Evidence map›Paper›PMID 42568708›Full record

ArticleResearch and practice in thrombosis and haemostasis2026

Temporal validation of the electronic health record cancer-associated thrombosis model in patients with low bleeding risk.

Jennifer La, Omid Jafari, Kaelyn Nannini, Nhan V Do, Mary T Brophy, Nathanael R Fillmore, Ang Li

Abstract readValidation Study
In one paragraph

Article in Research and practice in thrombosis and haemostasis, 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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0citing papers 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

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

7 authors.

Jennifer LaMassachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, Massachusetts, USA.
Omid JafariSection of Hematology-Oncology, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA.
Kaelyn NanniniMassachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, Massachusetts, USA.
Nhan V DoMassachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, Massachusetts, USA.
Mary T BrophyMassachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, Massachusetts, USA.
Nathanael R FillmoreMassachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, Massachusetts, USA.
Ang LiSection of Hematology-Oncology, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA.

Funding

AIM-AHEAD Coordinating Center - All Four CoresOT2OD032581 · OD · UNIVERSITY OF NORTH TEXAS HLTH SCI CTR · PI Paul Avillach, Bettina M. Beech · 2021 to 2026
$168.7M
Multi-modal dynamic risk prediction of thrombosis and bleeding in patients with cancerR01HL180402 · NHLBI · BAYLOR COLLEGE OF MEDICINE · PI Ang Li · 2025 to 2026
$1.4M
Epidemiology and Biomarkers in Transplant Associated Thrombotic Microangiopathy (TA-TMA): A Prospective Validation Cohort StudyK23HL159271 · NHLBI · BAYLOR COLLEGE OF MEDICINE · PI Ang Li · 2022 to 2026
$835k
NHLBI NIH HHS K23 HL159271NHLBI NIH HHS R01 HL180402NIH HHS OT2 OD032581
6 · The paper itself

Abstract

Background: The electronic health record cancer-associated thrombosis (EHR-CAT) model was derived to predict cancer-associated venous thromboembolism (VTE). Prior validations often relied on cancer registry data with reporting delays. Objectives: We aimed to perform an external temporal validation of the EHR-CAT model among patients at low risk of bleeding using contemporary Veterans Affairs electronic health record data. Methods: We conducted a retrospective cohort study in patients with active cancer who received systemic therapy within the national Veterans Affairs (VA) health care system from 2017 to 2024. The key inclusion criteria included: (1) having readily extractable data for EHR-CAT calculation without cancer registry data, (2) index date at first or subsequent lines of therapy, (3) exclusion of adjuvant endocrine monotherapy with low risk for VTE, and (4) application of anticoagulant clinical trial exclusion criteria to minimize bleeding risk. Patients from previously published studies were excluded. Systemic therapies were defined using the VA Corporate Data Warehouse, and one line was randomly selected. VTE outcomes were determined using validated VTE-Bidirectional Encoder Representations from Transformers natural language processing from clinical notes. Time-dependent C-statistic and calibration slope were assessed. Results: Among 65,341 patients with cancer receiving systemic therapy (42,865 first-line and 22,476 second-line or higher), median age was 71.9 years, and 95% were male. Most common cancers included prostate (16.1%), lung (14.8%), lymphoma (11.5%), and bladder (11.1%). The VTE incidence at 6 months was 5.4%. VTE was observed in 1.9%, 4.0%, 4.7%, 6.5%, 9.6%, and 12.3% of patients with EHR-CAT scores 0-, 1, 2, 3, 4, and 5+, respectively (C-statistic 0.67). Calibration slope was 0.876. Conclusion: The EHR-CAT model, when applied across different lines of therapy, demonstrated similar performance as in previous studies.

Indexed as

Electronic Health RecordsHemorrhageNeoplasmsVenous ThromboembolismAgedFemaleHumansMaleMiddle AgedReproducibility of ResultsRetrospective StudiesRisk AssessmentRisk FactorsTime FactorsUnited StatesUnited States Department of Veterans Affairsneoplasmsprediction algorithmsthromboemblismvalidation studyvenous thrombosis

Identifiers

PMID42568708
PMCPMC13448015

What Socratic holds

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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 Socratic graph.