Increasing stringency in symptom cluster research: a methodological exploration of symptom clusters in patients with inoperable lung cancer.
OBJECTIVE
To inductively explore the existence of symptom clusters among a homogenous group of patients with inoperable lung cancer close to diagnosis and to explore if the symptom clusters are consistent when examined with different instruments and analytical methods.


METHODS
Cross-sectional.


METHODS
Lung medicine department at two university hospitals in Sweden.


METHODS
400 patients (52% men, 48% women) newly diagnosed with lung cancer with a mean age of 64.5 years.


METHODS
Data were analyzed from various questionnaires, including the European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30, the EORTC LC13, and the Symptom Distress Scale. Items in the instruments were adapted to increase their correspondence. Symptom clusters were analyzed with Pearson correlations, cluster analysis, factor analysis, and Cronbach alphas.


METHODS
Symptom clusters.


RESULTS
Three clusters were found to be notably consistent across instruments and analyses: first, a pain cluster consisting of pain, nausea, bowel issues, appetite loss, and fatigue; second, a mood cluster consisting of mood, outlook, concentration, and insomnia; and third, a respiratory cluster consisting of breathing and cough, with fatigue and appetite loss closely related to more than one cluster in several analysis.


CONCLUSIONS
The authors found consistent symptom clusters for a large cohort of patients with lung cancer at a comparable point in their cancer trajectory, across different measurement tools and statistical methods.


CONCLUSIONS
The symptom cluster consistency for patients with lung cancer is an important finding because the relevance of symptom cluster research is questionable if consistency is lacking across data collection and analysis approaches. Achieving consistency is possible in symptom cluster research across instruments and analysis methods if instrument items are comparable.
Henoch
Ingela
I
Karolinska Institutet, Institution of Learning, Informatics, Management, and Ethics, Medical Management Centre, Stockholm, Sweden. ingela.henoch@ki.se
Ploner
Alexander
A
Tishelman
Carol
C
D016000:Cluster Analysis; D003430:Cross-Sectional Studies; D004417:Dyspnea / Q000209:etiology; D005221:Fatigue / Q000209:etiology; D005260:Female; D006304:Health Status; D006801:Humans; D008175:Lung Neoplasms / Q000150:complications / Q000451:nursing* / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D019964:Mood Disorders / Q000209:etiology; D009859:Oncology Nursing; D010146:Pain / Q000209:etiology; D007319:Sleep Initiation and Maintenance Disorders / Q000209:etiology; D011795:Surveys and Questionnaires