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Record W4391873259 · doi:10.1093/jcag/gwad061.107

A107 ANALYSIS OF THE EFFICACY IN TRANSITIONING FROM FOBT TO FIT FOR COLORECTAL CANCER SCREENING AT A SINGLE CENTRE IN ONTARIO

2024· article· en· W4391873259 on OpenAlexaffabout
Andrew Nguyen, G Porwal

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsCambridge Memorial Hospital
Fundersnot available
KeywordsColorectal cancerMedicineOncologyInternal medicineGynecologyCancer

Abstract

fetched live from OpenAlex

Abstract Background Colonoscopy is the gold standard for detecting colorectal cancer (CRC) and advanced lesions, but is an invasive and carries some risks, with limited availability and accessibility. Alternatively, the fecal occult blood test (FOBT) and fecal immunochemical test (FIT) are both non-invasive, cost-effective screening tests that can also be used to detect CRC, advanced lesions, and polyps, identifying individuals to be prioritized to undergo colonoscopy. FOBT screens for small amounts of blood in stool by detecting heme through a chemical reaction. FIT confirms the presence of blood in stool by using antibodies to detect hemoglobin. Prior to 2019, Ontario employed FOBT as the preferred method for CRC screening in eligible individuals. In early 2019, Ontario transitioned to FIT as the preferred screening test, due its established superior test performance for identifying patients with high risk lesions for colon cancer. Aims This single-centre retrospective study analyzed the change in efficacy of detecting advanced lesions, when transitioning from FOBT to FIT, as identified on subsequent colonoscopy Methods A retrospective chart review was conducted of approximately 1000 patients undergoing colonoscopy for FOBT or FIT at Cambridge Memorial Hospital, covering the period of transition from FOBT to FIT. Colonoscopies were performed by 10 endoscopists. Patients were stratified into 2 groups based on fecal test type, FOBT (N = 344) and FIT (N = 572). Overall and individual proportions of cancer, polyps, adenomas, advanced adenomas (AA), and sessile serrated adenomas (SSA) detection in the subsequent colonoscopies were calculated for both groups. The efficacy of both tests was then assessed using statistical analysis. Results In total, 344 patients were included for FOBT analysis and results included: cancer (5.52%), any polyp (56.69%), adenoma (43.6%), AA (20.64), and SSA (6.1%). In contrast, 572 patients were included for analysis of FIT group and results included: cancer (3.85%), any polyp (83.22%), adenoma (76.92%), AA (43.01), and SSA (12.94%). Cancer detection was similar in the 2 groups. There was significant improvement in polyp, adenoma, advanced adenoma, and sessile serrated adenoma detection with FIT compared to FOBT. This improvement was consistent in all endoscopists, but more pronounced in endoscopists with lower detection rates in FOBT cases. Conclusions The use of FIT as a screening stool test, as compared to FOBT, was associated with a significantly improved detection for polyps, adenomas, AA, and SSA, confirming greater accuracy and sensitivity of FIT as a screening tool. This result confirms the premise, at least at a single institution, that by switching to FIT, Ontario has improved colon cancer screening and prevention with more efficient and higher yield utilization of a limited and costly health care resource Funding Agencies None

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)0.001
metaresearch head score (Gemma)0.006
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 score0.148
Threshold uncertainty score0.297

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.018
GPT teacher head0.254
Teacher spread0.236 · 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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Citations1
Published2024
Admission routes2
Has abstractyes

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