Reinventing Nuclear Histo-score Utilizing Inherent Morphologic Cutoffs: Blue-brown Color H-score (BBC-HS)
Bibliographic record
Abstract
Immunohistochemistry (IHC) is a testing methodology that is widely used for large number of diagnostic, prognostic, and predictive biomarkers. Although IHC is a qualitative methodology, in addition to threshold-based stratification (positive vs. negative), the increasing levels of expression of some of these biomarkers often lead to more intense staining, which published evidence linked to specific diagnosis, prognosis, and responses to therapy. It is essential that the descriptive thresholds between positive and negative staining, as well as between frequently used graded categories of staining intensity (eg, 1+, 2+, 3+) are standardized and reproducible. Histo-score (H-score) is a frequently used scoring system that utilizes these categories. Our study introduces categorization of the cutoff points between positive and negative results and graded categories of staining intensity for nuclear IHC biomarker assays based on color interaction between hematoxylin and diaminobenzidine (DAB); the Blue-brown Color H-score (BBC-HS). Six cases of diffuse large B-cell lymphoma were stained for a nuclear marker MUM1. The staining was assessed by H-score by 12 readers. Short tutorial and illustrated instructions were provided to readers. The novel scoring system in this study uses the interaction between DAB (DAB, brown stain) and hematoxylin (blue counterstain) to set thresholds between "0" (negative nuclei), "1+" (weakly positive nuclei), "2+" (moderately positive nuclei), and "3+" (strongly positive nuclei). The readers recorded scores for 300 cells. Krippendorff alpha (K-alpha) and intraclass correlation coefficient (ICC) were calculated. We have also assessed if reliability improved when counting the first 100 cells, first 200 cells, and for the total 300 cells using K-alpha and ICC. To assess the performance of each individual reader, the mean H-score and percent positive score (PPS) for each case was calculated, and the bias was calculated between each reader's score and the mean. K-alpha was 0.86 for H-score and 0.76 for PPS. ICC was 0.96 for H-score and 0.92 for PPS. The biases for H-score ranged from -58 to 41, whereas for PPS it ranged from -27% to 33%. Overall, most readers showed very low bias. Two readers were consistently underscoring and 2 were consistently overscoring compared with the mean. For nuclear IHC biomarker assays, our newly proposed cutoffs provide highly reliable/reproducible results between readers for positive and negative results and graded categories of staining intensity using existing morphologic parameters. BBC-HS is easy to teach and is applicable to both human eye and image analysis. BBC-HS application should facilitate the development of new reliable/reproducible scoring schemes for IHC biomarkers.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".