PP134 The Impact Of Pan-Canadian Oncology Drug Review Coming Under The Remit Of The Canadian Agency For Drugs And Technologies In Health – Three Year Update
Bibliographic record
Abstract
Introduction: The pan-Canadian Oncology Drug Review (pCODR) was established in 2010 to bring consistent oncology drug assessments across Canadian provinces/territories. In April 2014, pCODR was transferred to the Canadian Agency for Drugs and Technologies in Health (CADTH). This transfer comprised two phases. In phase one, pCODR staff, processes, funding, and expertise remained intact as a program but under the government of CADTH. In phase two, beginning April 2015, better alignment of pCODR and CADTH evaluation criteria and review processes were explored. This research aims to see what effect the CADTH transfer has had on the number of appraisals conducted by pCODR and their recommendation rates. Methods: All publically available pCODR reports were extracted up to 22nd November 2017. The drug, indication, date and outcome were extracted. Statistical comparisons were made using Student's t-test. Results: Ninety-six appraisals have been conducted by pCODR, reflecting an average of 16 per year (10 in 2012, 18 in 2013, 9 in 2014, 24 in 2015, 19 in 2016, and 20 in 2017). The rate of appraisals was similar pre-CADTH transfer (14.2 per year [32 from January 2012 to March 2014]) versus post-CADTH transfer (13.7 per year [56 from April 2014 to November 2017]). Seventy-eight percent of pCODR outcomes were positive recommendations (defined as full recommendations [10 percent] or restricted/conditional recommendations [68 percent]) with 22 percent not recommended. Annually, positive recommendation rates were 70 percent in 2012, 89 percent in 2013, 78 percent in 2014, 79 percent in 2015, 74 percent in 2016, and 75 percent in 2017. There were no significant differences in recommendation rates since pCODR was transferred to CADTH irrespective if the phase one or phase two cut-off dates were used (p = 0.434 and 0.307, respectively). Conclusions: The number of appraisals and likelihood of a positive recommendation for oncology drugs has not been affected by the pCODR transfer to CADTH.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.082 | 0.280 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.021 | 0.021 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".