Changing the trajectory of Alzheimer’s disease: What is a meaningful delay in disease progression?
Bibliographic record
Abstract
Abstract Background Recent trials of anti‐amyloid therapies have shown it is possible to change the course of early symptomatic Alzheimer’s disease (AD). However, the limited durations of these trials with the associated limited decline in the patient populations have left questions about the clinical meaningfulness of the observed treatment differences. Through progression analysis, one can quantify trial results in terms of time delay of progression. Compared to treatment differences on clinical scales, time delays are arguably more interpretable to patients and their families. However, it is yet to be established what constitutes a meaningful time delay in AD progression. Method Assess how different hypothetical delays in disease progression in early symptomatic AD translate into treatment differences on the Clinical Dementia Rating Sum of Boxes (CDR‐SB) based on published results placebo‐arm trajectories in recent anti‐amyloid trials. Estimates are compared to published estimates of minimal clinically important differences (MCIDs) in AD and meaningful delays in progression in other diseases. Result Based on placebo arms from six recent trials of anti‐amyloid antibodies, a 6‐month delay over 18 months (33% slowing) corresponded to treatment differences on CDR‐SB between ‐0.5 and ‐0.8, a 12‐month delay (67% slowing) corresponded to treatment differences between ‐1.0 and ‐1.7, and completely stopping progression (18‐month delay) corresponded to treatment differences between ‐1.6 and ‐2.3 (Figure 1, Table 1). Observed treatment effects in the EMERGE, CLARITY‐AD and TRAILBLAZER‐ALZ trials are consistent with approximately 4‐6 months delay of progression (22‐30% slowing, Figure 1). Established MCIDs in CDR‐SB in early AD range between 1.0 and 1.6, suggesting that a 12‐month delay or 67% slowing of disease progression in an 18‐month trial would be considered borderline in terms of clinical meaningfulness. Conclusion Quantifying treatment effects in progressive diseases such as AD in terms of time delays or slowing of progression may offer a more meaningful interpretation of the treatment effects. Based on the trajectories of placebo group in recent trials, we found that treatment effects matching conventionally used MCIDs in AD would correspond to a very substantial slowing of disease (>67%), suggesting that current MCIDs for CDR‐SB are likely inflated.
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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 | 0.020 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".