Evidence map›Paper›PMID 41512230›Full record

ArticleJCO clinical cancer informatics2026

Novel Electronic Health Record-Based Data Commons for Pancreatic Cancer.

Kaleem S Ahmed, Clayton T Marcinak, Muhammad Maisam Ali, Sheriff M Issaka, Yonghe Yan, Gabriel McMahan, Thomas Callaci, Noelle K LoConte, Andrea Shiefelbein, Sharon Weber and 4 more

Abstract read
In one paragraph

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

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

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

14 authors.

Kaleem S AhmedDepartment of Surgery, University of Wisconsin-Madison, Madison, WI.ORCID 0000-0001-6798-5076
Clayton T MarcinakDepartment of Surgery, University of Wisconsin-Madison, Madison, WI.ORCID 0000-0001-9153-1218
Muhammad Maisam AliDepartment of Surgery, University of Wisconsin-Madison, Madison, WI.
Sheriff M IssakaDepartment of Surgery, University of Wisconsin-Madison, Madison, WI.
Yonghe YanClinical & Health Informatics Institute, University of Wisconsin-Madison, Madison, WI.
Gabriel McMahanDepartment of Informatics and Information Technology, University of Wisconsin-Madison, Madison, WI.ORCID 0000-0002-4395-6825
Thomas CallaciOffice of the Honest Broker, University of Wisconsin-Madison, Madison, WI.ORCID 0000-0001-8935-2253
Noelle K LoConteDepartment of Medicine, University of Wisconsin-Madison, Madison, WI.ORCID 0000-0002-3883-4153
Andrea ShiefelbeinMorgridge Institute for Research, Madison, WI.ORCID 0000-0001-5417-7635
Sharon WeberDepartment of Surgery, University of Wisconsin-Madison, Madison, WI.
Majid AfsharDepartment of Medicine, University of Wisconsin-Madison, Madison, WI.
Matthew M ChurpekDepartment of Medicine, University of Wisconsin-Madison, Madison, WI.
Jomol MathewDepartment of Informatics and Information Technology, University of Wisconsin-Madison, Madison, WI.
Syed Nabeel ZafarDepartment of Surgery, University of Wisconsin-Madison, Madison, WI.ORCID 0000-0003-3843-9687

Funding

UW COMPREHENSIVE CANCER CENTER SUPPORTP30CA014520 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI Justine Yang Bruce · 1985 to 2026
$142.6M
NCI NIH HHS P30 CA014520
6 · The paper itself

Abstract

purposeClinical research in pancreatic cancer (PC) has been limited because of a lack of granular data in national data sets. An electronic health record (EHR)-based data set specifically designed for PC has immense potential to advance research. This study describes the creation of an EHR-based data commons for patients with PC.

methodsWe generated an index cohort of adult patients at our institution diagnosed with PC (International Classification of Diseases for Oncology, codes C25.0-25.9) between January 1, 2010, and December 31, 2023. To develop the Pancreatic Cancer Data Commons (PCDC), we linked six data sources: (1) institutional EHR data, (2) cancer-specific data from the North American Association of Central Cancer Registries, (3) surgical outcomes from the National Surgical Quality Improvement Program, (4) community-level data from the American Community Survey, (5) national mortality data from Obituary.com, and (6) genomic data from the cBioPortal for Cancer Genomics. We evaluated the feasibility of using the Observational Medical Outcomes Partnership common data model. The data set is stored on a cloud-based, Health Insurance Portability and Accountability Act-secure, and National Institute of Standards and Technology-compliant server.

resultsThe PCDC currently includes data of 3,542 unique patients. The mean age at diagnosis is 66.6 ± 11.7 years; 53.3% is male, and 92.2% is White. Linkage to six national data sets increased the completeness of cancer-specific data from 31.3% to 71.6%. Most patients presented at stage IV (43.6%), followed by stage I (22.6%). As of the latest update, 1,074 (30.3%) patients were still alive.

conclusionThe PCDC is a centralized resource that solves a gap in PC research. The ability to securely link and analyze protected patient data is a strategic step toward enhancing clinical research and optimizing care for patients with PC. Our future work includes expanding the PCDC to multiple centers using common data models.

Indexed as

Electronic Health RecordsPancreatic NeoplasmsAgedFemaleHumansMaleRegistries

Identifiers

PMID41512230
PMCPMC12795310

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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.