Neuroblastoma With Opsoclonus-Myoclonus-Ataxia Syndrome: Role of Chemotherapy in the Management: Experience From a Tertiary Care Center in a Resource-limited Setting
Bibliographic record
Abstract
Children with neuroblastoma (NB) and opsoclonus-myoclonus-ataxia syndrome (OMAS) have a favorable oncologic outcome and overall survival. In contrast, despite intensive multidrug immunomodulation, the neurologic outcome is complicated by the relapsing nature of the neurologic symptoms and long-term neurobehavioral sequelae. Being associated with low-risk NB, there exists an ambiguity in the current literature regarding the administration of chemotherapy in these children. We reviewed our archives for children with NB-OMAS over a 22-year (January 1996 to January 2018) period. Eighteen children (10 female) with a median age at diagnosis of 23 months had NB-OMAS and were included. They had stage 1 (9/18; 50%), 2 (1/18; 5.5%), 3 (7/18; 39%), and 4 (1/18; 5.5%) disease according to the International Neuroblastoma Staging System. Multimodality therapy included surgery (16/18; 89%), chemotherapy (11/18; 61%), and immunomodulatory therapy (10/18; 55%). Complete oncologic remission was achieved in all children. Relapse of OMAS and presence of neurologic sequelae were observed in 1 (5.5%) and 5 (28%) cases, respectively. Presence of neurologic sequelae was significantly associated with low-tumor stage (P=0.036) and treatment without chemotherapy (P=0.003). Chemotherapy administration was the only variable significantly predicting a favorable neurologic outcome (95% confidence interval: 0.26-1.40, P=0.01). To conclude, our study including a limited cohort of patients highlights a favorable neurologic outcome associated with chemotherapy administration in children with NB-OMAS. However, further studies with larger sample size need to be conducted before drawing any definite conclusions.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".