Evidence map›Paper›PMID 42842045›Full record

ArticleCancer causes & control : CCC2026

Have we gotten better at diagnosing PDAC before it is too late?: Temporal trends in stage at diagnosis of pancreatic ductal adenocarcinoma in the United States.

Dina Hauptschein, Paul Kang, Surabhi Amar

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Article in Cancer causes & control : CCC, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Dina HauptscheinCreighton University Arizona Health Education Alliance, 3100 N. Central Ave., Phoenix, AZ, 85012, USA. dinahauptschein@creighton.edu.ORCID https://orcid.org/0009-0008-6618-6844
Paul KangCreighton University Arizona Health Education Alliance, 3100 N. Central Ave., Phoenix, AZ, 85012, USA.
Surabhi AmarCreighton University Arizona Health Education Alliance, 3100 N. Central Ave., Phoenix, AZ, 85012, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposePancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers in the United States, with most patients not being diagnosed until they present with symptomatic, advanced-stage disease. National trends in stage-specific PDAC incidence were analyzed to assess trends in stage-at-diagnosis over time and to evaluate whether advances in diagnosis and high-risk screening programs have helped shift detection towards earlier stages.

methodsA retrospective cohort study was conducted using the Surveillance, Epidemiology, and End Results (SEER) database. Patients diagnosed with PDAC between the years 2004 and 2023 were included. Age-adjusted incidence rates were calculated per 100,000 people. Trends were assessed using Joinpoint regression to estimate the average annual percent change (AAPC). Multivariable Negative Binomial regression was used to estimate incidence rate ratios (IRRs) with stage-specific cases, adjusting for age, sex, race/ethnicity, and calendar year.

resultsBetween the years 2004 and 2023, age-adjusted incidence rates of localized, regional, and distant-stage PDAC were 1.04, 1.26, and 4.94 per 100,000 population, respectively. Localized PDAC demonstrated the greatest increase over time, with an AAPC of 6.00% (95% CI: 4.96-7.49; p < 0.001), while distant-stage disease exhibited a small increase over time (AAPC 1.11%; 95% CI: 1.02-1.21; p < 0.001) and regional-stage disease did not change significantly (AAPC 0.27%; 95% CI: -1.18 to 1.92; p = 0.62). Localized-stage incidence accelerated further after approximately 2015, with APC increasing to 14.7% between 2015 and 2019. Similar localized-stage increases were observed across sex and racial/ethnic subgroups. In multivariable Negative Binomial regression, increasing age and Non-Hispanic Black race were associated with higher PDAC incidence, while female sex was associated with lower regional and distant incidence rates.

conclusionsThe findings suggest a stage shift toward increased diagnosis of localized PDAC over time. These trends may reflect improvements in imaging, surveillance of high-risk individuals, advances in endoscopic detection, and increasing diagnostic intensity, although rising underlying PDAC burden may also contribute. Further prospective studies are needed to determine whether these trends ultimately translate into meaningful improvements in survival outcomes.

Indexed as

Carcinoma, Pancreatic DuctalEarly Detection of CancerPancreatic NeoplasmsAgedFemaleHumansIncidenceMaleMiddle AgedNeoplasm StagingRetrospective StudiesSEER ProgramUnited StatesEarly detectionEpidemiology, and End Results (SEER)Incidence trendsLocalized diseasePancreatic ductal adenocarcinoma (PDAC)Surveillance

Identifiers

PMID42842045
PMCPMC13646018

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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.