Faculty of Social Sciences, Hellenic Open University, Bouboulinas 57, Patras, Greece.
Value Health. 2009 Nov-Dec;12(8):1151-7. doi: 10.1111/j.1524-4733.2009.00569.x. Epub 2009 Jun 25.
To estimate models, via ordinary least squares regression, for predicting Euro Qol 5D (EQ-5D), Short Form 6D (SF-6D), and 15D utilities from scale scores of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30).
Forty-eight gastric cancer patients, split up into equal subgroups by age, sex, and chemotherapy scheme, were interviewed, and the survey included the QLQ-C30, SF-36, EQ-5D, and 15D instruments, along with sociodemographic and clinical data. Model predictive ability and explanatory power were assessed by root mean square error (RMSE) and adjusted R(2) values, respectively. Pearson's r between predicted and reported utility indices was compared. Three random subsamples, half in size the initial sample, were created and used for "external" validation of the modeling equations.
Explanatory power was high, with adjusted R(2) reaching 0.909, 0.833, and 0.611 for 15D, SF-6D, and EQ-5D, respectively. After normalization of RMSE to the range of possible values, the prediction errors were 12.0, 5.4, and 5.6% for EQ-5D, SF-6D, and 15D, respectively. The estimation equations produced a range of utility scores similar to those achievable by the standard scoring algorithms. Predicted and reported indices from the validation samples were comparable thus confirming the previous results.
Evidence on the ability of QLQ-C30 scale scores to validly predict 15D and SF-6D utilities, and to a lesser extent, EQ-5D, has been provided. The modeling equations must be tried in future studies with larger and more diverse samples to confirm their appropriateness for estimating quality-adjusted life-year in cancer-patient trials including only the QLQ-C30.
通过普通最小二乘法回归估计模型，以预测欧洲癌症研究与治疗组织生活质量问卷（EORTC QLQ-C30）量表评分与 EQ-5D、SF-6D 和 15D 效用值之间的关系。
将 48 例胃癌患者按照年龄、性别和化疗方案分为相等的亚组，对其进行访谈，调查内容包括 QLQ-C30、SF-36、EQ-5D 和 15D 量表以及社会人口统计学和临床数据。通过均方根误差（RMSE）和调整后的 R2 值分别评估模型的预测能力和解释能力。比较预测和报告的效用指数之间的 Pearson r 值。创建了三个随机子样本，每个样本的大小均为初始样本的一半，用于对建模方程进行“外部”验证。
解释能力较高，调整后的 R2 值分别为 0.909、0.833 和 0.611，用于 15D、SF-6D 和 EQ-5D。在将 RMSE 归一化为可能值的范围后，EQ-5D、SF-6D 和 15D 的预测误差分别为 12.0%、5.4%和 5.6%。估计方程产生的效用评分范围与标准评分算法相当。验证样本中的预测和报告指标相似，从而证实了先前的结果。
提供了证据证明 QLQ-C30 量表评分能够有效地预测 15D 和 SF-6D 效用值，并且在较小程度上可以预测 EQ-5D。这些建模方程必须在未来的研究中，在更大和更多样化的样本中进行尝试，以确认它们在仅包含 QLQ-C30 的癌症患者试验中估计质量调整生命年的适用性。
