Evidence map›Paper›PMID 32543092›Full record

ArticleCancer medicine2020

A nomogram for prediction of stage III/IV gastric cancer outcome after surgery: A multicenter population-based study.

Zhiying Gao, Jing Ni, Hui Ding, Caiwang Yan, Chuanli Ren, Gang Li, Feng Pan, Guangfu Jin

Abstract readMulticenter Study
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 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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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

8 authors.

Zhiying GaoDepartment of Epidemiology and Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.ORCID 0000-0002-0252-3150
Jing NiDepartment of Epidemiology and Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Hui DingDepartment of Epidemiology and Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Caiwang YanDepartment of Epidemiology and Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Chuanli RenClinical Medical Testing Laboratory, Northern Jiangsu People's Hospital and Clinical Medical College of Yangzhou University, Yangzhou, China.ORCID 0000-0002-8386-3586
Gang LiDepartment of General Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Feng PanDepartment of Gastroenterology, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huai'an, China.
Guangfu JinDepartment of Epidemiology and Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.ORCID 0000-0003-0249-5337

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most patients with gastric cancer (GC) are first diagnosed at stage III-IV and surgery resection remains the primary therapeutic modality for these patients. However, clinical staging used for prediction of those patients provides limited information. We collected clinicopathological data and disease-progression information from 508 patients with stage III-IV GC at three Chinese hospitals and 1298 patients from the Surveillance, Epidemiology, and End Results database. Based on the stepwise multivariate regression model, we constructed a novel nomogram to predict overall survival (OS). The performance of discrimination for this model was measured using Harrell's concordance index (C-index) and receiver-operating characteristic curve (ROC), and was validated using calibration plots. Multivariate Cox regression analyses showed that tumor size, age at diagnosis, N stage, tumor grade, and distant metastases were outstanding independent prognostic factors of stage III-IV GC. We developed a nomogram based on these five prognostic predictors. In the training set, the C-index of the nomogram was 0.645 (95% CI: 0.611-0.679), which was higher than that of the American Joint Committee on Cancer TNM system alone (sixth TNM: 0.544; seventh TNM: 0.575; eighth TNM: 0.568). Similar results were observed in validation cohort. Moreover, calibration blots demonstrated good consistency between the actual and predicted OS probabilities. According to the nomogram, GC individuals could be classified into three groups (low-, middle-, and high-risk) (P < .001). Our nomogram complements the current staging system for prediction of individual prognosis with stage III-IV GC, and may be helpful for making individualized treatment decisions.

Indexed as

NomogramsFemaleHumansMaleMiddle AgedNeoplasm StagingPrognosisSEER ProgramStomach NeoplasmsTreatment OutcomenomogramprognosisSEER databasestomach neoplasm

Identifiers

PMID32543092
PMCPMC7402842

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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 OpenQuestion graph.