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Record W2794129241 · doi:10.1093/jcag/gwy008.245

A244 THE FECAL IMMUNOCHEMICAL TEST (FIT): SELECTED ASPECTS REGARDING ITS EFFECTIVENESS FOR COLORECTAL CANCER SCREENING IN QUEBEC CITY.

2018· article· en· W2794129241 on OpenAlexaffabout
Marc‐André Caron, G Lamarre, Philippe Grégoire, David Simonyan, N Laflamme

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsCentre hospitalier universitaire de QuébecUniversité Laval
Fundersnot available
KeywordsMedicineColorectal cancerColonoscopyFecal occult bloodTest (biology)AsymptomaticInternal medicineColorectal cancer screeningMedical prescriptionCancerFamily medicineNursing

Abstract

fetched live from OpenAlex

The FIT has been used in Quebec since September 2013 in replacement for guaiac fecal occult blood test (gFOBT) as part of the province’s colorectal cancer (CRC) screening program (PQDCCR). Its value has already been ascertained elsewhere in Canada and worldwide. For instance, one Canadian study including the data from five provinces obtained a positive predictive value (PPV) of 4.3% for the detection of CRC in average-risk patients. The performance of the FIT needs to be assessed in our province, especially as we use a higher positivity threshold value than in most screening programs. Moreover, there seems to remain a gap between formal indications for a FIT and its actual use in clinical practice. Thus, this research aims to evaluate some aspects related to the effectiveness of the FIT in our setting and its application by prescribers. The primary aim of the study was to determine the PPV for the detection of CRC, advanced adenomas (AA), and significant colorectal lesions (SCL, i.e. CRC and AA combined). The secondary aims of the study were to (i) examine the influence of specific variables on the test’s PPV, such as age, sex, presence of alarm features, and adequacy of the prescription of a FIT, and (ii) identify the FITs that were unjustified, i.e. that were requested for other than asymptomatic, average CRC risk patients. Using the software Endoworks® (Olympus®), in which all colonoscopy reports are saved, we identified retrospectively all colonoscopies conducted for a positive FIT in 2014 at two reference centers of the PQDCCR in Quebec City. We then reviewed manually every corresponding medical record to complete data collection. 559 colonoscopies were reviewed. We obtained PPVs of 6.8% and 46.9% for the detection of CRC and AA, respectively. The PPV for the detection of SCL was 56.1% among men and 45.0% among women (OR 1.56, 95% CI 1.11 – 2.20), whereas it was 59.5% among justified FITs and 43.9% among unwarranted ones (OR 1.88, 95% CI 1.34 – 2.63). Results for AA detection were similar to those of SCL. The PPV for the detection of CRC was 25.0% in the presence of an unexplained iron deficiency anemia and 6.5% when anemia was absent (p=0.0058). In 49.9% of cases, the prescription of a FIT was inappropriate, most often due to macroscopic rectal bleeding. The PPV of the FIT for detecting CRC is higher in our setting than in the rest of Canada, but the clinical significance of this difference is unclear. The test holds a better PPV for detecting SCL and AA among men, and when it is indicated according to PQDCCR recommendations. Unexplained iron deficiency anemia is associated with a higher rate of CRC detection. Half of the positive FITs were not indicated initially. Therefore, physicians should be made more aware of the appropriate use of the FIT. 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)0.002
metaresearch head score (Gemma)0.012
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 score0.074
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.016
GPT teacher head0.288
Teacher spread0.271 · 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".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

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