Symptom clusters and survival in Portuguese patients with advanced cancer

Cancer Med. 2016 Oct;5(10):2731-2739. doi: 10.1002/cam4.860. Epub 2016 Sep 13.

Abstract

This study aimed to identify clusters of symptoms, to determine the patient characteristics associated with identified, and determine their strength of association with survival in patients with advanced cancer (ACPs). Consecutively eligible ACPs not receiving cancer-specific treatment, and referred to a Tertiary Palliative Care Clinic, were enrolled in a prospective cohort study. At first consultation, patients rated 9 symptoms through the Edmonton Symptom Assessment System (0-10 scale) and 10 others using a Likert scale (1-5). Principal component analysis was used in an exploratory factor analysis to identify. Of 318 ACPs, 301 met eligibility criteria with a median (range) age of 69 (37-94) years. Three SCs were identified: neuro-psycho-metabolic (NPM) (tiredness, lack of appetite, lack of well-being, dyspnea, depression, and anxiety); gastrointestinal (nausea, vomiting, constipation, hiccups, and dry mouth) and sleep impairment (insomnia and sleep disturbance). Exploratory factor analysis accounted for 40% of variance of observed variables in all SCs. Shorter survival was observed for patients with the NPM cluster (58 vs. 23, P < 0.001), as well as for patients with two or more SCs (45 vs. 21, P = 0.005). In a multivariable model for survival at 30-days, age (HR: 0.98; 95% CI: 0.97-0.99; P = 0.008), hospitalization at inclusion (HR: 2.27; 95% CI: 1.47-3.51; P < 0.001), poorer performance status (HR: 1.90, 95% CI: 1.24-2.89; P = 0.003), and NPM (HR: 1.64; 95% CI: 1.17-2.31; P = 0.005), were associated with worse survival. Three clinically meaningful SC in patients with advanced cancer were identifiable. The NPM cluster and the presence of two or more SCs, had prognostic value in relation to survival.

Keywords: Advanced cancers; palliative care; solid tumors; survival; symptom clusters.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Cluster Analysis
  • Female
  • Humans
  • Male
  • Middle Aged
  • Neoplasms / mortality*
  • Neoplasms / pathology*
  • Portugal / epidemiology
  • Principal Component Analysis
  • Risk Factors
  • Survival Analysis