Estimating incidence and prevalence of polycythemia vera and associated eligibility for cytoreductive therapies in major US health plans
Bibliographic record
Abstract
Abstract Introduction: Polycythemia vera (PV) is a rare myeloproliferative neoplasm (MPN) characterized by elevated red blood cell production and associated with an increased risk of thromboembolic events, as well as potential progression to myelofibrosis or acute myeloid leukemia. Current treatment approaches for PV follow risk-adapted guidelines from the National Comprehensive Cancer Network (NCCN) and the European Leukemia Net (ELN), which stratify patients into high-risk and low-risk categories. This study aimed to estimate the number of incident and prevalent PV patients eligible for treatment per NCCN guidelines across major U.S. health plans. Methods: The literature was reviewed systematically to identify epidemiological estimates of prevalence and incidence of PV, determine the distribution of NCCN/ELN risk classifications, and assess eligibility for NCCN 1.2025-recommended cytoreductive therapies. Membership data for the eight largest U.S. commercial health plans were extracted from earnings releases, annual reports, and 10-K filings. These data were incorporated into Microsoft Excel to develop model inputs and calculate the base-case estimates of patients clinically eligible for NCCN-recommended therapies. Results: Nine sources were identified to provide data on PV epidemiology, ELN/NCCN risk classification distribution, and utilization of NCCN-recommended therapies through separate systematic searches. A mean of 1.17 (SD ± 0.29) incident and 50.94 (SD ± 5.01) prevalent polycythemia vera (PV) patients per 100,000 individuals were identified through literature. Across the eight health plans analyzed, the mean and median covered lives were 38,725,462 and 27,847,800, respectively. Among these health plans, an average of 453 (SD ± 385) incident and 19,728 (SD ± 16,771) prevalent PV patients were calculated. Of these, a mean of 323 (SD ± 274) incident high-risk and 14,057 (SD ± 11,949) prevalent high-risk PV patients were identified. The proportion of patients using cytoreductive therapy was 37.3%, corresponding to an average of 169 (SD ± 144) incident and 7,354 (SD ± 6,252) prevalent patients.Conclusion: There is significant variability in the estimates of both incident and prevalent PV populations eligible for NCCN-recommended cytoreductive therapies across U.S. commercial health plans, 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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".