A General Population Utility Valuation Study for Metastatic Epidural Spinal Cord Compression Health States
Bibliographic record
Abstract
STUDY DESIGN: General population utility valuation study. OBJECTIVE: This study obtained utility valuations from a Canadian general population perspective for 31 unique metastatic epidural spinal cord compression (MESCC) health states and determined the relative importance of MESCC-related consequences on quality-of-life. SUMMARY OF BACKGROUND DATA: Few prospective studies on the treatment of MESCC have collected quality-adjusted-life-year weights (termed "utilities"). Utilities are an important summative measure which distills health outcomes to a single number that can assist healthcare providers, patients, and policy makers in decision making. METHODS: We recruited a sample of 1138 adult Canadians using a market research company. Quota sampling was used to ensure that the participants were representative of the Canadian population in terms of age, sex, and province of residence. Using the validated MESCC module for the "Self-administered Online Assessment of Preferences" (SOAP) tool, participants were asked to rate six of the 31 MESCC health states, each of which presented varying severities of five MESCC-related dysfunctions (dependent; non-ambulatory; incontinent; pain; other symptoms). RESULTS: Participants equally valued all MESCC-related dysfunctions which followed a pattern of diminishing marginal disutility (each additional consequence resulted in a smaller incremental decrease in utility than the previous). These results demonstrate that the general population values physical function equal to other facets of quality-of-life. CONCLUSION: We provide a comprehensive set of ex ante utility estimates for MESCC health states that can be used to help inform decision making. This is the first study reporting direct utility valuation for a spinal disorder. Our methodology offers a feasible solution for obtaining quality-of-life data without collecting generic health status questionnaire responses from patients. LEVEL OF EVIDENCE: 4.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.003 | 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".