A Tool to Assess Risk of De Novo Opioid Abuse or Dependence

Abstract

Background Determining risk factors for opioid abuse or dependence will help clinicians practice informed prescribing and may help mitigate opioid abuse or dependence. The purpose of this study is to identify variables predicting opioid abuse or dependence. Methods A retrospective cohort study using de-identified integrated pharmacy and medical claims between October 2009 and September 2013. Patients with at least one opioid prescription claim during the index period (index claim) were identified. We ascertained risk factors using data from 12 months prior to index claim (pre-period) and captured abuse or dependency diagnosis using data from 12 months post index claim (post-period). We included continuously eligible (pre- and post-period) commercially insured patients aged 18 or older. We excluded patients with cancer, residence in a long-term care facility, or previous diagnosis of opioid abuse or dependence (identified by International Classification of Diseases-9th revision (ICD-9) code or buprenorphine/naloxone claim in the pre-period). The outcome was a diagnosis of opioid abuse (ICD9 code 304.0×) or dependence (305.5). Results The final sample consisted of 694,851 patients. Opioid abuse or dependence was observed in 2,067 patients (0.3%). Several factors predicted opioid abuse or dependence: younger age [per decade (older) odds ratio (OR) 0.68], being a chronic opioid user [OR 4.39], history of mental illness [OR 3.45], non-opioid substance abuse [OR 2.82], alcohol abuse [OR 2.37], high morphine equivalent dose per day user [OR 1.98], tobacco use [OR 1.80], obtaining opioids from multiple prescribers [OR 1.71], residing in the South [OR 1.65], West [OR 1.49], or Midwest [OR 1.24], using multiple pharmacies [OR 1.59], male gender [OR 1.43], and increased 30-day adjusted opioid prescriptions [OR 1.05]. Conclusions Readily available demographic, clinical, behavioral, pharmacy and geographic information can be used to predict likelihood of opioid abuse or dependence.

Effect of treatment modality on chronic opioid use in patients with T1/T2 oropharyngeal cancer

“…Although neither Pang et al nor Kwon et al found an association between age and chronic opioid use, multiple studies with significantly larger populations have demonstrated an increased risk of opioid dependence in younger patients . Likewise, we found that the risk of chronic opioid use doubled for a given individual compared to someone 10 years older in our cohort.…”

Chronic opioid use in patients undergoing treatment for oropharyngeal cancer

“…Younger OPSCC patients (age ≤ 62 years, P < .0001) were more at risk for chronic opioid use at 3 months posttreatment. Studies in noncancer patients, have shown that patients younger than 50 years of age are more likely to use and become dependent on opioids . It is also established that chronic pain is comorbid with mental illness .…”

“…Studies in noncancer patients, have shown that patients younger than 50 years of age are more likely to use and become dependent on opioids. 18 It is also established that chronic pain is comorbid with mental illness. 19 Moreover, adults with mood disorders are nearly twice as likely to use opioids long term for pain.…”

Wisdom of the CROUD: Development and validation of a patient-level prediction model for opioid use disorder using population-level claims data

“…Numerous models have been developed that predict opioid use disorder in patients who are current opioid users [6][7][8][9]. Models incorporating predictors such as opioid prescribing patters in addition to demographics, non-opioid substance abuse, mental health conditions, hepatitis and cancer and have been able to predict future opioid use disorder with high discriminative ability (area under the receiver operating characteristic curve (AUC) as high as 0.93) [6,9]. However, a model that can predict opioid use disorder at the point a patient is first dispensed an opioid (i.e., when the patient is opioid naïve) has not been developed.…”