Colposcopy referral rates post-introduction of primary screening with human papillomavirus testing: evidence from a large British Columbia cohort study
Bibliographic record
Abstract
Background: Shifting from cytology to human papillomavirus (HPV)-based cervical cancer screening will initially increase colposcopy referrals. The anticipated impact on health systems has been raised as a concern for implementation. It is unclear if the higher rate of colposcopy referrals is sustained after initial HPV-based screens or reverts to new lower baselines due to earlier detection and treatment of precancer. This study aimed to investigate long-term rates of colposcopy referrals after participation in HPV-based screening. Methods: Participants of HPV for Cervical Cancer Screening trial (HPV FOCAL) received one (HPV1, N = 6204) or two (HPV2, N = 9540) HPV-based screens. After exit, they returned to British Columbia's (BC) cytology screening program. A comparison cohort from the BC screening population (BCS, N = 1,140,745) was identified, mirroring trial inclusion criteria. All participants were followed for 10-14 years through the provincial screening registry. Colposcopy referral rates per 1000 screens were calculated for each group. Trial colposcopy referrals for HPV1 and HPV2 were calculated under two referral scenarios: (1) all HPV positive referred to colposcopy; (2) cytology triage with ASCUS or greater referred to colposcopy. Colposcopy referrals from post-trial screens in HPV1 an HPV2 and all screens in BCS were based on actual recommendations from the screening program. A multivariable flexible survival regression model compared hazard ratios (HR) throughout follow-up. Findings: Scenario 2 referral rates were higher during initial HPV screen(s) vs cytology screen (HPV1: 28 per 1000 screens (95% CI: 24, 33), HPV2: 32 per 1000 screens (95% CI: 29, 36), BCS: 8 per 1000 screens (95% CI: 8.9)). However, post-trial rates in HPV1 and HPV2 were significantly lower than in BCS. Cumulative rates in HPV1 and HPV2 approached the cumulative rate in BCS 11-12 years after HPV-based screening (HPV1: 11 per 1000 screens (95% CI: 10, 12), HPV2: 16 per 1000 screens (95% CI: 15-17), BCS: 11 per 1000 screens (95% CI: 10, 11)). Adjusted models demonstrated reductions in referral rates in HPV1 (HR = 0.6, 95% CI: 0.5, 0.7) and HPV2 (HR = 0.7, 95% CI: 0.6, 0.8) relative to BCS by 54 and 72 months post-final HPV screen respectively. Interpretation: Reduced colposcopy referral rates were observed after initial rounds of HPV-based screening. After initial HPV screening, referral rates to colposcopy after cytology triage were below the current rates seen in a centralized cytology program after approximately four years. Any expected increase in referrals at initiation of HPV-based screening could be countered by staged program implementation. Funding: This work was supported by the National Institutes of Health (R01 CA221918), Michael Smith Health Research BC (RT-2021-1595), and the Canadian Institutes of Health Research (MCT82072).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".