Primary central nervous system lymphoma in children: Insights from the three-year experience at the largest public-sector pediatric oncology center in Pakistan
Bibliographic record
Abstract
Objective: Primary CNS lymphoma (PCNSL) in children is a rare disease, and this study aimed to document the experience of dealing with this in our geographical and resource settings. Methodology: It was an ambidirectional cohort study conducted at the Department of Pediatric Hematology/Oncology and the Department of Pediatric Neurosurgery at the University of Child Health Sciences, The Children's Hospital Lahore, Pakistan from March 2024 to December 2024. This study included seven suspected and confirmed cases of PCNSL in children under the age of 16 years who presented to a public-sector specialized center in Pakistan over the three-year study period. Results: A total of seven cases of suspected PCNSL were included in the study. The median age at presentation was eight years, with a female-to-male ratio of 2.5:1. Most commonly presenting with a focal neurological deficit, with a median duration of symptoms of 12 weeks, and a median Lansky performance score of 50. Only 57% (04) of patients underwent surgical resection followed by adjuvant chemotherapy. Overall, 57% (03) of patients died, 29% (02) were lost to follow-up, and only 14% (01) are under treatment. Conclusion: PCNSL in children is equally rare in our part of the world, but has a dismal survival rate. Timely surgical intervention, improved supportive care, and a reduction in treatment abandonment might improve the prognosis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".