Evidence map›Paper›PMID 36849920›Full record

ArticleBMC cancer2023

An integrated strategy for deciding open versus laparoscopic hepatectomy for resectable primary liver cancer.

Yizhen Fu, Zhenyun Yang, Zili Hu, Zhoutian Yang, Jinbin Chen, Juncheng Wang, Zhongguo Zhou, Li Xu, Minshan Chen, Yaojun Zhang

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 98% 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Article
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

10 authors at 1 institution in 1 country.

Yizhen Fu *Sun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, P. R. China.
Zhenyun Yang *Sun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, P. R. China.
Zili HuSun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, P. R. China.
Zhoutian YangSun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, P. R. China.
Jinbin ChenSun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, P. R. China.
Juncheng WangSun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, P. R. China.
Zhongguo ZhouSun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, P. R. China.
Li XuSun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, P. R. China.
Minshan ChenSun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, P. R. China. chenmsh@sysucc.org.cn.
Yaojun ZhangSun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, P. R. China. zhangyuj@sysucc.org.cn.
Sun Yat-sen University · CN

Funding

National Natural Science Foundation of China No: 81874070
6 · The paper itself

Abstract

backgroundLaparoscopic liver resection (LLR) is now widely performed in treating primary liver cancer (PLC) and yields equal long-term and superior short-term outcomes to those of open liver resection (OLR). The optimal surgical approach for resectable PLC (rPLC) remains controversial. Herein, we aimed to develop a nomogram to determine the most appropriate resection approach for the individual patient.

methodsPatients with rPLC who underwent hepatectomy from January 2013 to December 2018 were reviewed. Prediction model for risky surgery during LLR was constructed.

resultsA total of 900 patients in the LLR cohort and 423 patients in the OLR cohort were included. A history of previous antitumor treatment, tumor diameter, tumor location and resection extent were independently associated with risky surgery of LLR. The nomogram which was constructed based on these risk factors demonstrated good accuracy in predicting risky surgery with a C index of 0.83 in the development cohort and of 0.76 in the validation cohort. Patients were stratified into high-, medium- or low-risk levels for receiving LLR if the calculated score was more than 0.8, between 0.2 and 0.8 or less than 0.2, respectively. High-risk patients who underwent LLR had more blood loss (441 ml to 417 ml) and a longer surgery time (183 min to 150 min) than those who received OLR.

conclusionsPatients classified into the high-risk level for LLR instead undergo OLR to reduce surgical risks and complications and patients classified into the low-risk level undergo LLR to maximize the advantages of minimally invasive surgery.

trial registrationThis study was registered in the Chinese Clinical Trial Registry (registration number: ChiCTR2100049446).

Indexed as

HepatectomyLaparoscopyLiver NeoplasmsHumansHepatocellular carcinomaLaparoscopic hepatectomyNomogramRiskSurgery

Identifiers

PMID36849920
PMCPMC9972775
OpenAlexW4322489955

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.