Risk Tool Shows Promise for Predicting Adverse Opioid-Related Outcomes in Cancer Survivors
Predictive models demonstrated the ability to anticipate adverse opioid-related outcomes among cancer survivors.
A study released by the National Cancer Institute demonstrated the potential for a risk tool to forecast adverse opioid-related outcomes among cancer survivors.
Personalized risk stratification approaches could guide management when prescribing opioids in patients with cancer, with further validation.
In this cohort of 106,732 Veteran cancer survivors, the overall incidence of persistent post-treatment opioid use was 8.3% (95% CI, 8.1-8.4) which varied by cancer type. The rates of persistent opioid use after treatment varied substantially by a patient’s history of opioid use prior to their cancer diagnosis.
Predictive models showed a high level of discrimination when identifying individuals at risk of adverse opioid-related outcomes including persistent opioid use (area under curve [AUC] = 0.85), future diagnoses of opioid abuse of dependence (AUC = 0.87), and admission for opioid abuse or toxicity (AUC = 0.78).
Researchers developed an online risk tool for these predictive models to assist with clinical implementation (www.CancerOpioidRisk.org).
“Similar to cancer stage informing the management of anti-neoplastic therapy, an accurate prediction of future opioid-related morbidity can be used to personalize pain management and mitigate adverse outcomes,” the researchers wrote.
Current guidelines suggest strategies including establishing a signed treatment agreement, periodic urine drug testing, patient and caregiver education, referrals to palliative medicine or a pain specialist, avoidance of high-risk formulations, and minimizing total daily dose for patients at increased risk of adverse opioid-related outcomes.
Cancers with more intensive, multi-modal therapies had the highest adjusted risk for persistent opioid use including esophagus, pancreas, liver, head and neck, and lung cancer. Prior opioid use was highly associated with future chronic use. The results also supported prior research indicating increased risk for opioid use among younger patients, the unemployed, current or former smokers, and those with a prior diagnosis of depression or drug abuse.
Other factors associated with opioid risk identified in this study such as race, median income, non-abusive alcohol use, comorbidity, body mass index, and cancer type have not been previously reported. Researchers also found no association between gender and persistent opioid use, which differs from other studies, though there was a skewed gender distribution due to the study population coming from within the VA healthcare system.
“Despite these limitations, this current study represents one of the largest comprehensive evaluations of persistent opioid use and abuse in cancer survivors, and the first to construct a predictive model in oncology patients,” the researchers wrote.
According to a study published in September of 2018 that looked at the opioid epidemic over the past 10 years, death from opioids as the primary cause noted on death certificates are 10 times less likely to occur in patients with cancer versus the general population.2
Validation in a non-VA cohort of cancer patients is required to help understand generalizability of the findings and determine the predictive ability for the general population.
References:
1. Vitzthum LK, Riviere P, Sheridan P, et al. Predicting Persistent Opioid Use, Abuse and Toxicity Among Cancer Survivors. International Journal of Radiation Oncology. September 2019;105(1);S71. doi:10.1016/j.ijrobp.2019.06.524.
2. Chino FL, Kamal A, Chino JP. Opioid-associated deaths in patients with cancer: A population study of the opioid epidemic over the past 10 years. Presented at: 2018 ASCO Quality care Symposium; September 28-29, 2018; Phoenix, AZ. Abstract 230.
