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Assessment of Machine Learning to Estimate the Individual Treatment Effect of Corticosteroids in Septic Shock
IMPORTANCE: The survival benefit of corticosteroids in septic shock remains uncertain. OBJECTIVE: To estimate the individual treatment effect (ITE) of corticosteroids in adults with septic shock in intensive care units using machine learning and to evaluate the net benefit of corticosteroids when th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Association
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7729430/ https://www.ncbi.nlm.nih.gov/pubmed/33301017 http://dx.doi.org/10.1001/jamanetworkopen.2020.29050 |
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author | Pirracchio, Romain Hubbard, Alan Sprung, Charles L. Chevret, Sylvie Annane, Djillali |
author_facet | Pirracchio, Romain Hubbard, Alan Sprung, Charles L. Chevret, Sylvie Annane, Djillali |
author_sort | Pirracchio, Romain |
collection | PubMed |
description | IMPORTANCE: The survival benefit of corticosteroids in septic shock remains uncertain. OBJECTIVE: To estimate the individual treatment effect (ITE) of corticosteroids in adults with septic shock in intensive care units using machine learning and to evaluate the net benefit of corticosteroids when the decision to treat is based on the individual estimated absolute treatment effect. DESIGN, SETTING, AND PARTICIPANTS: This cohort study used individual patient data from 4 trials on steroid supplementation in adults with septic shock as a training cohort to model the ITE using an ensemble machine learning approach. Data from a double-blinded, placebo-controlled randomized clinical trial comparing hydrocortisone with placebo were used for external validation. Data analysis was conducted from September 2019 to February 2020. EXPOSURES: Intravenous hydrocortisone 50 mg dose every 6 hours for 5 to 7 days with or without enteral 50 μg of fludrocortisone daily for 7 days. The control was either the placebo or usual care. MAIN OUTCOMES AND MEASURES: All-cause 90-day mortality. RESULTS: A total of 2548 participants were included in the development cohort, with median (interquartile range [IQR]) age of 66 (55-76) years and 1656 (65.0%) men. The median (IQR) Simplified Acute Physiology Score (SAPS II) was 55 [42-69], and median (IQR) Sepsis-related Organ Failure Assessment score on day 1 was 11 (9-13). The crude pooled relative risk (RR) of death at 90 days was 0.89 (95% CI, 0.83 to 0.96) in favor of corticosteroids. According to the optimal individual model, the estimated median absolute risk reduction was of 2.90% (95% CI, 2.79% to 3.01%). In the external validation cohort of 75 patients, the area under the curve of the optimal individual model was 0.77 (95% CI, 0.59 to 0.92). For any number willing to treat (NWT; defined as the acceptable number of people to treat to avoid 1 additional outcome considering the risk of harm associated with the treatment) less than 25, the net benefit of treating all patients vs treating nobody was negative. When the NWT was 25, the net benefit was 0.01 for the treat all with hydrocortisone strategy, −0.01 for treat all with hydrocortisone and fludrocortisone strategy, 0.06 for the treat by SAPS II strategy, and 0.31 for the treat by optimal individual model strategy. The net benefit of the SAPS II and the optimal individual model treatment strategies converged to zero for a smaller number willing to treat, but the individual model was consistently superior than model based on the SAPS II score. CONCLUSIONS AND RELEVANCE: These findings suggest that an individualized treatment strategy to decide which patient with septic shock to treat with corticosteroids yielded positive net benefit regardless of potential corticosteroid-associated side effects. |
format | Online Article Text |
