Evidence map›Paper›PMID 40956377›Full record

ArticleGastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association2025

Development and validation of a prognostic model incorporating patient reported outcomes for advanced gastric and esophageal carcinoma (AGOC) using individual patient data from two AGITG randomized clinical trials.

Sayeda Kamrun Naher, David Espinoza, Peter Grimison, Kohei Shitara, Nick Pavlakis, David Goldstein, Martin R Stockler, Rebecca Mercieca-Bebber, Katrin Marie Sjoquist

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association, 2025. 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

9 authors.

Sayeda Kamrun NaherNHMRC Clinical Trials Centre, the University of Sydney, Sydney, NSW, Australia. Sayeda.naher@health.nsw.gov.au.ORCID 0000-0002-9540-2760
David EspinozaNHMRC Clinical Trials Centre, the University of Sydney, Sydney, NSW, Australia.
Peter GrimisonChris O'Brien Lifehouse, Camperdown, NSW, Australia.
Kohei ShitaraGastrointestinal Oncology, Department of National Cancer Centre Hospital East, Chiba, Japan.
Nick PavlakisRoyal North Shore Hospital, St Leonards, NSW, Australia.
David GoldsteinPrince of Wales Hospital, University of New South Wales, Sydney, Australia.
Martin R StocklerNHMRC Clinical Trials Centre, the University of Sydney, Sydney, NSW, Australia.
Rebecca Mercieca-Bebber *NHMRC Clinical Trials Centre, the University of Sydney, Sydney, NSW, Australia.
Katrin Marie Sjoquist *NHMRC Clinical Trials Centre, the University of Sydney, Sydney, NSW, Australia.

Funding

National Health and Medical Research Council NHMRC Early Career Fellowship (APP1138100).National Health and Medical Research Council post graduate research scholarship
6 · The paper itself

Abstract

backgroundWe developed and validated a prognostic model incorporating readily accessible clinicopathological data and specific patient-reported outcomes (PROs).

methodsWe used data from two randomized trials comparing regorafenib to placebo: AGITG INTEGRATE IIa (n = 251) for model development and AGITG INTEGRATE (n = 152) for validation. Candidate variables were chosen from a systematic literature review and expert consultation. Significant prognostic factors in the multivariable model were identified using univariable Cox proportional hazards models with a p-value of < 0.1. Multivariable Cox proportional hazards models were developed using clinicopathological and PRO variables, with model selection refined using least absolute shrinkage and selection operator (LASSO). The model's discrimination and calibration were assessed using concordance indices (C-statistics) and calibration plots.

resultsUnivariable analysis identified 9 clinicopathological variables and 4 PRO domains that were prognostic for overall survival: body mass index (BMI), ECOG performance status, number of metastatic sites, liver involvement, treatment with regorafenib, neutrophil-lymphocyte ratio (NLR), LDH, albumin, CA 19-9, appetite loss, constipation, fatigue, and pain. The initial multivariable model (M1) incorporated geographic region (Asia vs non-Asia), performance status, number of metastatic sites, treatment with regorafenib, NLR, BMI, LDH, CA 19-9, and albumin. The preferred multivariable model (M2), including the abovementioned variables plus the 4 PROs, demonstrated superior discriminative ability with higher C-statistic values than models without PROs. Plots supported the model's calibration.

conclusionsIncorporating PROs into prognostic models for AGOC improved the accuracy of survival predictions. Further research is needed to validate its use in routine clinical practice.

Indexed as

Esophageal NeoplasmsPatient Reported Outcome MeasuresStomach NeoplasmsAgedFemaleHumansMaleMiddle AgedPhenylurea CompoundsPrognosisProportional Hazards ModelsPyridinesRandomized Controlled Trials as TopicSurvival RatePhenylurea CompoundsPyridinesregorafenibGastric cancerPatient reported outcomesPrognostic modelValidation

Identifiers

PMID40956377
PMCPMC12630199

What Socratic holds

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LicenceCC BY
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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 Socratic graph.