LMIC-20. REAL-WORLD EXPERIENCE IN DEALING WITH CHILDREN WITH SUSPECTED CENTRAL NERVOUS SYSTEM (CNS) TUMORS AT THE CHILDREN’S HOSPITAL LAHORE (UCHS), PAKISTAN
Bibliographic record
Abstract
Abstract BACKGROUND CNS tumors are the leading cause of cancer-related deaths in children in HICs, but data from LMICs are scarce. The objectives of this study were to document the trajectory of children with CNS tumors at a tertiary-care hospital in Pakistan. METHODS This prospective, analytic, cohort study recorded all new cases of suspected CNS tumors (birth to 16 years) presented from 2023/01/01 to 2023/12/31 at UCHS, Lahore. RESULTS A total of 145 cases were included. Median age at presentation was 7.0 years (1.5 months–15 years); male-to-female ratio was 1.4:1. Median time to presentation was 2 months (0.1 – 96 months); delay of >6 months was observed in 30.5% cases due to delayed presentation to medical facility (74%) and healthcare delay (26%). Headaches and vomiting (56%), focal neurological deficit (23%), and seizures (15%) were the most common presenting complaints. Consanguinity (46%), and family history of cancers (19%) were frequent; café au lait macules were observed in 9.7%. 50% tumors were infratentorial, 46% supratentorial and 4% spinal. Tumor excision was done in 45%, VP-shunts in 42%, and upfront chemotherapy in 2%. Only 60% had a final diagnosis. Tissue diagnosis in 39% cases showed Medulloblastoma (18 patients, 32%), Pilocytic Astrocytoma (27%), and High-grade glioma (16%) as the commonest diagnoses, while 21% had a radiological diagnosis based on CT/MRI features: DIPG/DMG (12%), Craniopharyngioma (7.6%), and Optic Pathway Glioma (1.4%). Of 18 medulloblastoma patients, only 7 received postoperative radiotherapy. Seventy (48%) patients expired (including 38 before surgery), 27% are on follow-up and 25% are LAMA/LTFU/defaulted treatment. One-year survival was 36% with median survival of 4 months (0.07-96 months). CONCLUSION Less than half of the patients with CNS tumors undergo active treatment, a large proportion leave treatment/follow-up and have poor overall survival. Considerable cases with cancer predisposition syndromes were suspected.
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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 | 0.001 | 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) | 0.004 | 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".