Validation of an oncology‐specific opioid risk calculator in cancer survivors. Issue 9 (30th December 2020)

• Record Type: Journal Article
• Authors: Riviere, Paul; Vitzthum, Lucas K.; Nalawade, Vinit; Deka, Rishi; Furnish, Timothy; Mell, Loren K.; Rose, Brent S.; Wallace, Mark; Murphy, James D.
• Is Part Of: Cancer. Volume 127:Issue 9(2021)
• Page Start: 1529
• Page End: 1535
• Publication Date: 2020-12-30
• Subjects: analgesics -- cancer pain -- cancer survivors -- clinical decision rules -- decision support techniques -- opioid -- opioid‐related disorders; Cancer -- Periodicals; Cancer -- Cytopathology -- Periodicals; 616.99405
• DOI: 10.1002/cncr.33410
• Languages: English
• ISSNs: 0008-543X

Abstract

Abstract : Background: Clinical guidelines recommend that providers risk‐stratify patients with cancer before prescribing opioids. Prior research has demonstrated that a simple cancer opioid risk score might help identify to patients with cancer at the time of diagnosis with a high likelihood of long‐term posttreatment opioid use. This current project validates this cancer opioid risk score in a generalizable, population‐based cohort of elderly cancer survivors. Methods: This study identified 44, 932 Medicare beneficiaries with cancer who had received local therapy. Longitudinal opioid use was ascertained from Medicare Part D data. A risk score was calculated for each patient, and patients were categorized into low‐, moderate‐, and high‐risk groups on the basis of the predicted probability of persistent opioid use. Model discrimination was assessed with receiver operating characteristic curves. Results: In the study cohort, 5.2% of the patients were chronic opioid users 1 to 2 years after the initiation of cancer treatment. The majority of the patients (64%) were at low risk and had a 1.2% probability of long‐term opioid use. Moderate‐risk patients (33% of the cohort) had a 5.6% probability of long‐term opioid use. High‐risk patients (3.5% of the cohort) had a 75% probability of long‐term opioid use. The opioid risk score had an area under the receiver operating characteristic curve of 0.869. Conclusions: This study found that a cancer opioid risk score could accurately identify individuals with a high likelihood of long‐term opioid use in a large, generalizable cohort of cancer survivors. Future research should focus on the implementation of these scores into clinical practice and how this could affect prescriber behavior and patient outcomes. Lay Summary: A novel 5‐question clinical decision tool allows physicians treating patients with cancer to accurately predict which patients will persistently be using opioid medications after completing therapy. Abstract : A recently published cancer opioid risk score predicting persistent opioid use in cancer survivors in the US Veterans Affairs Healthcare System now has been validated in an independent cohort of Medicare beneficiaries. This score has excellent discrimination (area under the curve = 0.869) and accurately stratifies patients.