Evidence map›Paper›PMID 34532819›Full record

ArticleAnnals of surgical oncology2021

Optimal Lymph Node Staging System in Evaluating Prognosis of Gallbladder Carcinoma: A Multi-institutional Study.

Chen Chen, Zhang Rui, Wu Yuhan, Zhang Yongjie, Qiu Yinghe, Yang Ning, Song Tianqiang, Lou Jianying, Li Jiangtao, Mao Xianhai and 5 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Annals of surgical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
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

12 citing papers in PubMed.

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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

15 authors.

Chen Chen *Department of Hepatobiliary Surgery, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Zhang Rui *Department of Hepatobiliary Surgery, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Wu YuhanDepartment of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, China.
Zhang YongjieDepartment of Biliary Surgery, Eastern Hepatobiliary Surgery Hospital, Affiliated to Naval Medical University, Shanghai, China.
Qiu YingheDepartment of Biliary Surgery, Eastern Hepatobiliary Surgery Hospital, Affiliated to Naval Medical University, Shanghai, China.
Yang NingDepartment of Biliary Surgery, Eastern Hepatobiliary Surgery Hospital, Affiliated to Naval Medical University, Shanghai, China.
Song TianqiangDepartment of Hepatobiliary Oncology, Tianjin Medical University Cancer Hospital, Tianjin, China.
Lou JianyingDepartment of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Li JiangtaoDepartment of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Mao XianhaiDepartment of Hepatobiliary Surgery, Hunan Provincial People's Hospital, Changsha, China.
Li ShengpingDepartment of Hepatobiliary Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Si ShubinDepartment of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, China.
Cai ZhiqiangDepartment of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, China.
Tang ZhaohuiDepartment of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China. tangzhaohui@yahoo.com.
Geng ZhiminDepartment of Hepatobiliary Surgery, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China. gengzhimin@mail.xjtu.edu.cn.

Funding

National Natural Science Foundation of China No. 62076194Shaanxi Key Research and Development Program No.2017ZDXM-SF-055, No.2017KW-060Shaanxi Natural Science Basic Research Program General Project No.2020SF-070The Multicenter Clinical Research Project of Shanghai Jiaotong University School of Medicine No.DLY201807
6 · The paper itself

Abstract

backgroundLymph node (LN) involvement is a critical prognostic factor in patients with gallbladder carcinoma (GBC). Controversy exists regarding optimal categorization of nodal metastasis status, including anatomical location of positive nodes (AJCC 7th N staging), number of metastatic lymph nodes (NMLN), log odds of metastatic LNs (LODDS), and lymph node ratio (LNR).

methodsPatients who underwent curative-intent resection for GBC from six Chinese tertiary hospitals between 2008 and 2013 were analyzed retrospectively. The relative discriminative abilities of the different LN staging systems were assessed by different models including the tree-augmented naïve Bayesian (TAN) model, Cox proportional hazards regression model, and binary logistic regression model.

resultsA total of 226 patients were involved in this cohort. Based on the TAN model and composite importance measures, the most important factor affecting the prognosis in the different LN staging systems was NMLN. Among the four TAN models which were built with 4 metastatic LN markers and baseline variables, the accuracy of the NMLN-based prognostic model was 88.15%, higher than 7th N staging (86.44%), LNR (87.34%), and LODDS (85.19%). The Cox model based on NMLN (C-index: 0.763, AIC: 1371.62) had a higher fitness than the others (7th N staging C-index: 0.756, AIC: 1375.51; LNR C-index: 0.759, AIC: 1378.82; LODDS C-index 0.748, AIC: 1390.99). The AUCs of different staging binary logistic regression models were NMLN (0.872), LNR (0.872), 7th N staging (0.869) and LODDS (0.856), respectively.

conclusionsNMLN was the optimal LN staging system in evaluating prognosis of GBC.

Indexed as

Gallbladder NeoplasmsBayes TheoremHumansLymphatic MetastasisLymph Node ExcisionLymph NodesNeoplasm StagingPrognosisRetrospective Studies

Identifiers

PMID34532819

What OpenQuestion holds

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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.