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A Method for Reconstructing Individual Patient Data From Kaplan-Meier Survival Curves That Incorporate Marked Censoring Times

Introduction. Access to individual patient data (IPD) can be advantageous when conducting cost-effectiveness analyses or indirect treatment comparisons. While exact times of censoring are often marked on published Kaplan-Meier (KM) curves, an algorithm for reconstructing IPD from such curves that al...

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Autores principales: Rogula, Basia, Lozano-Ortega, Greta, Johnston, Karissa M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8808036/
https://www.ncbi.nlm.nih.gov/pubmed/35128059
http://dx.doi.org/10.1177/23814683221077643
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author Rogula, Basia
Lozano-Ortega, Greta
Johnston, Karissa M.
author_facet Rogula, Basia
Lozano-Ortega, Greta
Johnston, Karissa M.
author_sort Rogula, Basia
collection PubMed
description Introduction. Access to individual patient data (IPD) can be advantageous when conducting cost-effectiveness analyses or indirect treatment comparisons. While exact times of censoring are often marked on published Kaplan-Meier (KM) curves, an algorithm for reconstructing IPD from such curves that allows for their incorporation is presently unavailable. Methods. An algorithm capable of incorporating marked censoring times was developed to reconstruct IPD from KM curves, taking as additional inputs the total patient count and coordinates of the drops in survival. The reliability of the algorithm was evaluated via a simulation exercise, in which survival curves were simulated, digitized, and then reconstructed. To assess the reliability of the reconstructed curves, hazard ratios (HRs) and quantiles of survival were compared between the original and reconstructed curves, and the reconstructed curves were visually inspected. Results. No systematic differences were found in HRs and quantiles in the original versus reconstructed curves. Upon visual inspection, the reconstructed IPD provided a close fit to the digitized data from the published KM curves. Inherent to the algorithm, censoring times were incorporated into the reconstructed data exactly as specified. Conclusion. This new algorithm can reliably be used to reconstruct IPD from reported KM survival curves in the presence of extractable censoring times. Use of the algorithm will allow health researchers to reconstruct IPD more closely by incorporating censoring times exactly as marked, requiring as additional inputs the total patient count and coordinates of the drops in survival.
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spelling pubmed-88080362022-02-03 A Method for Reconstructing Individual Patient Data From Kaplan-Meier Survival Curves That Incorporate Marked Censoring Times Rogula, Basia Lozano-Ortega, Greta Johnston, Karissa M. MDM Policy Pract Original Research Article Introduction. Access to individual patient data (IPD) can be advantageous when conducting cost-effectiveness analyses or indirect treatment comparisons. While exact times of censoring are often marked on published Kaplan-Meier (KM) curves, an algorithm for reconstructing IPD from such curves that allows for their incorporation is presently unavailable. Methods. An algorithm capable of incorporating marked censoring times was developed to reconstruct IPD from KM curves, taking as additional inputs the total patient count and coordinates of the drops in survival. The reliability of the algorithm was evaluated via a simulation exercise, in which survival curves were simulated, digitized, and then reconstructed. To assess the reliability of the reconstructed curves, hazard ratios (HRs) and quantiles of survival were compared between the original and reconstructed curves, and the reconstructed curves were visually inspected. Results. No systematic differences were found in HRs and quantiles in the original versus reconstructed curves. Upon visual inspection, the reconstructed IPD provided a close fit to the digitized data from the published KM curves. Inherent to the algorithm, censoring times were incorporated into the reconstructed data exactly as specified. Conclusion. This new algorithm can reliably be used to reconstruct IPD from reported KM survival curves in the presence of extractable censoring times. Use of the algorithm will allow health researchers to reconstruct IPD more closely by incorporating censoring times exactly as marked, requiring as additional inputs the total patient count and coordinates of the drops in survival. SAGE Publications 2022-01-31 /pmc/articles/PMC8808036/ /pubmed/35128059 http://dx.doi.org/10.1177/23814683221077643 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research Article
Rogula, Basia
Lozano-Ortega, Greta
Johnston, Karissa M.
A Method for Reconstructing Individual Patient Data From Kaplan-Meier Survival Curves That Incorporate Marked Censoring Times
title A Method for Reconstructing Individual Patient Data From Kaplan-Meier Survival Curves That Incorporate Marked Censoring Times
title_full A Method for Reconstructing Individual Patient Data From Kaplan-Meier Survival Curves That Incorporate Marked Censoring Times
title_fullStr A Method for Reconstructing Individual Patient Data From Kaplan-Meier Survival Curves That Incorporate Marked Censoring Times
title_full_unstemmed A Method for Reconstructing Individual Patient Data From Kaplan-Meier Survival Curves That Incorporate Marked Censoring Times
title_short A Method for Reconstructing Individual Patient Data From Kaplan-Meier Survival Curves That Incorporate Marked Censoring Times
title_sort method for reconstructing individual patient data from kaplan-meier survival curves that incorporate marked censoring times
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8808036/
https://www.ncbi.nlm.nih.gov/pubmed/35128059
http://dx.doi.org/10.1177/23814683221077643
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