Checkpoint Immunotherapy in Pediatrics: Here, Gone, and Back Again
Bibliographic record
Abstract
The role of immune checkpoint inhibitors (ICIs) in the treatment of pediatric cancers continues to evolve. Such therapies function by augmenting existing antitumor T-cell responses that have been rendered ineffective by inhibitory pathways. Although ICIs have proven highly effective for adult cancers, initial phase I/II clinical trials using single-agent ICIs against unselected pediatric cancers have been overall disappointing. With the exception of pediatric classic Hodgkin lymphoma, responses to ICIs have been infrequent, likely stemming from an inherent difference in the immunogenicity of childhood cancers, which, on average, have far fewer neoantigens than adult cancers. Recently, however, hope has reemerged that certain subsets of children with cancer may benefit from ICI therapies. In preliminary studies, patients with both pediatric hypermutated and SMARCB1-deficient cancers have had impressive responses to ICI therapies, likely as a result of underlying biologies that enhance neoantigen expression and tumoral inflammation. Dedicated trials are ongoing to fully evaluate the efficacy of ICIs for patients with these subsets of pediatric cancer.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".