Evidence map›Paper›PMID 32754227›Full record

ArticleTherapeutic advances in medical oncology2020

A cohort study and meta-analysis of the evidence for consideration of Lauren subtype when prescribing adjuvant or palliative chemotherapy for gastric cancer.

Kunning Wang, Enxiao Li, Rita A Busuttil, Joseph C Kong, Sharon Pattison, Joseph J Y Sung, Jun Yu, Emad M El-Omar, Julie A Simpson, Alex Boussioutas

Open access · goldAbstract read
In one paragraph

Article in Therapeutic advances in medical oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.8field-weighted citation impact, top 12% 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, 20 citations in OpenAlex.

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  8. Deep learning-based subtyping of gastric cancer histology predicts clinical outcome: a multi-institutional retrospective study.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2023
    Article
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  13. The dawn of precision medicine in diffuse-type gastric cancer.Therapeutic advances in medical oncology · 2022
    Review
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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

10 authors at 6 institutions in 4 countries.

Kunning WangDepartment of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, P. R. China.
Enxiao LiDepartment of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, P. R. China.
Rita A BusuttilSir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Victoria, Australia.
Joseph C KongSir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Victoria, Australia.
Sharon PattisonDepartment of Medicine, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.ORCID https://orcid.org/0000-0003-2188-3423
Joseph J Y SungDepartment of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, Li Ka Shing Institute of Health Sciences, CUHK Shenzhen Research Institute, The Chinese University of Hong Kong, Hong Kong SAR, China.
Jun YuDepartment of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, Li Ka Shing Institute of Health Sciences, CUHK Shenzhen Research Institute, The Chinese University of Hong Kong, Hong Kong SAR, China.
Emad M El-OmarDepartment of Medicine, St George & Sutherland Clinical School, University of New South Wales, Sydney, NSW, Australia.
Julie A SimpsonCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
Alex BoussioutasSir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Victoria, Australia.ORCID https://orcid.org/0000-0002-8109-6897
The University of Melbourne · AUChinese University of Hong Kong · HKFirst Affiliated Hospital of Xi'an Jiaotong University · CNSutherland Hospital · AUThe Royal Melbourne Hospital · AUUniversity of Otago · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe association between the survival or efficacy of chemotherapy and the Lauren subtype of gastric cancer (GC) remains unclear. We aimed to clarify whether patients with different Lauren subtypes have different survival after treatment with systemic chemotherapy: intestinal gastric cancer (IGC) patients survived better than patients with mixed type gastric cancer (MGC) or diffuse gastric cancer (DGC) after treatment with systemic chemotherapy. PATIENTS &

methodsRelevant studies for the meta-analysis were identified through searching Pubmed, Embase, Cochrane and Ovid up to March 2020. We also included our own prospectively collected cohort of patients that were followed over a 10-year period. Sub-group and sensitivity analyses were also performed.

resultsIn our prospective cohort, the overall survival (OS) of IGC patients receiving systemic chemotherapy (chemoIGC) [median OS 5.01 years, interquartile range (IQR) 2.63-6.71] was significantly higher than that of DGC patients receiving the same chemotherapy (chemoDGC) (median OS 1.33 years, IQR 0.78-3.33,

conclusionOur results support the consideration of Lauren subtype when prescribing systemic chemotherapy for GC, particularly for MGC or DGC, which may not benefit from chemotherapy. Lauren classification should be considered to stratify chemotherapy regimens to GC patients in future clinical trials, with particular relevance to MGC or DGC, which is more difficult to treat with current regimens.

Indexed as

chemotherapygastric cancerLauren subtypemeta-analysissurvival

Identifiers

PMID32754227
PMCPMC7378722
OpenAlexW3044045922

What OpenQuestion holds

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LicenceCC BY-NC
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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.