Clinical trials in Ontario’s quality-based funding model.
Bibliographic record
Abstract
186 Background: Clinical trials (CTs) are a key component of a quality cancer care system. When funding for systemic therapy services in Ontario transitioned in 2014 from a one-time payment for new cases to bundled payments for specific care activities (consultation, therapy, well follow-up, supportive care), a policy was developed to address public funding for systemic therapy in CTs. Methods: Treatment facilities receive funding from the Systemic Treatment-Quality Based Program (ST-QBP) for treatment with evidence-informed regimens inclusive of inexpensive drug, preparation and delivery costs. Under the new CT policy, randomized CTs with a standard of care comparator arm receive funding for all arms of the trial from the ST-QBP for older inexpensive drugs and all treatment administration costs at the band level for the disease type and stage. Non-randomized CTs are funded at the level of best supportive care or other appropriate band level. CT costs over and above the standard of care must be negotiated with industry sponsors. New and expensive drugs in CTs may be funded through separate provincial drug reimbursement programs if used according to publicly approved funding indications. Weekly joint reviews of new CT submissions by staff of the ST-QBP and drug reimbursement programs ensures timely communication to investigators concerning policy alignment and public funding and addresses potential concerns with regard to downstream access to expensive drugs. Results: As of January 29, 2016, 121 CT applications have been assessed (Phase 0 = 1, Phase I = 26, Phase II = 31, Phase III = 39, Phase IV = 1 and Multi-Phase = 23). Almost all CTs are aligned with the new policy and were assessed in a timely fashion. Assessments are posted on Cancer Care Ontario’s website within 1 week of review to allow all Ontario investigators access to this information. Conclusions: A clear CT funding policy and timely reviews support patient and investigator access to new and innovative therapies within an evidence-informed public funding model in Ontario, Canada. [Table: see text]
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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 | 0.067 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.042 | 0.004 |
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".