PS1 - 186 Needs Assessment for a Pediatric Proton Therapy Program in Canada
Bibliographic record
Abstract
Proton therapy enables normal tissue sparing for curative-intent treatment of children with cancer who require radiation therapy. In the USA and elsewhere, proton therapy is being rapidly adopted, and many new proton centres are being established. Without a proton centre in Canada, children and their families must travel abroad for treatment at high cost and has raised the question whether a Canadian proton therapy facility is needed. METHODS: Canadian Pediatric Oncology centres were surveyed to assess current and future clinical practices. Needs were modeled by screening the Alberta Cancer Registry, ascertaining the number of children eligible for proton RT and comparing to the number who actually received this therapy. RESULTS: Most centres (63%) referred children, and 49 children were referred abroad between 2008 and 2013. Referrals were estimated to increase to 36 cases per annum across Canada. Most respondents (75%) supported that proton therapy will reduce late effects in most or selected cases compared to photon therapy. The registry search revealed 37,170 patients irradiated of which 379 children (1.0%) were potentially eligible for proton therapy, accounting for 15.9% of the new cases of childhood cancers diagnosed in Alberta over the interval. CONCLUSIONS: A strong perceived need for a pediatric proton therapy in Canada was identified. Proton therapy utilization was lower than modeled needs. Future referrals are anticipated to increase, with annual estimated cost of approximately $60 million spent outside of Canada that could be invested within the Canadian health care economy. These issues are worthy of further national discussion.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".