Anticoagulation Treatment in Cancer-Associated Venous Thromboembolism: Assessment of Patient Preferences Using a Discrete Choice Experiment (COSIMO Study)
Bibliographic record
Abstract
INTRODUCTION: Clinical guidelines recommend anticoagulation therapy for the treatment of cancer-associated venous thromboembolism (VTE), but little is known about preferences. Therefore, the objective of this discrete choice experiment (DCE) was to elucidate patient preferences regarding anticoagulation convenience attributes. METHODS: Adult patients with cancer-associated VTE who switched to direct oral anticoagulants were included in a single-arm study (COSIMO). Patients were asked to decide between hypothetical treatment options based on a combination of the following attributes: route of administration (injection/tablet), frequency of intake (once/twice daily), need for regular controls of the international normalized ratio (INR) at least every 3 to 4 weeks (yes/no), interactions with food/alcohol (yes/no), and distance to treating physician (1 vs. 20 km) as an additional neutral attribute. DCE data were collected by structured telephone interviews and analyzed based on a conditional logit regression. RESULTS: Overall, 163 patients (mean age 63.7 years, 49.1% female) were included. They strongly preferred oral administration compared with self-injections (importance of this attribute for overall treatment decisions: 73.8%), and a treatment without dietary restrictions (11.8%). Even if these attributes were less important (7.2% and 6.5%, respectively), patients indicated a preference for a shorter distance to the treating physician and once-daily dosing compared with twice-daily intake. "Need for regular controls of INR at least every 3 to 4 weeks" showed no significant impact on the treatment decision (0.7%). CONCLUSION: This study showed that treatment-related decision making in cancer-associated VTE, assuming comparable effectiveness and safety of anticoagulant treatments, is predominantly driven by "route of administration," with patients strongly preferring oral administration.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".