Opioid Abuse Risk in Patients with Chronic Pain

VBCN - July 2015 Volume 2, No 2

Washington, DC—In the treatment of chronic nonmalignant pain, patient-specific factors, especially household income, more accurately predicted quality-of-life outcomes than opioid use, according to a study presented at the 2015 American Academy of Neurology annual meeting.

With more than 140,000 deaths from unintentional overdose, hundreds of thousands of hospital admissions because of overdose, and millions of Americans addicted to opioids, the plight of these analgesics has been called the worst man-made epidemic in modern medical history, according to Vitaly Gordin, MD, Department of Anesthesiology, Penn State Hershey Medical Center & College of Medicine, Hershey, PA. The ability to predict the risk–benefit profile could improve patient outcomes.

“These preliminary results suggest that depression assessment, educational status, and household income predict patient quality of life and opioid abuse risk just as well as, if not better than, opioid quantity-related factors,” said Dr Gordin.

Previous opioid therapy studies have focused on urban and suburban areas, minority populations, and/or abuse rather than therapeutic use. By contrast, Dr Gordin and colleagues investigated therapeutic chronic opioid use in a rural population to determine how patient-specific factors impact quality-of-life and therapeutic outcomes.

Survey Instruments

A total of 133 patients completed the RAND 36-Item Health Survey, a quality-of-life assessment that incorporates physical functioning, social functioning, role limitations, emotional well-being, and pain measures. The Opioid Risk Tool, also completed by patients, is a self-reported screening tool designed to assess the risk that chronic opioid use may result in aberrant behavior. Finally, patients were given the Patient Health Questionnaire-9 (PHQ-9) to screen for and measure the severity of depression.

Physicians supplied participant-specific medical information, the Pain Assessment and Documentation Tool (PADT), and the Diagnosis, Intractability, Risk, Efficacy (DIRE) tool.

“PADT assesses daily activities, side effects, drug-related behaviors, and analgesia. DIRE measures social support, treatment efficacy, and risk of aberrant behavior to assess the risk of opioid abuse and suitability of candidates for therapy,” Dr Gordin and colleagues noted.


Specific aspects of quality of life significantly correlated with demographic information. Household income positively correlated with increased social functioning (P = .012); improved physical functioning (P = .002); and increased emotional well-being (P = .002).

Educational status positively correlated with improved physical functioning (P = .007), and increased emotional well-being (P = .003).

In addition, the PHQ-9 depression assessment and antidepressant use positively correlated with opioid risk score (P = .002 and P = .001, respectively).

The PHQ-9 depression assessment score also negatively correlated with:

  • Average percentage of pain relieved (P = .037)
  • Treatment efficacy (P = .007).

“Histories of substance abuse, physical abuse, and sexual abuse poorly correlate with treatment efficacy, opioid risk, and patient quality of life,” Dr Gordin reported.

Daily opioid dose, by contrast, negatively correlated with physical functioning (P = .038), social functioning (P = .02), bodily pain (P = .046), and emotional well-being (P = .012).

“These results indicate that patients’ demographic information, in addition to relevant social and medical history, should be taken into account when assessing future patients with chronic pain for opioid management, and influence outcomes just as much, if not more, than a substance abuse history,” Dr Gordin said.

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