Functional Assessment of Cancer Therapy-General (FACT-G)
Also known as: FACT-General
The FACT-G is a 27-item self-report questionnaire measuring health-related quality of life in cancer patients across four key domains: physical, social/family, emotional, and functional well-being. Developed by Cella et al. in 1993, it has become one of the most widely used generic QoL instruments in oncology research and clinical practice, translated into 40+ languages and validated across diverse cancer populations.
Key highlights
- Extensively validated in 40+ languages and diverse cancer populations; strong psychometric properties (Cronbach α ≥0.85 for most subscales) and test–retest reliability (ICC ≥0.80).
- Responsive to clinical change; detects improvements from treatment or supportive interventions; demonstrates dose–response with symptom severity.
- Subscale specificity allows nuanced assessment; low burden on patients (5–10 min); easy scoring and interpretation for clinicians.
- Integrates well into modular system; FACT-B, FACT-H, FACT-C (colorectal), FACT-L (lung), FACT-O (ovarian) and others add cancer-specific items while maintaining core FACT-G structure.
Intuition
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How it works
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When to use it
FACT-G is appropriate for any cancer type and stage, from newly diagnosed through survivorship. It serves as a generic baseline before administering disease- or treatment-specific modules (FACT-B for breast cancer, FACT-H for head/neck, etc.). Use in clinical trials to measure QoL efficacy of novel therapies, in supportive care research to evaluate interventions (psychosocial, rehabilitation), and in routine clinical practice to track patient-reported outcomes and guide survivorship care planning. Particularly valuable for comparison across different cancer types or treatment modalities.
Strengths & limitations
- Extensively validated in 40+ languages and diverse cancer populations; strong psychometric properties (Cronbach α ≥0.85 for most subscales) and test–retest reliability (ICC ≥0.80).
- Responsive to clinical change; detects improvements from treatment or supportive interventions; demonstrates dose–response with symptom severity.
- Subscale specificity allows nuanced assessment; low burden on patients (5–10 min); easy scoring and interpretation for clinicians.
- Integrates well into modular system; FACT-B, FACT-H, FACT-C (colorectal), FACT-L (lung), FACT-O (ovarian) and others add cancer-specific items while maintaining core FACT-G structure.
- No single universal cutoff; requires clinical judgment and knowledge of population norms. Published means vary by cancer type, stage, and treatment phase, necessitating context-specific interpretation.
- Modest ceiling effect in early-stage or survivor populations with high baseline QoL; may miss subtle changes in already-well populations.
- Emotional and functional well-being subscales are relatively short (6–7 items each); limited granularity for single-domain changes.
- Dependent on literacy; may require simplified language or interviewer administration in some populations.
Common pitfalls
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Applications
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Frequently asked
Does FACT-G include fatigue assessment?
FACT-G includes one fatigue item ('I have energy to do daily activities'; item 4 in Physical Well-being subscale), but it is not a comprehensive fatigue assessment. For detailed fatigue profiling, use disease-specific FACT modules (e.g., FACT-G + FACT/GOG-Ntx for chemotherapy-related peripheral neuropathy) or dedicated fatigue scales (Piper Fatigue Scale, FACT-F Fatigue Subscale).
What is a clinically meaningful change in FACT-G scores?
Published estimates vary by subscale and population, but an overall change of ≥5–7 points on the total FACT-G score (out of 0–108) is generally considered clinically meaningful. Some analyses suggest effect-size benchmarks: small (d≈0.2), medium (d≈0.5), and large (d≈0.8). Use population-specific anchor-based data when available.
Can FACT-G be used in non-cancer chronic illness populations?
The FACT-G was developed specifically for cancer; using it in other chronic illnesses (e.g., diabetes, COPD) requires validation. While the constructs (physical, emotional, social, functional) are universal, cancer-specific language and symptom expectations may not align. Consult published validation studies before adapting FACT-G to non-cancer populations.
How do I account for cancer-type-specific differences when interpreting FACT-G?
Published norms exist for major cancer types (breast, lung, colorectal, ovarian, head/neck). Reference means for breast cancer: ~75–80; lung cancer: ~65–70; early-stage survivors: ~80–85. Always compare patient scores to cancer-type and treatment-phase matched reference data. Disease-specific FACT modules (FACT-B, FACT-L, FACT-C) may be more sensitive to type-specific symptoms.
Sources
- 1.Cella, D. F., Tulsky, D. S., Gray, G., et al. (1993). The Functional Assessment of Cancer Therapy scale: development and validation of a general measure. J Clin Oncol, 11(3), 570–579.
- 2.Brady, M. J., Cella, D. F., Mo, F., et al. (1997). Reliability and validity of the Functional Assessment of Cancer Therapy-Breast quality-of-life instrument. J Clin Oncol, 15(3), 974–986.
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Cite this page
ScholarGate. (2026, June 3). FACT-G. ScholarGate. https://scholargate.app/oncology-nursing/fact-g