IPD meta-analysis using quantile regressionZiren Jiang0Haitao Chu1Zhen Wang2M. Hassan Murad3Lianne K. Siegel4Division of Biostatistics and Health Data Science, University of MinnesotaDivision of Biostatistics and Health Data Science, University of MinnesotaEvidence-Based Practice Center, Robert D. and Patria E. Kern Center for the Science of Health Care Delivery, Mayo ClinicEvidence-Based Practice Center, Robert D. and Patria E. Kern Center for the Science of Health Care Delivery, Mayo ClinicDivision of Biostatistics and Health Data Science, University of MinnesotaAbstract Background Reference intervals, which define an interval in which a specific proportion of measurements from a healthy population are expected to fall, are commonly used in medical practice. Synthesizing information from multiple studies through meta-analysis can provide a more precise and representative reference interval than one derived from a single study. However, the current approaches for estimating the reference interval from a meta-analysis mainly rely on aggregate data and require parametric distributional assumptions that cannot always be checked. Methods With the availability of individual participant data (IPD), non-parametric methods can be used to estimate reference intervals without any distributional assumptions. Furthermore, patient-level covariates can be introduced to estimate personalized reference intervals that may be more applicable to specific patients. This paper introduces quantile regression as a method to estimate the reference interval from an IPD meta-analysis under the fixed effects model. Results We compared several non-parametric bootstrap methods through simulation studies to account for within-study correlation. Under fixed effects model, we recommend keeping the studies fixed and only randomly sampling subjects with replacement within each study. Conclusion We proposed to use the quantile regression in the IPD meta-analysis to estimate the reference interval. Based on the simulation results, we identify an optimal bootstrap strategy for estimating the uncertainty of the estimated reference interval. An example of liver stiffness measurements, a clinically important diagnostic test without explicitly established reference range in children, is provided to demonstrate the use of quantile regression in estimating both overall and subject-specific reference intervals.https://doi.org/10.1186/s12874-024-02378-0Reference intervalQuantile regressionMeta-analysisIndividual participant dataBootstrap |
| spellingShingle | Ziren Jiang Haitao Chu Zhen Wang M. Hassan Murad Lianne K. Siegel Estimating reference intervals from an IPD meta-analysis using quantile regression BMC Medical Research Methodology Reference interval Quantile regression Meta-analysis Individual participant data Bootstrap |
| title | Estimating reference intervals from an IPD meta-analysis using quantile regression |
| title_full | Estimating reference intervals from an IPD meta-analysis using quantile regression |
| title_fullStr | Estimating reference intervals from an IPD meta-analysis using quantile regression |
| title_full_unstemmed | Estimating reference intervals from an IPD meta-analysis using quantile regression |
| title_short | Estimating reference intervals from an IPD meta-analysis using quantile regression |
| title_sort | estimating reference intervals from an ipd meta analysis using quantile regression |
| topic | Reference interval Quantile regression Meta-analysis Individual participant data Bootstrap |
| url | https://doi.org/10.1186/s12874-024-02378-0 |
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