Estimating incident and prevalent essential thrombocythemia patients eligible for cytoreductive therapies in the US and Canada
Bibliographic record
Abstract
Abstract Introduction: Essential thrombocythemia (ET) is a rare type of myeloproliferative neoplasm (MPN) characterized by elevated platelet counts an elevated risk of thromboembolic events, bleeding and potential progression to myelofibrosis or acute myeloid leukemia. The current treatment landscape for ET remains limited, further complicated by historically non-specific ICD-10 diagnosis codes and ET patients incurring 2.3 times higher medical costs compared to matched controls. This study aimed to estimate the incidence and prevalence of ET patients eligible for National Comprehensive Cancer Network (NCCN) guideline-directed treatments within major U.S. health plans and in Canada. Methods: The literature was assessed systematically to gather epidemiological data on ET prevalence and incidence, determine the distribution of patients according to the revised IPSET-thrombosis risk stratification (rIPSET-T), and identify those eligible for NCCN 1.2025-recommended cytoreductive therapies. Membership data for the eight largest U.S. commercial health plans were sourced from earnings reports, annual filings, and 10-K reports. These data were used in Microsoft Excel to develop model inputs and conduct a base-case analysis estimating the size of the clinically treatment-eligible population potentially receiving NCCN-recommended therapies. Results: Sixteen references were identified across systematic literature searches detailing ET epidemiology, rIPSET-T risk distributions, and the use of NCCN-recommended treatments. For the eight health plans analyzed, the average (median) number of covered lives in the U.S. was 38,725,462 (27,847,800). In Canada, prescription drug coverage is limited to 79%, representing 25,557,474 covered lives in 2024. The analysis identified an average of 426 (SD±362) incident ET patients and 16,915 (SD±14,379) prevalent ET patients across U.S. health plans, while Canada had 281 incident and 11,164 prevalent ET patients. Among these, a mean of 192 (SD±109) incident high-risk and 8,797 (SD±7,479) prevalent intermediate- and high-risk rIPSET-T eligible patients were estimated for U.S. health plans, with corresponding figures for Canada being 127 incident high-risk and 5,806 prevalent intermediate- and high-risk patients. Cytoreductive therapy usage was found to be 72.5%, translating to an average of 128 (SD±109) incident and 5,101 (SD±3,690) prevalent patients for U.S. health plans, and 85 incident and 3,366 prevalent patients in Canada. Conclusion: There is significant variability in the estimates of both incident and prevalent ET populations eligible for NCCN-recommended cytoreductive therapies across U.S. commercial health plans and in Canada, which may influence formulary policy decisions.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.015 | 0.025 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".