Latent Class Analysis to Identify Novel Phenotypes in Exacerbations of COPD: A Retrospective, Multicenter Cohort Study

This study aimed to identify novel phenotypes in patients with exacerbations of chronic obstructive pulmonary disease (ECOPD) to enable precise management, as current phenotypic classifications show limited utility in predicting patient prognosis. By analyzing data from a robust, retrospective multicenter registry (<i>n</i> = 13,449) and leveraging 133 biomarkers with penalized Cox models, we developed a six-phenotype latent class analysis model. Phenotype 1 is distinguished by elevated direct bilirubin (Dbil) and lactate dehydrogenase (LDH). Phenotype 2 features a higher percentage of lymphocytes (LYMPH_pct) and lower percentage of neutrophils (NEUT_pct). Phenotype 3 is marked by increased generalized cardiovascular disease (gCVD) and reduced NEUT_pct. Phenotype 4 is related to higher NEUT_pct and lower LYMPH_pct. Phenotype 5 is associated with a higher prevalence of gCVD and surgical trauma history. Phenotype 6 stands out for its higher rates of respiratory failure and elevated pulse at admission. Compared with Phenotype 1, patients in Phenotype 6 have a significantly higher risk of all-cause mortality in both the development and validation sets, with adjusted hazard ratios of 2.06 (95% CI: 1.38-3.08) and 2.51 (95% CI: 1.43-4.04), respectively. These findings reveal novel ECOPD subgroups with significant prognostic differences, providing a crucial framework for implementing precision health management and improving patient outcomes.

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Journal
MedComm
Published
2025-10-28
DOI
https://doi.org/10.1002/mco2.70444
Primary Topic
Chronic Obstructive Pulmonary Disease (COPD) Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Latent Class Analysis to Identify Novel Phenotypes in Exacerbations of COPD: A Retrospective, Multicenter Cohort Study

Yumin Zhou, Jieqi Peng, Chen Xi-mo, Cuiqiong Dai et al.
MedComm
Chronic Obstructive Pulmonary Disease (COPD) Research
article

Latent Class Analysis to Identify Novel Phenotypes in Exacerbations of COPD: A Retrospective, Multicenter Cohort Study

Yumin Zhou, Jieqi Peng, Chen Xi-mo, Cuiqiong Dai, Leqing Zhu, Zhishan Deng, Kunning Zhou, Pixin Ran, Lifei Lu, Xiangqing Hou, Yuemao Li, Fan Wu, Qi Wan, Jie Hong, Xiaohui Wu, Jinrong Huang, Gaoying Tang
article en

Abstract

This study aimed to identify novel phenotypes in patients with exacerbations of chronic obstructive pulmonary disease (ECOPD) to enable precise management, as current phenotypic classifications show limited utility in predicting patient prognosis. By analyzing data from a robust, retrospective multicenter registry (<i>n</i> = 13,449) and leveraging 133 biomarkers with penalized Cox models, we developed a six-phenotype latent class analysis model. Phenotype 1 is distinguished by elevated direct bilirubin (Dbil) and lactate dehydrogenase (LDH). Phenotype 2 features a higher percentage of lymphocytes (LYMPH_pct) and lower percentage of neutrophils (NEUT_pct). Phenotype 3 is marked by increased generalized cardiovascular disease (gCVD) and reduced NEUT_pct. Phenotype 4 is related to higher NEUT_pct and lower LYMPH_pct. Phenotype 5 is associated with a higher prevalence of gCVD and surgical trauma history. Phenotype 6 stands out for its higher rates of respiratory failure and elevated pulse at admission. Compared with Phenotype 1, patients in Phenotype 6 have a significantly higher risk of all-cause mortality in both the development and validation sets, with adjusted hazard ratios of 2.06 (95% CI: 1.38-3.08) and 2.51 (95% CI: 1.43-4.04), respectively. These findings reveal novel ECOPD subgroups with significant prognostic differences, providing a crucial framework for implementing precision health management and improving patient outcomes.

MedCommVol. 6(11)
Guangzhou Experimental Station (CN), First Affiliated Hospital of Guangzhou Medical University (CN), Guangzhou Regenerative Medicine and Health Guangdong Laboratory (CN), State Key Laboratory of Respiratory Disease (CN), Guangzhou Medical University (CN)
Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Science and Technology Major Project
Openalex Percentile: Top 55%
Chronic Obstructive Pulmonary Disease (COPD) Research
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