Evidence map›Paper›PMID 32112260›Full record

ArticleDigestive diseases and sciences2021

Validation of the Enriching New-Onset Diabetes for Pancreatic Cancer Model in a Diverse and Integrated Healthcare Setting.

Wansu Chen, Rebecca K Butler, Eva Lustigova, Suresh T Chari, Bechien U Wu

Registry-linked trialAbstract readValidation Study
PubMed Publisher
In one paragraph

Article in Digestive diseases and sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04662879 (A Prospective Study of Algorithm-based Screening in Patients With Glycemically Defined New Onset Diabetes to Evaluate Risk for and Earlier Detection of Pancreatic Ductal Adenocarcinoma; Early Detection Initiative), which is not on this map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 7% of its field
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.

NCT04662879 naactive not recruitingnot on this map

A Prospective Study of Algorithm-based Screening in Patients With Glycemically Defined New Onset Diabetes to Evaluate Risk for and Earlier Detection of Pancreatic Ductal Adenocarcinoma; Early Detection Initiative (EDI) for Pancreatic Cancer

TypeinterventionalSponsorPancreatic Cancer Action NetworkRan2021 to 2028Enrolled8,869ConditionsHyperglycemia, Diabetes Mellitus, Pancreas Ductal AdenocarcinomaArmsEnriching New-onset Diabetes for Pancreatic Cancer (ENDPAC) score, Abdominal imaging
3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.

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  16. Pancreatic Cancer: A Review of Risk Factors.Life (Basel, Switzerland) · 2024
    Review
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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 at 3 institutions in 1 country.

Wansu ChenDepartment of Research and Evaluation, Kaiser Permanente Southern California, 100 S Los Robles, 2nd Floor, Pasadena, CA, 91101, USA. Wansu.Chen@KP.org.
Rebecca K ButlerDepartment of Research and Evaluation, Kaiser Permanente Southern California, 100 S Los Robles, 2nd Floor, Pasadena, CA, 91101, USA.
Eva LustigovaDepartment of Research and Evaluation, Kaiser Permanente Southern California, 100 S Los Robles, 2nd Floor, Pasadena, CA, 91101, USA.
Suresh T ChariDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA.
Bechien U WuDepartment of Gastroenterology, Center for Pancreatic Care, Los Angeles Medical Center, Southern California Permanente Medical Group, Los Angeles, CA, USA.
Kaiser Permanente · USLos Angeles Medical Center · USMayo Clinic in Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe risk of pancreatic cancer is elevated among people with new-onset diabetes (NOD). Based on Rochester Epidemiology Project Data, the Enriching New-Onset Diabetes for Pancreatic Cancer (END-PAC) model was developed and validated.

aimsWe validated the END-PAC model in a cohort of patients with NOD using retrospectively collected data from a large integrated health maintenance organization.

methodsA retrospective cohort of patients between 50 and 84 years of age meeting the criteria for NOD in 2010-2014 was identified. Each patient was assigned a risk score (< 1: low risk; 1-2: intermediate risk; ≥ 3: high risk) based on the values of the predictors specified in the END-PAC model. Patients who developed pancreatic ductal adenocarcinoma (PDAC) within 3 years were identified using the Cancer Registry and California State Death files. Area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were estimated.

resultsOut of the 13,947 NOD patients who were assigned a risk score, 99 developed PDAC in 3 years (0.7%). Of the 3038 patients who had a high risk, 62 (2.0%) developed PDAC in 3 years. The risk increased to 3.0% in white patients with a high risk. The AUC was 0.75. At the 3+ threshold, the sensitivity, specificity, PPV, and NPV were 62.6%, 78.5%, 2.0%, and 99.7%, respectively.

conclusionsIt is critical that prediction models are validated before they are implemented in various populations and clinical settings. More efforts are needed to develop screening strategies most appropriate for patients with NOD in real-world settings.

Indexed as

AgedAged, 80 and overCohort StudiesDelivery of Health Care, IntegratedDiabetes MellitusFemaleFollow-Up StudiesGlycemic IndexHumansMaleMiddle AgedPancreatic NeoplasmsRegistriesRetrospective StudiesRisk FactorsEND-PAC modelNew-onset diabetesPancreatic cancerRisk predictionRisk scoreValidation

Identifiers

PMID32112260
OpenAlexW3006975488

What OpenQuestion holds

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Registered trials

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.