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Prevalence and Correlates of Distress Detected by the Distress Thermometer and Problem List in Lung Cancer Patients: A Cross‐Sectional Study

Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: The distress thermometer (DT) is an effective tool for identifying distress among cancer patients worldwide. Our study objective is to evaluate the prevalence and severity of distress in lung cancer patients by using DT. METHODS: A total of 153 lung cancer patients were retrospective enrolled at the Lung Cancer Center of Peking Union Medical College Hospital. Participants completed three assessments: the clinical characteristics, the associated problem list (PL) scale and the DT. RESULTS: At a DT cut-off score of ≥ 4, 56.2% of lung cancer patients had significant distress, which was related to the number of PL items symptoms. Sleep (55.6%), fatigue (51.0%), and pain (47.7%) were the most commonly reported issues. Univariate logistic regression analysis revealed that a DT score ≥ 4 was significantly associated with most of the PL items, such as housing, child care, insurance, transportation, dealing with children and relatives, loneliness, depression, nervousness, sadness, worry, loss of interest in usual activities, sleep, memory/concentration, bathing, appearance, change in urination, fatigue, breathing, diarrhea, indigestion, constipation, eating, dizziness, pain, mouth sores, nausea, sexual issues, dry nose, tingling in hands/feet, and physical activity restrictions. However, multivariate regression analysis identified only the following as independent predictors of significant distress in patients with lung cancer: insurance, transportation, depression, sleep, mouth sores, and dry nose. CONCLUSION: This study recommends using the DT for screening lung cancer patients, and the involvement of the social services and psycho-oncology at the time of initial diagnosis and treatment.
Authors: Xiaomin Wei, Jun Liu, Haili Li, Wenjuan Wang, Ning Zhao, Chunyu Dong, Shuxian Zhang, Bijun Yu, Mengzhao Wang, Mei Li, Xiaohong Ning, Li Zhang, Xiaoyan Si
Language: English
Subfield: Oncology
Field: Medicine
Open Access status: gold
Estimated APC paid: $3,030
OpenAlex ID: W4417361944
FWCI: 0.363
Cites: 43
Cited by: 1
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