Department of Symptom Research, The University of Texas MD Anderson Cancer Center, Houston, TX.
ECOG-ACRIN Biostatistics Center, Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA.
JCO Oncol Pract. 2020 Sep;16(9):e893-e901. doi: 10.1200/JOP.19.00403. Epub 2020 May 5.
Symptom monitoring is attracting attention as a way to improve adherence to cancer therapy, reduce treatment-related toxicities, and possibly improve overall survival. How reporting thresholds affect symptom alert generation and clinical outcomes is poorly understood.
We analyzed data from 38 US health care institutions collected for the prospective Eastern Cooperative Oncology Group-American College of Radiology Imaging Network E2Z02 Symptom Outcomes and Practice Patterns study. Participants were outpatients receiving chemotherapy for breast (n = 642), colorectal (n = 486), or lung cancer (n = 340) who rated symptom severity using the MD Anderson Symptom Inventory at 2 assessment points 1 month apart. Percentages of patients with pain, dyspnea, fatigue, or distress at different thresholds (score of 4-7 on a 0-10 scale) were compared. The percentage of patients whose performance status had worsened at follow-up was used to estimate risk for missing clinically important symptom data by using higher severity thresholds.
At the guideline-recommended threshold of ≥ 4, suprathreshold rates were 60% for any of the 4 symptoms at the initial survey; performance status worsened at follow-up for 27% of all patients with any symptom rated ≥ 4 at the initiate survey. When the threshold was increased to ≥ 7, approximately half of patients (51%) with worsened performance status were not identified.
The burden to clinicians from an alert threshold of ≥ 4 (per many current guidelines) would be substantial. However, setting higher alert thresholds may miss a large percentage of patients who need clinical intervention. These results may inform resource planning when implementing electronic symptom screening at an institutional or practice level.
症状监测作为一种提高癌症治疗依从性、减少治疗相关毒性和提高总生存率的方法引起了关注。报告阈值如何影响症状警报的生成和临床结果尚不清楚。
我们分析了为前瞻性东部合作肿瘤组-美国放射肿瘤学会成像网络 E2Z02 症状结局和实践模式研究收集的来自 38 家美国医疗机构的数据。参与者为接受化疗的门诊患者,包括乳腺癌(n=642)、结直肠癌(n=486)或肺癌(n=340),他们在 1 个月的 2 次评估中使用 MD 安德森症状量表评估症状严重程度。比较了不同阈值(0-10 分制上的 4-7 分)下疼痛、呼吸困难、疲劳或苦恼的患者比例。使用更高的严重程度阈值来估计因更高的症状严重程度而导致错过重要临床症状数据的风险,随访时患者的表现状态恶化。
在指南推荐的≥4 阈值下,初始调查中任何 4 种症状的超阈值率为 60%;在初始调查中任何症状评分≥4 的所有患者中,27%的患者随访时表现状态恶化。当阈值增加到≥7 时,大约一半(51%)表现状态恶化的患者没有被识别出来。
对于许多当前指南中≥4 的警报阈值,临床医生的负担将是巨大的。然而,设定更高的警报阈值可能会错过很大一部分需要临床干预的患者。这些结果可能为在机构或实践层面实施电子症状筛查时的资源规划提供信息。