Lineberger Comprehensive Cancer Center, School of Medicine, The University of North Carolina, Chapel Hill, NC, USA.
Department of Health Policy and Management, The University of North Carolina At Chapel Hill, Chapel Hill, NC, USA.
Qual Life Res. 2021 Oct;30(10):2919-2928. doi: 10.1007/s11136-021-02871-9. Epub 2021 May 16.
To create a crosswalk that predicts Short Form 6D (SF-6D) utilities from Memorial Anxiety Scale for Prostate Cancer (MAX-PC) scores.
The data come from prostate cancer patients enrolled in the North Carolina Prostate Cancer Comparative Effectiveness & Survivorship Study (NC ProCESS, N = 1016). Cross-sectional data from 12- to 24-month follow-up were used as estimation and validation datasets, respectively. Participants' SF-12 scores were used to generate SF-6D utilities in both datasets. Beta regression mixture models were used to evaluate SF-6D utilities as a function of MAX-PC scores, race, education, marital status, income, employment status, having health insurance, year of cancer diagnosis and clinically significant prostate cancer-related anxiety (PCRA) status in the estimation dataset. Models' predictive accuracies (using mean absolute error [MAE], root mean squared error [RMSE], Akaike information criterion [AIC] and Bayesian information criterion [BIC]) were examined in both datasets. The model with the highest prediction accuracy and the lowest prediction errors was selected as the crosswalk.
The crosswalk had modest prediction accuracy (MAE = 0.092, RMSE = 0.114, AIC = - 2708 and BIC = - 2595.6), which are comparable to prediction accuracies of other SF-6D crosswalks in the literature. About 24% and 52% of predictions fell within ± 5% and ± 10% of observed SF-6D, respectively. The observed mean disutility associated with acquiring clinically significant PCRA is 0.168 (standard deviation = 0.179).
This study provides a crosswalk that converts MAX-PC scores to SF-6D utilities for economic evaluation of clinically significant PCRA treatment options for prostate cancer survivors.
建立一个转换工具，将前列腺癌患者的 Memorial Anxiety Scale for Prostate Cancer（MAX-PC）评分转换为 Short Form 6D（SF-6D）效用值。
数据来自参加北卡罗来纳前列腺癌比较效果和生存研究（NC ProCESS，N=1016）的前列腺癌患者。12-24 个月的随访横截面数据分别用作估计和验证数据集。在两个数据集中，使用参与者的 SF-12 评分生成 SF-6D 效用值。贝叶斯混合模型用于评估 MAX-PC 评分、种族、教育程度、婚姻状况、收入、就业状况、是否有健康保险、癌症诊断年份和前列腺癌相关焦虑的临床显著状态（PCRA）对估计数据集中 SF-6D 效用的影响。在两个数据集中，通过平均绝对误差（MAE）、均方根误差（RMSE）、赤池信息量准则（AIC）和贝叶斯信息准则（BIC）来检验模型的预测准确性。选择预测准确性最高且预测误差最低的模型作为转换工具。
该转换工具的预测准确性中等（MAE=0.092，RMSE=0.114，AIC=-2708，BIC=-2595.6），与文献中其他 SF-6D 转换工具的预测准确性相当。约 24%和 52%的预测值分别落在观察到的 SF-6D 的±5%和±10%范围内。与获得临床显著 PCRA 相关的观察到的平均不效用为 0.168（标准差=0.179）。
本研究提供了一个将 MAX-PC 评分转换为 SF-6D 效用的转换工具，可用于评估前列腺癌幸存者中治疗临床显著 PCRA 的治疗方案的经济效果。
