Second Version of the Short Form 6-Dimension Value Set Elicited From Patients With Breast and Colorectal Cancer
Bibliographic record
Abstract
BACKGROUND: Quality-adjusted life-year instruments help comparison among programs by capturing their effects in terms of utility. Generic instruments are applicable to everyone, and for this reason, they are known to lack sensitivity when measuring gains in some domains. Specific instruments tend to fill this gap but, in domains like cancer, existing instruments are either nonpreferences-based or based on the general population's preferences. PATIENTS AND METHODS: This study describes the development of a new value set for a well-known and highly used generic instrument, the Second Version of the Short Form 6-Dimension, to better consider the preferences of patients with cancer. In this aim, a hybrid approach combining the time trade-off and the discrete choice experiment was used. The population of interest was the Quebec population, Canada, with breast or colorectal cancer. Their preferences were elicited in 2 periods: before (T1) and 8 days after the beginning of a chemotherapy procedure (T2). RESULTS: A total of 2808 observations for the time trade-off and 2520 observations for the discrete choice experiment were used. The parsimonious model encompassing the 2 periods was the preferred model. The new value set allows a greater utility range than the EQ-5D-5L and the Second Version of the Short Form 6-Dimension reference value sets and helps in better considering patients experiencing severe health situations. A good correlation between these 2 instruments and other specific cancer instruments (ie, European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, QLU-C10D, and Functional Assessment of Cancer Therapy-General) was observed. Significative differences in utility values were also noted within periods and types of cancer.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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".