Validation of an oncology-specific opioid risk calculator in cancer survivors.

Journal Article (Journal Article)


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.


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.


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.


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.

Full Text

Duke Authors

Cited Authors

  • Riviere, P; Vitzthum, LK; Nalawade, V; Deka, R; Furnish, T; Mell, LK; Rose, BS; Wallace, M; Murphy, JD

Published Date

  • May 1, 2021

Published In

Volume / Issue

  • 127 / 9

Start / End Page

  • 1529 - 1535

PubMed ID

  • 33378556

Electronic International Standard Serial Number (EISSN)

  • 1097-0142

International Standard Serial Number (ISSN)

  • 0008-543X

Digital Object Identifier (DOI)

  • 10.1002/cncr.33410


  • eng