Prediction of survival in patients with colorectal liver metastases- development and validation of a prognostic score model.


Journal

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
ISSN: 1532-2157
Titre abrégé: Eur J Surg Oncol
Pays: England
ID NLM: 8504356

Informations de publication

Date de publication:
Dec 2022
Historique:
received: 03 11 2021
revised: 10 05 2022
accepted: 17 06 2022
pubmed: 6 7 2022
medline: 15 12 2022
entrez: 5 7 2022
Statut: ppublish

Résumé

Metastatic spread of colorectal cancer to the liver impacts prognosis. Advances in chemotherapy have resulted in increased resectability rates and thereby improved survival in patients with colorectal liver metastases (CRLM). However, criteria are needed to ensure that patients selected for hepatic resection benefit from the invasive therapy. The study aimed to construct a predictive model for overall survival (OS) in patients with CRLM, based on preoperatively available information. The retrospective cohort study reviewed all patients with CRLM discussed at multidisciplinary team conference at Karolinska University Hospital, Stockholm, Sweden, 2013-2018. Independent prognostic factors for OS were identified, based on which a score model was generated. The model was validated on patients treated for CRLM at Hôpital Universitaire Paul Brousse, Villejuif, France, 2007-2018. Calibration and discrimination methods were used for internal and external validation. The Swedish development cohort included 1013 patients, the French validation cohort 391 patients. Poor OS was significantly associated with age>60years (hazard ratio (HR) 3.57 (95%CI 2.18-9.94)), number of CRLM (HR 4.59 (2.83-12.20)), diameter of largest CRLM>5 cm (HR 2.59 (1.74-5.03)), right-sided primary tumour (HR 2.98 (2.00-5.80)), extrahepatic disease (HR 4.14 (2.38-15.87)) and non-resectability (HR 0.77 (0.66-0.90)). The C-statistic for prediction of OS was .74, in the development cohort and 0.69 in the validation cohort. The presented predictive score model can adequately predict OS for patients at the initial diagnosis of CRLM. The prognostic model could be of clinical value in the management of all patients with CRLM, by predicting individualized survival and thereby facilitating treatment recommendations.

Sections du résumé

BACKGROUND BACKGROUND
Metastatic spread of colorectal cancer to the liver impacts prognosis. Advances in chemotherapy have resulted in increased resectability rates and thereby improved survival in patients with colorectal liver metastases (CRLM). However, criteria are needed to ensure that patients selected for hepatic resection benefit from the invasive therapy. The study aimed to construct a predictive model for overall survival (OS) in patients with CRLM, based on preoperatively available information.
METHODS METHODS
The retrospective cohort study reviewed all patients with CRLM discussed at multidisciplinary team conference at Karolinska University Hospital, Stockholm, Sweden, 2013-2018. Independent prognostic factors for OS were identified, based on which a score model was generated. The model was validated on patients treated for CRLM at Hôpital Universitaire Paul Brousse, Villejuif, France, 2007-2018. Calibration and discrimination methods were used for internal and external validation.
RESULTS RESULTS
The Swedish development cohort included 1013 patients, the French validation cohort 391 patients. Poor OS was significantly associated with age>60years (hazard ratio (HR) 3.57 (95%CI 2.18-9.94)), number of CRLM (HR 4.59 (2.83-12.20)), diameter of largest CRLM>5 cm (HR 2.59 (1.74-5.03)), right-sided primary tumour (HR 2.98 (2.00-5.80)), extrahepatic disease (HR 4.14 (2.38-15.87)) and non-resectability (HR 0.77 (0.66-0.90)). The C-statistic for prediction of OS was .74, in the development cohort and 0.69 in the validation cohort.
CONCLUSION CONCLUSIONS
The presented predictive score model can adequately predict OS for patients at the initial diagnosis of CRLM. The prognostic model could be of clinical value in the management of all patients with CRLM, by predicting individualized survival and thereby facilitating treatment recommendations.

Identifiants

pubmed: 35786533
pii: S0748-7983(22)00523-6
doi: 10.1016/j.ejso.2022.06.021
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2432-2439

Informations de copyright

Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest None.

Auteurs

Christina Villard (C)

Department of Transplantation Surgery, Karolinska University Hospital, Stockholm, Sweden; Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden. Electronic address: christina.villard@ki.se.

Ahmed Abdelrafee (A)

Gastrointestinal Surgery Center, Department of Surgery, Mansoura University, Mansoura, Egypt.

Miriam Habib (M)

Centre Hépato-Biliaire AP-HP Hôpital Paul Brousse, Equipe Recherche « Chronothérapie, Cancers et Transplantation » Université Paris-Saclay, Villejuif, France.

Nelson Ndegwa (N)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden.

Carl Jorns (C)

Department of Transplantation Surgery, Karolinska University Hospital, Stockholm, Sweden; Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden.

Ernesto Sparrelid (E)

Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden; Department of Cancer, Division of Upper GI, Karolinska University Hospital, Stockholm, Sweden.

Marc-Antoine Allard (MA)

Centre Hépato-Biliaire AP-HP Hôpital Paul Brousse, Equipe Recherche « Chronothérapie, Cancers et Transplantation » Université Paris-Saclay, Villejuif, France.

René Adam (R)

Centre Hépato-Biliaire AP-HP Hôpital Paul Brousse, Equipe Recherche « Chronothérapie, Cancers et Transplantation » Université Paris-Saclay, Villejuif, France.

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