MétaCan
Menu
Back to cohort
Record W4206507311 · doi:10.3233/cbm-210366

Comparison of CINtec PLUS cytology and cobas HPV test for triaging Canadian patients with LSIL cytology referred to colposcopy: A two-year prospective study

2022· article· en· W4206507311 on OpenAlexaffabout

Bibliographic record

VenueCancer Biomarkers · 2022
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsHamilton Health SciencesMcMaster UniversityUniversity of British ColumbiaSt. Joseph’s Healthcare HamiltonSt. John’s Health Sciences CentreMcGill UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsColposcopyReferralCytologyProspective cohort studyPap testCervical screeningTest (biology)

Abstract

fetched live from OpenAlex

OBJECTIVES & METHODS: CINtec PLUS and cobas HPV tests were compared for triaging patients referred to colposcopy with a history of LSIL cytology in a 2-year prospective study. Cervical specimens were tested once at enrollment, and test positivity rates determined. Test performance was ascertained with cervical intraepithelial neoplasia grade 2 or worse (CIN2+) and CIN3 or worse (CIN3+) serving as clinical endpoints. RESULTS: In all ages, (19-76 years, n= 598), 44.3% tested CINtec PLUS positive vs. 55.4% HPV positive (p< 0.001). To detect CIN2+ (n= 99), CINtec PLUS was 81.8% sensitive vs. 93.9% for HPV testing (p= 0.009); genotype 16/18-specific sensitivity was 46.5%. Specificity was 52.9% vs. 36.6%, respectively (p< 0.001). In all ages, to detect CIN3+ (n= 44), sensitivity was 93.2% for both tests; genotype 16/18-specific sensitivity was 52.3%. Specificity was 48.4% for CINtec PLUS vs. 31.1% for HPV testing (p< 0.001). In patients < 30 years, CINtec was 91.7% sensitive vs 95.8% for HPV testing (p= 0.549). CONCLUSIONS: CINtec PLUS or cobas HPV test could serve as a predictor of CIN3+ with high sensitivity in patients referred to colposcopy with a history of LSIL regardless of age while significantly reducing the number of LSIL referral patients requiring further investigations and follow-up in colposcopy clinics.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.166
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.042
GPT teacher head0.397
Teacher spread0.354 · 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 teacher head, 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

Citations7
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueCancer BiomarkersSame topicCervical Cancer and HPV ResearchFrench-language works237,207