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2023 article

Stratification of Stage II Colon Cancer Using Recurrence Prediction Value

1Citations signalées, ce qui n’est pas une note de qualité
10Institutions déclarées
3Pays d’affiliation déclarés

Rattachement africain : jp, us, jo. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

OBJECTIVE: To create a recurrence prediction value (RPV) of high-risk factor and identify the patients with high risk of cancer recurrence. BACKGROUND: There are several high-risk factors known to lead to poor outcomes. Weighting each high-risk factor based on their association with increased risk of cancer recurrence can provide a more precise understanding of risk of recurrence. METHODS: We performed a multi-institutional international retrospective analysis of patients with stage II colon cancer patients who underwent surgery from 2010 to 2020. Patient data from a multi-institutional database were used as the Training data, and data from a completely separate international database from 2 countries were used as the Validation data. The primary endpoint was recurrence-free survival. RESULTS: A total of 739 patients were included from Training data. To validate the feasibility of RPV, 467 patients were included from Validation data. Training data patients were divided into RPV low (n=564) and RPV high (n=175). Multivariate analysis revealed that risk of recurrence was significantly higher in the RPV high than the RPV low [hazard ratio (HR) 2.628; 95% confidence interval (CI) 1.887-3.660; P <0.001). Validation data patients were divided into 2 groups (RPV low, n=420) and RPV high (n=47). Multivariate analysis revealed that risk of recurrence was significantly higher in the RPV high than the RPV low (HR 3.053; 95% CI 1.962-4.750; P <0.001). CONCLUSIONS: RPV can identify stage II colon cancer patients with high risk of cancer recurrence worldwide.

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Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Stratification of Stage II Colon Cancer Using Recurrence Prediction Value
Date Crossref
12/10/2023
Éditeur
Ovid Technologies (Wolters Kluwer Health)
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Les institutions déclarées

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Colorectal Cancer Screening and DetectionColorectal Cancer Surgical TreatmentsRadiomics and Machine Learning in Medical Imaging

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