Real-World Patient- and Caregiver-reported Outcomes in Advanced Breast Cancer
Bibliographic record
Abstract
Background: Advanced breast cancer (abc) represents a substantial burden for patients and caregivers. In the present study, we aimed to estimate quality of life (qol), utility, productivity loss, pain, health care resource utilization, and costs for patients with abc, and qol, utility, and productivity loss for their caregivers. Methods: This multicentre prospective non-interventional study was conducted in Canada. Eligible participants were postmenopausal women with estrogen receptor-positive, her2-negative unresectable abc and their caregivers. Validated questionnaires were used to measure qol, utility, productivity loss, and pain. Patients and caregivers were classified into 4 health states typically used in oncology economic modelling: first-line progression-free (1l-pf), first-line progressive disease (1l-pd), second- or subsequent-line progression-free (≥2l-pf), and second- or subsequent-line progressive disease (≥2l-pd). Results: Most patients and caregivers accepted to participate, with total recruitment of 202 patients and 78 caregivers. Compared with patients in pf, patients in pd had lower mean qol scores (52.9 ± 29.9 for 1l-pd vs. 68.2 ± 23.2 for 1l-pf, and 54.0 ± 23.6 for ≥2l-pd vs. 66.0 ± 22.1 for ≥2l-pf), lower mean utility values (0.64 ± 0.22 for 1l-pd vs. 0.73 ± 0.20 for 1l-pf, and 0.65 ± 0.25 for ≥2l-pd vs. 0.74 ± 0.18 for ≥2l-pf), and greater productivity loss (39.4 ± 27.7 for 1l-pd vs. 27.5 ± 30.1 for 1l-pf, and 37.6 ± 29.2 for ≥2l-pd vs. 32.0 ± 29.0 for ≥2l-pf). Compared with caregivers of patients in pf, caregivers of patients in pd had lower qol scores and utility values, and greater productivity loss. Conclusions: Study results indicate that, for patients and caregivers, pd health states are associated with a deterioration of qol and utility and a decrease in productivity in both 1l and ≥2l.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".