Khorana score and thromboembolic risk in stage II-III colorectal cancer patients: a

Khorana score adjuvant chemotherapy colorectal cancer thrombosis

Journal

Therapeutic advances in medical oncology
ISSN: 1758-8340
Titre abrégé: Ther Adv Med Oncol
Pays: England
ID NLM: 101510808

Informations de publication

Date de publication:
2020
Historique:
received: 12 01 2019
accepted: 09 12 2019
entrez: 4 2 2020
pubmed: 6 2 2020
medline: 6 2 2020
Statut: epublish

Résumé

The risk of venous thromboembolic events (VTE) during adjuvant chemotherapy for colorectal cancer (CRC) is unknown. We aim to evaluate if the Khorana score (KS) can predict this risk, and if it represents a prognostic factor for overall survival (OS) through a A logistic regression model was used to test the associations between the risk of VTE and the KS. The results are expressed as odds ratios (OR) with 95% confidence intervals (95% CI). To assess the effect of the KS on OS, multivariable analyses using Cox regression models were performed. The results are expressed as hazard ratios (HR) with 95% CI. Among 1380 CRC patients with available data, the VTE risk ( The use of the KS did not predict VTEs in a low-moderate thromboembolic risk population as CRC. These data did not support the use of KS to predict VTE during adjuvant chemotherapy, and suggest that other risk assessment models should be researched.

Sections du résumé

BACKGROUND BACKGROUND
The risk of venous thromboembolic events (VTE) during adjuvant chemotherapy for colorectal cancer (CRC) is unknown. We aim to evaluate if the Khorana score (KS) can predict this risk, and if it represents a prognostic factor for overall survival (OS) through a
METHODS METHODS
A logistic regression model was used to test the associations between the risk of VTE and the KS. The results are expressed as odds ratios (OR) with 95% confidence intervals (95% CI). To assess the effect of the KS on OS, multivariable analyses using Cox regression models were performed. The results are expressed as hazard ratios (HR) with 95% CI.
RESULTS RESULTS
Among 1380 CRC patients with available data, the VTE risk (
CONCLUSIONS CONCLUSIONS
The use of the KS did not predict VTEs in a low-moderate thromboembolic risk population as CRC. These data did not support the use of KS to predict VTE during adjuvant chemotherapy, and suggest that other risk assessment models should be researched.

Identifiants

pubmed: 32010236
doi: 10.1177/1758835919899850
pii: 10.1177_1758835919899850
pmc: PMC6974756
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1758835919899850

Commentaires et corrections

Type : ErratumIn

Informations de copyright

© The Author(s), 2020.

Déclaration de conflit d'intérêts

Conflict of interest statement: The authors declare that there is no conflict of interest.

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Auteurs

Sandro Barni (S)

Oncology Unit, Medical Science Department, ASST Bergamo Ovest, Treviglio (BG), Italy.

Gerardo Rosati (G)

Medical Oncology Unit, Ospedale San Carlo, Potenza, Italy.

Sara Lonardi (S)

Medical Oncology Unit 1, Istituto Oncologico Veneto-IRCCS, Padova, Italy.

Nicoletta Pella (N)

Medical Oncology Unit, Azienda Ospedaliero Universitaria Santa Maria della Misericordia, Udine, Italy.

Maria Banzi (M)

Medical Oncology Unit, Arcispedale Santa Maria Nuova-IRCCS, Reggio Emilia, Italy.

Maria G Zampino (MG)

Gastrointestinal Medical Oncology Unit and Neuroendocrine Tumors, Istituto Europeo di Oncologia-IRCCS, Milano, Italy.

Katia F Dotti (KF)

Medical Oncology Unit, Fondazione Istituto Nazionale Tumori-IRCCS, Milano, Italy.

Lorenza Rimassa (L)

Medical Oncology and Hematology Unit, Humanitas Cancer Center, Humanitas Clinical and Research Center, Rozzano (MI), Italy.

Paolo Marchetti (P)

Medical Oncology Unit, Sant'Andrea Hospital, Sapienza University of Rome and IDI-IRCCS, Roma, Italy.

Evaristo Maiello (E)

Medical Oncology Unit, Hospital Casa Sollievo della Sofferenza-IRCCS, San Giovanni Rotondo, Italy.

Fabrizio Artioli (F)

Medical Oncology Unit Ramazzini Hospital, Carpi (MO), Italy.

Daris Ferrari (D)

Medical Oncology Unit, Azienda Ospedaliera San Paolo, Milano, Italy.

Roberto Labianca (R)

Cancer Center ASST Papa Giovanni XXIII, Bergamo, Italy.

Paolo Bidoli (P)

Medical Oncology Unit San Gerardo dei Tintori Hospital, Monza, Italy.

Alberto Zaniboni (A)

Medical Oncology Unit, Fondazione Poliambulanza, Brescia, Italy.

Alberto Sobrero (A)

Medical Oncology Unit, IRCCS San Martino-IST, Genova, Italy.

Vincenzo Iaffaioli (V)

Abdominal Medical Oncology, National Cancer Institute, IRCCS Foundation Pascale, Napoli, Italy.

Sabino De Placido (S)

Department of Clinical Medicine and Surgery, Federico II University, Napoli, Italy.

Gian Luca Frassineti (GL)

Department of Medical Oncology, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori IRST, IRCCS, Meldola, Italy.

Andrea Ciarlo (A)

Medical Oncology Unit, Prato Hospital, Prato, Italy.

Angela Buonadonna (A)

Medical Oncology Unit Centro di Riferimento Oncologico Aviano-IRCCS, Aviano, Italy.

Nicola Silvestris (N)

Medical Oncology Unit Ospedale Oncologico 'Giovanni Paolo II' and Scientific Directorate-IRCCS, Bari, Italy.

Elena Piazza (E)

Medical Oncology Unit AOU Sacco Hospital, Milano, Italy.

Lorenzo Pavesi (L)

Medical Oncology Unit Fondazione Maugeri-IRCCS, Pavia, Italy.

Mauro Moroni (M)

Medical Oncology Unit AO San Carlo Borromeo, Milano, Italy.

Mario Clerico (M)

Medical Oncology Department ASL Biella, Biella, Italy.

Massimo Aglietta (M)

Candiolo Cancer Institute FPO-IRCCS, Candiolo, Italy, Department of Oncology, University of Torino, Torino, Italy.

Paolo Giordani (P)

Medical Oncology Unit AO Ospedali Riuniti Marche Nord, Pesaro, Italy.

Francesca Galli (F)

Laboratory of Methodology for Clinical Research, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy.

Fabio Galli (F)

Laboratory of Methodology for Clinical Research, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy.

Fausto Petrelli (F)

Oncology Unit, Medical Science Department, ASST Bergamo Ovest, Piazzale Ospedale 1, Treviglio (BG), 24047, Italy.

Classifications MeSH