id | pubmed-7729430 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Medical Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-77294302020-12-18 Assessment of Machine Learning to Estimate the Individual Treatment Effect of Corticosteroids in Septic Shock Pirracchio, Romain Hubbard, Alan Sprung, Charles L. Chevret, Sylvie Annane, Djillali JAMA Netw Open Original Investigation IMPORTANCE: The survival benefit of corticosteroids in septic shock remains uncertain. OBJECTIVE: To estimate the individual treatment effect (ITE) of corticosteroids in adults with septic shock in intensive care units using machine learning and to evaluate the net benefit of corticosteroids when the decision to treat is based on the individual estimated absolute treatment effect. DESIGN, SETTING, AND PARTICIPANTS: This cohort study used individual patient data from 4 trials on steroid supplementation in adults with septic shock as a training cohort to model the ITE using an ensemble machine learning approach. Data from a double-blinded, placebo-controlled randomized clinical trial comparing hydrocortisone with placebo were used for external validation. Data analysis was conducted from September 2019 to February 2020. EXPOSURES: Intravenous hydrocortisone 50 mg dose every 6 hours for 5 to 7 days with or without enteral 50 μg of fludrocortisone daily for 7 days. The control was either the placebo or usual care. MAIN OUTCOMES AND MEASURES: All-cause 90-day mortality. RESULTS: A total of 2548 participants were included in the development cohort, with median (interquartile range [IQR]) age of 66 (55-76) years and 1656 (65.0%) men. The median (IQR) Simplified Acute Physiology Score (SAPS II) was 55 [42-69], and median (IQR) Sepsis-related Organ Failure Assessment score on day 1 was 11 (9-13). The crude pooled relative risk (RR) of death at 90 days was 0.89 (95% CI, 0.83 to 0.96) in favor of corticosteroids. According to the optimal individual model, the estimated median absolute risk reduction was of 2.90% (95% CI, 2.79% to 3.01%). In the external validation cohort of 75 patients, the area under the curve of the optimal individual model was 0.77 (95% CI, 0.59 to 0.92). For any number willing to treat (NWT; defined as the acceptable number of people to treat to avoid 1 additional outcome considering the risk of harm associated with the treatment) less than 25, the net benefit of treating all patients vs treating nobody was negative. When the NWT was 25, the net benefit was 0.01 for the treat all with hydrocortisone strategy, −0.01 for treat all with hydrocortisone and fludrocortisone strategy, 0.06 for the treat by SAPS II strategy, and 0.31 for the treat by optimal individual model strategy. The net benefit of the SAPS II and the optimal individual model treatment strategies converged to zero for a smaller number willing to treat, but the individual model was consistently superior than model based on the SAPS II score. CONCLUSIONS AND RELEVANCE: These findings suggest that an individualized treatment strategy to decide which patient with septic shock to treat with corticosteroids yielded positive net benefit regardless of potential corticosteroid-associated side effects. American Medical Association 2020-12-10 /pmc/articles/PMC7729430/ /pubmed/33301017 http://dx.doi.org/10.1001/jamanetworkopen.2020.29050 Text en Copyright 2020 Pirracchio R et al. JAMA Network Open. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the CC-BY License. |
spellingShingle | Original Investigation Pirracchio, Romain Hubbard, Alan Sprung, Charles L. Chevret, Sylvie Annane, Djillali Assessment of Machine Learning to Estimate the Individual Treatment Effect of Corticosteroids in Septic Shock |
title | Assessment of Machine Learning to Estimate the Individual Treatment Effect of Corticosteroids in Septic Shock |
title_full | Assessment of Machine Learning to Estimate the Individual Treatment Effect of Corticosteroids in Septic Shock |
title_fullStr | Assessment of Machine Learning to Estimate the Individual Treatment Effect of Corticosteroids in Septic Shock |
title_full_unstemmed | Assessment of Machine Learning to Estimate the Individual Treatment Effect of Corticosteroids in Septic Shock |
title_short | Assessment of Machine Learning to Estimate the Individual Treatment Effect of Corticosteroids in Septic Shock |
title_sort | assessment of machine learning to estimate the individual treatment effect of corticosteroids in septic shock |
topic | Original Investigation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7729430/ https://www.ncbi.nlm.nih.gov/pubmed/33301017 http://dx.doi.org/10.1001/jamanetworkopen.2020.29050 |
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