Abstract 4303: Programmed death ligand 1 (PD-L1) expression in paired melanoma tumor samples
Bibliographic record
Abstract
Abstract Background: There is limited information on changes in PD-L1 expression levels over time in melanoma. Methods: PD-L1 expression was measured in melanoma tumor samples collected at different time points from the same patient using a prototype immunohistochemistry (IHC) assay with the 22C3 antibody. PD-L1 positivity was defined as staining in ≥1% of cells. The concordance of PD-L1 expression in paired samples was analyzed by treating the IHC proportion score as a continuous variable or classifying staining as positive or negative. Results: 48 patients were included. Median age was 65 years (range, 23-85), 73% were male, and 60% had stage I-IIIA disease. All first samples and 85% of second samples were surgical samples. The median interval between sample collection dates was 25.3 months (range, 3.1-203.5). There was no statistically significant correlation of the PD-L1 IHC proportional score between paired samples (Pearson correlation coefficient, 0.13). 40% of patients had an increased proportion score at the second time point, and 10% had a decreased score. The prevalence of PD-L1 positivity was 31% in first samples and 46% in second samples. The concordance rate was 65% (95% CI, 49%-78%) when PD-L1 expression was categorized as positive or negative (Table). The concordance rate was similar in paired samples collected within and beyond 2 years. Concordance of PD-L1 Expression in Paired Melanoma Samples (N = 48)Later Time PointPD-L1 ExpressionPositive, n (%)Negative, n (%)Earlier Time PointPositive10 (20.8)5 (10.4)Negative12 (25.0)21 (43.7) Conclusion: Our preliminary analysis did not suggest a significant correlation of PD-L1 expression in paired melanoma samples collected at different time points. Similar results were observed when samples were categorized as PD-L1 positive or PD-L1 negative. The 35% discordance rate between initial and subsequent tumor samples should be considered if PD-L1 expression is used for selection of enrollment in clinical trials. Citation Format: Torben Steiniche, Allan Vestergaard Danielsen, Zhen (Adelle) Wang, Patricia Switten Nielsen, Lars Bastholt, Henrik Schmidt, Inge Marie Svane, Marisa Dolled-Filhart, Kenneth Emancipator, Dianna Y. Wu, Michael Busch-Sorensen, Wei Zhou. Programmed death ligand 1 (PD-L1) expression in paired melanoma tumor samples. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4303. doi:10.1158/1538-7445.AM2015-4303
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".