Immunohistochemistry Use by Diagnostic Category and Pathologist in 4477 Prostate Core Biopsy Sets Assessed at Two Hospitals
Bibliographic record
Abstract
BACKGROUND: Immunohistochemistry (IHC) use in prostate cores is not routinely determined and its value assessed. METHODS: Pathology reports for cases accessioned 2011 to 2017 at two hospitals were retrieved. IHC orders by pathologist and hospital were extracted with a custom program and tabulated. The diagnostic category (and highest grade cancer if applicable) was obtained by a hierarchical (free text) string matching algorithm. RESULTS: The study period contained 4477 biopsy sets. Categorized by worst pathology (% stained), the cohort was: benign: 1184 cases (42%); prostatic intraepithelial neoplasia: 168 (68%); suspicious: 323 (93%); grade group 1 cancer (WHO1): 900 (78%); grade group two (WHO2): 840 (60%); WHO3 cancer: 451 (54%); WHO4 cancer: 363 (46%); WHO5 cancer: 215 (56%); cancer grade not specified: 33 (52%). The hospital was a predictor; site A(2716 biopsies) and site B(1761) accounted for 10,183 and 14,852 IHC, respectively. The cases with IHC decreased in the last 4 years (site A: 57->45%, site B: 79->73%). Thirty-five pathologists read >20 cases each and together interpreted 4418 (range, 21 to 415; median, 88). In total 24,766 IHCs were done on the 4,418 cases (5.6/case). The mean/median/SD/max/min IHCs/case for the 35 pathologists was 5.6/4.1/3.9/15.2/0.9. High IHC users (1st and 2nd quintile pathologists) called more suspicious for malignancy but not significantly more WHO1 than low IHC users. CONCLUSIONS: IHC use is most frequent at the benign/malignant interface, and dependent on the pathologist and hospital; however, it is independent of WHO1 cancer rate. Diagnostic rate information can inform and define appropriate and rational IHC use. We plan to follow IHC utilization retrospectively in relation to the diagnostic category going forward.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".