Patient and physician perceptions regarding treatment expectations and symptomatology in polycythemia vera: Insights from the Landmark 2.0 global health survey
Bibliographic record
Abstract
Polycythemia vera (PV) is a myeloproliferative neoplasm associated with a high symptom and psychological burden, resulting in decreased quality of life (QoL). Patients with PV have an increased risk of cardiovascular (CV) complications, making regular monitoring crucial. The Landmark 2.0 survey was conducted worldwide among patients with PV and their treating physicians to identify any potential gaps in perceptions regarding PV management. Data were collected between April 2021 and April 2022 from physicians and patients across 11 countries. Overall, 133 physicians and 274 patients with PV participated in the survey. There were discrepancies between physicians and patients in reporting whether symptom assessments and basic CV assessments were conducted during routine visits (83% vs. 68% and 64% vs. 55%, respectively). Emotional assessments were not performed routinely (reported by 36% of physicians and 34% of patients). Patients attributed the highest impact on QoL to physical symptoms (67%); however, physicians were less likely to report highly prevalent symptoms such as bruising, difficulty sleeping, inactivity, and depression among the most common symptoms. While both physicians and patients aimed for symptom improvement, their treatment goals differed: physicians focused on managing hematocrit, preventing thrombotic events, and reducing spleen size, while patients focused on slowing down disease progression. Patient satisfaction with treatment was generally high but decreased in later therapy stages. Overall, these data underscore the disparity in patient-physician perceptions of PV management and treatment expectations, showing the gaps in communication and the need for greater patient education, as well as highlighting areas for potential improvement in clinical practice.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".