Memorial Sloan Kettering Cancer Center, New York, NY, USA.
DeltaQuest Foundation, Inc., Concord, MA, USA; Departments of Medicine and Orthopaedic Surgery, Tufts University School of Medicine, Boston, MA, USA.
Value Health. 2019 Feb;22(2):225-230. doi: 10.1016/j.jval.2018.07.875. Epub 2018 Aug 31.
Patient response burden is often raised as a human subject concern in consideration of the length or complexity of patient-reported outcome (PRO) instruments used in oncology.
To quantify patient response burden and identify its predictive factors.
Data were collected presurgically during a prospective trial that used a comprehensive symptom and health-related quality-of-life (HRQOL) PRO assessment. A subset of patients also completed HRQOL interviews. Response burden was captured using an internally developed six-item instrument. Demographic and clinical characteristics as well as HRQOL scores were examined as potential predictors using hierarchical regression. Response burden was used to predict participant dropout at the first follow-up interval.
A total of 275 patients (mean age 67.5 years; 23.6% female) completed surveys (n = 126) or surveys in addition to interviews (n = 149). Patients experienced low response burden (mean 12.19 ± 11.65). Repetitive questions were identified by 60 patients (21.8%), whereas 31.6% indicated that additional information should be gathered; 35 patients (12.7%) identified repetitive questions and expressed a desire for additional items. Low self-reported cognitive function was a significant predictor of higher response burden (β = -0.20; t(270) = -3.38; P = 0.01; model-adjusted R = 0.04). Response burden was not a significant predictor of study dropout.
Despite completing a large battery of PRO measures and interviews, patients reported minimal response burden, with nearly one-third expressing that more questions should have been asked. Patients with lower cognitive function are more likely to report higher response burden when completing PRO measures. Further examination of patient characteristics related to response burden may reveal useful pathways for tailoring patient-centered interventions.
在考虑肿瘤学中使用的患者报告结局(PRO)工具的长度或复杂性时,患者应答负担常被视为人体受试者关注的问题。
量化患者应答负担并确定其预测因素。
数据在一项前瞻性试验中于术前采集,该试验使用了全面的症状和健康相关生活质量(HRQOL)PRO 评估。一小部分患者还完成了 HRQOL 访谈。使用内部开发的六分量表来衡量应答负担。使用分层回归分析检查人口统计学和临床特征以及 HRQOL 评分是否为潜在预测因素。使用应答负担来预测首次随访间隔时的参与者脱落。
共有 275 名患者(平均年龄 67.5 岁;23.6%为女性)完成了调查(n=126)或调查加访谈(n=149)。患者的应答负担较低(平均 12.19±11.65)。60 名患者(21.8%)认为问题重复,而 31.6%的患者表示应收集更多信息;35 名患者(12.7%)认为问题重复并希望增加项目。自我报告的认知功能较低是应答负担较高的显著预测因素(β=-0.20;t(270)=-3.38;P=0.01;模型调整后的 R=0.04)。应答负担不是研究脱落的显著预测因素。
尽管患者完成了大量 PRO 措施和访谈,但报告的应答负担很小,近三分之一的患者表示应提出更多问题。在完成 PRO 措施时,认知功能较低的患者更有可能报告更高的应答负担。进一步研究与应答负担相关的患者特征可能会揭示针对患者为中心的干预措施的有用途径。