In a recent study using a large population of patients, a cancer opioid risk scoring system showed a high degree of accuracy in predicting patients treated for cancer who had a strong likelihood of developing long-term opioid use. The study results were published in the journal Cancer.

In this study, a cancer opioid risk scoring model that had previously been developed was validated using data from a population of 44,932 Medicare beneficiaries treated for cancer with a local therapy. Patients were stratified into low-, moderate-, and high-risk groups based on predicted long-term opioid use risk scores. The scoring algorithm utilized metrics that involved presence of a depression diagnosis, use of chemotherapy, and opioid use patterns in the year before cancer treatment.

The primary study endpoint was persistent prescription opioid use between 1 and 2 years following the start of local treatment, with persistent opioid use defined as having filled a supply for 120 or more days or filling 10 or more opioid prescriptions during this period.

At 1 to 2 years following the start of the cancer treatment, 5.2% of the patients demonstrated chronic opioid use. Nearly two-thirds of patients in the study population were considered low-risk for long-term opioid use, approximately one-third were considered moderate-risk, and a small subset of patients were considered to be high-risk. Probabilities of long-term opioid use were 1.2% for the low-risk group, 5.6% for the moderate-risk group, and 75.1% for the high-risk group.

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Sensitivity and specificity of the model were assessed using a receiver operating characteristic curve analysis, which showed an area under the curve of 0.869. Additionally, an analysis comparing predicted and observed rates of long-term opioid use at 2 years showed a high level of agreement.

According to the study investigators, when applied to this large population of Medicare beneficiaries, the model performed similarly well to how it performed in earlier research. “Overall, the few factors in this cancer opioid risk score enable categorization of patients into 3 distinct risk groups with respect to the likelihood of persistent future opioid use,” wrote the researchers in their report.

Disclosures: Some authors declared affiliations with or received funding from the pharmaceutical industry. Please refer to the original article for a full list of disclosures.


Riviere P, Vitzthum LK, Nalawade V, et al. Validation of an oncology-specific opioid risk calculator in cancer survivors. Cancer. Published online December 30, 2020. doi:10.1002/cncr.33410