Impact of post-colposcopy management on women's long-term worries: results from the UK population-based TOMBOLA trial
Bibliographic record
Abstract
BACKGROUND: Effective cervical screening reduces cancer incidence and mortality. However, these benefits may be accompanied by some harms, potentially including, adverse psychological impacts. Studies suggest women may have concerns about various specific issues, such as cervical cancer. AIM: To compare worries about cervical cancer, future fertility, having sex, and general health between women managed by alternative policies at colposcopy. DESIGN: Multicentre individually-randomised controlled trial, nested within the National Health Service Cervical Screening Programmes. SETTING: UK. METHODS: 1515 women, aged 20-59 years, with low-grade cytology who attended colposcopy during February 2001-October 2002, were randomised to immediate loop excision or punch biopsies with recall for treatment if cervical intraepithelial neoplasia (CIN)2/3 was confirmed. Women completed questionnaires at recruitment and after 12, 18, 24 and 30 months. Outcomes were prevalence of worries at each time-point (point prevalence) and at any time-point during follow-up (12-30 months; cumulative prevalence). Primary analysis was by intention-to-treat (ITT); secondary per-protocol analysis compared groups according to management received among women with an abnormal transformation zone. RESULTS: Cumulative prevalence of worries was: cervical cancer 40%; having sex 26%, future fertility 24%, and general health 60%. In ITT analyses, there were no statistically significant differences between management arms in cumulative or point prevalence of any of the worries. In per-protocol analyses, between-group differences were significant only for future fertility; cumulative prevalence was highest in women who underwent punch biopsies and treatment. CONCLUSIONS: There is no difference in the prevalence of specific worries in women randomised to alternative post-colposcopy management policies. ISRCTN: 34841617.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".