A Retrospective Analysis of the Therapeutic Outcomes of 117 Neuroblastoma Patients Treated at a Single Pediatric Oncology Center in China
Bibliographic record
Abstract
OBJECTIVE: Recent therapeutic advances have greatly enhanced the survival rates of patients with neuroblastoma (NB). However, the outcomes of neuroblastoma patients in China, particularly those with high-risk (HR) NB, remain limited. METHOD: We retrospectively analyzed the clinical data and outcomes of NB patients who were treated at a tertiary pediatric cancer facility in China between January 2013 and October 2021. RESULTS: A total of 117 NB patients were recruited. Patients with very low-risk (VLR), low-risk (LR), intermediate-risk (IR), and HR-NB patients made up 4%, 27%, 15%, and 54% of total patient population, respectively. Patients diagnosed between 2013 and 2018 were treated according to the protocol of Sun Yat-Sen University Cancer Center and those diagnosed between 2019 and 2021 were treated according to the COG ANBL0531 or ANBL0532 protocol with or without autologous stem cell transplantation (ASCT). The 5-year EFS and OS of all risk groups of patients were 67.29% and 77.90%, respectively. EFS and OS were significantly decreased in patients with higher risk classifications (EFS: VLR/LR vs IR vs HR: 97.22% vs 67.28% vs 51.83%; ***P = .001; OS: VLR/LR vs IR vs HR: 97.06% vs 94.12% vs 64.38%; *P = .046). In HR-NB patients treated according to the COG protocol between 2019 and 2021, the 3-year OS of patients who received tandem ASCT was significantly greater than those who did not receive ASCT (93.33% % vs 47.41%; *P = .046; log-rank test). EFS was not significantly different between patients with and without ASCT (72.16% vs 60.32%). CONCLUSION: Our findings show that patients with lower risk classification have a positive prognosis for survival. The prognosis of patients with HR-NB remains in need of improvement. ASCT may enhance OS in HR-NB patients; however, protocol adjustment may be necessary to increase EFS in these patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".