ALPlat criterion for the resection of hepatocellular carcinoma based on a predictive model of posthepatectomy liver failure.


Journal

Surgery
ISSN: 1532-7361
Titre abrégé: Surgery
Pays: United States
ID NLM: 0417347

Informations de publication

Date de publication:
02 2020
Historique:
received: 21 06 2019
revised: 19 09 2019
accepted: 26 09 2019
pubmed: 16 11 2019
medline: 10 5 2020
entrez: 16 11 2019
Statut: ppublish

Résumé

The indocyanine green test is used widely to evaluate the risk of posthepatectomy liver failure for hepatocellular carcinoma. A more convenient and reliable scoring system is desired owing to limited accuracy and availability of the indocyanine green test. This study aimed to establish a new selection criterion for liver resection in HCC. We reviewed retrospectively 876 patients undergoing a partial hepatectomy for hepatocellular carcinoma between 2007 and 2015 in 8 affiliated hospitals. Posthepatectomy liver failure grades B and C were regarded as posthepatectomy liver failure. We identified the risk factors for posthepatectomy liver failure and established a predictive model based on a formula for the probability of posthepatectomy liver failure. External validation was performed in an additional cohort of 250 patients. Posthepatectomy liver failure occurred in 92 patients (11%). The area under the receiver operating characteristic curve for the prediction of posthepatectomy liver failure was 0.646 for the platelet count, 0.641 for albumin, 0.623 for the percentage of liver remnant, and 0.607 for the plasma disappearance rate of indocyanine green. Logistic regression analysis provided a formula for the probability of posthepatectomy liver failure consisting of platelet count, albumin, and liver remnant. We defined platelet count + 90 × albumin as the ALPlat index and established an ALPlat-based criterion for operative resection that secured the same risk assumed by the indocyanine green-based criterion (Makuuchi's criterion). This criterion exhibited a greater sensitivity and specificity than the indocyanine green-based criterion in the validation cohort. The ALPlat criterion is a simple and useful method to assess liver function and to make therapeutic decisions in patients with hepatocellular carcinoma.

Sections du résumé

BACKGROUND
The indocyanine green test is used widely to evaluate the risk of posthepatectomy liver failure for hepatocellular carcinoma. A more convenient and reliable scoring system is desired owing to limited accuracy and availability of the indocyanine green test. This study aimed to establish a new selection criterion for liver resection in HCC.
METHODS
We reviewed retrospectively 876 patients undergoing a partial hepatectomy for hepatocellular carcinoma between 2007 and 2015 in 8 affiliated hospitals. Posthepatectomy liver failure grades B and C were regarded as posthepatectomy liver failure. We identified the risk factors for posthepatectomy liver failure and established a predictive model based on a formula for the probability of posthepatectomy liver failure. External validation was performed in an additional cohort of 250 patients.
RESULTS
Posthepatectomy liver failure occurred in 92 patients (11%). The area under the receiver operating characteristic curve for the prediction of posthepatectomy liver failure was 0.646 for the platelet count, 0.641 for albumin, 0.623 for the percentage of liver remnant, and 0.607 for the plasma disappearance rate of indocyanine green. Logistic regression analysis provided a formula for the probability of posthepatectomy liver failure consisting of platelet count, albumin, and liver remnant. We defined platelet count + 90 × albumin as the ALPlat index and established an ALPlat-based criterion for operative resection that secured the same risk assumed by the indocyanine green-based criterion (Makuuchi's criterion). This criterion exhibited a greater sensitivity and specificity than the indocyanine green-based criterion in the validation cohort.
CONCLUSION
The ALPlat criterion is a simple and useful method to assess liver function and to make therapeutic decisions in patients with hepatocellular carcinoma.

Identifiants

pubmed: 31727326
pii: S0039-6060(19)30681-6
doi: 10.1016/j.surg.2019.09.021
pii:
doi:

Types de publication

Journal Article Validation Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

410-416

Commentaires et corrections

Type : CommentIn
Type : CommentIn

Informations de copyright

Copyright © 2019 Elsevier Inc. All rights reserved.

Auteurs

Gen Yamamoto (G)

Department of Surgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Kojiro Taura (K)

Department of Surgery, Kyoto University Graduate School of Medicine, Kyoto, Japan. Electronic address: ktaura@kuhp.kyoto-u.ac.jp.

Iwao Ikai (I)

Department of Surgery, National Hospital Organization Kyoto Medical Centre, Kyoto, Japan.

Takahisa Fujikawa (T)

Department of Surgery, Kokura Memorial Hospital, Kitakyushu, Japan.

Ryuta Nishitai (R)

Department of Surgery, Kyoto-Katsura Hospital, Kyoto, Japan.

Satoshi Kaihara (S)

Department of Surgery, Kobe City Medical Centre General Hospital, Kobe, Japan.

Masazumi Zaima (M)

Department of Surgery, Shiga General Hospital, Moriyama, Japan.

Hiroaki Terajima (H)

Department of Surgery, Tazuke Kofukai Medical Research Institute Kitano Hospital, Osaka, Japan.

Tsunehiro Yoshimura (T)

Department of Surgery, Tenriyorodusoudanjyo Hospital, Tenri, Japan.

Yukinori Koyama (Y)

Department of Surgery, Shimane Prefectural Central Hospital, Izumo, Japan.

Kazutaka Tanabe (K)

Department of Surgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Takahiro Nishio (T)

Department of Surgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Yukihiro Okuda (Y)

Department of Surgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Yoshinobu Ikeno (Y)

Department of Surgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Kenji Yoshino (K)

Department of Surgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Keita Fukuyama (K)

Department of Surgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Satoru Seo (S)

Department of Surgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Etsuro Hatano (E)

Department of Surgery, Hyogo College of Medicine, Nishinomiya, Japan.

Shinji Uemoto (S)

Department of Surgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.

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Classifications MeSH