Smartphone pain app for assessment of radiation-induced oral mucositis pain.

Authors

Aditya V. Shreenivas

Aditya V. Shreenivas

Medical College of Wisconsin, Milwaukee, WI

Aditya V. Shreenivas, Jared Robbins, Yi Hu, Santhosh Yegnaraman, Sergey Tarima, Alexander V. Ng, Nicole Moore, Lauren Opielinski, Stuart J. Wong

Organizations

Medical College of Wisconsin, Milwaukee, WI, The University of Arizona, Tucson, AZ, University of Wisconsin, Milwaukee, Milwaukee, WI, Marquette University College of Health Sciences, Milwaukee, WI, Marquette University, Milwaukee, WI

Research Funding

Other
MCW Cancer Center.

Background: Oral Mucositis related pain is one of the most common radiation therapy (RT) related toxicities associated with the treatment of head and neck cancer (HNC). Questionnaire-based assessment of mucositis pain is based on a patient's recall which can be inaccurate sometimes. Therefore, real-time monitoring of patient-reported pain is required for better evaluation of mucositis pain. Methods: We performed a single-arm, observational study (NCT02727062) to investigate the feasibility of a smartphone-based pain app (OMP) in assessing mucositis pain in locally advanced HNC patients(pts) undergoing a course of definitive or adjuvant RT (> 50 Gy), +/- chemotherapy, for oral cavity or oropharynx cancer. The app prompted pts to input pain severity scores using a visual analog (0-10) scale (VAS) at multiple time points during a day throughout the study. OMP software-generated time-weighted average weekly summary measure of pain by integrating multiple serial daily pain assessments. In addition, pts completed weekly Brief pain inventory (BPI) and MD Anderson head & neck symptom inventory (MDASI-HN) questionnaires. Feasibility surveys were also collected to assess the ease of use of OMP and the burden of study participation. Responses to questions on this survey were scored on a scale of 0-3, with 0 standing for not at all and 3 for extremely. Linear mixed models (LMM) controlling for person random effects were used to evaluate association and quantify differences between average weekly pain (AWP) calculated by OMP and AWP recorded using VAS by BPI survey (question 5). LMM was also used to evaluate the association between AWP score from OMP and BPI pain score with MDASI-HN scores. Descriptive statistics, including averages and frequency, were used to analyze feasibility surveys. Results: We report results of 15 pts who have complete data out of 18 registered pts. Using LMM, we compared AWP score curves calculated from BPI and OMP. We observed that both curves followed a parallel trajectory. However, pain scores calculated from OMP were 0.40 units higher than BPI pain. The Bland-Altman plot also confirmed that BPI pain and OMP did not clearly agree. Additionally, AWP scores from OMP had a positive correlation with fatigue (p < 0.001), drowsiness (p < 0.001), decreased activity (p < 0.001), and interference with work (p < 0.001) related scores recorded in MDASI-HN. In terms of feasibility, most surveys indicated that it was extremely easy for subjects to enter responses and not at all difficult for them to use all features of OMP. Furthermore, study participation did not interfere with subjects’ usual activities. Conclusions: Our study showed that pain scores calculated through OMP were, on average higher than those reported by BPI. It also showed the correlation between pain and physical activity. Hence, utilization of OMP in conjunction with questionnaires may improve our understanding of the severity of mucositis-related pain. Clinical trial information: NCT02727062.

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Abstract Details

Meeting

2022 ASCO Quality Care Symposium

Session Type

Poster Session

Session Title

Poster Session B

Track

Palliative and Supportive Care,Technology and Innovation in Quality of Care,Quality, Safety, and Implementation Science

Sub Track

Tools for Management of Treatment and Adverse Effects

Clinical Trial Registration Number

NCT02727062

Citation

J Clin Oncol 40, 2022 (suppl 28; abstr 420)

DOI

10.1200/JCO.2022.40.28_suppl.420

Abstract #

420

Poster Bd #

F23

Abstract Disclosures

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