This aim of this study was to evaluate the association of medical, surgical, sociodemographic, and psychological factors with pain severity, pain interference, opioid administration and subsequent hospital admission in cancer patients presenting to the ED with pain. Cancer patients presenting to the ED with a complaint of acute pain (> 4/10 NRS) completed validated self-report measures assessing sociodemographic, cancer and medical history, pain (BPI), and psychosocial factors (depression, anxiety, pain catastrophizing, and sleep disturbance). ED pain scores, opioid administration (converted to MME/hour) and inpatient admission were abstracted from the medical record. Univariable analyses were conducted to individually compare predictors with outcomes, and significant predictors were used to build multivariable models for each predictor. Patients (n=175) were 55% female, predominantly white (81%), frequently had metastatic disease (76%), and 42% reported current outpatient opioid use for pain. On multivariable regression analyses, only current outpatient opioid use was independently associated with all pain-related outcomes (severity, interference, and MME/hour). Higher catastrophizing and sleep disturbance were both significantly associated with greater pain severity and interference. History of chronic pain prior to cancer diagnosis, depression, and income were significantly associated only with pain severity, and greater formal education and greater anxiety were associated only with pain interference. No significant associations were observed for hospital admission. Patients' medical, sociodemographic, and psychosocial characteristics were variably associated with worse pain severity and interference, opioid administration in the ED, with multivariable analyses suggesting ongoing outpatient opioid use and psychosocial variables are important predictors of pain outcomes. Our findings suggest that a more person-centered assessment of potential pain modulators may help identify individuals with cancer whose analgesic regimen would benefit from optimization and targeted multimodal and preventive analgesic therapies. Grant support from The National Palliative Care Research Center Kornfeld Scholars Award and a grant from the NIH (NIH/NIGMS: R35 GM128691).