Outcomes After Treatment of Cervical Intraepithelial Neoplasia Among Women With HIV
Bibliographic record
Abstract
OBJECTIVE: To describe outcomes after treatment of cervical intraepithelial neoplasia (CIN) in women with HIV. MATERIALS AND METHODS: Women in two prospective cohort studies, the Women's Interagency HIV Study (WIHS) and the HIV Epidemiology Research Study (HERS), were followed every 6 months after treatment of CIN using human papillomavirus (HPV) testing and cytology with colposcopy as indicated. Identification of CIN or a squamous intraepithelial lesion (SIL) within 6 months was defined as treatment failure and later disease as recurrence. RESULTS: Follow-up was available for 170 HIV-seropositive and 15 HIV-seronegative women. Treatment failed in 84 (45%) women (79 HIV seropositive and 5 HIV seronegative). Failure was more likely in women with lower CD4 counts (CD4 < 200 cells/microL: odds ratio [OR] = 2.96; 95% CI = 1.4-6.2) and detectable HPV DNA (OR 8.20; 95% CI = 1.8-37.4; p = .01). After successful treatment, recurrence-free probabilities at 1,2, 3, and 5 years were .79, .64, .49, and .34, respectively. HIV-seronegative women were less likely to recur than HIV-seropositive women (p = .03). In multivariable analysis of HIV-positive women, recurrence was more likely among women treated for CIN 2,3 (hazard ratio [HR] = 2.4; 95% CI = 1.4-4.8), those with CD4 count of less than 200 cells/microL (HR = 2.9; 95% CI = 1.3-6.5) and those with HPV after treatment (HR 2.9; 95% CI = 1.4-6.1); oncogenic HPV was more strongly associated with recurrence than nononcogenic HPV (p(trend) = .009). Most failures and recurrences were low grade, but one adenocarcinoma was diagnosed 4.2 years after therapy for CIN 1. CONCLUSION: Treatment failure and recurrence are common in women with HIV but are usually low grade.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".