Model to predict major complications following liver resection for HCC in patients with metabolic syndrome.
Journal
Hepatology (Baltimore, Md.)
ISSN: 1527-3350
Titre abrégé: Hepatology
Pays: United States
ID NLM: 8302946
Informations de publication
Date de publication:
01 05 2023
01 05 2023
Historique:
received:
09
05
2022
accepted:
01
10
2022
pmc-release:
01
05
2024
medline:
20
4
2023
pubmed:
17
1
2023
entrez:
16
1
2023
Statut:
ppublish
Résumé
Metabolic syndrome (MS) is rapidly growing as risk factor for HCC. Liver resection for HCC in patients with MS is associated with increased postoperative risks. There are no data on factors associated with postoperative complications. The aim was to identify risk factors and develop and validate a model for postoperative major morbidity after liver resection for HCC in patients with MS, using a large multicentric Western cohort. The univariable logistic regression analysis was applied to select predictive factors for 90 days major morbidity. The model was built on the multivariable regression and presented as a nomogram. Performance was evaluated by internal validation through the bootstrap method. The predictive discrimination was assessed through the concordance index. A total of 1087 patients were gathered from 24 centers between 2001 and 2021. Four hundred and eighty-four patients (45.2%) were obese. Most liver resections were performed using an open approach (59.1%), and 743 (68.3%) underwent minor hepatectomies. Three hundred and seventy-six patients (34.6%) developed postoperative complications, with 13.8% major morbidity and 2.9% mortality rates. Seven hundred and thirteen patients had complete data and were included in the prediction model. The model identified obesity, diabetes, ischemic heart disease, portal hypertension, open approach, major hepatectomy, and changes in the nontumoral parenchyma as risk factors for major morbidity. The model demonstrated an AUC of 72.8% (95% CI: 67.2%-78.2%) ( https://childb.shinyapps.io/NomogramMajorMorbidity90days/ ). Patients undergoing liver resection for HCC and MS are at high risk of postoperative major complications and death. Careful patient selection, considering baseline characteristics, liver function, and type of surgery, is key to achieving optimal outcomes.
Sections du résumé
BACKGROUND
Metabolic syndrome (MS) is rapidly growing as risk factor for HCC. Liver resection for HCC in patients with MS is associated with increased postoperative risks. There are no data on factors associated with postoperative complications.
AIMS
The aim was to identify risk factors and develop and validate a model for postoperative major morbidity after liver resection for HCC in patients with MS, using a large multicentric Western cohort.
MATERIALS AND METHODS
The univariable logistic regression analysis was applied to select predictive factors for 90 days major morbidity. The model was built on the multivariable regression and presented as a nomogram. Performance was evaluated by internal validation through the bootstrap method. The predictive discrimination was assessed through the concordance index.
RESULTS
A total of 1087 patients were gathered from 24 centers between 2001 and 2021. Four hundred and eighty-four patients (45.2%) were obese. Most liver resections were performed using an open approach (59.1%), and 743 (68.3%) underwent minor hepatectomies. Three hundred and seventy-six patients (34.6%) developed postoperative complications, with 13.8% major morbidity and 2.9% mortality rates. Seven hundred and thirteen patients had complete data and were included in the prediction model. The model identified obesity, diabetes, ischemic heart disease, portal hypertension, open approach, major hepatectomy, and changes in the nontumoral parenchyma as risk factors for major morbidity. The model demonstrated an AUC of 72.8% (95% CI: 67.2%-78.2%) ( https://childb.shinyapps.io/NomogramMajorMorbidity90days/ ).
CONCLUSIONS
Patients undergoing liver resection for HCC and MS are at high risk of postoperative major complications and death. Careful patient selection, considering baseline characteristics, liver function, and type of surgery, is key to achieving optimal outcomes.
Identifiants
pubmed: 36646670
doi: 10.1097/HEP.0000000000000027
pii: 01515467-202305000-00012
pmc: PMC10121838
mid: NIHMS1868224
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
1527-1539Subventions
Organisme : NCI NIH HHS
ID : P30 CA008748
Pays : United States
Commentaires et corrections
Type : CommentIn
Informations de copyright
Copyright © 2023 American Association for the Study of Liver Diseases.
