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What patient characteristics are associated with benefit from treatment with COVID-19 convalescent plasma (CCP)?
This prognostic study of 2287 patients hospitalized with COVID-19 identified a combination of baseline characteristics that predict a gradation of benefit from CCP compared with treatment without CCP. Preexisting health conditions (diabetes, cardiovascular and pulmonary diseases), blood type A or AB, and earlier stage of COVID-19 were associated with a larger treatment benefit.
These findings suggest that simple patient information collected at hospitalization can be used to guide CCP treatment decisions for patients with COVID-19.
Identifying which patients with COVID-19 are likely to benefit from COVID-19 convalescent plasma (CCP) treatment may have a large public health impact.
To develop an index for predicting the expected relative treatment benefit from CCP compared with treatment without CCP for patients hospitalized for COVID-19 using patients’ baseline characteristics.
Design, Setting, and Participants
This prognostic study used data from the COMPILE study, ie, a meta-analysis of pooled individual patient data from 8 randomized clinical trials (RCTs) evaluating CCP vs control in adults hospitalized for COVID-19 who were not receiving mechanical ventilation at randomization. A combination of baseline characteristics, termed the treatment benefit index (TBI), was developed based on 2287 patients in COMPILE using a proportional odds model, with baseline characteristics selected via cross-validation. The TBI was externally validated on 4 external data sets: the Expanded Access Program (1896 participants), a study conducted under Emergency Use Authorization (210 participants), and 2 RCTs (with 80 and 309 participants).
Receipt of CCP.
Main Outcomes and Measures
World Health Organization (WHO) 11-point ordinal COVID-19 clinical status scale and 2 derivatives of it (ie, WHO score of 7-10, indicating mechanical ventilation to death, and WHO score of 10, indicating death) at day 14 and day 28 after randomization. Day 14 WHO 11-point ordinal scale was used as the primary outcome to develop the TBI.
A total of 2287 patients were included in the derivation cohort, with a mean (SD) age of 60.3 (15.2) years and 815 (35.6%) women. The TBI provided a continuous gradation of benefit, and, for clinical utility, it was operationalized into groups of expected large clinical benefit (B1; 629 participants in the derivation cohort [27.5%]), moderate benefit (B2; 953 [41.7%]), and potential harm or no benefit (B3; 705 [30.8%]). Patients with preexisting conditions (diabetes, cardiovascular and pulmonary diseases), with blood type A or AB, and at an early COVID-19 stage (low baseline WHO scores) were expected to benefit most, while those without preexisting conditions and at more advanced stages of COVID-19 could potentially be harmed. In the derivation cohort, odds ratios for worse outcome, where smaller odds ratios indicate larger benefit from CCP, were 0.69 (95% credible interval [CrI], 0.48-1.06) for B1, 0.82 (95% CrI, 0.61-1.11) for B2, and 1.58 (95% CrI, 1.14-2.17) for B3. Testing on 4 external datasets supported the validation of the derived TBIs.
Conclusions and Relevance
The findings of this study suggest that the CCP TBI is a simple tool that can quantify the relative benefit from CCP treatment for an individual patient hospitalized with COVID-19 that can be used to guide treatment recommendations. The TBI precision medicine approach could be especially helpful in a pandemic.
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CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships. If applicable, all relevant financial relationships have been mitigated.
Accepted for Publication: December 15, 2021.
Published: January 25, 2022. doi:10.1001/jamanetworkopen.2021.47375
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Park H et al. JAMA Network Open.
Corresponding Author: Eva Petkova, PhD, Division of Biostatistics, Department of Population Health, New York University Grossman School of Medicine, 180 Madison Ave, Room 2-55, New York, NY 10016 (email@example.com).
Author Contributions: Drs Park and Petkova had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Tarpey, Liu, Goldfeld, Ray, Villa, Verdun, Scibona, Burgos Pratx, Duarte, Hsue, Meyfroidt, Ortigoza, Pirofski, Troxel, Antman, Petkova.
Acquisition, analysis, or interpretation of data: Park, Tarpey, Liu, Y. Wu, D. Wu, Li, Zhang, Ganguly, Ray, Paul, Bhattacharya, Belov, Huang, Forshee, Verdun, Yoon, Agarwal, Simonovich, Burgos Pratx, Belloso, Avendaño-Solá, Bar, Duarte, Luetkemeyer, Meyfroidt, Nicola, Mukherjee, Ortigoza, Pirofski, Rijnders, Antman, Petkova.
Drafting of the manuscript: Park, Tarpey, Liu, Y. Wu, Li, Zhang, Burgos Pratx, Hsue, Pirofski, Petkova.
