Evidence map›Paper›PMID 38726268›Full record

ArticleAmerican journal of cancer research2024

Nomogram models for predicting overall and cancer-specific survival in early-onset gastric cancer patients: a population-based cohort study.

Xiaoyan Wang, Xiaoman Niu, Fengbin Zhang, Jiaxiang Wu, Haotian Wu, Tongkun Li, Jiaxuan Yang, Ping'an Ding, Honghai Guo, Yuan Tian and 4 more

Abstract read
In one paragraph

Article in American journal of cancer research, 2024. 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
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.

  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

14 authors.

Xiaoyan WangThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.
Xiaoman NiuThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.
Fengbin ZhangThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.
Jiaxiang WuThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.
Haotian WuThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.
Tongkun LiThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.
Jiaxuan YangThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.
Ping'an DingThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.
Honghai GuoThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.
Yuan TianThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.
Peigang YangThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.
Zhidong ZhangThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.
Dong WangThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.
Qun ZhaoThird Department of Surgery, The Fourth Hospital of Hebei Medical University Shijiazhuang 050011, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To develop nomogram models for predicting the overall survival (OS) and cancer-specific survival (CSS) of early-onset gastric cancer (EOGC) patients. A total of 1077 EOGC patients from the Surveillance, Epidemiology, and End Results (SEER) database were included, and an additional 512 EOGC patients were recruited from the Fourth Hospital of Hebei Medical University, serving as an external test set. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic factors. Based on these factors, two nomogram models were established, and web-based calculators were developed. These models were validated using receiver operating characteristics (ROC) curve analysis, calibration curves, and decision curve analysis (DCA). Multivariate analysis identified gender, histological type, stage, N stage, tumor size, surgery, primary site, and lung metastasis as independent prognostic factors for OS and CSS in EOGC patients. Calibration curves and DCA curves demonstrated that the two constructed nomogram models exhibited good performance. These nomogram models demonstrated superior performance compared to the 7th edition of the AJCC tumor-node-metastasis (TNM) classification (internal validation set: 1-year OS: 0.831 vs 0.793, P = 0.072; 1-year CSS: 0.842 vs 0.816, P = 0.190; 3-year OS: 0.892 vs 0.857, P = 0.039; 3-year CSS: 0.887 vs 0.848, P = 0.018; 5-year OS: 0.906 vs 0.880, P = 0.133; 5-year CSS: 0.900 vs 0.876, P = 0.109). In conclusion, this study developed two nomogram models: one for predicting OS and the other for CSS of EOGC patients, offering valuable assistance to clinicians.

Indexed as

cancer-specific survivalEarly-onset gastric cancernomogramoverall survivalSEER

Identifiers

PMID38726268
PMCPMC11076259

What Socratic holds

Textmetadata
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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 Socratic graph.