Incidence and Clinicopathologic Characteristics of Human Papillomavirus–independent Invasive Squamous Cell Carcinomas of the Cervix
Bibliographic record
Abstract
We aimed to determine the frequency of human papillomavirus-independent (HPVI) cervical squamous cell carcinoma (SCC) and to describe clinicopathologic characteristics. Among 670 patients with surgically treated SCCs in an established multi-institutional cohort, 447 had available tissue. Tissue microarrays were constructed and studied by in situ hybridization (ISH) for high-risk and low-risk human papillomavirus (HPV) mRNA and immunohistochemistry for p16 and p53. Tumors were HPVI if negative by HPV ISH and they failed to show diffuse p16 positivity by immunohistochemistry, and human papillomavirus-associated (HPVA) if positive by HPV ISH. Ten HPVI SCCs and 435 HPVA SCCs were identified; 2 cases were equivocal and excluded from analysis. The overall rate of HPVI SCC was low (2%) but was higher among older patients (7% in patients above 60 y of age and 17% in patients above 70 y of age). Compared with HPVA, patients with HPVI SCC were significantly older (median age, 72 vs. 49, P <0.001) and diagnosed at a higher stage (40% vs. 18% with stage III/IV disease, P =0.055). p53 expression was varied; 2 cases (20%) had null expression and 8 (80%) had wild-type expression. HPVI SCCs were heterogenous, with keratinizing, nonkeratinizing, and warty morphologies observed. Several cases had a precursor lesion reminiscent of differentiated vulvar intraepithelial neoplasia, with prominent basal atypia and hypereosinophilia or a basaloid-like morphology. Two patients (20%) had distant recurrences within 12 months, and 3 (30%) died of disease during follow-up. HPVI SCCs are rare tumors that are more common among older patients with higher stage disease and have important clinical and histologic differences from HPVA SCCs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".