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Record W2988950881 · doi:10.1182/blood-2019-128095

Patient Preferences Regarding Anticoagulation Therapy in Patients with Cancer Having a VTE Event - a Discrete Choice Experiment in the Cosimo Study

2019· article· en· W2988950881 on OpenAlexaffabout
Nils Picker, Alexander T. Cohen, Anthony Maraveyas, Jan Beyer‐Westendorf, Agnes Yuet Ying Lee, LG Mantovani, Yoriko De Sanctis, Khaled Abdelgawwad, Samuel Fatoba, Miriam Bach, Thomas Wilke

Bibliographic record

VenueBlood · 2019
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineVitamin K antagonistDosingRivaroxabanObservational studyRegimenWarfarinCancerIntensive care medicineInternal medicine

Abstract

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Introduction: Current guidelines recommend low-molecular-weight heparins (LMWH) over Vitamin K Antagonists (VKA) or Non-Vitamin K Antagonist Oral Anticoagulants (NOAC) for the treatment of cancer-associated venous thromboembolism (CAT), but also highlight that ultimately the choice of anticoagulant depends on patient-specific factors such as patient preferences, which is important for the acceptance of the treatment and, thus, for adherence and persistence. So far, little is known about the specific preferences of patients with CAT with respect to anticoagulation therapy. More specifically, the impact of dosing regimen, convenience and costs on patient preferences in CAT is poorly understood. Therefore, the objective of this discrete choice experiment (DCE) was to elucidate patient preferences regarding anticoagulation convenience attributes. Methods: Adult patients with active cancer who experienced a CAT event and for whom the decision was made to start a treatment with rivaroxaban after being treated with the standard of care anticoagulation (LMWH/VKA) for at least four weeks were included in a multinational, observational, single-arm study (COSIMO). As part of this study, a DCE was presented to the participants, who were asked to decide between complete hypothetical treatment options based on a combination of different attributes, regardless of efficacy or safety. The following attributes were preselected in a face-to-face discussion with three focus patients and in-depth interviews with four additional patients: route of administration (injection / tablet),frequency of intake (once / twice daily),need of regular controls of the International Normalized Ratio (INR) at least every 3-4 weeks (yes/no),interactions with food/alcohol (yes/no). Additionally, distance to treating physician (1 km vs. 20 km) was included as neutral comparator to express patients' overall utility in terms of a comprehensible unit. The relative importance of treatment attributes in terms of distances were calculated based on ratios between the utility estimates for each attribute. A fractional factorial design was generated resulting in nine hypothetical choice sets, supplemented by a test choice set to assess the consistency of a patient's responses. DCE data was collected by semi-structured telephone interviews, performed between week 4 and week 12 after enrollment of patients in the study and start of rivaroxaban. For each patient participating in the DCE interview, a written informed consent was obtained. Patient preferences were analyzed based on a conditional logit regression model. Results: Overall, 163 patients were included (Europe: 119; Canada: 41; Australia: 3), mean age 63.7 years, 49.1% were females and diagnosed with cancer for on average 22.4 months. Most patients in the COSIMO study changed to rivaroxaban from LMWH (> 95.0 %). The median time from diagnosis of index CAT event to conduct of DCE was 150 days (IQR 88-229). Patients strongly preferred oral administration compared to self-injections and drugs that can be taken irrespective of type of food or alcohol consumption (Figure 1). Furthermore, patients indicated slight preference for a shorter distance to the treating physician and a once daily dosing regimen compared to a twice-daily intake. The attribute "INR controls" showed no significant impact on the treatment decision. In order of patients' preference for their choice of treatment, the route of administration was by far the most important attribute for a patient's choice (73.8% of the overall decision), followed by food interactions (11.8%), the distance to treating physician (7.2%) and the intake frequency (6.5%). Accordingly, the expected utility of patients receiving an oral anticoagulation can be expressed as willingness to travel an additional distance of 192 km to the treating physician in order to avoid an injection. Conclusions Treatment related decision-making of patients with CAT, assuming equal effectiveness and safety of treatments, is predominantly driven by "route of administration", indicating a strong preference for oral intake. Disclosures Picker: Ingress-Health: Employment. Cohen:Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; ACI Clinical: Consultancy; GLG: Consultancy; GlaxoSmithKline: Consultancy, Speakers Bureau; Daiichi-Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; CSL Behring: Consultancy; Boston Scientific: Consultancy; AbbVie: Consultancy; Boehringer-Ingelheim: Consultancy, Speakers Bureau; Bayer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Aspen: Consultancy, Speakers Bureau; Guidepoint Global: Consultancy; Johnson and Johnson: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Leo Pharma: Consultancy; Medscape: Consultancy, Speakers Bureau; McKinsey: Consultancy; Navigant: Consultancy; ONO: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Portola: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy; Temasek Capital: Consultancy; TRN: Consultancy; UK Government Health Select Committee: Other: advised the UK Government Health Select Committee, the all-party working group on thrombosis, the Department of Health, and the NHS, on the prevention of VTE; Lifeblood: Other: advisor to Lifeblood: the thrombosis charity and is the founder of the European educational charity the Coalition to Prevent Venous Thromboembolism. Maraveyas:Bayer AG: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria; Pfizer: Honoraria. Beyer-Westendorf:Pfizer: Honoraria, Research Funding; Bayer HealthCare: Honoraria, Research Funding; Boehringer Ingelheim: Honoraria, Research Funding; Daiichi Sankyo: Honoraria, Research Funding. Lee:Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Bayer: Consultancy, Honoraria; LEO Pharma: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria. Mantovani:Fondazione Charta: Consultancy; Bayer AG: Honoraria; Boehringer Ingelheim: Honoraria, Research Funding; Pfizer: Honoraria; Daiichi Sankyo: Research Funding. De Sanctis:Bayer US LLC: Employment, Equity Ownership. Abdelgawwad:Bayer AG: Employment. Fatoba:Bayer AG: Employment. Bach:Bayer AG: Employment. Wilke:Astra Zeneca: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Novo Nordisk: Consultancy, Honoraria; Pharmerit: Consultancy, Honoraria; Bayer AG: Consultancy, Honoraria; LEO Pharma: Consultancy, Honoraria; GlaxoSmithKline: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Boehringer Ingelheim: Consultancy, Honoraria.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.237
GPT teacher head0.503
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations5
Published2019
Admission routes2
Has abstractyes

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