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Abstract PR014: FIT for red flag signs and symptoms of early onset colorectal cancer: low value or viable diagnostic tool?

2025· article· en· W4417201463 on OpenAlexaboutno aff
Daniel Sabater Minarim, Kylie Morgan, Lin Liu, Matthew P. Banegas, Maria Elena Martinez, Samir Gupta, Joshua Demb

Bibliographic record

VenueClinical Cancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsnot available
Fundersnot available
KeywordsIncidence (geometry)Hazard ratioPopulationProportional hazards modelConfidence intervalCumulative incidenceCohortAnemia

Abstract

fetched live from OpenAlex

Abstract Purpose: Early-onset colorectal cancer (EOCRC) incidence is rising in a predominantly symptomatic population of young adults. Effective triage tools are needed to identify high-risk individuals in this relatively low incidence population. We examined fecal immunochemical test (FIT) use among adults ages <50 with red flag signs and symptoms for EOCRC and evaluated whether FIT use is predictive of EOCRC risk. Methods: Retrospective cohort study of US Veterans (ages 18-49) receiving Veterans Health Administration (VHA) care during 1999-2022 with a documented EOCRC red flag sign or symptom (abdominal distension, abdominal pain, anemia [non-specific and iron-deficiency], change in bowel habits, constipation, diarrhea, hematochezia, nausea/vomiting) based on International Classification of Diseases, 9th (ICD-9) or 10th (ICD-10) Revision codes, or lab results. The primary exposure was FIT uptake and result, documented via lab results, shown as a three-level variable (no FIT use, negative FIT or positive FIT). The primary outcome was EOCRC diagnosis, derived from linkages to the VA Oncology Domain and National Death Index. Covariates included age at symptom presentation, sex, race and ethnicity, and number of symptoms within 60 days of first symptom presentation. Participants entered the study at first symptom onset and were followed until the first of: incident or fatal EOCRC diagnosis, non-EOCRC-related death, 2 years follow-up, age 50 or December 31, 2022. We derived cumulative CRC incidence estimates using Kaplan-Meier estimation. Multivariable, mixed-effects Cox regression models were used to estimate adjusted hazard ratios (aHR) and 95% confidence intervals (CI) for CRC risk among those who received a FIT test. Results: Among 751,116 Veterans, 38,019 (5.1%) received a FIT. The most common symptoms yielding a FIT were abdominal pain (29.6%), anemia (20.4%), hematochezia (18.5%), and diarrhea (16.4%). Approximately 76% of patients who received a FIT had one symptom at presentation. Among 38,019 patients who received a FIT, 6,191 (16.3%) had a positive finding. Approximately 1,295 (21%) of 6,191 FIT-positive patients received a diagnostic colonoscopy compared to 46,693 (6.6%) of 713,097 non-FIT patients. After two years of follow-up, patients with a positive FIT had a 1.44% cumulative EOCRC incidence (95% CI: 1.12%-1.77%), compared to a 0.12% among those with a negative FIT (95% CI; 0.08%-0.16%) and 0.12% among those who did not receive a FIT (95% CI: 0.12%-0.13%). The findings correspond to an aHR for EOCRC of 12.81 (95% CI: 8.47-19.36) for FIT-positive patients compared to those with a negative FIT. Conclusions: Among adults ages 18-49 presenting with a red flag sign or symptom to VHA care, FIT use was low. However, a positive FIT result was linked to a substantially elevated EOCRC risk relative to a negative result. To address potential concerns about generalizability, future research should confirm whether systematic use of FIT as a clinical triage tool could help identify symptomatic adults at high EOCRC risk who need a diagnostic colonoscopy. Citation Format: Daniel Sabater Minarim, Kylie Morgan, Lin Liu, Matthew P. Banegas, Maria Elena Martinez, Samir Gupta, Josh Demb. FIT for red flag signs and symptoms of early onset colorectal cancer: low value or viable diagnostic tool? [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr PR014.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.136
GPT teacher head0.491
Teacher spread0.355 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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