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Record W2074899208 · doi:10.1097/ogx.0b013e3181e62ec1

The Role of Human Papillomavirus Testing in the Management of Women With Low-Grade Abnormalities: Multicentre Randomized Controlled Trial

2010· article· en· W2074899208 on OpenAlexaff
Seonaidh Cotton, Linda Sharp, Julian Little, Margaret Cruickshank, Rashmi Seth, Lisa Smart, I. D. Duncan, Kirsten Harrild, Keith Neal, Norman Waugh

Bibliographic record

VenueObstetrical & Gynecological Survey · 2010
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsColposcopyMedicineCervical intraepithelial neoplasiaRandomized controlled trialObstetricsGynecologyCervical screeningReferralCervical cancerInternal medicineFamily medicineCancer

Abstract

fetched live from OpenAlex

Cytology testing in the NHS Cervical Screening Programs in the United Kingdom has identified over a quarter of a million women with precancerous low-grade abnormalities (mild dyskaryosis or borderline nuclear abnormalities [BNA]). Some investigators have suggested that human papillomavirus (HPV) testing could help decide which of these women should be referred for colposcopy and which could safely be returned to routine recall. This multicenter randomized-controlled trial used data from a previous Trial Of Management of Borderline and Other Low-grade Abnormal smears Group (TOMBOLA) trial to determine whether an HPV test is useful among women with mild dyskaryosis or BNA in the choice between cytological surveillance and colposcopy, and after referral whether HPV testing is useful in choosing treatment (either immediate large loop excision of the transformation zone (LLETZ) or biopsy with selective recall. The study subjects were 4439 women, 20 to 59 years of age, with mild dyskaryosis or BNA at enrollment. HPV analysis was performed using the polymerase chain reaction assay with the GP5+/6+ general primer system. Both the study subjects and those involved in management were blinded to the HPV testing results. In the first of 2 randomizations, women were assigned to either cytological surveillance every 6 months or referral for immediate colposcopy. In the second randomization, women referred for colposcopy were assigned either to immediate LLETZ or biopsies with selective recall for LLETZ. Both randomizations were stratified for HPV status and age. In addition, the association between HPV status and the presence of cervical intraepithelial neoplasia (CIN) grade 2 or more severe disease (CIN2 or worse) was examined in women who underwent colposcopy. At the end of the 3-year follow-up, all women were invited for an exit examination, which included colposcopy. No significant interactions were found between management and HPV status, showing that HPV positivity among women with low-grade cytologic abnormalities at recruitment was not effective in the choice of immediate colposcopy over cytological surveillance (P = 0.76) or immediate LLETZ over biopsy and recall (P = 0.27). No difference was found between women with mild dyskaryosis and BNA in the sensitivity of a single HPV test in detection of CIN2 or worse, whereas specificity was higher in those with BNA (71.3%; 95% confidence interval [CI], 68.5%–74.1% vs. 46.9%; 95% CI, 42.2%–51.6%). With increasing age, the sensitivity decreased and the specificity increased. There was a high negative predictive value, especially among women with BNA (94.5%; 95% CI, 92.9%–96.0%). About 22% of women across all ages with CIN2 or worse were HPV negative. Conversely, 40% of HPV positive women did not have CIN. HPV was a more reliable predictor among women aged 40 or more compared with younger women. These findings indicate that a single HPV test may be useful in women over 40 years of age in determining which women with low-grade abnormal cytology should be referred for colposcopy, but may not be useful in women 40 years of age or less, or for determining the most effective management at colposcopy.

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)0.008
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.030
GPT teacher head0.316
Teacher spread0.286 · 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.

Study designRandomized trial
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

Citations1
Published2010
Admission routes1
Has abstractyes

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