Association of Symptoms and Collaborative Care Intervention (TACcare) with Systemic Inflammation Biomarkers in End-Stage Kidney Disease.

BACKGROUND: Patient-reported symptoms are associated with inflammation biomarkers in many chronic diseases. We examined associations of inflammation biomarkers with pain, fatigue, and depression in patients with end-stage kidney disease (ESKD) and the effects of a Technology Assisted stepped Collaborative Care (TACcare) intervention on these biomarkers. METHODS: In the TACcare multi-site randomized control trial, data on patient-reported symptoms were collected at baseline, 3, and 6 months. Anti-inflammatory [interleukin 1 receptor agonist (IL-1RA), IL-10], pro-inflammatory [tumor necrosis factor alpha (TNF-α), high sensitivity C-reactive protein (hs-CRP), IL-6] and regulatory [IL-2] biomarkers were assayed. Linear mixed-effects modeling was used to examine within- and between-group differences after adjusting for age, sex, race, and comorbidities. RESULTS: Among the 160 patients (mean age 58±14 years, 55% men, 52% white), there were no significant associations between inflammation biomarkers and pain, fatigue or depression at baseline. Both intervention and control group demonstrated reductions in IL-10 and IL-1RA over 6 months (ß range=-1.22 to -0.40, p range=<0.001 to 0.02) At 3 months, the treatment group exhibited decreases in TNF-α (ß=-0.22, p<0.001) and IL-2 (ß=-0.71, p<0.001), whereas the control group showed increases in IL-6/IL-10 ratio (ß=0.33, p=0.03). At 6 months, both groups exhibited decreases in IL-2 (ß range=-0.66 to -0.57,p<0.001); the control group showed significant increases in the ratio of IL-6/IL-10 (ß=0.75,p<0.001) and decrease in TNF-α (ß=-0.16, p=0.02). Compared to controls, the treatment group demonstrated significantly decreased IL-2 at 3 months (ß=-0.53, p<0.001). Significant interaction effects of treatment were observed on the association between changes in pro-inflammatory biomarkers (TNF-α and hs-CRP) levels and changes in symptom scores from baseline to 6 months. CONCLUSIONS: The TACcare intervention had a short-term impact on reducing inflammatory burden in patients with ESKD. More studies are needed to confirm our findings and to determine if these biomarkers mediate the link between symptoms and disease progression.

Diurnal and Daily Symptom Variation in Patients with End-Stage Kidney Disease: An Ecological Momentary Assessment Study.

BACKGROUND: Patients with end-stage kidney disease (ESKD) on hemodialysis (HD) experience a high symptom burden which is compounded by unpredictable fluctuations in symptom severity. Few studies have used ecological momentary assessment (EMA) to determine how symptoms vary over time. This study aimed to characterize the diurnal and day-to-day variability in symptoms among HD patients. METHODS: Patients enrolled in the Technology Assisted Collaborative Care (TACcare) trial rated the intensity of physical, cognitive, and mood symptoms using an automated telephone-administered version of the Daytime Insomnia Symptom Scale (DISS) at four time-points (morning, early afternoon, late afternoon, evening) for seven consecutive days at baseline. Confirmatory factor analysis (CFA) was used to verify the original four-factor solution for the DISS: sleepiness/fatigue (SF), alert cognition (AC), positive mood (PM), and negative mood (NM). Symptom domain scores were calculated for each time point and mixed modeling with random patient effects was used to examine differences in daily symptoms daily time points between HD and non-HD days after controlling for age, gender, race, and comorbidity burden. RESULTS: One hundred and sixty patients were enrolled (mean±SD age 58±14 years, 45% women, 52% White). Diurnal symptom variation existed; trends were non-linear and differed by HD vs. non-HD days. Day-to-day symptom variation also existed; patients endorsed better physical, cognitive, and mood states (i.e., higher AC and PM) as well as lower symptom burden (i.e., lower SF and NM) on non-HD days compared to HD days at all time-points. The greatest day-to-day mean differences (MDs) were observed in the early afternoon for all symptom domains: AC (MD=0.17 p<0.001), PM (MD=0.28, p<0.001), SF (MD=-0.66, p<0.001), and NM (MD=-0.26, p<0.001). CONCLUSIONS: Patients with ESKD demonstrate diurnal variation in symptoms and greater symptom burden on HD days compared to non-HD days, with the most extreme differences in symptom severity occurring in the early afternoon.

