Lo Stephen B, Shin Joosun, Holtze Mia E, Post Kathryn E, Eche-Ugwu Ijeoma Julie, Temel Jennifer S, Cooley Mary E, Greer Joseph A
Center for Psychiatric Oncology & Behavioral Sciences, Massachusetts General Hospital, Boston, MA, USA.
Harvard Medical School, Boston, MA, USA.
Support Care Cancer. 2025 Jul 18;33(8):700. doi: 10.1007/s00520-025-09757-3.
Dyspnea impacts most patients with advanced lung cancer. However, research on dyspnea has been limited by using unidimensional self-report measures despite its multidimensional nature (sensory-perceptual experience, affective distress, and functional impact), which requires a comprehensive evaluation. To identify distinct patient profiles of dyspnea presentation and evaluate differences in demographic, clinical characteristics, and patient-reported outcomes (i.e., functional impairment, quality of life, co-occurring symptoms, and self-efficacy).
A cross-sectional, secondary analysis of 247 patients with advanced lung cancer reporting moderate-to-severe dyspnea was conducted using baseline data from a randomized controlled trial testing a behavioral intervention for dyspnea. The patient profiles of dyspnea were identified using latent profile analysis of the Cancer Dyspnea Scale. Differences among the profiles were assessed through parametric and non-parametric methods.
Four-class solutions were identified: All Mild (A-Mild: 53%), Moderate Effort and Discomfort & Mild Anxiety (Moderate ED & Mild A: 25.9%), All Moderate (A-Moderate: 16.6%), and All Severe (A-Severe: 4.5%) dyspnea profiles. No significant differences were found among demographic and clinical variables across the profiles. Compared to the A-Mild profile, the other three profiles reported more significant functional impairment due to dyspnea, increased levels of depression, anxiety, and fatigue, and reduced quality of life. The A-Severe profile exhibited lower self-efficacy than the Moderate ED & Mild A and the A-Moderate profiles.
Our findings highlight the multidimensional nature of dyspnea, which results in distinct patient presentations. Clinicians can create targeted interventions tailored to individual needs by classifying dyspnea symptom profiles.
呼吸困难影响大多数晚期肺癌患者。然而,尽管呼吸困难具有多维度性质(感觉-知觉体验、情感痛苦和功能影响),但对其的研究一直受限于使用单维度的自我报告测量方法,而这需要进行全面评估。以识别呼吸困难表现的不同患者特征,并评估人口统计学、临床特征和患者报告结局(即功能损害、生活质量、并发症状和自我效能)的差异。
使用一项针对呼吸困难的行为干预随机对照试验的基线数据,对247例报告有中度至重度呼吸困难的晚期肺癌患者进行横断面二次分析。使用癌症呼吸困难量表的潜在类别分析来识别呼吸困难的患者特征。通过参数和非参数方法评估各特征之间的差异。
确定了四类情况:所有轻度(A-轻度:53%)、中度用力与不适及轻度焦虑(中度ED与轻度A:25.9%)、所有中度(A-中度:16.6%)和所有重度(A-重度:4.5%)呼吸困难特征。各特征在人口统计学和临床变量方面未发现显著差异。与A-轻度特征相比,其他三个特征报告因呼吸困难导致的功能损害更显著,抑郁、焦虑和疲劳水平升高,生活质量降低。A-重度特征的自我效能低于中度ED与轻度A特征和A-中度特征。
我们的研究结果突出了呼吸困难的多维度性质,这导致了不同的患者表现。临床医生可以通过对呼吸困难症状特征进行分类,制定针对个体需求的有针对性的干预措施。