Distinction of <i>Condylomata Acuminata</i> From Vulvar Vestibular Papules or Pearly Penile Papules Using Ki-67 Immunostaining
Bibliographic record
Abstract
BACKGROUND: Ki-67 is an immunohistochemical stain used as a nuclear proliferation marker. It is nonspecific, and is expressed in all active phases of the cell cycle. Vulvar vestibular papules in women and pearly penile papules in men are benign fibrous papules on the genitals, are noninfectious, and do not require treatment. However, these lesions can be clinically confused with condylomata acuminata induced by human papillomavirus (HPV), which have medical and social implications. OBJECTIVE: Because HPV infection is known to induce expression of proliferation markers, we propose that Ki-67 be used to differentiate condylomata acuminata from vulvar vestibular papules or pearly penile papules on pathologic examination. METHODS: We reviewed a total of 26 lesions from 18 patients of previously pathologically diagnosed lesions, including condylomata acuminata (11 lesions), vulvar vestibular papules (10 lesions), and pearly penile papules (5 lesions). All slides were stained with Ki-67, reviewed, and categorized as positive or negative for Ki-67 staining by 1 investigator who was unaware of the original diagnosis. RESULTS: Eleven out of 11 cases of condylomata acuminata were identified as positive for Ki-67 staining. Ten out of 10 cases of vulvar vestibular papules were negative for Ki-67. Five out of 5 cases of pearly penile papules were negative for Ki-67. CONCLUSION: Ki-67 is a reliable marker to pathologically distinguish benign vulvar vestibular papules in women, or pearly penile papules in men, from HPV-induced condylomata acuminata.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".