TY - GEN
T1 - RWD162 Development and validation of a predictive model for the risk of sarcopenia in patients with COPD
AU - yu, zhenjie
N1 - Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s)
PY - 2025/10
Y1 - 2025/10
N2 - Objectives: Sarcopenia is a clinical condition common in patients with COPD. It can exacerbate respiratory difficulties and physical function decline in patients with COPD, thereby affecting their prognosis. This study aimed to establish a simplified tool for screening sarcopenia in patients with COPD. Methods: This study enrolled 268 patients from Tianjin, China, between June 2022 and December 2023. Sarcopenia was defined and assessed according to the criteria set by the Asian Working Group for Sarcopenia 2019, using the SARC-CalF scale. Of the 268 patients, 189 were selected for the training dataset. A screening nomogram was developed using logistic regression analysis to facilitate the diagnosis of sarcopenia. We included 79 consecutive patients to validate the screening model. Results: The mean age of the enrolled patients (182 men and 86 women) was 71.49 ± 0.51. The overall rate of sarcopenia in patients with COPD was 31.81%. Multivariate logistic regression analysis revealed that low body mass index (BMI), high modified medical research council (mMRC) scores, history of alcohol consumption, and negative approach to medical coping were predictive factors for sarcopenia among patients with COPD. These factors were used to construct a nomogram model, which demonstrated good consistency and accuracy, with high C-indexes of 0.948 and 0.915 in the training and verification sets, respectively. Additionally, it exhibited a well-fitted calibration curve and decision curve analysis, indicating good model discrimination. Additionally, P-values of the Hosmer–Lemeshow test for the training and validation cohorts were 0.882 and 0.931, respectively, indicating high calibration and good predictive performance of the model. Conclusions: The predictive model indicates that patients with COPD with low BMI, high mMRC scores, a history of alcohol consumption, and a negative approach to coping with the disease are at a high risk of developing sarcopenia. This model offers valuable insights for clinical practitioners, facilitating early screening and targeted interventions for sarcopenia in patients with COPD.
AB - Objectives: Sarcopenia is a clinical condition common in patients with COPD. It can exacerbate respiratory difficulties and physical function decline in patients with COPD, thereby affecting their prognosis. This study aimed to establish a simplified tool for screening sarcopenia in patients with COPD. Methods: This study enrolled 268 patients from Tianjin, China, between June 2022 and December 2023. Sarcopenia was defined and assessed according to the criteria set by the Asian Working Group for Sarcopenia 2019, using the SARC-CalF scale. Of the 268 patients, 189 were selected for the training dataset. A screening nomogram was developed using logistic regression analysis to facilitate the diagnosis of sarcopenia. We included 79 consecutive patients to validate the screening model. Results: The mean age of the enrolled patients (182 men and 86 women) was 71.49 ± 0.51. The overall rate of sarcopenia in patients with COPD was 31.81%. Multivariate logistic regression analysis revealed that low body mass index (BMI), high modified medical research council (mMRC) scores, history of alcohol consumption, and negative approach to medical coping were predictive factors for sarcopenia among patients with COPD. These factors were used to construct a nomogram model, which demonstrated good consistency and accuracy, with high C-indexes of 0.948 and 0.915 in the training and verification sets, respectively. Additionally, it exhibited a well-fitted calibration curve and decision curve analysis, indicating good model discrimination. Additionally, P-values of the Hosmer–Lemeshow test for the training and validation cohorts were 0.882 and 0.931, respectively, indicating high calibration and good predictive performance of the model. Conclusions: The predictive model indicates that patients with COPD with low BMI, high mMRC scores, a history of alcohol consumption, and a negative approach to coping with the disease are at a high risk of developing sarcopenia. This model offers valuable insights for clinical practitioners, facilitating early screening and targeted interventions for sarcopenia in patients with COPD.
U2 - 10.1016/j.vhri.2025.101471
DO - 10.1016/j.vhri.2025.101471
M3 - RGC 32 - Refereed conference paper (with host publication)
T3 - Value in Health Regional Issues
BT - ISPOR Real-World Evidence Summit 2025
ER -