Efficacy and safety of dinutuximab in the management of high-risk neuroblastoma: A systematic review and meta-analysis.
Bibliographic record
Abstract
e22000 Background: Neuroblastoma (NB) is a malignant tumor of the sympathetic nervous system that usually occurs in children below 5 years of age. High-risk neuroblastoma (HR-NB) has a poor prognosis despite a number of treatment strategies. Dinutuximab, an anti-GD2 monoclonal antibody, has been recently added to the standard of care due to its improved prognosis. We aimed to systematically assess the outcomes of HR-NB patients treated with dinutuximab and compare them with those on other treatment regimens. Methods: A comprehensive search strategy was used to search PubMed and the Cochrane Library for articles investigating the effect of dinutuximab on the outcomes of patients with HR-NB. Eligibility criteria included: 1) Diagnosis of HR-NB based on INRG and INSS staging and MYCN status 2) Dinutuximab as the primary agent used in the intervention group 3) Mean/median follow-up time greater than 6 months. Three investigators independently reviewed and extracted relevant articles. Any disagreements were addressed through consultation with other authors. The risk of bias assessment of the selected articles was conducted using the Cochrane Risk of Bias Tool for randomized controlled trials (RCTs) and the Newcastle-Ottawa scale for observational studies. Review Manager software was used to obtain and display the meta-analysis estimates in forest plots. Random effects models were used to calculate the mean difference and overall estimated effects for continuous variables. The primary outcomes were all-cause mortality and 5-year event-free survival (5-year-EFS). Results: Five studies, including two RCTs, two secondary analyses of clinical trials, and one retrospective cohort study, comprising 1,393 participants, were included in the analysis. 686 of the patients received dinutuximab, while the remaining 707 patients were assigned to other therapies as controls. Dinutuximab was associated with lower all-cause mortality as compared to control [pooled RR, 0.41; 95% CI, 0.22-0.75, P = 0.004, I2 = 31%]. 5-year-EFS was also greater for patients treated with dinutuximab [MD: 0.12; 95% CI, 0.09-0.16; P < 0.001, I2= 98%]. Conclusions: Our findings suggest that dinutuximab is linked to a significant reduction in overall mortality and a noteworthy improvement in the 5-Year-EFS for patients with HR-NB, when compared to other treatment options.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".