Clinical and Scientific Challenges to Effectiveness Studies Under Coverage with Evidence Development in Alzheimer’s Disease
Bibliographic record
Abstract
The Centers for Medicare and Medicaid Services (CMS) has recently issued a national coverage determination for US Food and Drug Administration (FDA)-approved anti-amyloid monoclonal antibodies (mAbs) for the treatment of Alzheimer's disease (AD) under coverage with evidence development (CED). CED schemes are complex, costly, and challenging, and often fail to achieve intended objectives because of administrative and implementation issues. AD is a heterogeneous, progressive neurodegenerative disorder with complex care pathway that additionally presents scientific challenges related to the choice of study design and methods used in evaluating CED schemes. These challenges are herein discussed. Clinical findings from the US Veterans Affairs healthcare system help inform our discussion of specific challenges to CED-required effectiveness studies in AD.
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 | 0.626 | 0.811 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.019 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".