Evidence map›Paper›PMID 34616522›Full record

ArticleWorld journal of gastrointestinal oncology2021

Prognostic value of modified Lauren classification in gastric cancer.

Fei-Long Ning, Nan-Nan Zhang, Jun Wang, Yi-Feng Jin, Hong-Guang Quan, Jun-Peng Pei, Yan Zhao, Xian-Tao Zeng, Masanobu Abe, Chun-Dong Zhang

Abstract read
In one paragraph

Article in World journal of gastrointestinal oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

10 authors.

Fei-Long NingDepartment of General Surgery, Xuzhou Hospital of Traditional Chinese Medicine, Xuzhou 221000, Jiangsu Province, China.
Nan-Nan ZhangState Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, The Fourth Military Medical University, Xi'an 710000, Shannxi Province, China.
Jun WangDepartment of General Surgery, Xuzhou Hospital of Traditional Chinese Medicine, Xuzhou 221000, Jiangsu Province, China.
Yi-Feng JinDepartment of General Surgery, Jiading Hospital of Traditional Chinese Medicine, Shanghai 201800, China.
Hong-Guang QuanDepartment of General Surgery, Xuzhou Hospital of Traditional Chinese Medicine, Xuzhou 221000, Jiangsu Province, China.
Jun-Peng PeiDepartment of Gastrointestinal Surgery, The Fourth Affiliated Hospital of China Medical University, Shenyang 110032, Liaoning Province, China.
Yan ZhaoDepartment of Stomach Surgery, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, Shenyang 110042, Liaoning Province, China.
Xian-Tao ZengCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, Hubei Province, China.
Masanobu AbeDivision for Health Service Promotion, The University of Tokyo, Tokyo 113-0033, Japan.
Chun-Dong ZhangDepartment of Gastrointestinal Surgery, The Fourth Affiliated Hospital of China Medical University, Shenyang 110032, Liaoning Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt remains controversial as to which pathological classification is most valuable in predicting the overall survival (OS) of patients with gastric cancer (GC).

aimTo assess the prognostic performances of three pathological classifications in GC and develop a novel prognostic nomogram for individually predicting OS.

methodsPatients were identified from the Surveillance, Epidemiology, and End Results program. Univariate and multivariate analyses were performed to identify the independent prognostic factors. Model discrimination and model fitting were evaluated by receiver operating characteristic curves and Akaike information criteria. Decision curve analysis was performed to assess clinical usefulness. The independent prognostic factors identified by multivariate analysis were further applied to develop a novel prognostic nomogram.

resultsA total of 2718 eligible GC patients were identified. The modified Lauren classification was identified as one of the independent prognostic factors for OS. It showed superior model discriminative ability and model-fitting performance over the other pathological classifications, and similar results were obtained in various patient settings. In addition, it showed superior net benefits over the Lauren classification and tumor differentiation grade in predicting 3- and 5-year OS. A novel prognostic nomogram incorporating the modified Lauren classification showed superior model discriminative ability, model-fitting performance, and net benefits over the American Joint Committee on Cancer 8

conclusionThe modified Lauren classification shows superior net benefits over the Lauren classification and tumor differentiation grade in predicting OS. A novel prognostic nomogram incorporating the modified Lauren classification shows good model discriminative ability, model-fitting performance, and net benefits.

Indexed as

Gastric cancerPathological classificationPrognostic modelSurvival outcomeTumor-node-metastasis classification

Identifiers

PMID34616522
PMCPMC8465445

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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.