Risk of Anal Cancer in a Cohort With Human Papillomavirus–Related Gynecologic Neoplasm
Bibliographic record
Abstract
OBJECTIVE: To assess the development of anal cancer in women diagnosed with a human papillomavirus-related cervical, vulvar, or vaginal neoplasm. METHODS: Using data from National Cancer Institute's Surveillance, Epidemiology and End Results program from 1973 through 2007, 189,206 cases with either in situ or invasive cervical, vulvar, or vaginal neoplasm were followed for 138,553,519 person-years for the development of subsequent primary anal cancer. Standardized incidence ratios were calculated from the observed number of subsequent anal cancers compared with those expected based on age-, race-, and calendar year-specific rates in the nonaffected population. RESULTS: Anal cancer developed in 255 women with a history of in situ or invasive gynecologic neoplasm, aggregate standardized incidence ratio of 13.6 (95% confidence interval [CI] 11.9-15.3), indicating a 13-fold increase in anal cancer compared with expected. The standardized incidence ratio for anal cancer incidence among women with in situ vulvar cancer was 22.2 (95% CI 16.7-28.4) and was 17.4 (95% CI 11.5-24.4) for those with invasive vulvar cancer. The standardized incidence ratio for anal cancer incidence in women with in situ cervical cancer was 16.4 (95% CI 13.7-19.2) and was 6.2 (95% CI 4.1-8.7) for women with invasive cervical cancer. The standardized incidence ratio for anal cancer incidence among women with in situ vaginal cancer was 7.6 (95% CI 2.4-15.6) and was 1.8 (95% CI 0.2-5.3) for invasive vaginal cancer. CONCLUSION: Women with human papillomavirus-related gynecologic neoplasm are at higher risk for developing anal cancer compared with the general population. This high-risk population may benefit from close observation and screening for anal cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".