Daniel C McFarland1, Kelly Shaffer2, William Breitbart2, Barry Rosenfeld3, Andrew H Miller4. 1. Division of Network Services, Department of Medicine, Memorial Sloan Kettering Cancer Center, West Harrison, New York. 2. Department of Psychiatry and Behavioral Sciences, Memorial Sloan Kettering Cancer Center, New York, New York. 3. Department of Psychology, Fordham University, Bronx, New York. 4. Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia.
Abstract
BACKGROUND: Depression is highly prevalent in lung cancer. Although there is a known association between inflammation and depression, this relationship has not been examined in patients with lung cancer who undergo treatment with immune and other targeted drug therapies. Peripheral blood C-reactive protein (CRP), a marker of systemic inflammation, may help identify metastatic lung cancer patients with inflammation-associated depression. METHOD: Patients with metastatic lung cancer undergoing treatment were evaluated for depression using the Hospital Anxiety and Depression Scale (HADS). Inflammation (CRP and CRP cutoffs ≥1 and ≥3 mg/mL) and demographic and treatment variables were analyzed for association with depression. RESULTS: One hundred nine consecutive participants exhibited an average plasma CRP concentration of 1.79 mg/mL (median, 0.75 mg/mL [standard deviation, 2.5 mg/mL), and 20.7% had a CRP concentration of ≥3.0 mg/mL; 23.9% met depression screening criteria (HADS ≥8). A log transformation of CRP was significantly correlated with depression severity (r = 0.47, P < .001). CRP was the only covariate to predict depression severity (P = .008) in a multivariate model including lung cancer disease subtype and type of systemic treatment. Receiver operating characteristic analysis indicated that CRP had moderate predictive accuracy in identifying elevated depression (area under the curve = 0.74). A cutoff of CRP ≥3.0 generated high specificity (88%) but identified only 50% of those with elevated depression. CONCLUSION: Elevated CRP is associated with depression in patients with metastatic lung cancer. Thus, CRP may identify a subset of lung cancer patients with inflammation-induced depression and may be useful in predicting response to treatments that target inflammation or its downstream mediators on the brain.
BACKGROUND:Depression is highly prevalent in lung cancer. Although there is a known association between inflammation and depression, this relationship has not been examined in patients with lung cancer who undergo treatment with immune and other targeted drug therapies. Peripheral blood C-reactive protein (CRP), a marker of systemic inflammation, may help identify metastatic lung cancerpatients with inflammation-associated depression. METHOD:Patients with metastatic lung cancer undergoing treatment were evaluated for depression using the Hospital Anxiety and Depression Scale (HADS). Inflammation (CRP and CRP cutoffs ≥1 and ≥3 mg/mL) and demographic and treatment variables were analyzed for association with depression. RESULTS: One hundred nine consecutive participants exhibited an average plasma CRP concentration of 1.79 mg/mL (median, 0.75 mg/mL [standard deviation, 2.5 mg/mL), and 20.7% had a CRP concentration of ≥3.0 mg/mL; 23.9% met depression screening criteria (HADS ≥8). A log transformation of CRP was significantly correlated with depression severity (r = 0.47, P < .001). CRP was the only covariate to predict depression severity (P = .008) in a multivariate model including lung cancer disease subtype and type of systemic treatment. Receiver operating characteristic analysis indicated that CRP had moderate predictive accuracy in identifying elevated depression (area under the curve = 0.74). A cutoff of CRP ≥3.0 generated high specificity (88%) but identified only 50% of those with elevated depression. CONCLUSION: Elevated CRP is associated with depression in patients with metastatic lung cancer. Thus, CRP may identify a subset of lung cancerpatients with inflammation-induced depression and may be useful in predicting response to treatments that target inflammation or its downstream mediators on the brain.
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