Introduction: Cancer has its own disease burden and patients usually suffer from symptom clusters when they are referred for palliative treatment. Identification of symptom cluster trajectories will help clinician to take into account measures that can optimize quality of life of palliative patients. Therefore the aim of this paper is to determine the overall prevalence of symptoms and symptoms clusters in different disease groups according to etiology at the time of first visit to Palliative care clinic by using HIS Palliative First Assessment note indicating Edmonton symptom scale.
Method: It’s a cross sectional study conducted in a tertiary care cancer hospital. Statistical analysis was carried out using the SPSS software (version 20.0; SPSS, Chicago, IL, USA). Continuous variables were stated as mean ± standard deviation and categorical variables were expressed as frequencies and percentages. Agglomerative hierarchical cluster analysis was used to create the symptom clusters.
Results: The most prevalent symptoms were pain (91.8%), Anxiety (88.5%), depression (87.4%), tiredness (84.1%), lack of appetite (74.7%), nausea (57.1%), drowsiness (50.5%) and shortness of breath (46.2%). Two symptom clusters were defined as a result of cluster analysis; depression, anxiety, pain, tiredness, lack of appetite and nausea, drowsiness and shortness of breath.
Conclusion: Symptom cluster study is a beneficial tool to improve overall patient’s health. By treating these symptom clusters, morbidity of palliative patients can be significantly decreased.
Palliative care, Quality of Life assessment, Prevalence, Edmonton symptom assessment scale, Symptom clusters, Malignancies, Morbidity.