Critical revision of the manuscript for important intellectual content: Park, Tarpey, Goldfeld, D. Wu, Zhang, Ganguly, Ray, Paul, Bhattacharya, Belov, Huang, Villa, Forshee, Verdun, Yoon, Agarwal, Simonovich, Scibona, Burgos Pratx, Belloso, Avendaño-Solá, Bar, Duarte, Luetkemeyer, Meyfroidt, Nicola, Mukherjee, Ortigoza, Pirofski, Rijnders, Troxel, Antman, Petkova.
Statistical analysis: Park, Tarpey, Liu, Goldfeld, Y. Wu, D. Wu, Li, Zhang, Ganguly, Paul, Bhattacharya, Belov, Forshee, Burgos Pratx, Troxel, Petkova.
Obtained funding: Scibona, Hsue, Luetkemeyer, Petkova.
Administrative, technical, or material support: Park, Ganguly, Ray, Paul, Bhattacharya, Belov, Huang, Villa, Simonovich, Scibona, Burgos Pratx, Avendaño-Solá, Bar, Petkova.
Supervision: Liu, Ray, Forshee, Verdun, Scibona, Duarte, Hsue, Nicola, Pirofski, Antman, Petkova.
Conflict of Interest Disclosures: Dr Yoon reported receiving grants from the G. Harold and Leila Y. Mathers Foundation during the conduct of the study. Dr Duarte reported receiving personal fees from Amgen, Astellas, Bristol Myers Squibb, Gilead Sciences, Jazz Pharmaceuticals, Kiadis Pharma, Miltenyi Biotec, Merck Sharp and Dohme, Omeros, Pfizer, Sanofi Oncology, Sobi, and Takeda outside the submitted work. Dr Hsue reported receiving honoraria from Gilead Sciences and Merck and receiving grants from Novartis outside the submitted work. Dr Luetkemeyer reported receiving grants from the Steve and Marti Diamond Charitable Foundation during the conduct of the study and grants from Gilead Sciences, Eli Lilly and Co, and EMD Serono outside the submitted work. Dr Meyfroidt reported receiving grants from the Belgian Health Care Knowledge Center and the Research Foundation Flanders during the conduct of the study. Dr Pirofski reported receiving grants the G. Harold and Leila Y. Mathers Foundation during the conduct of the study. Dr Rijnders reported receiving grants from Erasmus MC Foundation during the conduct of the study. No other disclosures were reported.
Funding/Support: The design and conduct of the study; data collection, management, analysis, and interpretation of the data; and preparation of the manuscript for publication were supported by grant UL1TR001445 from the National Center for Advancing Translational Sciences of the National Institutes of Health (NIH). The statistical methodology and the extensions necessary for its applicability in the context of convalescent plasma use for treating COVID-19 were developed with support from grant R01MH099003 from National Institute of Mental Health of the NIH.
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the US Food and Drug Administration.
Additional Contributions: Alison Bateman-House, PhD (New York University), Eric Boersma, PhD (Erasmus University), David Glidden, PhD (University of California, San Francisco), Lakshmanan Jeyaseelan, PhD (Christian Medical College), Emmanuel Lesaffre, PhD (Katholieke University of Leuven), Grigorios Papageorgiou, (Erasmus University), Aitor Perez, PhD (Pivotal CRO), Suman Pramanik, MD (Army Hospital), Aranzazu Sancho-Lopez, MD, PhD (Hospital Universitario Puerta de Hierro Majadahonda), André Siqueira, MD (University of Brasilia), John Szumowski, MD, MPH (University of California, San Francisco), Séverine Vermeire , MD, PhD (Universitait Ziekenhuis Leuven), John Younger, MD (University City Science Center), Pamela Shaw, PhD (Kaiser Permanente Washington Health Research Institute), and Geert Verbeke, PhD (Katholieke University of Leuven), served on the data safety monitoring board for the COMPILE study. Barbee Whitaker, PhD (Center for Biologics Evaluation and Research, Office of Biostatistics and Epidemiology, Food and Drug Administration), facilitated the validation of TBI in 1 of the external data sets. Michael Joyner, MD, (Mayo Clinic, Human and Integrative Physiology and Clinical Pharmacology Laboratory), conducted the study that collected 1 of the validation data sets and allowed the use of those data for validation. Rickey Carter, PhD (Mayo Clinic, Biostatistics), was the biostatistician for a study that provided 1 of the external data sets for validation of the TBI and commented on the TBI development and validation. R. Todd Ogden, PhD (Columbia University, Department of Biostatistics), and David DeMets, PhD (University of Wisconsin, Biostatistics), discussed with the study team the methodology for the TBI and its application to this study. Judith S. Hochman, MD (New York University, School of Medicine), and Corita Grudzen, MD (New York University, School of Medicine), provided administrative support for the study. None of these individuals were compensated for their time.
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