Doxycycline Plus Bortezomib-Containing Regimens for the Treatment of Light-Chain Amyloidosis in the Frontline Setting: Experience from the Amyloidosis Program of Calgary
Bibliographic record
Abstract
Background: Pre-clinical and retrospective data suggest that doxycycline added to treatment regimens has benefit in AL amyloidosis. However, a recent multicenter, open-label, randomized controlled trial in AL amyloidosis patients treated with CyBorD did not demonstrate a progression-free survival (PFS) or cardiac PFS benefit with added doxycycline. Objective: The main objective of this study was to explore the role of doxycycline combined with bortezomib-containing regimens (BCRs) for newly diagnosed AL amyloidosis patients with cardiac involvement and to compare them with a cohort of concurrent patients treated with BCR only. Material and Methods: AL amyloidosis patients, newly diagnosed between January 2012 and March 2022, who were treated with BCR at the Amyloidosis Program of Calgary (APC) were evaluated. Results: Sixty-four concurrent patients were identified. Thirty-nine patients received doxycycline in addition to BCR (BCR-D) for a median of 8 months. The overall response rate was similar among the groups. No significant differences in VGPR/CR, dFLC at 1 month, time to first response, time to best response, or organ responses were noted between the BCR alone and BCR-D groups. Summary and Conclusions: Our retrospective study demonstrated that doxycycline combined with BCR failed to prolong OS, PFS, or cardiac responses compared with BCR alone in patients with cardiac AL amyloidosis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".