Low psoas muscle index associates with long-term mortality in cirrhosis: construction of a nomogram.
Nomogram
gait speed
liver cirrhosis
psoas muscle index
sarcopenia
Journal
Annals of translational medicine
ISSN: 2305-5839
Titre abrégé: Ann Transl Med
Pays: China
ID NLM: 101617978
Informations de publication
Date de publication:
Mar 2020
Mar 2020
Historique:
entrez:
2
5
2020
pubmed:
2
5
2020
medline:
2
5
2020
Statut:
ppublish
Résumé
To develop a nomogram incorporating indicator of muscle waste to prognosticate long-term mortality in liver cirrhosis (LC), and identify the prognostic impact of psoas muscle index (PMI). A total of 251 LC patients who underwent computed tomography were included in this study. Multiple Cox regression was performed, and sex-specific nomogram models incorporating PMI were developed. The utility of the proposed models were evaluated by Harrell's concordance index (C-index), calibration curve and decision curve analysis. X-tile was used to determine optimal cutpoint for stratifying subjects with distinct outcomes. Subgroup analysis was implemented in terms of age and MELD score. The correlation between PMI and gait speed was also evaluated. On multiple analysis, independent predictors for 3-year all-cause mortality were age, BMI, PMI and MELD for males, and age, PMI and MELD for females. Both nomogram models gave rise to moderately strong discrimination, with a C-index of 0.792 (95% CI: 0.723-0.861) in males and 0.715 (95% CI: 0.637-0.793) in females, respectively. The calibration curve implied predicted survival corresponding optimally with the actual outcomes. The proposed models were feasible in clinical settings based on decision curve analysis. On subgroup analysis, PMI might confer valid predictive value on LC patients with MELD <15. Moreover, a definitely positive correlation between PMI and gait speed was revealed. Our proposed nomogram embedding PMI rendered an individualized predictive tool for long-term mortality in LC. The diminishing value of PMI is likely indicative of muscle dysfunction.
Sections du résumé
BACKGROUND
BACKGROUND
To develop a nomogram incorporating indicator of muscle waste to prognosticate long-term mortality in liver cirrhosis (LC), and identify the prognostic impact of psoas muscle index (PMI).
METHODS
METHODS
A total of 251 LC patients who underwent computed tomography were included in this study. Multiple Cox regression was performed, and sex-specific nomogram models incorporating PMI were developed. The utility of the proposed models were evaluated by Harrell's concordance index (C-index), calibration curve and decision curve analysis. X-tile was used to determine optimal cutpoint for stratifying subjects with distinct outcomes. Subgroup analysis was implemented in terms of age and MELD score. The correlation between PMI and gait speed was also evaluated.
RESULTS
RESULTS
On multiple analysis, independent predictors for 3-year all-cause mortality were age, BMI, PMI and MELD for males, and age, PMI and MELD for females. Both nomogram models gave rise to moderately strong discrimination, with a C-index of 0.792 (95% CI: 0.723-0.861) in males and 0.715 (95% CI: 0.637-0.793) in females, respectively. The calibration curve implied predicted survival corresponding optimally with the actual outcomes. The proposed models were feasible in clinical settings based on decision curve analysis. On subgroup analysis, PMI might confer valid predictive value on LC patients with MELD <15. Moreover, a definitely positive correlation between PMI and gait speed was revealed.
CONCLUSIONS
CONCLUSIONS
Our proposed nomogram embedding PMI rendered an individualized predictive tool for long-term mortality in LC. The diminishing value of PMI is likely indicative of muscle dysfunction.
Identifiants
pubmed: 32355802
doi: 10.21037/atm.2020.02.49
pii: atm-08-06-358
pmc: PMC7186727
doi:
Types de publication
Journal Article
Langues
eng
Pagination
358Informations de copyright
2020 Annals of Translational Medicine. All rights reserved.
Déclaration de conflit d'intérêts
Conflicts of Interest: CS serves as an unpaid section editor of Annals of Translational Medicine from Oct 2019 to Sep 2020. The other authors have no conflicts of interest to declare.
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