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Predicting Risk of 1-Year Hospitalization Among Patients with Pulmonary Arterial Hypertension
INTRODUCTION: US claims-based analyses emphasize the substantial hospitalization burden of patients with pulmonary arterial hypertension (PAH) and the significant need for improved monitoring and more timely interventions. A claims-based predictive model may be useful to assist healthcare providers...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Healthcare
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079144/ https://www.ncbi.nlm.nih.gov/pubmed/37024760 http://dx.doi.org/10.1007/s12325-023-02501-5 |
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author | Zhang, Chang Tsang, Yuen He, Jinghua Panjabi, Sumeet |
author_facet | Zhang, Chang Tsang, Yuen He, Jinghua Panjabi, Sumeet |
author_sort | Zhang, Chang |
collection | PubMed |
description | INTRODUCTION: US claims-based analyses emphasize the substantial hospitalization burden of patients with pulmonary arterial hypertension (PAH) and the significant need for improved monitoring and more timely interventions. A claims-based predictive model may be useful to assist healthcare providers and payers in identifying patients with PAH at increased hospitalization risk. To address this aim, we constructed statistical models using baseline patient variables available in administrative healthcare claims to predict patients’ risk for all-cause and PH-related hospitalization within 1 year of initiating ≥ 1 PAH indicated medication. METHODS: Adult patients with PAH who newly initiated ≥ 1 PAH indicated medication were selected from the MarketScan Commercial and Medicare Supplemental databases (January 1, 2009–January 31, 2019). Cox regression models were built with a randomly selected training set and evaluated using a validation set of remaining patients. Predictive variables for the models were selected in three steps: clinical knowledge, univariate analysis, and backward stepwise selection. RESULTS: Within 1 year of initiating ≥ 1 PAH indicated medication, 1502/3872 (38.8%) had an all-cause hospitalization and 950/3872 (24.5%) had a pulmonary hypertension (PH)-related hospitalization. Predictive risk factors for all-cause hospitalization were Quan–Charlson Comorbidity Index (CCI) score 2–3 [hazard ratio (HR) 1.229; P = 0.038] and ≥ 4 (HR 1.531; P < 0.001), claims-based frailty index (CFI) score > 1 (highest frailty level; HR 1.301; P = 0.018), hemoptysis (HR 1.254; P = 0.016), malaise/fatigue (HR 1.150; P = 0.037), history of PH-related hospitalization (HR 1.171; P = 0.011), non-PH-related ER visit (HR 1.713; P = 0.014), and higher non-PH-related outpatient visit cost (HR 1.069; P < 0.001). Predictive risk factors for PH-related hospitalization were female sex (HR 1.264; P = 0.004), Quan-CCI score ≥ 4 (HR 1.408; P = 0.008), portal hypertension (HR 1.565; P = 0.019), CFI score > 1 (HR 1.522; P = 0.002), dyspnea (HR 1.259; P = 0.023), and history of PH-related hospitalization (HR 1.273; P = 0.002). CONCLUSIONS: The US claims-based predictive models showed acceptable performance to predict 1-year hospitalization among patients with PAH. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12325-023-02501-5. |
format | Online Article Text |
id | pubmed-10079144 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Healthcare |
record_format | MEDLINE/PubMed |
spelling | pubmed-100791442023-04-07 Predicting Risk of 1-Year Hospitalization Among Patients with Pulmonary Arterial Hypertension Zhang, Chang Tsang, Yuen He, Jinghua Panjabi, Sumeet Adv Ther Original Research INTRODUCTION: US claims-based analyses emphasize the substantial hospitalization burden of patients with pulmonary arterial hypertension (PAH) and the significant need for improved monitoring and more timely interventions. A claims-based predictive model may be useful to assist healthcare providers and payers in identifying patients with PAH at increased hospitalization risk. To address this aim, we constructed statistical models using baseline patient variables available in administrative healthcare claims to predict patients’ risk for all-cause and PH-related hospitalization within 1 year of initiating ≥ 1 PAH indicated medication. METHODS: Adult patients with PAH who newly initiated ≥ 1 PAH indicated medication were selected from the MarketScan Commercial and Medicare Supplemental databases (January 1, 2009–January 31, 2019). Cox regression models were built with a randomly selected training set and evaluated using a validation set of remaining patients. Predictive variables for the models were selected in three steps: clinical knowledge, univariate analysis, and backward stepwise selection. RESULTS: Within 1 year of initiating ≥ 1 PAH indicated medication, 1502/3872 (38.8%) had an all-cause hospitalization and 950/3872 (24.5%) had a pulmonary hypertension (PH)-related hospitalization. Predictive risk factors for all-cause hospitalization were Quan–Charlson Comorbidity Index (CCI) score 2–3 [hazard ratio (HR) 1.229; P = 0.038] and ≥ 4 (HR 1.531; P < 0.001), claims-based frailty index (CFI) score > 1 (highest frailty level; HR 1.301; P = 0.018), hemoptysis (HR 1.254; P = 0.016), malaise/fatigue (HR 1.150; P = 0.037), history of PH-related hospitalization (HR 1.171; P = 0.011), non-PH-related ER visit (HR 1.713; P = 0.014), and higher non-PH-related outpatient visit cost (HR 1.069; P < 0.001). Predictive risk factors for PH-related hospitalization were female sex (HR 1.264; P = 0.004), Quan-CCI score ≥ 4 (HR 1.408; P = 0.008), portal hypertension (HR 1.565; P = 0.019), CFI score > 1 (HR 1.522; P = 0.002), dyspnea (HR 1.259; P = 0.023), and history of PH-related hospitalization (HR 1.273; P = 0.002). CONCLUSIONS: The US claims-based predictive models showed acceptable performance to predict 1-year hospitalization among patients with PAH. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12325-023-02501-5. Springer Healthcare 2023-04-06 2023 /pmc/articles/PMC10079144/ /pubmed/37024760 http://dx.doi.org/10.1007/s12325-023-02501-5 Text en © The Author(s), under exclusive licence to Springer Healthcare Ltd., part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Research Zhang, Chang Tsang, Yuen He, Jinghua Panjabi, Sumeet Predicting Risk of 1-Year Hospitalization Among Patients with Pulmonary Arterial Hypertension |
title | Predicting Risk of 1-Year Hospitalization Among Patients with Pulmonary Arterial Hypertension |
title_full | Predicting Risk of 1-Year Hospitalization Among Patients with Pulmonary Arterial Hypertension |
title_fullStr | Predicting Risk of 1-Year Hospitalization Among Patients with Pulmonary Arterial Hypertension |
title_full_unstemmed | Predicting Risk of 1-Year Hospitalization Among Patients with Pulmonary Arterial Hypertension |
title_short | Predicting Risk of 1-Year Hospitalization Among Patients with Pulmonary Arterial Hypertension |
title_sort | predicting risk of 1-year hospitalization among patients with pulmonary arterial hypertension |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079144/ https://www.ncbi.nlm.nih.gov/pubmed/37024760 http://dx.doi.org/10.1007/s12325-023-02501-5 |
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