Expanding the Pediatric Neuro-Oncology Teleconference Experience: From Twinning to International Cases Discussions
Bibliographic record
Abstract
PURPOSE: Video teleconferencing in neuro-oncology is feasible and sustainable. The well-established, 20-year long monthly teleconference between King Hussein Cancer Center (KHCC), Jordan, and SickKids, Canada, is an example. Since 2018, several regional centers joined these meetings to discuss their patients' management plans. We aim to evaluate this experience. METHODS: We reviewed the minutes of 56 meetings (2018-2023). Preconference local treatment plans were compared with postconference recommendations. We documented the implementation of recommendations and the impact perceived by the treating oncologists. RESULTS: Two hundred fifty-one patients were discussed: 137 from Jordan and 114 from eight other countries. Four of the 14 participating oncologists had formal pediatric neuro-oncology training. Of the 227 patients (90%), where the local multidisciplinary team had suggested a preconference plan, the teleconference recommendations concurred with the proposed plan in 50% of cases, agreed on it and proposed an alternative option in 18%, and disagreed in 32%. The difference in recommendations mostly affected the proposed treatment modality. In 64% of discordant plans and 50% of alternative plans, the treating team applied the recommendations. The main challenges in applying the recommendations were attributed to patient-related factors (51%), local team consensus on a different plan (26%), or logistic difficulties (23%). The high patient load, longer involvement in teleconferencing, formal neuro-oncology training, and well-established multidisciplinary team helped the KHCC team formulate more concordant plans. CONCLUSION: This experience illustrates the potential benefit for physicians to get an expert opinion on challenging cases. The participating oncologists valued the shared educational experience, especially those related to molecular testing and treatment implications. Joining such regional teleconferences is of particular importance to centers with small patient volume or those lacking a pediatric neuro-oncologist.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".