Unmet needs and barriers in venous thromboembolism education and awareness among people living with cancer: a global survey
Bibliographic record
Abstract
BACKGROUND: Venous thromboembolism (VTE) is a major preventable cause of morbidity, disability, and mortality in subjects with cancer. A global appraisal of cancer-associated VTE education and awareness is not available. OBJECTIVES: To evaluate VTE-related education, awareness, and unmet needs from the perspective of people living with cancer using a quantitative and qualitative approach. METHODS: This cross-sectional study used data from an online-based survey covering multidimensional domains of cancer-associated VTE. Data are presented descriptively. Potential differences across participant subgroups were explored. RESULTS: Among 2262 patients with cancer from 42 countries worldwide, 55.3% received no VTE education throughout their cancer journey, and an additional 8.2% received education at the time of VTE diagnosis only, leading to 63.5% receiving no or inappropriately delayed education. When education was delivered, only 67.8% received instructions to seek medical attention in case of VTE suspicion, and 36.9% reported scarce understanding. One-third of participants (32.4%) felt psychologically distressed when becoming aware of the potential risks and implications connected with cancer-associated VTE. Most responders (78.8%) deemed VTE awareness highly relevant, but almost half expressed concerns about the quality of education received. While overall consistent, findings in selected survey domains appeared to numerically differ across age group, ethnicity, continent of residence, educational level, metastatic status, and VTE history. CONCLUSION: This study involving a large and diverse population of individuals living with cancer identifies important unmet needs in VTE-related education, awareness, and support across healthcare systems globally. These findings unveil multilevel opportunities to expedite patient-centered care in cancer-associated VTE prevention and management.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".