Systemic inflammation response index (SIRI) as predictor of anastomotic leakage after total gastrectomy for gastric cancer.


Journal

Surgical oncology
ISSN: 1879-3320
Titre abrégé: Surg Oncol
Pays: Netherlands
ID NLM: 9208188

Informations de publication

Date de publication:
Aug 2022
Historique:
received: 25 01 2022
revised: 20 04 2022
accepted: 06 06 2022
pubmed: 19 6 2022
medline: 14 9 2022
entrez: 18 6 2022
Statut: ppublish

Résumé

Esophago-jejunostomy leakage (EJL) it the most dreaded septic complication after total gastrectomy for gastric cancer. Early detection and treatment of this complication may improve outcomes. Systemic Inflammation Response Index (SIRI) is a marker that reflects systemic inflammation. The SIRI was developed in a training cohort of 180 patients who underwent elective open total gastrectomy with esophago-jejunal anastomosis for gastric cancer from January 2009 to December 2013. To verify the prognostic value of SIRI score we recruited 192 patients treated from January 2014 to December 2021 as the validation cohort. The optimal cut-off value of SIRI was determined by receiver operating characteristic curve. Univariate and multivariate analysis was performed. An optimal cut-off point for the SIRI of 0.82 divided the patients into a low SIRI group and high SIRI group in the training cohort. Patients with a SIRI ≥0.82 was found to be significantly associated with EJL. Univariable analysis showed that NLR, PLR, MLR, SII, and SIRI were prognostic factors for EJL in the training cohort. In multivariable analysis, EJL high level of SIRI was identified as independent prognostic factor. Preoperative SIRI may be helpful in identifying patients at greater risk for developing EJL after total gastrectomy.

Sections du résumé

BACKGROUND BACKGROUND
Esophago-jejunostomy leakage (EJL) it the most dreaded septic complication after total gastrectomy for gastric cancer. Early detection and treatment of this complication may improve outcomes. Systemic Inflammation Response Index (SIRI) is a marker that reflects systemic inflammation.
METHODS METHODS
The SIRI was developed in a training cohort of 180 patients who underwent elective open total gastrectomy with esophago-jejunal anastomosis for gastric cancer from January 2009 to December 2013. To verify the prognostic value of SIRI score we recruited 192 patients treated from January 2014 to December 2021 as the validation cohort. The optimal cut-off value of SIRI was determined by receiver operating characteristic curve. Univariate and multivariate analysis was performed.
RESULTS RESULTS
An optimal cut-off point for the SIRI of 0.82 divided the patients into a low SIRI group and high SIRI group in the training cohort. Patients with a SIRI ≥0.82 was found to be significantly associated with EJL. Univariable analysis showed that NLR, PLR, MLR, SII, and SIRI were prognostic factors for EJL in the training cohort. In multivariable analysis, EJL high level of SIRI was identified as independent prognostic factor.
CONCLUSIONS CONCLUSIONS
Preoperative SIRI may be helpful in identifying patients at greater risk for developing EJL after total gastrectomy.

Identifiants

pubmed: 35716547
pii: S0960-7404(22)00085-8
doi: 10.1016/j.suronc.2022.101791
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

101791

Informations de copyright

Copyright © 2022 Elsevier Ltd. All rights reserved.

Auteurs

Mario Schietroma (M)

Department of Surgery, University of L'Aquila, San Salvatore Hospital, L'Aquila, Italy. Electronic address: mario.schietroma@univaq.it.

Lucia Romano (L)

Department of Surgery, University of L'Aquila, San Salvatore Hospital, L'Aquila, Italy. Electronic address: lucia.romano1989@libero.it.

Daniela Schiavi (D)

Department of Surgery, University of L'Aquila, San Salvatore Hospital, L'Aquila, Italy. Electronic address: schiavi.d@hotmail.it.

Beatrice Pessia (B)

Department of Surgery, University of L'Aquila, San Salvatore Hospital, L'Aquila, Italy. Electronic address: pessiabeatrice87@gmail.com.

Antonella Mattei (A)

Department of Life, Health &Environmental Sciences, University of L'Aquila, L'Aquila, Italy. Electronic address: antonella.mattei@univaq.it.

Fabiana Fiasca (F)

Department of Life, Health &Environmental Sciences, University of L'Aquila, L'Aquila, Italy. Electronic address: fabiana.fiasca@alice.it.

Francesco Carlei (F)

Department of Surgery, University of L'Aquila, San Salvatore Hospital, L'Aquila, Italy. Electronic address: francesco.carlei@univaq.it.

Antonio Giuliani (A)

Department of Surgery, University of L'Aquila, San Salvatore Hospital, L'Aquila, Italy. Electronic address: antonio.giuliani77@gmail.com.

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Classifications MeSH