Evidence map›Paper›PMID 29775599›Full record

ArticleGastroenterology2018

Model to Determine Risk of Pancreatic Cancer in Patients With New-Onset Diabetes.

Ayush Sharma, Harika Kandlakunta, Sajan Jiv Singh Nagpal, Ziding Feng, William Hoos, Gloria M Petersen, Suresh T Chari

2 registry-linked trialsAbstract readValidation Study
In one paragraph

Article in Gastroenterology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 213 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
213citing papers in PubMed, 11 pooled it
10.8field-weighted citation impact, top 1% 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.

NCT05306028 phase2active not recruitingstarted 2022, after this paper: background citation

Administration of Metformin and Insulin to Pancreatic Cancer Related Diabetes Mellitus (Type 3c)

Ran2022Enrolled20Registered outcomes4Posted comparisons0ConditionsDiabete Mellitus, Pancretic CancerArmsMetformin or insulin treatment
PMID 25403204PMID 28114552PMID 19111249other papers from this trial
Open the trial in the graph
NCT04662879 naactive not recruitingnot on this mapstarted 2021, after this paper: background citation

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

213 citing papers in PubMed, 11 syntheses or guidelines pooled it, 359 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Diagnostic Risk Prediction Models for Upper Gastrointestinal Cancers: A Systematic Review.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
    Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Pooled it
  10. Pooled it
  11. Pooled it
  12. Trial
  13. Trial
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review

153 more citing papers are in PubMed but not listed here.

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 at 4 institutions in 1 country.

Ayush SharmaDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
Harika KandlakuntaDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
Sajan Jiv Singh NagpalDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
Ziding FengDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
William HoosPancreatic Cancer Action Network, Manhattan Beach, California.
Gloria M PetersenDepartment of Health Science Research, Mayo Clinic, Rochester, Minnesota.
Suresh T ChariDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota. Electronic address: chari.suresh@mayo.edu.
Mayo Clinic · USMayo Clinic in Florida · USPancreatic Cancer Action Network · USThe University of Texas MD Anderson Cancer Center · US

Funding

Consortium for the Study of Chronic Pancreatitis, Diabetes and Pancreatic Cancer: Coordinating and Data Management Center (CSCPDPC-CDMC)U01DK108328 · NIDDK · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Liang Li, Suyu Liu · 2015 to 2026
$32.8M
Rochester Epidemiology ProjectR01AG034676 · NIA · MAYO CLINIC ROCHESTER · PI ROCCA, WALTER A, ST SAUVER, JENNIFER LYNN · 2010 to 2019
$9.5M
The Exocrine and Endocrine Pancreas in Type 2 Diabetes, Pancreatitis and Cancer (Admin Supplement)U01DK108288 · NIDDK · MAYO CLINIC ROCHESTER · PI Santhi Swaroop Vege · 2015 to 2026
$5.9M
NIA NIH HHS R01 AG034676NIDDK NIH HHS U01 DK108288NIDDK NIH HHS U01 DK108328
6 · The paper itself

Abstract

BACKGROUND &

aimsOf patients with new-onset diabetes (NOD; based on glycemic status) older than 50 years, approximately 1% are diagnosed with pancreatic cancer (PC) within 3 years. We aimed to develop and validate a model to determine risk of PC in patients with NOD.

methodsWe retrospectively collected data from 4 independent and nonoverlapping cohorts of patients (N = 1,561) with NOD (based on glycemic status; data collected at date of diagnosis and 12 months previously) in the Rochester Epidemiology Project from January 1, 2000 through December 31, 2015 to create our model. The model weighed scores for 3 factors identified in the discovery cohort to be most strongly associated with PC (64 patients with PC and 192 with type 2 diabetes): change in weight, change in blood glucose, and age at onset of diabetes. We called our model Enriching New-Onset Diabetes for Pancreatic Cancer (ENDPAC). We validated the locked-down model and cutoff score in an independent population-based cohort of 1,096 patients with diabetes; of these, 9 patients (82%) had PC within 3 years of meeting the criteria for NOD.

resultsIn the discovery cohort, the END-PAC model identified patients who developed PC within 3 years of diabetes onset (area under receiver operating characteristic curve 0.87); a score of at least 3 identified patients who developed PC with 80% sensitivity and specificity. In the validation cohort, a score of at least 3 identified 7 of 9 patients with PC (78%) with 85% specificity; the prevalence of PC in patients with a score of at least 3 (3.6%) was 4.4-fold greater than in patients with NOD. A high END-PAC score in patients who did not have PC (false positives) was often due to such factors as recent steroid use or different malignancy. An ENDPAC score no higher than 0 (in 49% of patients) meant that patients had an extremely low risk for PC. An END-PAC score of at least 3 identified 75% of patients in the discovery cohort more than 6 months before a diagnosis of PC.

conclusionsBased on change in weight, change in blood glucose, and age at onset of diabetes, we developed and validated a model to determine risk of PC in patients with NOD based on glycemic status (END-PAC model). An independent prospective study is needed to further validate this model, which could contribute to early detection of PC.

Indexed as

Patient-Specific ModelingAgedAge FactorsBlood GlucoseBody WeightDiabetes Mellitus, Type 2FemaleHumansMaleMiddle AgedPancreatic NeoplasmsPrevalenceProspective StudiesRetrospective StudiesRisk AssessmentRisk FactorsBlood GlucoseBiomarkerEnriching New-Onset Diabetes for Pancreatic CancerPancreasScreening

Identifiers

PMID29775599
PMCPMC6120785
OpenAlexW2803190522

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.