Evidence map›Paper›PMID 32959672›Full record

ArticleCancer control : journal of the Moffitt Cancer Center

A Nomogram Based on Aspartate Aminotransferase/Alanine Aminotransferase (AST/ALT) Ratio to Predict Prognosis After Surgery in Gastric Cancer Patients.

Linfang Li, Qiuyao Zeng, Ning Xue, Miantao Wu, Yaqing Liang, Qingxia Xu, Lingmin Feng, Shan Xing, Shulin Chen

Open access · goldAbstract read
In one paragraph

Article in Cancer control : journal of the Moffitt Cancer Center. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 8% of its field
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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Linfang LiDepartment of Clinical Laboratory Medicine, 71067Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.ORCID https://orcid.org/0000-0002-2336-9885
Qiuyao ZengDepartment of Clinical Laboratory Medicine, 71067Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
Ning XueDepartment of Clinical Laboratory, Affiliated Tumor Hospital of Zhengzhou University, 377327Henan Tumor Hospital, Zhengzhou, China.
Miantao WuDepartment of Clinical Laboratory Medicine, 71067Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
Yaqing LiangDepartment of Clinical Laboratory Medicine, 71067Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
Qingxia XuDepartment of Clinical Laboratory, Affiliated Tumor Hospital of Zhengzhou University, 377327Henan Tumor Hospital, Zhengzhou, China.
Lingmin FengJia Yuan Medical Reagent Co Ltd, Guangzhou, China.
Shan XingDepartment of Clinical Laboratory Medicine, 71067Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
Shulin ChenDepartment of Clinical Laboratory Medicine, 71067Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.ORCID https://orcid.org/0000-0003-0816-2664
Sun Yat-sen University · CNZhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionUsing the TMN classification alone to predict survival in patients with gastric cancer has certain limitations, we conducted this study was to develop an effective nomogram based on aspartate aminotransferase/alanine aminotransferase (AST/ALT) ratio to predict overall survival (OS) in surgically treated gastric cancer.

methodswe retrospectively analyzed 190 cases of gastric cancer and used Cox regression analysis to identify the significant prognostic factors for OS in patients with resectable gastric cancer. The predictive accuracy of nomogram was assessed using a calibration plot, concordance index (C-index) and decision curve. This was then compared with a traditional TNM staging system. Based on the total points (TPS) by nomogram, we further divided patients into different risk groups.

resultsmultivariate analysis of the entire cohort revealed that independent risk factors for survival were age, clinical stage and AST/ALT ratio, which were entered then into the nomogram. The calibration curve for the probability of OS showed that the nomogram-based predictions were in good agreement with actual observations. Additionally, the C-index of the established nomogram for predicting OS had a superior discrimination power compared to the TNM staging system [0.794 (95% CI: 0.749-0.839) vs 0.730 (95% CI: 0.688-0.772),

conclusionthe established nomogram is associated with a more accurate prognostic prediction for individual patients with resectable gastric cancer.

Indexed as

NomogramsAdenocarcinomaAlanine TransaminaseAspartate AminotransferasesBiomarkers, TumorFemaleFollow-Up StudiesGastrectomyHumansLymphatic MetastasisMaleMiddle AgedPrognosisRetrospective StudiesStomach NeoplasmsSurvival RateAlanine TransaminaseAspartate AminotransferasesBiomarkers, TumorAST/ALT ratioclassifiergastric cancernomogramprognosis

Identifiers

PMID32959672
PMCPMC7513419
OpenAlexW3087318717

What OpenQuestion holds

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LicenceCC BY-NC
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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.