King Madeleine T, Cella David, Osoba David, Stockler Martin, Eton David, Thompson Joanna, Eisenstein Amy
Psycho-oncology Co-operative Research Group School of Psychology, University of Sydney, New South Wales, Australia;
Patient Relat Outcome Meas. 2010 Jul;1:119-26. doi: 10.2147/PROM.S10621. Epub 2010 Sep 23.
Our aim was to develop evidence-based interpretation guidelines for the Functional Assessment of Cancer Therapy-General (FACT-G), a cancer-specific health-related quality of life (HRQOL) instrument, from a range of clinically relevant anchors, incorporating expert judgment about clinical significance. Three clinicians with many years' experience managing cancer patients and using HRQOL outcomes in clinical research reviewed 71 papers. Blinded to the FACT-G results, they considered the clinical anchors associated with each FACT-G mean difference, predicted which dimensions of HRQOL would be affected, and whether the effects would be trivial, small, moderate, or large. These size classes were defined in terms of clinical relevance. The experts' judgments were then linked with FACT-G mean differences, and inverse-variance weighted mean differences were calculated for each size class. Small, medium, and large differences (95% confidence interval) from 1,118 cross-sectional comparisons were as follows: physical well-being 1.9 (0.6-3.2), 4.1 (2.7-5.5), 8.7 (5.2-12); functional well-being 2.0 (0.5-3.5), 3.8 (2.0-5.5), 8.8 (4.3-13); emotional well-being 1.0 (0.1-2.6), 1.9 (0.3-3.5), no large differences; social well-being 0.7 (-0.7 to 2.1), 0.8 (-2.9 to 4.5), no large differences. Results from 436 longitudinal comparisons tended to be smaller than the corresponding cross-sectional results. These results augment other interpretation guidelines for FACT-G with information on sample size, power calculations, and interpretation of cancer clinical trials that use FACT-G.
我们的目标是从一系列临床相关的锚定指标出发,结合关于临床意义的专家判断,为癌症特异性健康相关生活质量(HRQOL)工具——癌症治疗功能评估通用版(FACT-G)制定基于证据的解读指南。三位在管理癌症患者以及在临床研究中使用HRQOL结果方面拥有多年经验的临床医生对71篇论文进行了审查。在对FACT-G结果不知情的情况下,他们考虑了与每个FACT-G平均差异相关的临床锚定指标,预测HRQOL的哪些维度会受到影响,以及影响是微不足道、小、中等还是大。这些量级类别是根据临床相关性定义的。然后将专家的判断与FACT-G平均差异联系起来,并为每个量级类别计算逆方差加权平均差异。来自1118次横断面比较的小、中、大差异(95%置信区间)如下:身体健康1.9(0.6 - 3.2)、4.1(2.7 - 5.5)、8.7(5.2 - 12);功能健康2.0(0.5 - 3.5)、3.8(2.0 - 5.5)、8.8(4.3 - 13);情绪健康1.0(0.1 - 2.6)、1.9(0.3 - 3.5),无大差异;社会健康0.7(-0.7至2.1)、0.8(-2.9至4.5),无大差异。436次纵向比较的结果往往小于相应的横断面结果。这些结果通过关于样本量、功效计算以及使用FACT-G的癌症临床试验解读的信息,扩充了FACT-G的其他解读指南。