Evidence map›Paper›PMID 34777583›Full record

ArticleTherapeutic advances in medical oncology2021

Comprehensive analysis of prognostic value of lymph node classifications in esophageal squamous cell carcinoma: a large real-world multicenter study.

Junmiao Wen, Jiayan Chen, Donglai Chen, Salma K Jabbour, Tao Xue, Xufeng Guo, Haitao Ma, Fei Ye, Yiming Mao, Jian Shu and 5 more

Open access · goldAbstract read
In one paragraph

Article in Therapeutic advances in medical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 14% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

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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 at 8 institutions in 2 countries.

Junmiao WenDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Jiayan ChenDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Donglai ChenDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
Salma K JabbourDepartment of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA.
Tao XueDepartment of Cardiothoracic Surgery, Zhongda Hospital Southeast University, Nanjing, China.
Xufeng GuoDepartment of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Haitao MaDepartment of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Fei YeDepartment of Thoracic Surgery, Affiliated Hai'an Hospital of Nantong University, Nantong, China.
Yiming MaoDepartment of Thoracic Surgery, Suzhou Kowloon Hospital, Shanghai Jiao Tong University School of Medicine, Suzhou, China.
Jian ShuDepartment of Cardiothoracic Surgery, The First People's Hospital of Taicang, Taicang, China.
Yangyang LiuDepartment of Vascular Surgery, Zhangjiagang First People's Hospital, Suzhou, China.
Xueguan LuDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Zhen ZhangDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Yongbing ChenDepartment of Thoracic Surgery, The Second Affiliated Hospital of Soochow University, No. 1055, Sanxiang Road, Suzhou 215000, China.
Min FanDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, No. 270 Dong-An Road, Shanghai 200032, China.ORCID https://orcid.org/0000-0002-7595-092X
Shanghai Medical College of Fudan University · CNSoochow University · CNShanghai Jiao Tong University · CNNantong University · CNRutgers, The State University of New Jersey · USTaizhou First People's Hospital · CNTongji University · CNZhongda Hospital Southeast University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe aim to assess the prognostic ability of three common lymph node-based staging algorithms, namely, the number of positive lymph nodes (pN), the lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) in patients with esophageal squamous cell carcinoma (ESCC).

methodsA total of 3902 ESCC patients treated at 10 Chinese institutions between 2003 and 2013 were included, along with 2465 patients from the Surveillance, Epidemiology, and End Results (SEER) database. The prognostic ability of the aforementioned algorithms was evaluated using time-dependent receiver operating characteristic (tdROC) curves,

resultsLODDS had better prognostic performance than pN or LNR in both continuous and stratified patterns. In the multicenter cohort, the multivariate analysis showed that the model based on LODDS classification was superior to the others in predictive accuracy and discriminatory capacity. Two nomograms integrating LODDS classification and other clinicopathological risk factors associated with OS as well as cancer-specific mortality were constructed and validated in the SEER database. Finally, a novel TN

conclusionAmong the three lymph node-based staging algorithms, LODDS demonstrated the highest discriminative capacity and prognostic accuracy for ESCC patients. The nomograms and novel TN

Indexed as

cancer stagingesophageal cancermetastasisprognostic biomarkersreal-world analysis

Identifiers

PMID34777583
PMCPMC8573486
OpenAlexW3214141713

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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.