The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Diabetes, Weight Change, and Pancreatic Cancer Risk
Open accessAbstract
Importance: Pancreatic cancer is the third-leading cause of cancer death in the United States; however, few high-risk groups have been identified to facilitate early diagnosis strategies. Objective: To evaluate the association of diabetes duration and recent weight change with subsequent risk of pancreatic cancer in the general population. Design, Setting, and Participants: This cohort study obtained data from female participants in the Nurses' Health Study and male participants in the Health Professionals Follow-Up Study, with repeated exposure assessments over 30 years. Incident cases of pancreatic cancer were identified from self-report or during follow-up of participant deaths. Deaths were ascertained through reports from the next of kin, the US Postal Service, or the National Death Index. Data collection was conducted from October 1, 2018, to December 31, 2018. Data analysis was performed from January 1, 2019, to June 30, 2019. Exposures: Duration of physician-diagnosed diabetes and recent weight change. Main Outcome and Measures: Hazard ratios (HRs) for subsequent development of pancreatic cancer. Results: Of the 112 818 women (with a mean [SD] age of 59.4 [11.7] years) and 46 207 men (with a mean [SD] age of 64.7 [10.8] years) included in the analysis, 1116 incident cases of pancreatic cancers were identified. Compared with participants with no diabetes, those with recent-onset diabetes had an age-adjusted HR for pancreatic cancer of 2.97 (95% CI, 2.31-3.82) and those with long-standing diabetes had an age-adjusted HR of 2.16 (95% CI, 1.78-2.60). Compared with those with no weight loss, participants who reported a 1- to 4-lb weight loss had an age-adjusted HR for pancreatic cancer of 1.25 (95% CI, 1.03-1.52), those with a 5- to 8-lb weight loss had an age-adjusted HR of 1.33 (95% CI, 1.06-1.66), and those with more than an 8-lb weight loss had an age-adjusted HR of 1.92 (95% CI, 1.58-2.32). Participants with recent-onset diabetes accompanied by weight loss of 1 to 8 lb (91 incident cases per 100 000 person-years [95% CI, 55-151]; HR, 3.61 [95% CI, 2.14-6.10]) or more than 8 lb (164 incident cases per 100 000 person-years [95% CI, 114-238]; HR, 6.75 [95% CI, 4.55-10.00]) had a substantially increased risk for pancreatic cancer compared with those with neither exposure (16 incident cases per 100 000 person-years; 95% CI, 14-17). Incidence rates were even higher among participants with recent-onset diabetes and weight loss with a body mass index of less than 25 before weight loss (400 incident cases per 100 000 person-years) or whose weight loss was not intentional judging from increased physical activity or healthier dietary choices (334 incident cases per 100 000 person-years). Conclusions and Relevance: This study demonstrates that recent-onset diabetes accompanied by weight loss is associated with a substantially increased risk for developing pancreatic cancer. Older age, previous healthy weight, and no intentional weight loss further elevate this risk.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“One such cohort is subjects with new-onset diabetes and a high score (≥3) on the Enriching New-Onset Diabetes for Pancreatic Cancer (END-PAC) model.4”
From Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis (2022) · cites this paper as [4]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Early detection offers survival benefit beyond lead time, as tumors are smaller in volume and more likely to be resectable when detected earlier.2-4”
From Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis (2022) · cites this paper as [4]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Siegel, R. L., Miller, K. D., & Jemal, A. (2020) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21590 · Cited by 20,444
Diagnosis and Classification of Diabetes Mellitus
American Diabetes Association (2010) · Diabetes Care · doi:10.2337/dc11-s062 · Cited by 14,094
Spencer, P. M., Cameron, J. L., & Lin, L. (2000) · Cited by 7,202
Diagnosis and classification of diabetes mellitus
American Diabetes Association (2010) · Diabetes Care · doi:10.2337/dc10-s062 · Cited by 5,491
(1996) · Institutional Research Information System University of Turin (University of Turin) · doi:10.1111/j · Cited by 5,486
FOLFIRINOX or Gemcitabine as Adjuvant Therapy for Pancreatic Cancer
Conroy, T., Hammel, P., Hebbar, M., Ben Abdelghani, M., Wei, A. C., Raoul, J.-L., Choné, L., Francois, E., Artru, P., Biagi, J. J., et al. (2018) · New England Journal of Medicine · doi:10.1056/nejmoa1809775 · Cited by 2,874
Ryan, D. P., Hong, T. S., & Bardeesy, N. (2014) · New England Journal of Medicine · doi:10.1056/nejmra1404198 · Cited by 2,348
Kamisawa, T., Wood, L. D., Itoi, T., & Takaori, K. (2016) · The Lancet · doi:10.1016/s0140-6736(16)00141-0 · Cited by 2,212
Prospective study of alcohol consumption and risk of coronary disease in men.
