br to pill burden or poor efficacy of antidepressants in
to pill burden, or poor efficacy of antidepressants in these populations.4,42,43 Newer treatment options for
depression in kidney disease patients, such as adjuvant psychotherapy, collaborative care interventions and incorporation of patient preferences in depression management remain to be tested. To this end, our ongoing Technology Assisted Collaborative Care
(TACcare) trial (Clinical trials NCT03440853) will test the effectiveness of a collaborative care interven-tion targeting symptom clusters (fatigue, pain, and depression) on symptom levels and inflammatory me-diators in 150 ESKD patients on hemodialysis.44
Our study begins to explore the predictors of symp-tom clusters in patients with kidney disease. The lack of significant associations between symptom clusters
and a number of sociodemographic, clinical, and biochemical variables in kidney disease patients in
our study is similar to previous findings in dialysis pa-tients.16,39 This is in Omadacycline to advanced cancer pa-
tients, in which we observed meaningful associations between sociodemographic factors and biochemical variables and specific symptoms, as has been previously described.45 It may be that in advanced CKD and ESKD patients, there are other predictors that are not routinely captured. These may include patient’s coping strategies, perceived social support, and cul-tural beliefs that may affect their subjective perception of symptoms.46 In addition, there may be untested biochemical or genetic mechanisms. For instance, in cancer patients, symptoms and symptom cluster have been found to be independently associated with proin-flammatory cytokines as well as hypothalamic-pituitary disturbances causing elevations in cortisol, ACTH, epinephrine, and norepinephrine.47 Genome-wide as-sociations with symptom clusters have also begun to be explored. Illi and colleagues found that a minor allele of IL4 rs2243248 was linked to high levels of pain, fatigue, sleep disturbances, and depression in a sample of cancer patients.48 Future studies in kidney disease patients should explore these novel inflamma-tory, hormonal, and genetic predictors of symptoms and symptom clusters.
The study has many strengths including the large sample size of patients, use of validated instruments to assess the three symptoms with available clinical cut-offs to be able to compare across instruments, and comparison of symptom clusters across chronic dis-eases. Limitations of the study included the lack of other symptoms that may also have high rates in CKD, ESKD, and cancer patients (e.g., sleep, nausea and vomiting, loss of appetite, itching) and may have confounding associations with fatigue, pain, and depressive symptoms. In addition, the studies used different instruments to assess pain and depression across patient cohorts. Finally, the prevalence of depressive symptoms among CKD patients in our study was lower than that reported in the literature, thus may have confounded our results.49
The findings of trachea study represent one of the first studies comparing symptom clusters across different chronic diseases. Patients with CKD and ESRD have similar burden of pain, fatigue, and depressive symp-toms compared to those with cancer. These symptoms often coexist and are highly correlated but form distinct symptom clusters among these patient groups and may suggest differences in the underlying biolog-ical or genetic mechanisms. We identified some modi-fiable clinical predictors of these symptom clusters;
however, further research is warranted to better understand the pathophysiological mechanisms. In addition, future research should evaluate additional symptoms to better characterize symptom clusters such as sleep disturbances, nausea and vomiting, loss of appetite and monitor longitudinal changes in symp-toms and symptom clusters over time.
Disclosures and Acknowledgments
The authors declare no conflicts of interest.