Références
J Am Coll Surg. 2019 Nov;229(5):467-478.e1
pubmed: 31398386
J Chronic Dis. 1987;40(5):373-83
pubmed: 3558716
J Clin Oncol. 2015 Feb 20;33(6):550-8
pubmed: 25512453
HPB (Oxford). 2013 Jan;15(1):78-84
pubmed: 23216782
J Physiol Pharmacol. 2013 Feb;64(1):3-9
pubmed: 23568965
Br J Surg. 2021 Mar 12;108(2):196-204
pubmed: 33711132
Hepatology. 2016 Mar;63(3):827-38
pubmed: 26599351
Hepatobiliary Surg Nutr. 2015 Dec;4(6):391-7
pubmed: 26734623
Lancet. 2010 Jan 16;375(9710):181-3
pubmed: 20109902
Eur J Surg Oncol. 2022 Jan;48(1):103-112
pubmed: 34325939
Surgery. 2011 May;149(5):680-8
pubmed: 21316725
J Hepatol. 2000;32(1 Suppl):141-56
pubmed: 10728801
Surgery. 2021 May;169(5):1054-1060
pubmed: 33358472
Liver Int. 2018 Feb;38(2):321-330
pubmed: 28736952
Liver Cancer. 2017 Jun;6(3):204-215
pubmed: 28626732
Br J Surg. 2013 Jan;100(1):113-21
pubmed: 23147992
Br J Surg. 2010 Sep;97(9):1331-9
pubmed: 20641066
J Gastrointest Surg. 2016 Jan;20(1):189-98; discussion 198
pubmed: 26553267
Hepatology. 2005 Jun;41(6):1313-21
pubmed: 15915461
Surgery. 2012 Aug;152(2):218-26
pubmed: 22828143
J Am Coll Cardiol. 2006 Mar 21;47(6):1093-100
pubmed: 16545636
World J Surg. 2018 Aug;42(8):2606-2616
pubmed: 29372372
J Hepatol. 2016 Jun;64(6):1388-402
pubmed: 27062661
Arch Surg. 2009 Jan;144(1):46-51
pubmed: 19153324
Hepatology. 2010 Jun;51(6):1972-8
pubmed: 20209604
Circulation. 2009 Oct 20;120(16):1640-5
pubmed: 19805654
JHEP Rep. 2020 Oct 08;3(1):100190
pubmed: 33294830
J Hepatol. 2015 Jul;63(1):93-101
pubmed: 25646890
Ann Surg. 2013 Jul;258(1):1-7
pubmed: 23728278
Ann Surg. 2012 Oct;256(4):624-33
pubmed: 22964732
J Gastrointest Surg. 2021 Oct;25(10):2545-2552
pubmed: 33547584
J Clin Epidemiol. 2016 Jan;69:245-7
pubmed: 25981519
J Hepatol. 2020 Jul;73(1):202-209
pubmed: 32278004
J Am Coll Surg. 2017 Nov;225(5):639-649
pubmed: 28838869
Hepatology. 2011 Aug;54(2):463-71
pubmed: 21538440
J Clin Transl Hepatol. 2020 Mar 28;8(1):76-86
pubmed: 32274348
JAMA Surg. 2020 Nov 1;155(11):e203336
pubmed: 32965483
Ann Surg. 2004 Aug;240(2):205-13
pubmed: 15273542
HPB (Oxford). 2011 Dec;13(12):846-59
pubmed: 22081919
J Gastrointest Surg. 2002 Jan-Feb;6(1):88-94
pubmed: 11986023
J Hepatol. 2018 Jul;69(1):182-236
pubmed: 29628281
Medicine (Baltimore). 2017 Jun;96(24):e7142
pubmed: 28614241
J Hepatol. 2020 Jan;72(1):75-84
pubmed: 31499131
Br J Cancer. 2013 Jan 15;108(1):222-8
pubmed: 23169288
J Gastrointest Surg. 2019 Apr;23(4):739-744
pubmed: 30430431
J Gastroenterol Hepatol. 2016 May;31(5):1031-6
pubmed: 26647219
Dis Colon Rectum. 2019 Jul;62(7):849-858
pubmed: 31188186
Acta Endocrinol (Buchar). 2020 Oct-Dec;16(4):470-478
pubmed: 34084239
J Hepatocell Carcinoma. 2015 Feb 23;2:19-27
pubmed: 27508191
J Gastrointest Surg. 2011 Aug;15(8):1450-8
pubmed: 21512848
Hepatology. 2010 May;51(5):1820-32
pubmed: 20432259
Nat Rev Clin Oncol. 2015 Apr;12(4):213-26
pubmed: 25601442
Ann Surg. 2016 Apr;263(4):761-77
pubmed: 26700223
Asian J Endosc Surg. 2011 Aug;4(3):143-6
pubmed: 22776279
Hepatology. 2011 Jul;54(1):344-53
pubmed: 21520200
Surgery. 2011 May;149(5):713-24
pubmed: 21236455
Stat Med. 1997 May 15;16(9):965-80
pubmed: 9160492
Nat Rev Dis Primers. 2021 Jan 21;7(1):6
pubmed: 33479224