Analysis of indirect treatment comparisons in national health technology assessments and requirements for industry submissions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Aim: To determine the preferred methodologies of health technology assessment (HTA) agencies across Europe, Canada and Australia to ascertain acceptance of indirect treatment comparisons (ITC) as a source of comparative evidence. Method: A review of official submission guidelines and analysis of comments in HTA submissions that have used different ITC methodologies. Conclusion: ITC is generally accepted as a technique that allows demonstration of noninferiority to a comparator provided the chosen methodology and underlying assumptions are clear and justified. However, HTA agencies are more likely to closely scrutinize submitted data and evaluate statistical significance of results when superiority is claimed. In addition, the HTA agencies in scope tended to be cautious and only accept ITC data as support for similarity of treatments.
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.
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 | 0.032 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it