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05971nam a2201033Ia 4500 |
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10-1001-jamanetworkopen-2021-47375 |
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|a 25743805 (ISSN)
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|a Development and Validation of a Treatment Benefit Index to Identify Hospitalized Patients With COVID-19 Who May Benefit From Convalescent Plasma
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|b NLM (Medline)
|c 2022
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|z View Fulltext in Publisher
|u https://doi.org/10.1001/jamanetworkopen.2021.47375
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|a Importance: Identifying which patients with COVID-19 are likely to benefit from COVID-19 convalescent plasma (CCP) treatment may have a large public health impact. Objective: 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). Exposure: 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. Results: 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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|a aged
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|a Aged
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|a artificial ventilation
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|a blood group typing
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|a Blood Grouping and Crossmatching
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|a comorbidity
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|a Comorbidity
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|a COVID-19
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|a female
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|a Female
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|a hospitalization
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|a Hospitalization
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|a human
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|a Humans
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|a Immunization, Passive
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|a male
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|a Male
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|a middle aged
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|a Middle Aged
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|a odds ratio
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|a Odds Ratio
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|a pandemic
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|a Pandemics
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|a passive immunization
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|a patient selection
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|a Patient Selection
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|a plasma
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|a Plasma
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|a Respiration, Artificial
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|a SARS-CoV-2
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|a severity of illness index
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|a Severity of Illness Index
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|a therapeutic index
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|a Therapeutic Index
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|a therapy
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|a treatment outcome
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|a Treatment Outcome
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|a World Health Organization
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|a World Health Organization
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|a Agarwal, A.
|e author
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|a Antman, E.M.
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|a Avendaño-Solá, C.
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|a Bar, K.J.
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|a Belloso, W.
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|a Belov, A.
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|a Bhattacharya, P.
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|a Burgos Pratx, L.
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|a Duarte, R.F.
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|a Forshee, R.
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|a Ganguly, D.
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|a Goldfeld, K.
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|a Hsue, P.Y.
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|a Huang, Y.
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|a Li, Y.
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|a Liu, M.
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|a Luetkemeyer, A.F.
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|a Meyfroidt, G.
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|a Mukherjee, A.
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|a Nicola, A.M.
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|a Ortigoza, M.B.
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|a Park, H.
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|a Paul, S.R.
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|a Petkova, E.
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|a Pirofski, L.-A.
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|a Ray, Y.
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|a Rijnders, B.J.A.
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|a Scibona, P.
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|a Simonovich, V.A.
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|a Tarpey, T.
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|a Troxel, A.
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|a Verdun, N.C.
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|a Villa, C.
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|a Wu, D.
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|a Wu, Y.
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|a Yoon, H.A.
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|a Zhang, J.
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|t JAMA network open
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