Symptom clusters in patients with lung cancer: a literature review. (August 2011)

• Record Type: Journal Article
• Authors: Chen, Emily; Nguyen, Janet; Cramarossa, Gemma; Khan, Luluel; Leung, Andrew; Lutz, Steve; Chow, Edward
• Is Part Of: Expert review of pharmacoeconomics & outcomes research. Volume 11:Number 4(2011)
• Page Start: 433
• Page End: 439
• Publication Date: 2011-08
• Subjects: factor analysis -- lung cancer -- symptom cluster -- symptom distress -- symptom management; Pharmacology -- Economic aspects -- Periodicals; 338.47615105
• DOI: 10.1586/erp.11.56
• Languages: English
• ISSNs: 1473-7167

Abstract

Objective: To provide a review of literature reporting empirically determined symptom clusters in lung cancer patients.Method: We conducted a literature search on symptom clusters in lung cancer patients using MEDLINE, EMBASE and CINAHL. Studies examining the presence of predetermined clusters were excluded. The five relevant studies identified were published between 1997 and 2009.Results: Overall, the five studies reported significantly diverse findings with regards to symptom cluster quantity and composition in lung cancer patients. The number of symptom clusters extracted varied from one to four per study. The number of symptoms in a cluster ranged from two to 11. The only cluster that was consistently identified in two studies was composed of nausea and vomiting symptoms. Respiratory clusters identified in two studies were also comparable, containing both dyspnea and cough, among other symptoms. Methodological disparities, including differences in sample population characteristics, assessment tools and analytical methods, were evident in the five studies reviewed.Conclusion: Symptom cluster exploration is a developing area of research in the oncology field and is promising in providing insights into diagnosis, prognostication and symptom management. Disparities in methodology are significant barriers to producing comparable results. These inconsistencies result in a lack of consensus in symptom clusters in lung cancer populations, thus impeding the determination of clinically relevant findings.