Key Takeaways
- In AL amyloidosis response assessment, ≥50% difference in dFLC from baseline defines hematologic response thresholds in consensus guidance
- A systematic review reported that delayed diagnosis in amyloidosis is common, with median delays of about 6 months or more across included studies
- A meta-analysis reported that biopsy sensitivity varies by tissue site, with bone marrow biopsy having lower sensitivity than involved organ biopsy
- Daratumumab-containing regimens produced high overall hematologic response rates in newly diagnosed AL amyloidosis cohorts (reported as ORR in trial analyses)
- In ATTR-ACT, tafamidis reduced the rate of cardiovascular-related hospitalization events compared with placebo (rate ratio reported)
- In APOLLO, 5.5% of patients experienced treatment-related adverse events leading to discontinuation (reported safety discontinuation rate)
- Over 50% of AL amyloidosis patients in real-world claims datasets had cardiac diagnosis codes in the first year after amyloidosis diagnosis
- In a U.S. budget impact analysis, annual incremental costs for commercially available amyloidosis drugs can exceed $100 million at national scale depending on uptake assumptions
- The NICE technology appraisal for tafamidis for transthyretin amyloid cardiomyopathy considered incremental cost-effectiveness versus best supportive care and reported QALY gains (TA reference in guidance)
- ATTRwt has increasing prevalence with age, with most diagnoses occurring in older adults (median age reported across cohorts)
Key amyloidosis data show promising treatments, persistent diagnostic delays, and significant real world clinical and cost burdens.
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How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Priyanka Sharma. (2026, February 13). Amyloidosis Statistics. Gitnux. https://gitnux.org/amyloidosis-statistics
Priyanka Sharma. "Amyloidosis Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/amyloidosis-statistics.
Priyanka Sharma. 2026. "Amyloidosis Statistics." Gitnux. https://gitnux.org/amyloidosis-statistics.
References
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- 2ncbi.nlm.nih.gov/pmc/articles/PMC8090401/
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- 13pubmed.ncbi.nlm.nih.gov/33298609/
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- 14nice.org.uk/guidance/ta533
- 15nice.org.uk/guidance/ta533/chapter/1-Recommendations
- 16cadth.ca/sites/default/files/htis/2020-04/HRP%20Final%20CADTH%20Report%20Patisiran.pdf
- 17cadth.ca/sites/default/files/hta/2019-11/OTN%20Final%20Report%20Inotersen.pdf
- 20sciencedirect.com/science/article/pii/S0278691521000806







