A Preliminary Validation of an Optimal Cutpoint in Total Number of Patient-Reported Symptoms in Head and Neck Cancer for Effective Alignment of Clinical Resources With Patients’ Symptom Burden
Janet H. Van Cleave, C. Concert, Maria Kamberi, Elise Zahriah, Allison Most, J. Mojica, Ann Riccobene, Nora Russo, Eva Liang, Kenneth S. Hu, Adam S. Jacobson, Zujun Li, Lindsey E. Moses, M. Persky, M. Persky, Theresa Tran, Abraham A. Brody, Arum Kim, B. Egleston
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Abstract
Patients with head and neck cancer (HNC) often experience high symptom burden leading to lower quality of life (QoL). This study aims to conceptually model optimal cutpoint by examining where the total number of patient-reported symptoms exceeds patients’ coping capacity, leading to a decline in QoL in patients with HNC. Secondary data analysis of 105 individuals with HNC enrolled in a clinical usefulness study of the NYU Electronic Patient Visit Assessment (ePVA), a digital patient-reported symptom measure. Patients completed ePVA and European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 v3.0. The total number of patient-reported symptoms was the sum of symptoms as identified by the ePVA questionnaire. Analysis of variance was used to define the optimal cutpoint. Study participants had a mean age of 61.5, were primarily male (67.6%), and had stage IV HNC (53.3%). The cutpoint of 10 symptoms was associated with a significant decline of QoL (F = 44.8, P < .0001), dividing the population into categories of low symptom burden (<10 symptoms) and high symptom burden (≥10 symptoms). Analyses of EORTC function subscales supported the validity of 10 symptoms as the optimal cutpoint (physical: F = 28.3, P < .0001; role: F = 21.6, P < .0001; emotional: F = 9.5, P = .003; social: F = 33.1, P < .0001). In HNC, defining optimal cutpoints in the total number of patient-reported symptoms is feasible. Cutpoints in the total number of patient-reported symptoms may identify patients experiencing a high symptom burden from HNC. Using optimal cutpoints of the total number of patient-reported symptoms may help effectively align clinical resources with patients’ symptom burden.