Evidence map›Paper›PMID 37314474›Full record

ArticleEuropean radiology2023

Predicting symptomatic post-hepatectomy liver failure in patients with hepatocellular carcinoma: development and validation of a preoperative nomogram.

Haiyi Long, Chuan Peng, Hong Ding, Yun Zheng, Jianhua Zhou, Wei Chen, Xian Zhong, Yifan Shi, Yu Duan, Xiaohua Xie and 3 more

Abstract read
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In one paragraph

Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 4 pooled it
3.0field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 4 syntheses or guidelines pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Guideline
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  8. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 2 institutions in 1 country.

Haiyi LongDivision of Interventional Ultrasound, Department of Medical Ultrasonics, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhong Shan Road 2, Guangzhou, 510080, China.
Chuan PengDepartment of Ultrasonography, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China.
Hong DingDepartment of Ultrasound, Huashan Hospital, Fudan University. No. 12 Middle Urumqi Road, Shanghai, 200040, China.
Yun ZhengDepartment of Liver Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China.
Jianhua ZhouDepartment of Ultrasonography, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China.
Wei ChenDepartment of Pancreaticobiliary Surgery, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhong Shan Road 2, Guangzhou, 510080, China.
Xian ZhongDivision of Interventional Ultrasound, Department of Medical Ultrasonics, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhong Shan Road 2, Guangzhou, 510080, China.
Yifan ShiDivision of Interventional Ultrasound, Department of Medical Ultrasonics, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhong Shan Road 2, Guangzhou, 510080, China.
Yu DuanDivision of Interventional Ultrasound, Department of Medical Ultrasonics, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhong Shan Road 2, Guangzhou, 510080, China.
Xiaohua XieDivision of Interventional Ultrasound, Department of Medical Ultrasonics, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhong Shan Road 2, Guangzhou, 510080, China.
Ming KuangDivision of Interventional Ultrasound, Department of Medical Ultrasonics, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhong Shan Road 2, Guangzhou, 510080, China.
Xiaoyan Xie *Division of Interventional Ultrasound, Department of Medical Ultrasonics, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhong Shan Road 2, Guangzhou, 510080, China. xiexyan@mail.sysu.edu.cn.
Manxia Lin *Division of Interventional Ultrasound, Department of Medical Ultrasonics, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhong Shan Road 2, Guangzhou, 510080, China. linmxia@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-2969-0020
Sun Yat-sen University · CNFudan University · CN

Funding

Major Research Plan 92059201Natural Science Foundation of Guangdong Province 2021A1515012367Natural Science Foundation of Guangdong Province 2023A1515012464
6 · The paper itself

Abstract

objectiveTo develop and validate a nomogram based on liver stiffness (LS) for predicting symptomatic post-hepatectomy (PHLF) in patients with hepatocellular carcinoma (HCC).

methodsA total of 266 patients with HCC were enrolled prospectively from three tertiary referral hospitals from August 2018 to April 2021. All patients underwent preoperative laboratory examination to obtain parameters of liver function. Two-dimensional shear wave elastography (2D-SWE) was performed to measure LS. Three-dimensional virtual resection obtained the different volumes including future liver remnant (FLR). A nomogram was developed by using logistic regression and determined by receiver operating characteristic (ROC) curve analysis and calibration curve analysis, which was validated internally and externally.

resultsA nomogram was constructed with the following variables: FLR ratio (FLR of total liver volume), LS greater than 9.5 kPa, Child-Pugh grade, and the presence of clinically significant portal hypertension (CSPH). This nomogram enabled differentiation of symptomatic PHLF in the derivation cohort (area under curve [AUC], 0.915), internal fivefold cross-validation (mean AUC, 0.918), internal validation cohort (AUC, 0.876) and external validation cohort (AUC, 0.845). The nomogram also showed good calibration in the derivation, internal validation, and external validation cohorts (Hosmer-Lemeshow goodness-of-fit test, p = 0.641, p = 0.06, and p = 0.127, respectively). Accordingly, the safe limit of the FLR ratio was stratified using the nomogram.

conclusionAn elevated level of LS was associated with the occurrence of symptomatic PHLF in HCC. A preoperative nomogram integrating LS, clinical and volumetric features was useful in predicting postoperative outcomes in patients with HCC, which might help surgeons in the management of HCC resection. CLINICAL RELEVANCE STATEMENT: A serial of the safe limit of the future liver remnant was proposed by a preoperative nomogram for hepatocellular carcinoma, which might help surgeons in 'how much remnant is enough in liver resection'. KEY POINTS: • An elevated liver stiffness with the best cutoff value of 9.5 kPa was associated with the occurrence of symptomatic post-hepatectomy liver failure in hepatocellular carcinoma. • A nomogram based on both quality (Child-Pugh grade, liver stiffness, and portal hypertension) and quantity of future liver remnant was developed to predict symptomatic post-hepatectomy liver failure for HCC, which enabled good discrimination and calibration in both derivation and validation cohorts. • The safe limit of future liver remnant volume was stratified using the proposed nomogram, which might help surgeons in the management of HCC resection.

Indexed as

Carcinoma, HepatocellularHypertension, PortalLiver FailureLiver NeoplasmsHepatectomyHumansNomogramsProspective StudiesRetrospective StudiesFuture liver remnantHepatectomyHepatocellular carcinomaLiver failureLiver stiffness

Identifiers

PMID37314474
OpenAlexW4380577396

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.