Validation of the 7‐item Functional Assessment of Cancer Therapy‐General (FACT‐G7) as a short measure of quality of life in patients with advanced cancer
Bibliographic record
Abstract
BACKGROUND: Assessing quality of life is essential for individuals with advanced cancer, but lengthy assessments can be burdensome. The authors investigated the psychometric characteristics of the FACT-G7, a 7-item quality-of-life measure derived from the Functional Assessment of Cancer Therapy-General (FACT-G) scale, in advanced cancer. METHODS: Data were obtained from outpatients with advanced cancer who were enrolled in a randomized controlled trial of early palliative care. At baseline, 228 intervention participants and 233 control participants (N = 461) completed the FACT-G and measures of symptom severity, quality of life near the end of life, problematic medical communication, and satisfaction with care. Follow-up measures were administered monthly for 4 months. RESULTS: The FACT-G7 showed good internal consistency (Cronbach α = .72-.80), and its single-factor structure was supported. It correlated strongly with the FACT-G total, physical, and functional indices and with symptom severity (absolute r = 0.73-0.92); more moderately with the FACT-G emotional index and with symptom impact and preparation for the end of life (r = .40-.71); and least with the FACT-G social/family index and with relationship with health care provider, life completion, problematic medical communication, and care satisfaction measures (absolute r = .26-.44). Eastern Cooperative Oncology Group performance status groups differed on FACT-G7 scores, as expected (all P < .001). Improvements in FACT-G7 scores in the intervention group compared with the control group at 3-month (P = .049) and 4-month (P = .034) follow-up supported responsiveness to change and somewhat greater sensitivity than the FACT-G scores. CONCLUSIONS: The FACT-G7 is a valid, brief measure particularly of the physical and functional facets of quality of life. It may enable rapid quality-of-life assessments in patients with advanced cancer.
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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) | 0.001 | 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) | 0.001 | 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 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".