<p><b>PURPOSE: </b>Despite evidence-based guidelines recommending early palliative care, it remains unclear how to identify and refer oncology patients, particularly in settings with constrained access to palliative care. We hypothesize that patient-reported outcome (PRO) data can be used to characterize patients with palliative care needs. To determine if PRO data can identify latent phenotypes that characterize indications for specialty palliative care referral.</p><p><b>METHODS: </b>We conducted a retrospective study of self-reported symptoms on the Edmonton Symptom Assessment System collected from solid tumor oncology patients (n = 745) referred to outpatient palliative care. Data were collected as part of routine clinical care from October 2012 to March 2018 at eight community and academic sites. We applied latent profile analysis to identify PRO phenotypes and examined the association of phenotypes with clinical and demographic characteristics using multinomial logistic regression.</p><p><b>RESULTS: </b>We identified four PRO phenotypes: (1) Low Symptoms (n = 295, 39.6%), (2) Moderate Pain/Fatigue + Mood (n = 180, 24.2%), (3) Moderate Pain/Fatigue + Appetite + Dyspnea (n = 201, 27.0%), and (4) High Symptoms (n = 69, 9.3%). In a secondary analysis of 421 patients, we found that two brief items assessing social and existential needs aligned with higher severity symptom and psychological distress phenotypes.</p><p><b>CONCLUSION: </b>Oncology patients referred to outpatient palliative care in a real-world setting can be differentiated into clinically meaningful phenotypes using brief, routinely collected PRO measures. Latent modeling provides a mechanism to use patient-reported data on a population level to identify distinct subgroups of patients with unmet palliative needs.</p>

<p><strong>BACKGROUND: </strong>Adherence to healthy behaviors reduces risks of cardiovascular disease and death in the general population. However, among people with kidney disease, a group at higher risk for cardiovascular disease, such benefits have not been established.</p>

<p><strong>METHODS: </strong>We pooled data from three cohort studies with a total of 27,271 participants. Kidney function was categorized on the basis of eGFR (≥60, 45 to &lt;60, and &lt;45 ml/min per 1.73 m). We used proportional hazard frailty models to estimate associations between healthy behaviors (not smoking, at recommended body mass index [BMI], physical activity, healthy diet, and moderate to no alcohol intake) and outcomes (all-cause death, major coronary events, ischemic stroke, and heart failure events).</p>

<p><strong>RESULTS: </strong>All recommended lifestyle behaviors were significantly associated with lower risks of death, regardless of eGFR. Not smoking (versus current) and any moderate to vigorous physical activity (versus none) was significantly associated with reduced risks of major coronary and heart failure events, regardless of eGFR. Any (versus no) moderate or vigorous physical activity significantly associated with decreased risk of ischemic stroke events only among those with eGFR ≥60. Moderate to no daily alcohol intake (versus excessive) was significantly associated with an increased risk of major coronary events, regardless of eGFR. For heart failure events, a BMI of 18.5 to 30 associated with decreased risk, regardless of eGFR. Across all eGFR categories, the magnitude of risk reduction for death and all cardiovascular outcomes increased with greater numbers of recommended lifestyle behaviors.</p>

<p><strong>CONCLUSIONS: </strong>Recommended lifestyle behaviors are associated with lower risk of death and cardiovascular disease events among individuals with or without reduced kidney function, supporting lifestyle behaviors as potentially modifiable risk factors for people with kidney disease.</p>