Impact of a PD-L1 Learning Collaborative: outcomes from a mixed-methods evaluation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Introduction/Objective PD-L1 Immunohistochemistry testing is often required to determine eligibility for immune checkpoint inhibitor therapy. An ASCP PD-L1 Learning Collaborative (LC) was formed aiming to: 1) identify ways to streamline PD-L1 testing; 2) encourage members to locally implement changes; and 3) develop a resource guide for the community. Methods/Case Report The PD-L1 LC (n=38 pathologists and laboratory professionals) participated in 3 activities: 1) 4 meetings in which LC members discussed current literature and practice; 2) 3 30-minute on-demand, credit-bearing panel videos, in which selected LC members summarized the LC outputs and shared their experiences; and 3) a guide summarizing resources relevant to streamlining PD-L1 testing. The mixed-methods evaluation included: 1) five- minute surveys before (n=24), immediately after (n=11) and 7-months post-LC (n=17); 2) polling questions (2-4 per meeting); 3) semi-structured interviews (n=5). Quantitative data was analysed using descriptive and inferential analysis, qualitative data using a thematic analysis / inductive reasoning approach. Results (if a Case Study enter NA) Baseline data confirmed delays in testing caused by unstandardized PD-L1 testing processes and suboptimal confidence in PD-L1 validation and methodologies. Post-LC, members self-reported perceived increased knowledge and higher confidence levels regarding discussion of PD-L1 scientific evidence and best practices. At the 7-month follow-up, 59% of respondents reported at least one PD-L1-related practice change, with 29% of participants selecting:1) Improving protocols for specimen acquisition, handling, or processing; 2) Improving communication with multidisciplinary care team; 3) Optimizing biomarker testing workflows. Remaining suboptimal knowledge post-LC suggests need for further educational efforts. Participants identified “Tumor-specific considerations” as the main resource missing for PD-L1 testing. Conclusion A learning collaborative has shown impact in improving PD-L1 testing processes and related practices among a group of pathology professionals. The group successfully made available three panel videos and a resource guide, and PD-L1-related practice changes were reported. Future initiatives should address remaining gaps and develop tumor-specific PD-L1 testing considerations.
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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 | 0.022 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 it