Abstract 279: Eligibility and Cost Estimates for Anti-inflammatory Therapy for Atherosclerotic Disease: Implications of the CANTOS Trial for the US Adult Population
Bibliographic record
Abstract
Background: The CANTOS trial supports the use of canakinumab to target residual inflammatory risk for secondary cardiovascular prevention. To better understand the potential impact of these findings, we use nationally representative data to estimate the number of US adults who qualify for therapy with canakinumab and the projected cost burden on the US health system based on its current pricing. Methods: In National Health and Nutrition Examination Survey (NHANES) 2005-10, we identified all adults with a prior MI and elevated hsCRP ≥2 mg/L, and fulfilling all eligibility criteria for CANTOS. Further, we also assessed the number of individuals not receiving statins who might be potentially eligible. Statin non-users were considered potentially eligible if they would have had hsCRP ≥2mg/L even after assuming a maximal hsCRP lowering of 50% with statin therapy in all patients. We used survey methods to obtain weighted estimates for the eligible adults in the US population. Annual costs were estimated at $60000/year for canakinumab therapy. Results: Of the 17689 adults sampled in NHANES during 2005-2010, 16608 (94%) had hsCRP testing. Of these, 684 (3.0%), representing an estimated 6.8 million (95% CI 5.7-7.8 million) US adults, had a history of MI (Figure 1). Among those with a prior MI, 42% did not report using a statin. Among statin-users, 44% had an hsCRP<2 mg/L (32% overall). After applying CANTOS inclusion and exclusion criteria, 21% (unweighted n=128) of adults with a prior MI on statin therapy, representing 1.4 million (95% CI 1.1-1.8 million) US adults, were canakinumab-eligible. A further 9% of AMI patients would be eligible after accounting for statin-associated hsCRP lowering in statin non-users (Figure 1). Cumulatively, 31% (unweighted n=207) of adults with a prior MI, representing 2.1 million (95% CI 1.6-2.5 million) US adults would potentially qualify for canakinumab therapy. The treatment of 5% to 100% of all CANTOS-eligible US adults would cost payers $6-$124 billion/year. Conclusion: Nearly 1 in 3 or 2.1 million US adults with a prior MI are potential treatment candidates. Assuming current canakinumab prices would incur an annual financial burden of up to 124 billion dollars in the United States. Further work is needed to define the population that achieves favorable value with treatment.
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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 | 0.021 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".