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Machine Learning-Augmented Propensity Score Analysis of Percutaneous Coronary Intervention in Over 30 Million Cancer and Non-cancer Patients

Background: It is unknown to what extent the clinical benefits of PCI outweigh the risks and costs in patients with vs. without cancer and within each cancer type. We performed the first known nationally representative propensity score analysis of PCI mortality and cost among all eligible adult inpa...

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Autores principales: Monlezun, Dominique J., Lawless, Sean, Palaskas, Nicolas, Peerbhai, Shareez, Charitakis, Konstantinos, Marmagkiolis, Konstantinos, Lopez-Mattei, Juan, Mamas, Mamas, Iliescu, Cezar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055825/
https://www.ncbi.nlm.nih.gov/pubmed/33889598
http://dx.doi.org/10.3389/fcvm.2021.620857
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author Monlezun, Dominique J.
Lawless, Sean
Palaskas, Nicolas
Peerbhai, Shareez
Charitakis, Konstantinos
Marmagkiolis, Konstantinos
Lopez-Mattei, Juan
Mamas, Mamas
Iliescu, Cezar
author_facet Monlezun, Dominique J.
Lawless, Sean
Palaskas, Nicolas
Peerbhai, Shareez
Charitakis, Konstantinos
Marmagkiolis, Konstantinos
Lopez-Mattei, Juan
Mamas, Mamas
Iliescu, Cezar
author_sort Monlezun, Dominique J.
collection PubMed
description Background: It is unknown to what extent the clinical benefits of PCI outweigh the risks and costs in patients with vs. without cancer and within each cancer type. We performed the first known nationally representative propensity score analysis of PCI mortality and cost among all eligible adult inpatients by cancer and its types. Methods: This multicenter case-control study used machine learning–augmented propensity score–adjusted multivariable regression to assess the above outcomes and disparities using the 2016 nationally representative National Inpatient Sample. Results: Of the 30,195,722 hospitalized patients, 15.43% had a malignancy, 3.84% underwent an inpatient PCI (of whom 11.07% had cancer and 0.07% had metastases), and 2.19% died inpatient. In fully adjusted analyses, PCI vs. medical management significantly reduced mortality for patients overall (among all adult inpatients regardless of cancer status) and specifically for cancer patients (OR 0.82, 95% CI 0.75–0.89; p < 0.001), mainly driven by active vs. prior malignancy, head and neck and hematological malignancies. PCI also significantly reduced cancer patients' total hospitalization costs (beta USD$ −8,668.94, 95% CI −9,553.59 to −7,784.28; p < 0.001) independent of length of stay. There were no significant income or disparities among PCI subjects. Conclusions: Our study suggests among all eligible adult inpatients, PCI does not increase mortality or cost for cancer patients, while there may be particular benefit by cancer type. The presence or history of cancer should not preclude these patients from indicated cardiovascular care.
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spelling pubmed-80558252021-04-21 Machine Learning-Augmented Propensity Score Analysis of Percutaneous Coronary Intervention in Over 30 Million Cancer and Non-cancer Patients Monlezun, Dominique J. Lawless, Sean Palaskas, Nicolas Peerbhai, Shareez Charitakis, Konstantinos Marmagkiolis, Konstantinos Lopez-Mattei, Juan Mamas, Mamas Iliescu, Cezar Front Cardiovasc Med Cardiovascular Medicine Background: It is unknown to what extent the clinical benefits of PCI outweigh the risks and costs in patients with vs. without cancer and within each cancer type. We performed the first known nationally representative propensity score analysis of PCI mortality and cost among all eligible adult inpatients by cancer and its types. Methods: This multicenter case-control study used machine learning–augmented propensity score–adjusted multivariable regression to assess the above outcomes and disparities using the 2016 nationally representative National Inpatient Sample. Results: Of the 30,195,722 hospitalized patients, 15.43% had a malignancy, 3.84% underwent an inpatient PCI (of whom 11.07% had cancer and 0.07% had metastases), and 2.19% died inpatient. In fully adjusted analyses, PCI vs. medical management significantly reduced mortality for patients overall (among all adult inpatients regardless of cancer status) and specifically for cancer patients (OR 0.82, 95% CI 0.75–0.89; p < 0.001), mainly driven by active vs. prior malignancy, head and neck and hematological malignancies. PCI also significantly reduced cancer patients' total hospitalization costs (beta USD$ −8,668.94, 95% CI −9,553.59 to −7,784.28; p < 0.001) independent of length of stay. There were no significant income or disparities among PCI subjects. Conclusions: Our study suggests among all eligible adult inpatients, PCI does not increase mortality or cost for cancer patients, while there may be particular benefit by cancer type. The presence or history of cancer should not preclude these patients from indicated cardiovascular care. Frontiers Media S.A. 2021-04-06 /pmc/articles/PMC8055825/ /pubmed/33889598 http://dx.doi.org/10.3389/fcvm.2021.620857 Text en Copyright © 2021 Monlezun, Lawless, Palaskas, Peerbhai, Charitakis, Marmagkiolis, Lopez-Mattei, Mamas and Iliescu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cardiovascular Medicine
Monlezun, Dominique J.
Lawless, Sean
Palaskas, Nicolas
Peerbhai, Shareez
Charitakis, Konstantinos
Marmagkiolis, Konstantinos
Lopez-Mattei, Juan
Mamas, Mamas
Iliescu, Cezar
Machine Learning-Augmented Propensity Score Analysis of Percutaneous Coronary Intervention in Over 30 Million Cancer and Non-cancer Patients
title Machine Learning-Augmented Propensity Score Analysis of Percutaneous Coronary Intervention in Over 30 Million Cancer and Non-cancer Patients
title_full Machine Learning-Augmented Propensity Score Analysis of Percutaneous Coronary Intervention in Over 30 Million Cancer and Non-cancer Patients
title_fullStr Machine Learning-Augmented Propensity Score Analysis of Percutaneous Coronary Intervention in Over 30 Million Cancer and Non-cancer Patients
title_full_unstemmed Machine Learning-Augmented Propensity Score Analysis of Percutaneous Coronary Intervention in Over 30 Million Cancer and Non-cancer Patients
title_short Machine Learning-Augmented Propensity Score Analysis of Percutaneous Coronary Intervention in Over 30 Million Cancer and Non-cancer Patients
title_sort machine learning-augmented propensity score analysis of percutaneous coronary intervention in over 30 million cancer and non-cancer patients
topic Cardiovascular Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055825/
https://www.ncbi.nlm.nih.gov/pubmed/33889598
http://dx.doi.org/10.3389/fcvm.2021.620857
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