Identification of Patient-Reported Outcome Phenotypes Among Oncology Patients With Palliative Care Needs

PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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

Measurement of the inclusive semileptonic branching fraction of B mesons and |Vcb|

We present a measurement of the electron spectrum from inclusive semileptonic {\it B} decay, using 5.1 fb$^{-1}$ of $\Upsilon(4S)$ data collected with the Belle detector. A high-momentum lepton tag was used to separate the semileptonic {\it B} decay electrons from secondary decay electrons. We obtained the branching fraction, ${\cal B}(B\to X e^+ \nu) = (10.90 \pm 0.12 \pm 0.49)$, with minimal model dependence. From this measurement, we derive a value for the Cabibbo-Kobayashi-Maskawa matrix element $|V_{cb}| = 0.0408 \pm 0.0010 {\rm (exp)} \pm 0.0025{\rm (th)}$.Comment: 16 pages, 3 figures, 3 table

Direct effect of p,p'- DDT on mice liver

ABSTRACT Contact with the pesticide dichlorodiphenyltrichloroethane (p,p′-DDT) can be the cause of various harmful effects in humans, wildlife, and the environment. This pesticide is known to be persistent, lipophilic, resistant to degradation, and bioaccumulive in the environment and to be slowly released into bloodstream. Growing evidence shows that exposure to DDT is linked to type 2 diabetes mellitus. Individuals exposed to elevated levels of DDT and its metabolite have an increased prevalence of diabetes and insulin resistance. To evaluate these possible relationships, experiments were performed on eight-week-old female mice, divided into three groups (n = 10 per group): Group 1 received a vehicle-control intraperitoneal (i.p.) injection of sesame oil; Groups 2 and 3 received an i.p. dose of 50 and 100 µg/g p,p′-DDT respectively, dissolved in sesame oil. All groups were treated once daily for four days. Real-time PCR analysis of several genes was undertaken. Additionally, biochemical parameters and histopathological changes were measured. NQO1, HMOX1, NR1I3 and NR3C1 were up-regulated in DDT-exposed animals compared to the vehicle control group, while only SREBP1 was down-regulated in the 100 µg/g group. MTTP and FABP5, not previously reported for DDT exposure, but involved in regulation of fatty acid fluxes, could also function as biomarkers cross-talking between these signaling pathways. These results suggest that beyond epidemiological data, there is increasing molecular evidence that DDT may mimic different processes involved in diabetes and insulin resistance pathways