Evidence map›Paper›PMID 42006299›Full record

ArticleiScience2026

Global welfare-based economic burden of gastric cancer and projections to 2050.

Hai Zhu, Qingyang Fang, Gang Wang, Xinyang He, Yiren He

Abstract read
In one paragraph

Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

5 authors.

Hai ZhuDepartment of Gastric Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China.
Qingyang FangDepartment of Gastric Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China.
Gang WangDepartment of General Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China.
Xinyang HeDepartment of Gastric Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China.
Yiren HeDepartment of Gastric Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastric cancer (GC) imposes substantial welfare losses that are rarely monetized. Using GC disability-adjusted life years (DALYs) from the Global Burden of Disease Study 2021 and GDP from the World Bank, we estimated the value of lost welfare (VLW) by monetizing DALYs based on a willingness-to-pay framework. Both undiscounted and discounted values were estimated, and trends were projected to 2050. In 2021, the global VLW from GC was Int$2,470.34 billion (undiscounted) and Int$1,681.55 billion (discounted), equivalent to 1.615% and 1.099% of GDP, respectively. East Asia contributed the largest VLW, with China bearing the highest national burden. High-middle-SDI regions bore the greatest absolute burden, whereas relative burden increasingly shifted toward low-SDI regions. Welfare losses rose sharply with age and occurred earlier in men than in women. Under current trends, global VLW is projected to increase by 58.41% by 2050, highlighting growing economic and equity challenges worldwide.

Indexed as

health sciencesmedical specialtymedicineoncologypublic health

Identifiers

PMID42006299
PMCPMC13084429

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.