BACKGROUND: Inflammation may contribute to the high prevalence of depressive symptoms seen in lung cancer. "Sickness behavior" is a cluster of symptoms induced by inflammation that are similar but distinct from depressive symptoms. The Sickness Behavior Inventory-Revised (SBI-R) was developed to measure sickness behavior. We hypothesized that the SBI-R would demonstrate adequate psychometric properties in association with inflammation. METHOD: Participants with stage IV lung cancer (n = 92) were evaluated for sickness behavior using the SBI-R. Concomitant assessments were made of depression (Patient Hospital Questionniare-9, Hospital Anxiety and Depression Scale) and inflammation [C-reactive protein (CRP)]. Classical test theory (CTT) was applied and multivariate models were created to explain SBI-R associations with depression and inflammation. Factor Analysis was also used to identify the underlying factor structure of the hypothesized construct of sickness behavior. A longitudinal analysis was conducted for a subset of participants. RESULTS: The sample mean for the 12-item SBI-R was 8.3 (6.7) with a range from 0 to 33. The SBI-R demonstrated adequate internal consistency with a Cronbach's coefficient of 0.85, which did not increase by more than 0.01 with any single-item removal. This analysis examined factor loadings onto a single factor extracted using the principle components method. Eleven items had factor loadings that exceeded 0.40. SBI-R total scores were significantly correlated with depressive symptoms (r = 0.78, p < 0.001) and CRP (r = 0.47, p < 0.001). Multivariate analyses revealed that inflammation and depressive symptoms explained 67% of SBI-R variance. SIGNIFICANCE OF RESULTS: The SBI-R demonstrated adequate reliability and construct validity in this patient population with metastatic lung cancer. The observed findings suggest that the SBI-R can meaningfully capture the presence of sickness behavior and may facilitate a greater understanding of inflammatory depression.
BACKGROUND:Inflammation may contribute to the high prevalence of depressive symptoms seen in lung cancer. "Sickness behavior" is a cluster of symptoms induced by inflammation that are similar but distinct from depressive symptoms. The Sickness Behavior Inventory-Revised (SBI-R) was developed to measure sickness behavior. We hypothesized that the SBI-R would demonstrate adequate psychometric properties in association with inflammation. METHOD:Participants with stage IV lung cancer (n = 92) were evaluated for sickness behavior using the SBI-R. Concomitant assessments were made of depression (Patient Hospital Questionniare-9, Hospital Anxiety and Depression Scale) and inflammation [C-reactive protein (CRP)]. Classical test theory (CTT) was applied and multivariate models were created to explain SBI-R associations with depression and inflammation. Factor Analysis was also used to identify the underlying factor structure of the hypothesized construct of sickness behavior. A longitudinal analysis was conducted for a subset of participants. RESULTS: The sample mean for the 12-item SBI-R was 8.3 (6.7) with a range from 0 to 33. The SBI-R demonstrated adequate internal consistency with a Cronbach's coefficient of 0.85, which did not increase by more than 0.01 with any single-item removal. This analysis examined factor loadings onto a single factor extracted using the principle components method. Eleven items had factor loadings that exceeded 0.40. SBI-R total scores were significantly correlated with depressive symptoms (r = 0.78, p < 0.001) and CRP (r = 0.47, p < 0.001). Multivariate analyses revealed that inflammation and depressive symptoms explained 67% of SBI-R variance. SIGNIFICANCE OF RESULTS: The SBI-R demonstrated adequate reliability and construct validity in this patient population with metastatic lung cancer. The observed findings suggest that the SBI-R can meaningfully capture the presence of sickness behavior and may facilitate a greater understanding of inflammatory depression.
Authors: Donald R Sullivan; Christopher W Forsberg; Linda Ganzini; David H Au; Michael K Gould; Dawn Provenzale; Christopher G Slatore Journal: J Clin Oncol Date: 2016-10-31 Impact factor: 44.544