• Sriram Yennurajalingam, Tonya Edwards, Joseph Arthur, Zhanni Lu, Elif Erdogan, Jimi S Malik, Syed Mujtaba Ali Naqvi, Jimin Wu, Diane D Liu, Janet L Williams, David Hui, Suresh K Reddy, and Eduardo Bruera.
• Department of Palliative Care, Rehabilitation and Integrative Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX.
• Palliat Support Care. 2021 Feb 1; 19 (1): 3-10.

ObjectiveNon-medical opioid use (NMOU) is a growing crisis. Cancer patients at elevated risk of NMOU (+risk) are frequently underdiagnosed. The aim of this paper was to develop a nomogram to predict the probability of +risk among cancer patients receiving outpatient supportive care consultation at a comprehensive cancer center.Method3,588 consecutive patients referred to a supportive care clinic were reviewed. All patients had a diagnosis of cancer and were on opioids for pain. All patients were assessed using the Edmonton Symptom Assessment Scale (ESAS), Screener and Opioid Assessment for Patients with Pain (SOAPP-14), and CAGE-AID (Cut Down-Annoyed-Guilty-Eye Opener) questionnaires. "+risk" was defined as an SOAPP-14 score of ≥7. A nomogram was devised based on the risk factors determined by the multivariate logistic regression model to estimate the probability of +risk.Results731/3,588 consults were +risk. +risk was significantly associated with gender, race, marital status, smoking status, depression, anxiety, financial distress, MEDD (morphine equivalent daily dose), and CAGE-AID score. The C-index was 0.8. A nomogram was developed and can be accessed at https://is.gd/soappnomogram. For example, for a male Hispanic patient, married, never smoked, with ESAS scores for depression = 3, anxiety = 3, financial distress = 7, a CAGE score of 0, and an MEDD score of 20, the total score is 9 + 9+0 + 0+6 + 10 + 23 + 0+1 = 58. A nomogram score of 58 indicates the probability of +risk of 0.1.Significance Of ResultsWe established a practical nomogram to assess the +risk. The application of a nomogram based on routinely collected clinical data can help clinicians establish patients with +risk and positively impact care planning.

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