Evidence map›Paper›PMID 42649380›Full record

ArticleBritish journal of cancer2026

Risk prediction model for brain metastasis risk among patients diagnosed with primary gastrointestinal cancers.

Marc Vincent N Barcelona, Kaushik Jagannath Kataki, Fadwa Abdel Rahman, Fabio Y Moraes, Barbara Ann Millar, Tatiana Conrad, Dana Keilty, Andrew Hope, Alexander Sun, Paul Kongkham and 4 more

Abstract read
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In one paragraph

Article in British journal of cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

14 authors.

Marc Vincent N BarcelonaRadiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada. marcvincentbarcelona1@gmail.com.ORCID http://orcid.org/0000-0002-1559-6447
Kaushik Jagannath KatakiRadiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Fadwa Abdel RahmanRadiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Fabio Y MoraesDepartment of Oncology, Kingston Health Sciences Centre, Kingston, ON, Canada.ORCID http://orcid.org/0000-0003-3407-9215
Barbara Ann MillarRadiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Tatiana ConradDepartment of Radiation Oncology, University of Toronto, Toronto, ON, Canada.
Dana KeiltyRadiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Andrew HopeRadiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Alexander SunRadiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Paul KongkhamDepartment of Neurosurgery, Princess Margaret Cancer Centre, University of Toronto, Toronto, ON, Canada.
Elena ElimovaDivision of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University of Toronto, Toronto, ON, Canada.
Yangqing DengDepartment of Biostatistics, University Health Network, Toronto, ON, Canada.ORCID http://orcid.org/0000-0001-6218-3437
David ShultzRadiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.ORCID http://orcid.org/0000-0001-8242-6555
Michael YanRadiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada. Michael.Yan@uhn.ca.ORCID http://orcid.org/0000-0002-8387-6563

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe risk of radiotherapy-treated brain metastasis (BrM) in gastrointestinal (GI) cancers is poorly defined. We aimed to determine its incidence and develop a clinically interpretable prediction model.

methodsPatients with GI cancers diagnosed between 2005-2020 were identified from our registry. Receipt of brain radiotherapy was used to define radiotherapy-treated BrM. Logistic regression was performed on a training cohort to identify BrM predictors, which were then used to construct a risk score, and validate performance in a held-out cohort. Model performance was assessed with receiver operating characteristic (ROC) analysis, calibration, Brier score, and Multiple imputation by chained equations (MICE) sensitivity analysis.

resultsAmong 14,863 eligible patients, the 15-year cumulative incidence of clinically treated BrM was 1.89%. Median OS following BrM was 3.7 months. Logistic regression was performed in 11,022 patients with complete data. In the complete-case training cohort (n = 7348), significant predictors included primary site, clinical stage, chemotherapy, and recurrence at presentation. The AUC was 0.80, with good calibration and Brier score 0.012. Medium- and high-risk groups had higher BrM risk in validation (HR 4.57 and 11.35, respectively).

conclusionsWe developed an internally validated prediction model for BrM in GI cancers. External validation is required.

Identifiers

PMID42649380

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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.