Human Papillomavirus Vaccination
Bibliographic record
Abstract
Sir: Human papillomavirus has been identified as a major causative agent of many cancers (e.g., genital, anus, oropharynx, and digits).1 It is responsible for the most years of life expectancy lost (29 years) compared with all other major cancers occurring among women.1 Approximately 26,200 cancers per year are attributable to human papillomavirus, with 8800 occurring in men. Over 40 percent of female subjects aged 14 to 59 are human papillomavirus–positive, with 30 percent positive for a high-risk subtype.2 Although preventative vaccine is currently available, its use is promoted mainly among general practitioners and gynecologists. Currently, two vaccines are commonly used: Gardasil (Merck & Co., Inc., Kenilworth, N.J.), which protects against human papillomavirus types 6, 11, 16, and 18; and Cervarix (GlaxoSmithKline, Brentford, United Kingdom), which protects against types 16 and 18. These subtypes are associated with the development of cancer (mostly squamous cell carcinomas), with 70 percent of cervical cancers caused by types 16 and 18. Multiple studies show a reduction in the incidence of both cancer and precancerous lesions with vaccination.2 Vaccination is now recommended for female subjects aged 9 to 45 years and male subjects aged 9 to 26 years.1–5,9 When clinically indicated, treatment for many of these cancers is surgery. Because of the extent of resection and the sensitive areas involved, reconstructive surgery is needed to restore form and function. If there is failure of first-line chemotherapy, radiation therapy, or chemoradiation therapy, surgery is usually the next treatment option, and is often associated with high morbidity and low overall disease-free survival.6 Surgical management of these cancers involves a multidisciplinary team approach, with plastic surgeons involved in wound closure or reconstruction. Recent reports show that 90 percent of digital squamous cell carcinomas are caused by human papillomavirus.7 Digital lesions are usually missed and, if not caught in time, can lead to invasive disease requiring digital amputation.7 It is for these reasons that the plastic surgery community should help raise awareness of the numerous benefits associated with human papillomavirus vaccination. Currently, common screening methods for human papillomavirus cancers use the Papanicolaou test to identify cervical dysplasia. However, screening tests are not routinely performed to identify oropharyngeal cancer caused by human papillomavirus.8 Advanced oropharyngeal cancers may be treated with surgery, many of which require reconstruction to restore form and function to the face and mouth.8 After performing a literature review between 1965 and 2014, 36 studies were identified that describe surgical treatment of human papillomavirus. This review demonstrated a robust number of studies and a total of 484 patients affected by human papillomavirus–related cancer that required reconstructive surgery. Although this may not represent the entirety of surgery performed for human papillomavirus–related cancer, it represents a significant health burden that could be mitigated by a preventative health effort among plastic surgeons. There is a clear need to improve awareness about human papillomavirus vaccination. Smoking cessation and weight loss are common discussions between plastic surgeons and their patients. Plastic surgeons should counsel patients about human papillomavirus vaccination to decrease related cancers. DISCLOSURE None of the authors has a financial interest in any of the products or devices mentioned in this article. Dino Zammit, B.Sc. McGill University Jonathan Kanevsky, M.D., C.M. McGill University Health Centre Julian Diaz, B.Sc. McGill University Mario Luc, M.Sc., M.D. McGill University Health Centre Montreal, Quebec, Canada
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.079 | 0.032 |
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".