Biomarkers of response to PD-1/PD-L1 inhibition
Bibliographic record
Abstract
Immunotherapy is a promising treatment strategy for cancer that has recently shown unprecedented survival benefits in selected patients. A number of immunomodulatory agents that target immune system checkpoints such as the cytotoxic T-lymphocyte antigen 4 (CTLA-4), the programmed death-1 (PD-1) or its ligand (PD-L1), have received regulatory approval for the treatment of multiple cancers including malignant melanoma, non-small cell lung cancer, renal cell carcinoma, classical Hodgkin lymphoma, and recurrent or metastatic head and neck squamous cell carcinoma. Nevertheless, a substantial proportion of patients treated with checkpoint inhibitors have little or no benefit while these treatments are costly and might have associated toxicities. Hence, the establishment of valid predictors of treatment response has become a priority. This review summarizes the current evidence around biomarkers of response to PD-1/PD-L1 inhibition, considering features related to the tumor and to the host immune system.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".