MO561PREFERENCES OF DIALYSIS-DEPENDENT PATIENTS FOR TREATMENT OF ANAEMIA OF CHRONIC KIDNEY DISEASE IN AUSTRALIA AND CANADA: A DISCRETE CHOICE EXPERIMENT
Bibliographic record
Abstract
Abstract Background and Aims Anaemia is a common complication of chronic kidney disease (CKD) and is associated with reduced quality of life, cardiovascular complications, early mortality and a high economic burden for patients. Current treatment options for anaemia of CKD include subcutaneous (SC) or intravenous (IV) erythropoiesis-stimulating agents (ESAs) with or without supplementary iron and blood transfusions. New oral therapies for anaemia, such as hypoxia-inducible factor prolyl hydroxylase inhibitors, are in development and may have advantages for patients compared with ESAs. It is therefore crucial to understand the treatment attributes that patients consider most important. This study aimed to investigate patient preferences for potential anaemia of CKD treatments in adults with dialysis-dependent (DD) CKD in Australia and Canada. Method Adult patients with DD CKD completed a discrete choice experiment (DCE) online survey. In each scenario, patients were asked to choose between three hypothetical treatment alternatives (‘oral pill’, ‘subcutaneous injection’ and ‘intravenous injection’) with differing levels of attributes and an opt-out option (none of these treatments/current treatment) to treat anaemia of CKD. Treatment attributes focused on administration (where, how often and by whom), purchasing (where it is collected and the cost per month), additional benefits (e.g. whether it reduces ‘bad’/LDL cholesterol), side effects (chance of hospitalization from a heart attack or stroke due to the medicine) and the need for rescue therapy (IV iron or blood transfusion). The attributes and their levels were derived from existing market research, the literature and expert opinion. A mixed multinomial logit model, which allows for preference heterogeneity, was used to quantify the overall value of such treatments and the relative importance of each of the defining attributes. Australian patients were divided into those who were eligible for reduced prescription charges under the Pharmaceutical Benefits Scheme, such as the elderly or those on low incomes (referred to as concessions), and those who were not (general patients). Prescription charge concessions did not apply for Canadian patients. Results This preliminary analysis included 61 patients with DD CKD from Australia (n = 22) and Canada (n = 39). The majority of patients were receiving haemodialysis (Australia, 72.7%; Canada, 61.5%), and more than half received their dialysis in a clinic or hospital (Australia, 54.5%; Canada, 76.9%); 50% of the Australian patients were concessions. In both countries, patients were likely to choose a new treatment alternative over the opt-out, with the greatest preference for oral treatment among Australian general and Canadian patients, all else being equal. For Australian concession patients, cost per month was the most important attribute across all treatment options; the risk of side effects (i.e. hospitalization from a heart attack or stroke) was the second most important attribute, with patients preferring treatments with the lowest possible risk. For Australian general and Canadian patients, the risk of side effects and the cost per month were the two most important attributes, and had similar levels of importance. Patients in both countries were also concerned about the risk of needing rescue therapy, and valued reductions in the amount of ‘bad’/LDL cholesterol. Conclusion Results from this DCE study showed that the risk of side effects and the costs of treatment are the most important attributes for hypothetical anaemia of CKD treatment for patients with DD CKD. Australian general and Canadian patients showed a preference for oral therapy over SC or IV injection, all other factors being equal. These findings may help to guide clinicians when selecting treatments for anaemia of CKD for their patients, and may provide useful information when assessing the value of new or future treatments.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".