Rimm, E. B., Giovannucci, E. L., Willett, W. C., Colditz, G. A., Ascherio, A., Rosner, B., & Stampfer, M. J. (1991) · The Lancet · doi:10.1016/0140-6736(91)90542-w · Cited by 1,239
Self-citationPhysical activity and incidence of non-insulin-dependent diabetes mellitus in women
Manson, J. E., Stampfer, M. J., Colditz, G. A., Willett, W. C., Rosner, B., Hennekens, C. H., Speizer, F. E., Rimm, E. B., & Krolewski, A. S. (1991) · The Lancet · doi:10.1016/0140-6736(91)90664-b · Cited by 1,164
Self-citation
Cited by
Sorted by citations
Pancreatic cancer epidemiology: understanding the role of lifestyle and inherited risk factors
Klein, A. P. (2021) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-021-00457-x · Cited by 1,258
Advances in the epidemiology of pancreatic cancer: Trends, risk factors, screening, and prognosis
Cai, J., Chen, H., Lu, M., Zhang, Y., Lu, B., You, L., Zhang, T., Dai, M., & Zhao, Y. (2021) · Cancer Letters · doi:10.1016/j.canlet.2021.06.027 · Cited by 495
A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories
Placido, D., Yuan, B., Hjaltelin, J. X., Zheng, C., Haue, A. D., Chmura, P. J., Yuan, C., Kim, J., Umeton, R., Antell, G., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02332-5 · Cited by 349
Self-citationMukherjee, S., Patra, A., Khasawneh, H., Korfiatis, P., Rajamohan, N., Suman, G., Majumder, S., Panda, A., Johnson, M. P., Larson, N. B., et al. (2022) · Gastroenterology · doi:10.1053/j.gastro.2022.06.066 · Cited by 187
Multiplexed analysis of EV reveals specific biomarker composition with diagnostic impact
Spitzberg, J. D., Ferguson, S. W., Yang, K. S., Peterson, H. M., Carlson, J., & Weissleder, R. (2023) · Nature Communications · doi:10.1038/s41467-023-36932-z · Cited by 158
Metadata
- Authors
- Yuan, C., Babic, A., Khalaf, N., Nowak, J. A., Brais, L. K., Rubinson, D. A., Ng, K., Aguirre, A. J., Pandharipande, P. V., Fuchs, C. S., Giovannucci, E. L., Stampfer, M. J., Rosenthal, M. H., Sander, C., Kraft, P., & Wolpin, B. M.
- Affiliations
- Harvard University (US)
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts
- Michael E. DeBakey VA Medical Center (US)
- Brigham and Women's Hospital (US)
- Yale Cancer Center (US)
- Corresponding author
- Yuan, Chen
- ORCID
- Venue
- JAMA Oncology
- Publisher
- American Medical Association (AMA)
- Published
- 2020-10-08
- Volume
- 6
- Issue
- 10
- Pages
- e202948
- ISSN
- 2374-2437 (ISSN-L)
- PMC
- PMC7426876
- OpenAlex
- W3048739465
- Cited by
- 150
- References
- 40
- Citations by year
- 2026: 28 · 2025: 31 · 2024: 17 · 2023: 24 · 2022: 28 · 2021: 22
- FWCI
- 6.68
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA Oncology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute (K08CA218420, R01CA205406)
- Topics
- Health Sciences › Medicine › Oncology › Pancreatic and Hepatic Oncology Research
- Health Sciences › Medicine › Oncology › Cancer Risks and Factors
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolism, Diabetes, and Cancer
- Keywords
- pancreatic cancer risk, diabetes duration, weight loss, recent-onset diabetes, long-standing diabetes, diabetes and cancer association, cancer risk factors, prospective cohort, Nurses' Health Study, Health Professionals Follow-up Study, early cancer detection, obesity and cancer risk, cancer screening guidelines, cancer survivorship, cancer survivorship support services, survivorship care
- MeSH terms
- Adult, Aged, Aged, 80 and over, Female, Humans, Male, Middle Aged, Pancreatic Neoplasms, Cohort Studies, Weight Loss, Body Mass Index, Incidence, Diabetes Complications
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review