Development and validation of the disease-specific QOL-CD quality of life questionnaire for patients with Cushing’s disease
Bibliographic record
Abstract
OBJECTIVE: Cushing's disease (CD) patients experience a range of debilitating symptoms that impair quality of life (QOL) as assessed using generic measures. These generic measures are inadequate to capture the disease-specific burden of illness. The development of the CD-specific QOL-CD measure of QOL using items generated by CD patients and healthcare professionals will provide a holistic assessment of patient outcomes and efficacy of novel therapies. METHODS: A total of 96 CD patients participated. A list of 177 items (version 1.0) was generated by treated CD patients (n = 9), caregivers (n = 2), healthcare providers (n = 7), and results of a MEDLINE search. Item reduction was performed through content analysis and dual scaling. Patients' rating of importance was incorporated to reduce to a final version of 56 items (version 3.0). Evidence for test-retest reliability was sought through administering the QOL-CD 1 week apart and Cronbach's α of each subscale. Construct validity was assessed through extreme group analysis and comparison with the normal Canadian population. Concurrent validity was sought through comparison with the SF-36, Functional Assessment of Cancer Therapy-Brain (FACT-Br), and Karnofsky Performance Status (KPS). Perioperative testing was conducted on CD patients (n = 25) against nonfunctioning pituitary adenoma controls (n = 25) through pre- and postoperative testing. RESULTS: A total of 96 CD patients (86 females and 10 males; mean age 45.23 ± 14.16 years) participated. The QOL-CD was feasible (mean completion time 15 minutes, with 70% believing accurate capture of QOL), reliable (CD 1 week apart: r = 0.86; control 1 week apart: r = 0.83; Cronbach's α: general health = 0.73, emotional health = 0.85, physical health = 0.78, mental status = 0.82, social well-being = 0.63, medical treatment = 0.54), and valid (extreme group testing p < 0.001; SF-36 and QOL-CD general health: r = 0.56, social well-being: r = 0.21, emotional health: r = 0.61, total score: r = 0.58; FACT-Br and QOL-CD physical health: r = 0.47, social well-being: r = 0.21, emotional health: r = 0.34, total score: r = 0.68; KPS and QOL-CD general health: r = 0.32, total score: r = 0.14). Perioperative testing of CD patients (n = 25) demonstrated improvement in all subscales postoperatively, with a significant difference in emotional health (p < 0.001) and physical health (p < 0.001). CONCLUSIONS: The QOL-CD questionnaire has been developed for patients with CD and has demonstrated evidence for validity and reliability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".