Immunohistochemistry for Prostate Biopsy—Impact on Histological Prostate Cancer Diagnoses and Clinical Decision Making
Bibliographic record
Abstract
BACKGROUND: To test the value of immunohistochemistry (IHC) staining in prostate biopsies for changes in biopsy results and its impact on treatment decision-making. METHODS: Between January 2017-June 2020, all patients undergoing prostate biopsies were identified and evaluated regarding additional IHC staining for diagnostic purpose. Final pathologic results after radical prostatectomy (RP) were analyzed regarding the effect of IHC at biopsy. RESULTS: < 0.01) and less suspicious baseline characteristics than patients without IHC. Of 185 patients with positive IHC and PCa detection, IHC led to a change in biopsy results in 81 (43.8%) patients. Of these patients with changes in biopsy results due to IHC, 42 (51.9%) underwent RP with 59.5% harboring ≥pT3 and/or Gleason 7-10. CONCLUSIONS: Patients with IHC stains had less suspicious characteristics than patients without IHC. Moreover, in patients with positive IHC and PCa detection, a change in biopsy results was observed in >40%. Patients with changes in biopsy results partly underwent RP, in which 60% harbored significant PCa.
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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 | 0.007 | 0.022 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".