RARE-01. ASSESSING THE SYMPTOM DIAGNOSTIC INTERVAL FOR CHILDREN WITH CENTRAL NERVOUS SYSTEM TUMOURS
Bibliographic record
Abstract
Abstract Background Diagnostic delays in pediatric neuro-oncology is a subject of distress for families and providers. We aimed to evaluate the symptom diagnostic interval (SDI) and influencing variables for children with CNS tumors. Methods This retrospective study analyzed 210 patients diagnosed from 2001–2018 and managed at the tertiary care facility in Halifax, Canada. SDI was defined as time from first symptom until tissue diagnosis or, if not available, imaging diagnosis. Non-parametric tests were used to compare SDI between groups. Results Median SDI was 12.4 weeks (IQR 4.3–30), longer than 7 other studies of 1308 children reporting medians of 4.5–10 weeks (p < 0.01). Most common tumors and their median SDI included low-grade glioma (LGG) (n=97, 46%; 17.9 weeks), medulloblastoma (n=31, 15%; 8.7 weeks), high-grade glioma (HGG) and DIPG (n=23, 11%; 5.6 weeks), and ependymoma (n=13, 6%; 13.6 weeks). The most common initial reported symptom included headache (n=63; 30%), nausea/vomiting (n=27, 18%), seizure (n=24, 12%), and visual impairment (n=13, 6.3%). Patients aged 0–3 years had a shorter SDI than patients 10 years and older (SDI 8.7 vs 14.6 weeks; p = 0.03). Tumor category showed longer SDI for LGG versus HGG (p = 0.003), DIPG (p = 0.02), medulloblastoma (p = 0.03) and other embryonal tumors (p = 0.03). Longer SDI was not associated with increased risk of disease progression for LGG (p = 0.93), medulloblastoma (p = 0.89), or ependymoma (p = 0.5). No difference in SDI was found with regard to diagnosis era, ethnicity, socioeconomic status, or distance to the tertiary care facility. Conclusion SDI at our centre is longer than previously reported studies. SDI is linked to tumor biology and its relevance within specific tumor groups deserves further investigation given it doesn’t appear to predict tumor progression/recurrence, yet families and providers feel distress when delays in diagnosis are perceived.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".