Steel J L, Eton D T, Cella D, Olek M C, Carr B I
University of Pittsburgh School of Medicine, Starzl Transplantation Institute, Liver Cancer Center, Pittsburgh, PA 15213, USA.
Ann Oncol. 2006 Feb;17(2):304-12. doi: 10.1093/annonc/mdj072. Epub 2005 Dec 15.
To test the reliability, sensitivity to change in biomarkers associated with disease progression and response to treatment, and clinical meaningfulness of the Functional Assessment of Cancer Therapy-Hepatobiliary (FACT-Hep) in patients with hepatobiliary carcinoma.
One hundred and fifty-eight patients diagnosed with hepatobiliary carcinoma were prospectively studied. Health-related quality of life (HRQL) was assessed at baseline (prior to treatment), 3-month follow-up (n=55) and 6-month follow-up (n=27).
The internal consistency of all the scales of the FACT-Hep were adequate at all time points (>0.75). The FACT-Hep was found to be sensitive to changes in clinical indicators (alkaline phosphate, alpha-fetoprotein, hemoglobin and survival) that reflect disease progression and response to treatment. Combined results from distribution-based and cross-sectional anchor-based analyses provide the following minimally important difference (MID) estimates: FACT-General (FACT-G) subscales=2-3; FACT-G=6-7; Hepatobiliary Cancer Subscale=5-6; FACT-Hep=8-9; Trial Outcome Index=7-8; and FACT-Hepatobiliary Symptom Index=2-3 points.
The FACT-Hep is a reliable instrument that is responsive to clinical indicators of disease progression and response to treatment. The MID estimates can aid interpretation of HRQL data and facilitate sample size calculation in clinical trials.
为了测试癌症治疗功能评估-肝胆(FACT-Hep)量表在肝胆癌患者中的可靠性、对与疾病进展和治疗反应相关的生物标志物变化的敏感性以及临床意义。
对158例诊断为肝胆癌的患者进行前瞻性研究。在基线(治疗前)、3个月随访(n = 55)和6个月随访(n = 27)时评估健康相关生活质量(HRQL)。
FACT-Hep所有量表在各个时间点的内部一致性均良好(>0.75)。发现FACT-Hep对反映疾病进展和治疗反应的临床指标(碱性磷酸酶、甲胎蛋白、血红蛋白和生存率)的变化敏感。基于分布和基于横断面锚定分析的综合结果提供了以下最小重要差异(MID)估计值:FACT-通用(FACT-G)子量表=2-3;FACT-G = 6-7;肝胆癌子量表=5-6;FACT-Hep = 8-9;试验结果指数=7-8;以及FACT-肝胆症状指数=2-3分。
FACT-Hep是一种可靠的工具,对疾病进展和治疗反应的临床指标有反应。MID估计值有助于解释HRQL数据并便于在临床试验中计算样本量。