Abstract 6239: Colposcopy referral rates in an organized cytology-based cervix screening program after receipt of multiple rounds of HPV-based screening in the FOCAL trial
Bibliographic record
Abstract
Abstract Purpose: Due to the increased sensitivity but reduced specificity of HPV testing compared to cytology to detect cervical lesions, a shift from cytology to HPV-based screening will initially raise population colposcopy referrals rates, which could put a strain on the healthcare system. However, it is unclear if this increase persists past the initial round of HPV screening or if rates will subsequently decrease due to earlier detection of precancer using HPV screening, which once treated may not reoccur. Methods: Participants of the HPV FOr CervicAL Cancer (FOCAL) randomized controlled trial (N = 25,223; 2008-2016) received up to two rounds of HPV-based cervix screening during the trial before returning to the cytology-based screening program in British Columbia, Canada (BC). After trial exit, participants were followed through the provincial screening program, which collects results from all screens received in BC, to detect any referral to colposcopy. A comparison cohort from the BC general screening population was created by selecting individuals who were eligible for FOCAL but not invited to participate and pulling their screening data from the provincial registry over the same time period. Post-trial colposcopy rates, calculated per-screen (not per participant), were calculated for the FOCAL population and comparison cohort overall and for those who received one round of HPV testing, those who received two rounds, those who received a negative result on their one round of testing, and those who received two negative results on their two rounds of testing. Results: The post-trial colposcopy referral rate in the overall FOCAL population was lower than in the comparison cohort. FOCAL had 180 referrals out of 30654 screens (5.9 per 1000 screens, 95%CI: 5.1-6.8), whereas the comparison cohort had 1765/177880 (9.9/1000, 95%CI: 9.5-10.4). The rates between those who had one versus two HPV tests were similar: one test: 99/17599 (5.6/1000, 95%CI: 4.6-6.8); two tests: 100/16945 (5.9/1000, 95%CI: 4.9-7.2). Rates were much lower among those who received negative results: one negative result: 55/15551 (3.5/1000, 95%CI: 2.7-4.6); two negative results: 40/12438 (3.2/1000, 95%CI: 2.4-4.4). Conclusions: After the first round of HPV-based cervix screening, colposcopy rates may decrease potentially below that seen in a cytology-based program. To avoid a surge in colposcopy referrals that could exceed health system capacity, the introduction of HPV-based screening should be done in waves, for example by inviting a new age group each year to HPV-based screening. Citation Format: Anna Gottschlich, Jennifer J. Anderson, Lovedeep Gondara, Marette Lee, Dirk van Niekerk, Laurie W. Smith, Darrel Cook, Lily Proctor, Joy Melnikow, Gavin Stuart, Ruth E. Martin, Stuart Peacock, Eduardo L. Franco, Mel Krajden, Gina Ogilvie. Colposcopy referral rates in an organized cytology-based cervix screening program after receipt of multiple rounds of HPV-based screening in the FOCAL trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6239.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| 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) | 0.010 | 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".