Colposcopy referral rates post-introduction of primary screening with human papillomavirus testing: evidence from a large British Columbia cohort study
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».