Cargando…

A possible combined appraisal pattern: predicting the prognosis of patients after esophagectomy

OBJECTIVE: To investigate the predictive merit of combined preoperative nutritional condition and systemic inflammation on the prognosis of patients receiving esophagectomy, with the assessment of model construction to extract a multidisciplinary phantom having clinical relevance and suitability. ME...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, LiangLiang, Yu, GuoCan, Zhao, WuChen, Ye, Bo, Shu, YuSheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10201727/
https://www.ncbi.nlm.nih.gov/pubmed/37211596
http://dx.doi.org/10.1186/s12957-023-03020-x
Descripción
Sumario:OBJECTIVE: To investigate the predictive merit of combined preoperative nutritional condition and systemic inflammation on the prognosis of patients receiving esophagectomy, with the assessment of model construction to extract a multidisciplinary phantom having clinical relevance and suitability. METHODS: The software of R 4.1.2 was utilized to acquire the survival optimal truncation value and the confusion matrix of survival for the continuity variables. SPSS Statistics 26 was employed to analyze the correlation of parameters, where including t-test, ANOVA and the nonparametric rank sum test shall. Pearson chi-square test was used for categorical variables. The survival curve was retrieved by Kaplan–Meier method. Univariate analysis of overall survival (OS) was performed through log-rank test. Cox analysis was for survival analyze. The performance of the prediction phantom through the area under curve (AUC) of receiver operating characteristic curve (ROC), decision curve analysis (DCA), nomogram and clinical impact curve (CIC) was plotted by R. RESULTS: The AUC value of albumin-globulin score and skeletal muscle index (CAS) is markedly superior. Patients with diminished AGS and greater SMI were associated with improved overall survival (OS) and recurrence-free survival (RFS) (P < 0.01). The CAS composite evaluation model was calibrated with better accuracy and predictive performance. The DCA and CIC indicated a relatively higher net revenue for the prediction model. CONCLUSIONS: The prediction model including the CAS score has excellent accuracy, a high net revenue, and favorable prediction function. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-023-03020-x.