Evidence map›Paper›PMID 35301382›Full record

ArticleScientific reports2022

Development of web-based dynamic nomogram to predict survival in patients with gastric cancer: a population-based study.

Atefeh Talebi, Nasrin Borumandnia, Hassan Doosti, Somayeh Abbasi, Mohamad Amin Pourhoseingholi, Shahram Agah, Seidamir Pasha Tabaeian

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. SOX plus sintilimabWorld journal of gastrointestinal oncology · 2025
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4 · The record

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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

7 authors.

Atefeh TalebiColorectal Research Center, Iran University of Medical Sciences, Tehran, Iran.
Nasrin BorumandniaUrology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, 1666663111, Tehran, Iran. borumand.n@gmail.com.
Hassan DoostiDepartment of Mathematics and Statistics, Macquarie University, Sydney, Australia.
Somayeh AbbasiDepartment of Mathematics, Isfahan (khorasgan) Branch, Islamic Azad University, Isfahan, Iran.
Mohamad Amin PourhoseingholiGastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Shahram AgahInternal Medicine and Gastroenterology, Colorectal Research Center, Iran University of Medical Sciences, Tehran, Iran.
Seidamir Pasha TabaeianColorectal Research Center, Iran University of Medical Sciences, Tehran, Iran. aptabaiyan@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastric cancer (GC) is the fifth most frequent malignancy worldwide and the third leading cause of cancer-associated mortality. The study's goal was to construct a predictive model and nomograms to predict the survival of GC patients. This historical cohort study assessed 733 patients who underwent treatments for GC. The univariate and multivariable Cox proportional hazard (CPH) survival analyses were applied to identify the factors related to overall survival (OS). A dynamic nomogram was developed as a graphical representation of the CPH regression model. The internal validation of the nomogram was evaluated by Harrell's concordance index (C-index) and time-dependent AUC. The results of the multivariable Cox model revealed that the age of patients, body mass index (BMI), grade of tumor, and depth of tumor elevate the mortality hazard of gastric cancer patients (P < 0.05). The built nomogram had a discriminatory performance, with a C-index of 0.64 (CI 0.61, 0.67). We constructed and validated an original predictive nomogram for OS in patients with GC. Furthermore, nomograms may help predict the individual risk of OS in patients treated for GC.

Indexed as

NomogramsStomach NeoplasmsCohort StudiesHumansInternetNeoplasm StagingPrognosisRetrospective Studies

Identifiers

PMID35301382
PMCPMC8931071

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