Modeling the Cost and Health Impacts of Diagnostic Strategies in Patients with Suspected Transthyretin Cardiac Amyloidosis
Bibliographic record
Abstract
Background Transthyretin cardiac amyloidosis (ATTR‐CMP) is an increasingly recognized and treatable cause of heart failure with preserved ejection fraction. Multimodality cardiac imaging is recommended for ATTR‐CMP diagnosis, but its cost‐effectiveness in current clinical practice has not been well studied. Methods and Results Using a microsimulation model, we compared the cost‐effectiveness of a combination of strategies involving 99m technetium pyrophosphate (PYP), cardiac magnetic resonance imaging, and endomyocardial biopsy for the diagnosis of ATTR‐CMP. We developed a decision analytic model to project health care costs and lifetime quality‐adjusted life years for symptomatic, older patients who present with congestive heart failure, with an increased left ventricular wall thickness and a 13% prevalence of ATTR‐CMP. Rates of clinical events, costs, and quality‐of‐life values were estimated from published literature. The analysis was conducted from a US health care system perspective with health and cost outcomes discounted annually at 3%. In the base‐case scenario, using a fixed tafamidis price of $16 000 annually (previously identified cost‐effective price), total health care costs per person were lowest for the PYP‐only strategy ($209 415) and highest for endomyocardial biopsy strategy ($215 881). Of the 7 strategies examined, the PYP‐only strategy had the highest net monetary benefit using a willingness‐to‐pay threshold of $100 000/quality‐adjusted life year. Results were sensitive to variations in model inputs for PYP and cardiac magnetic resonance imaging specificity, cost of tafamidis, and willingness‐to‐pay thresholds. Conclusions Our model‐based analyses showed that a PYP‐only strategy to diagnose ATTR‐CMP is the most cost‐effective strategy, at willingness‐to‐pay threshold of $100 000/quality‐adjusted life year. At higher threshold ($150 000/quality‐adjusted life year), sequential tests involving PYP and cardiac magnetic resonance imaging may be considered cost effective.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".