Chemo-immunotherapy with dinutuximab beta in patients with relapsed/progressive high-risk neuroblastoma: does chemotherapy backbone matter?
Bibliographic record
Abstract
BACKGROUND: Addition of anti-GD2 antibodies to temozolomide-based chemotherapy has demonstrated increased antitumor activity and progression-free survival in patients with relapsed/progressive high-risk neuroblastoma. However, chemo-immunotherapy is not yet approved for this indication. This study presents the chemo-immunotherapy experience in patients with relapsed/progressive high-risk neuroblastoma treated within the off-label use program of the Neuroblastoma Committee of the French Society of Pediatric Oncology (SFCE). METHODS: Dinutuximab beta (dB) was administered alongside temozolomide-topotecan (TOTEM) or temozolomide-irinotecan (TEMIRI) at first disease relapse/progression or topotecan-cyclophosphamide (TopoCyclo) at further relapse/progression. Real-world data on demographics, treatment, antitumor activity and safety was collected from all patients after inclusion in SACHA-France (NCT04477681), a prospective national registry, which documents safety and efficacy data on innovative anticancer therapies prescribed to patients ≤ 25 years old as compassionate or off-label use. RESULTS: Between February 2021 and July 2023, 39 patients with confirmed relapsed/progressive high-risk neuroblastoma (median age 6 years, range 1-24) were treated with dB+TopoCyclo (n = 24) or dB+TOTEM/TEMIRI (n = 15) across 17 centers. In total, 163 chemo-immunotherapy cycles were administered, main toxicities were mild or moderate, with higher incidence of hematological adverse drug reactions with dB+TopoCyclo than dB+TOTEM/TEMIRI. Objective response rate was 42% for dB+TopoCyclo (CI95% 22-63%) and 40% for dB+TOTEM/TEMIRI (CI95% 16-68%). CONCLUSION: Similar objective response rates for dB+TopoCyclo and dB+TOTEM/TEMIRI in patients with relapsed/progressive high-risk neuroblastoma emphasize the importance of chemo-immunotherapy, irrespective of the chemotherapy backbone.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".