Study of unmet needs in symptomatic veterans with advanced cancer: incidence, independent predictors and unmet needs outcome model

Abstract

Veteran patients possess distinctive characteristics such as a higher mortality rate, lower socioeconomic status and poorer health status. We report the prevalence and predictors of unmet needs and examine the association between unmet needs and quality of life (QOL). Two hundred ninety-six male cancer patients who presented with distressing symptom(s) completed the following instruments: a 14-item multidimensional unmet needs questionnaire, Functional Assessment of Cancer Therapy (FACT-G), Memorial Symptom Assessment Scale-Short Form (MSAS-SF) and other validated measurements of function, depression, health and social support. Multiple linear regression models were used to identify independent predictors of each unmet needs domain and of total unmet needs. The relationships between total unmet needs, QOL and multidimensional variables were also explored. The median number of total unmet needs was three, and the most frequently reported unmet needs areas were physical (80.0%), activities of daily living (53.3%), nutrition (46.1%) and emotional (32.5%). Different predictors of each unmet needs domain were identified. Younger age was associated with a higher risk of unmet needs in physical, economic and medical domains. Higher psychological symptom distress was associated with more unmet needs in the emotional/social, economic and medical domains. Physical symptom distress, extent of disease and health measure were only significant in the physical unmet needs domain. The depression, psychological and physical symptom distress scores, confident and affective social support scores, total unmet needs and age independently predicted FACT-G total QOL score (R(2)=63%, P < 0.00001). Patients with higher psychological, physical symptom distress and depression scores, younger age, lower functional status and metastatic disease were more likely to report more unmet needs. The total number of unmet needs was predictive of QOL. The unmet needs and QOL outcomes model was developed but needs further validation.