Department of Biostatistics, Gillings School of Global Public Health at the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida.
Clin Cancer Res. 2023 Aug 15;29(16):3142-3150. doi: 10.1158/1078-0432.CCR-23-0396.
Minimally invasive biomarkers have been used as important indicators of treatment response and progression in cancers such as prostate and ovarian. Unfortunately, all biomarkers are not prognostic in all cancer types and are often not routinely collected. Patient-reported outcomes (PRO) provide a non-obtrusive, personalized measure of a patient's quality of life and symptomatology, reported directly from the patient, and are increasingly collected as part of routine care. Previous literature has shown correlations between specific PROs (i.e., insomnia, fatigue) and overall survival. Although promising, these studies often only consider single time points and ignore patient-specific dynamic changes in individual PROs, which might be early predictors of treatment response or progression.
In this study, PRO dynamics were analyzed to determine if they could be used as interradiographic predictors of tumor volume changes among 85 patients with non-small cell lung cancer undergoing immunotherapy. PRO questionnaires and tumor volume scans were completed biweekly and monthly, respectively. Correlation and predictive analysis were conducted to identify specific PROs that could accurately predict patient response.
Changes in tumor volume over time were significantly correlated with dizziness (P < 0.005), insomnia (P < 0.05), and fatigue (P < 0.05). In addition, cumulative changes in insomnia could predict progressive disease with a 77% accuracy, on average 45 days prior to the next imaging scan.
This study presents the first time that patient-specific PRO dynamics have been considered to predict how individual patients will respond to treatment. This is an important first step in adapting treatment to improve response rates.
微创生物标志物已被用作前列腺和卵巢等癌症治疗反应和进展的重要指标。不幸的是,并非所有生物标志物在所有癌症类型中都具有预后价值,而且通常不会常规收集。患者报告的结果 (PRO) 提供了患者生活质量和症状的非侵入性、个性化衡量标准,直接由患者报告,并越来越多地作为常规护理的一部分收集。以前的文献表明,特定的 PRO(即失眠、疲劳)与总生存期之间存在相关性。尽管很有希望,但这些研究通常只考虑单一时间点,忽略了个体 PRO 的患者特定动态变化,这些变化可能是治疗反应或进展的早期预测指标。
在这项研究中,分析了 PRO 动态,以确定它们是否可以用作 85 名接受免疫治疗的非小细胞肺癌患者肿瘤体积变化的影像学间预测指标。PRO 问卷和肿瘤体积扫描分别每两周和每月完成一次。进行了相关性和预测分析,以确定哪些特定的 PRO 可以准确预测患者的反应。
肿瘤体积随时间的变化与头晕(P < 0.005)、失眠(P < 0.05)和疲劳(P < 0.05)显著相关。此外,失眠的累积变化可以以 77%的准确率平均提前 45 天预测进展性疾病。
本研究首次提出将患者特定的 PRO 动态考虑在内,以预测个体患者对治疗的反应。这是适应治疗以提高反应率的重要第一步。