P3.189 Recurrence of human papillomavirus external genital wart infection among high-risk adults in montrÉal, quÉbec
Bibliographic record
Abstract
Introduction External genital warts (EGW) are associated with high psychosocial burden and health care costs, may be difficult to treat, and recur frequently. However, the incidence of recurrent EGW is not well characterised; this is especially true in a post-human papilloma virus (HPV) vaccination era. The objectives of this study were to assess the incidence of subsequent HPV-related EGW in high-risk male and female adults, as well as ascertain patient profile and disease characteristics, in a real-world Canadian clinical setting. Methods A retrospective chart review study was conducted at Clinique médicale l’Actuel, a sexual health clinic in Montréal, Québec, Canada. Eligible patients were 18–45 years of age with a first diagnosis of EGW between July 1, 2006 and June 30, 2012. Results A total of 400 first-episode EGW cases were identified. Up to 6 subsequent episodes were documented, with 194 (48.5%) patients reporting at least 1 subsequent EGW episode. Median time to 1st subsequent EGW episode was 3.97 years, and the incidence density rate for all subsequent episodes was 0.18/100 patient-years. Over 90% of patients reported clearance of the first subsequent episode, with median time to clearance of 0.30 years. Regardless of subsequent episode number, >95% of patients received treatment, primarily cryotherapy, with high-risk sexual behaviour reducing as number of episodes increased. Conclusion Overall, a high rate of subsequent EGW episodes was observed in this high-risk population despite high treatment rates and improvement in high-risk sexual behaviour with increasing number of subsequent episodes. This is the first assessment of the rate of EGW recurrence in a Canadian clinical setting, in addition to proving information related to risk factors, clinical manifestations, and interventions. These data, assessed in a pre-vaccination Québec healthcare system, may be compared to future EGW rates in order to evaluate the impact of a governmentally-funded HPV vaccination program. Support: R. Thomas has received consulting fees from AbbVie, Gilead, Merck, and ViiV; M. Steben has received speaker honoraria or participated in Advisory Boards for Merck, Paladin, Valeant and Inovio; M. Stutz and E. Rampakakis are both employees of JSS Medical Research; C. Rodier and F. DeAngelis are both employees of Merck Canada Inc.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".