Evidence map›Paper›PMID 32588982›Full record

ArticleCancer medicine2020

Development and validation of a pretreatment nomogram to predict overall survival in gastric cancer.

Etsuro Bando, Xinge Ji, Michael W Kattan, Ho Seok Seo, Kyo Young Song, Cho-Hyun Park, Maria Bencivenga, Giovanni de Manzoni, Masanori Terashima

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 5 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

21 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  8. A prognostic nomogram to predict the cancer-specific survival of patients with initially diagnosed metastatic gastric cancer: a validation study in a Chinese cohort.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
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  14. A model established using marital status and other factors from the Surveillance, Epidemiology, and End Results database for early stage gastric cancer.Journal of investigative medicine : the official publication of the American Federation for Clinical Research · 2022
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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

9 authors.

Etsuro BandoDivision of Gastric Surgery, Shizuoka Cancer Center, Shizuoka, Japan.
Xinge JiDepartment of Quantitative Health Sciences, The Cleveland Clinic, Cleveland, OH, USA.
Michael W KattanDepartment of Quantitative Health Sciences, The Cleveland Clinic, Cleveland, OH, USA.ORCID 0000-0002-3840-4161
Ho Seok SeoDivision of Gastrointestinal Surgery, Department of Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Kyo Young SongDivision of Gastrointestinal Surgery, Department of Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Cho-Hyun ParkDivision of Gastrointestinal Surgery, Department of Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Maria BencivengaDivision of General and Upper Gastrointestinal Surgery, Department of Surgery, University of Verona, Verona, Italy.
Giovanni de ManzoniDivision of General and Upper Gastrointestinal Surgery, Department of Surgery, University of Verona, Verona, Italy.
Masanori TerashimaDivision of Gastric Surgery, Shizuoka Cancer Center, Shizuoka, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPretreatment clinical staging is essential to select therapy. However, there have been no published pretreatment gastric cancer nomograms constructed using pretreatment clinical prognostic factors, including in nonresection patients. We aimed to develop a new pretreatment gastric cancer nomogram for individualized prediction of overall survival (OS).

methodsThe nomogram was developed using data of 5231 Japanese gastric cancer patients, and it was created with a Cox regression model. Fifteen clinical variables, which were obtained at pretreatment, were collected and registered. Data of two independent cohorts of patients from Seoul St. Mary's Hospital (1001 patients), and the University of Verona (389 patients) formed the external validation cohorts. The model was validated internally and externally using measures of discrimination (Harrell's C-index), calibration, and decision curve analysis.

resultsThe developed nomogram showed good discrimination, with a C-index of 0.855; that of the American Joint Committee on Cancer (AJCC) clinical stage was 0.819. In the external validation procedure, the C-indexes were 0.856 (AJCC, 0.795) in the Seoul St. Mary's cohort and 0.714 (AJCC, 0.648) in the University of Verona cohort. The nomogram performed well in the calibration and decision curve analyses when applied to both the internal and external validation cohorts. A stage-specific subset survival analysis of the three risk groups calculated using the nomogram also showed the superiority of nomogram-prediction when compared to AJCC.

conclusionThis new pretreatment model accurately predicts OS in gastric cancer and can be used for patient counseling in clinical practice and stratification in clinical trials.

Indexed as

NomogramsAdultAgedAged, 80 and overAntigens, Tumor-Associated, CarbohydrateCalibrationCarcinoembryonic AntigenChi-Square DistributionDecision Support TechniquesFemaleHumansMaleMiddle AgedProportional Hazards ModelsSeverity of Illness IndexStomach NeoplasmsAntigens, Tumor-Associated, Carbohydratecarbohydrate antigen 199, humanCarcinoembryonic Antigenclinical staginggastric cancerpretreatment nomogramthe American Joint Committee on Cancer

Identifiers

PMID32588982
PMCPMC7433838

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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.