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Quality of life as a prognostic indicator of survival: A pooled analysis of individual patient data from canadian cancer trials group clinical trials

机译:生存的寿命质量作为生存的预后指标:来自加拿大癌症试验组临床试验的个体患者数据的汇总分析

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BACKGROUND The aims of this study were to externally validate an established association between baseline health‐related quality of life (HRQOL) scores and survival and to assess the added prognostic value of HRQOL with respect to demographic and clinical indicators. METHODS Pooled data were analyzed from 17 randomized controlled trials opened by the Canadian Cancer Trials Group between 1991 and 2004; they included survival and baseline HRQOL data from 3606 patients with 8 different cancer sites. The models included sex, age (≤60 vs 60 years), World Health Organization performance status (0 or 1 vs 2‐4), distant metastases (no vs yes), and 15 European Organization for Research and Treatment of Cancer (EORTC) Core Quality‐of‐Life Questionnaire (QLQ‐C30) scales. Analyses were conducted with multivariate Cox proportional hazards models and were stratified by cancer site. Harrell's discrimination C‐index was used to calculate the predictive accuracy of the model when HRQOL parameters were added to clinical and demographic variables. The added value of adding HRQOL scales to clinical and demographic variables was illustrated with Kaplan‐Meier curves. RESULTS In the stratified, multivariate model, HRQOL parameters—global health status (hazard ratio [HR], 0.97; 95% confidence interval [CI], 0.95‐1.00; P ??. 0001), dyspnea (HR, 1.04; 95% CI, 1.02‐1.06; P ??. 0002), and appetite loss (HR, 1.06; 95% CI, 1.04‐1.08; P ??. 0001)—were independent prognostic factors in addition to the demographic and clinical variables (all P values??.05). Adding these HRQOL variables to the clinical variables resulted in an added relative prognostic value for survival of 5%. CONCLUSIONS These results confirm previous findings showing that baseline HRQOL scores on the EORTC QLQ‐C30 provide prognostic information in addition to information from clinical measures. However, the impact of specific domains may differ across studies. Cancer 2018. ? 2018 American Cancer Society .
机译:背景技术本研究的目的是在外部验证基线健康相关生活质量(HRQOL)评分和生存之间的建立关联,并评估HRQOL关于人口统计学和临床​​指标的增加的预后价值。方法从1991年至2004年间加拿大癌症试验组开通的17项随机对照试验中分析了汇总数据;它们包括来自3606名不同癌症部位的3606名患者的存活和基线HRQOL数据。该模型包括性,年龄(≤60vs& 60年),世界卫生组织性能状态(0或1 vs 2-4),远程转移(NO vs是),以及15个欧洲研究和治疗癌症组织( EORTC)核心生活质量问卷(QLQ-C30)秤。用多元COX比例危害模型进行分析,并被癌症遗址分层。 Harrell的辨别C折射用于计算在将HRQOL参数添加到临床和人口变量时模型的预测精度。用Kaplan-Meier曲线向临床和人口变量添加HRQOL尺度的附加值。结果分层,多变量模型,HRQOL参数 - 全球健康状况(危险比[HR],0.97; 95%置信区间[CI],0.95-1.00;p≤000001),呼吸困难(HR,1.04; 95%CI,1.02-1.06; p?& 0002)和食欲损失(HR,1.06; 95%CI,1.04-1.08; p?& 0001) - 除了独立的预后因素人口统计和临床变量(所有P值?&Δ05)。将这些HRQOL变量添加到临床变量中,导致增额预后值为5%。结论这些结果证实了先前的研究结果,表明EORTC QLQ-C30上的基线HRQOL分数还提供了来自临床措施的信息的预后信息。然而,特定域的影响可能跨研究不同。癌症2018年。 2018年美国癌症协会。

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