Characteristics of drugs for ultra-rare diseases versus drugs for other rare diseases in HTA submissions made to the CADTH CDR
Bibliographic record
Abstract
BACKGROUND: It has been suggested that ultra-rare diseases should be recognized as distinct from more prevalent rare diseases, but how drugs developed to treat ultra-rare diseases (DURDs) might be distinguished from drugs for 'other' rare diseases (DORDs) is not clear. We compared the characteristics of DURDs to DORDs from a health technology assessment (HTA) perspective in submissions made to the CADTH Common Drug Review. We defined a DURD as a drug used to treat a disease with a prevalence ≤ 1 patient per 100,000 people, a DORD as a drug used to treat a disease with a prevalence > 1 and ≤ 50 patients per 100,000 people. We assessed differences in the level and quantity of evidence supporting each HTA submission, the molecular basis of treatment agents, annual treatment cost per patient, type of reimbursement recommendation made by CADTH, and reasons for negative recommendations. RESULTS: We analyzed 14 DURD and 46 DORD submissions made between 2004 and 2016. Compared to DORDs, DURDs were more likely to be biologic drugs (OR = 6.06, 95%CI 1.25 to 38.58), to have been studied in uncontrolled clinical trials (OR = 23.11, 95%CI 2.23 to 1207.19), and to have a higher annual treatment cost per patient (median difference = CAN$243,787.75, 95%CI CAN$83,396 to CAN$329,050). Also, submissions for DURDs were associated with a less robust evidence base versus DORDs, as DURD submissions were less likely to include data from at least one double-blinded randomized controlled trial (OR = 0.13, 95%CI 0.02 to 0.70) and have smaller patient cohorts in clinical trials (median difference = -108, 95%CI -234 to -50). Furthermore, DURDs are less likely to receive a positive reimbursement recommendation (OR = 0.22, 95%CI 0.05 to 0.91), and low level of evidence was the major contributor for a negative recommendation. CONCLUSIONS: The results suggest that DURDs could be viewed as distinct category from an HTA perspective. Applying the same HTA decision-making framework to DURDs and DORDs might have contributed the higher rate of negative reimbursement recommendations made for DURDs. Recognition of DURDs as a distinct subgroup of DRDs by explicitly defining DURDs based on objective criteria may facilitate the implementation of HTA assessment process that accounts for the issues associated with DURD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".