Predictors and Consequences of Cancer and Non-Cancer-Related Pain in Those Diagnosed with Primary and Metastatic Cancers.

OBJECTIVES: The aims of the study were to (1) describe types of pain in cancer patients, (2) examine the predictors and consequences of pain, (3) investigate the association between type of pain and survival, and (4) examine potential biological mediators of pain and survival. METHODS: This was a secondary analysis of baseline data from patients diagnosed with cancer. Patients answered questionnaires that assessed sociodemographic characteristics, pain, depression, sleep, and fatigue. Blood was collected and cytokine assays were performed. Analysis of variance, Kaplan-Meier, and Cox regression survival analyses were used to test the aims. RESULTS: Of the 779 patients diagnosed with cancer, the mean age was 63.5 years, 57.8% male, and 90.6% White. Of those who reported pain (total 70.3%), 46.5% stated their pain was cancer-related while 53.5% stated their pain was non-cancer-related. While both cancer and non-cancer-related pain was associated with depressive symptoms, fatigue, and sleep duration, those with cancer-related pain had significantly higher rates of depressive symptoms (F(1,516) = 21.217, p < 0.001) and fatigue (F(1,516) = 30.973, p < 0.001) but not poorer sleep (F(1,497) = 0.597, p = 0.440). After adjusting for sociodemographic, disease-related characteristics, depression, sleep duration, and morphine milligram equivalent, patient reports of cancer-related pain were significantly associated with poorer survival (HR = 0.646, 95% CI = 0.459-0.910, p = 0.012) compared to those with non-cancer-related pain, which was not associated with survival (HR = 1.022, 95% CI = 0.737-1.418, p = 0.896). Cytokines did not significantly mediate the link between pain and survival. CONCLUSION: While nearly half of the pain reported was cancer-related, both types of pain resulted in greater symptom burden, but only cancer-related pain was associated with survival.

Social Support is Associated with Survival in Patients Diagnosed with Gastrointestinal Cancer.

PURPOSE: The aim of this study was to examine the link between psychological, behavioral, and social factors and survival in patients diagnosed with gastrointestinal cancer. METHODS: A cohort of gastrointestinal cancer patients were administered a battery of questionnaires that assessed trauma, depression, social support, sleep, diet, exercise, quality of life, tobacco and alcohol use, pain, and fatigue. Analyses included Pearson's correlations, analyses of variance, Kaplan Meier survival, and Cox regression analyses. RESULTS: Of the 568 patients, the majority were male (57.9%) and Caucasian (91.9%), with a mean age of 61 (S.D. = 10.7). The level of perceived social support was comparable to patients with other medical conditions. Sociodemographic predictors of social support included the number of years of education (r = 0.109, p = 0.05), marital status (F(6,387) = 5.465, p ≤ 0.001), and whether the patients' income met the family's basic needs (F(1,377) = 25.531, p < 0.001). Univariate analyses revealed that older age (p < 0.001), male gender (p = 0.007), being black (p = 0.005), diagnosis of hepatocellular carcinoma (p = 0.046), higher body mass index (p = 0.022), larger tumor size (p = 0.032), initial treatment including chemotherapy rather than surgery (p < 0.001), and lower level of perceived social support (p = 0.037) were associated with poorer survival. Using multivariate Cox regression and adjusting for all factors found to be significant in univariate survival analyses, older age (p = 0.024) and lower perceived social support (HR = 0.441, 95% CI = 0.233, 0.833; p = 0.012) were the factors that remained significantly associated with poorer survival. CONCLUSION: There are several biological and psychosocial factors that predict cancer mortality. Social support appears to be a robust factor affecting mortality in gastrointestinal cancer patients.