BACKGROUND
Advanced lung cancer patients often have chronic lung disease with reduced exercise capacities and various symptoms leading to altered quality of life (QoL). No studies have assessed pulmonary rehabilitation (PR) employing a mobile app and an Internet of Things device in advanced lung cancer patients undergoing chemotherapy.
OBJECTIVE
This study aimed to determine the feasibility and efficacy of smartphone app–based PR on exercise capacity, symptom management, and QoL in patients with advanced lung cancer undergoing chemotherapy.
METHODS
A total of 100 patients were recruited in a prospective, single-arm intervention study using a smartphone app–based PR program for 12 weeks. Exercise capacity (6-min walking distance, 6MWD), QoL, symptom scale scores, and distress indexes were investigated.
RESULTS
A total of 90 patients completed the PR program. The most common cause of drop out was hospitalization because of cancer progression. After PR, there was significant improvement in the 6MWD; 380.1 m (SD 74.1) at baseline, 429.1 m (SD 58.6) at 6 weeks (P<.001), and 448.1 m (SD 50.0) at 12 weeks (P<.001). However, the dyspnea scale score showed no significant improvement in the patients overall, but there was a trend for improvement in those with a stable tumor response (P=.07). Role (P=.02), emotional (P<.001), and social functioning (P=.002) scale scores showed significant improvement after PR. Symptom scale scores for fatigue (P<.001), anorexia (P=.047), and diarrhea (P=.01) also showed significant improvement. There was significant improvement in depression (P=.048) and anxiety (P=.01), whereas there was no significant change in QoL (P=.06) and severity of pain (P=.24).
CONCLUSIONS
Smartphone app–based PR represents an effective and feasible program to improve exercise capacity and to manage symptoms and distress in patients with advanced lung cancer who are undergoing chemotherapy.
Usefulness of Pulmonary Rehabilitation in Non-small Cell Lung Cancer Patients Based on Pulmonary Function Tests and Muscle Analysis Using Computed Tomography Images
