A machine learning predictive model for recurrence of resected distal cholangiocarcinoma: Development and validation of predictive model using artificial intelligence.
Eur J Surg Oncol
; 50(7): 108375, 2024 Jul.
Article
em En
| MEDLINE
| ID: mdl-38795677
ABSTRACT
INTRODUCTION:
Distal Cholangiocarcinoma (dCCA) represents a challenge in hepatobiliary oncology, that requires nuanced post-resection prognostic modeling. Conventional staging criteria may oversimplify dCCA complexities, prompting the exploration of novel prognostic factors and methodologies, including machine learning algorithms. This study aims to develop a machine learning predictive model for recurrence after resected dCCA. MATERIAL ANDMETHODS:
This retrospective multicentric observational study included patients with dCCA from 13 international centers who underwent curative pancreaticoduodenectomy (PD). A LASSO-regularized Cox regression model was used to feature selection, examine the path of the coefficient and create a model to predict recurrence. Internal and external validation and model performance were assessed using the C-index score. Additionally, a web application was developed to enhance the clinical use of the algorithm.RESULTS:
Among 654 patients, LNR (Lymph Node Ratio) 15, neural invasion, N stage, surgical radicality, and differentiation grade emerged as significant predictors of disease-free survival (DFS). The model showed the best discrimination capacity with a C-index value of 0.8 (CI 95 %, 0.77%-0.86 %) and highlighted LNR15 as the most influential factor. Internal and external validations showed the model's robustness and discriminative ability with an Area Under the Curve of 92.4 % (95 % CI, 88.2%-94.4 %) and 91.5 % (95 % CI, 88.4%-93.5 %), respectively. The predictive model is available at https//imim.shinyapps.io/LassoCholangioca/.CONCLUSIONS:
This study pioneers the integration of machine learning into prognostic modeling for dCCA, yielding a robust predictive model for DFS following PD. The tool can provide information to both patients and healthcare providers, enhancing tailored treatments and follow-up.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias dos Ductos Biliares
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Inteligência Artificial
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Pancreaticoduodenectomia
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Colangiocarcinoma
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Aprendizado de Máquina
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Recidiva Local de Neoplasia
Limite:
Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Eur J Surg Oncol
Assunto da revista:
NEOPLASIAS
Ano de publicação:
2024
Tipo de documento:
Article