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Racial, Ethnic, and Sex-based Disparities among High-risk Individuals Undergoing Pancreatic Cancer Surveillance

2023· article· en· W4378952102 on OpenAlex
Bryson W. Katona, Kelsey Klute, Randall E. Brand, Jessica N. Everett, James J. Farrell, Kieran Hawthorne, Vivek Kaul, Sonia S. Kupfer, Salvatore Paiella, Diane M. Simeone, Daniel A. Sussman, George Zogopoulos, Aimee L. Lucas, Fay Kastrinos, Yan Bi, Teresa A. Brentnall, Daniel C. Chung, Julie Earl, Srinivas Gaddam, Steve Gallinger, John J. Graff, William Greenhalf, Aaron J. Grossberg, Philip Hart, Gregory Idos, Joanne Jeter, James Lindberg, Andrew M. Lowy, Jennifer B. Permuth, Maria Raitses‐Gurevich, Kasmintan A. Schrader, Jens T. Siveke, Elena M. Stoffel, Marlies Vornhuelz, Raymond Wadlow

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCancer Prevention Research · 2023
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsMcGill University
FundersNational Cancer InstituteCook Medical
KeywordsMedicineEthnic groupHealth equityCancerPancreatic cancerInternal medicineFamily medicineDemographyPublic healthPathology

Abstract

fetched live from OpenAlex

Since its inception two years ago, the international, multicenter Pancreatic Cancer Early Detection (PRECEDE) Consortium has enrolled high-risk individuals (HRI) undergoing pancreatic ductal adenocarcinoma (PDAC) surveillance. Herein we aim to evaluate enrollment disparities in PRECEDE. Data on HRIs enrolled between May 2020 and March 2022 were collected, with HRIs defined as participants enrolled in PRECEDE meeting guideline-based criteria for PDAC surveillance. Of 1,273 HRIs enrolled, 1,113 were eligible for inclusion, with 47.2% meeting familial pancreatic cancer criteria without a known pathogenic variant (PV) and the remainder having a pathogenic variant in a PDAC-risk gene (CDKN2A, STK11, PRSS1, BRCA1, BRCA2, PALB2, ATM, MLH1, MSH2, MSH6, PMS2, or EPCAM). Study participants were predominantly from the United States (82.7%), the most common age range at enrollment was 60-69 years (37.4%), and a non-PDAC cancer was present in 32.4%. There were racial/ethnic- and sex-based disparities among enrolled subjects, as the majority of participants were female (65.9%) and self-reported white (87.7%), with only 2.9% having Hispanic ethnicity. While more than 97% of participants consented to utilize imaging data and biosamples for research, there was no difference in rate of consent based on race/ethnicity, sex, or age, thereby demonstrating uniform participation in research activities among all subgroups after enrollment. Ensuring that diversity of HRIs in PDAC surveillance programs mirrors the communities served by participating centers is important. Substantial racial/ethnic- and sex-based disparities persist among recently enrolled HRIs undergoing PDAC surveillance, and therefore reducing these disparities will be a major focus of the PRECEDE Consortium moving forward. PREVENTION RELEVANCE: Pancreatic cancer surveillance is critical to decreasing pancreatic cancer mortality; therefore, it is important that pancreatic cancer surveillance studies enroll diverse patients. We demonstrate that substantial racial/ethnic- and sex-based disparities exist amongst enrollment in the international PRECEDE consortium, highlighting the dire need for future efforts to reduce these disparities. See related Spotlight, p. 305.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.116
GPT teacher head0.460
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it