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Precision Medicine Tool Improves Predictability of Opioid Use Disorder

May 24, 2017
An algorithm based on genetic markers and independent risk factors was designed to provide a risk stratification aid for clinical opioid prescribing and management.

Interview with Maneesh Sharma, MD, and Gerardo Miranda-Comas, MD

The Proove Opioid Risk (POR) profile may be a useful tool in identifying patients who need additional monitoring, guidance, or more conservative therapy while taking opioids,1 said Maneesh Sharma, MD, director of the Interventional Pain Institute in Baltimore, Maryland.  

Patients deemed at moderate to high risk for opioid dependence based on their POR score showed significantly greater risk of developing opioid use disorder (OUD),1 according to the results of a study published in Pharmacogenomics and Personalized Medicine.1

“There is increasing importance of precision medicine and more thorough clinical decision algorithms for complex patient cases,” Dr. Sharma said, coauthor of the multicenter, observational study assessing the efficacy of this tool. “This information may prove important when formulating multimodal approaches to therapy, implementing judicious opioid prescribing practices, and preventing addiction,” Dr. Sharma told Practical Pain Management.

A precision medicine tool may improve predictability of patient risk for opioid use disorder.

Study Design

In this study,1 the researcher team evaluated the performance of the POR profile in 908 patients with chronic, noncancer pain who were prescribed opioids: 258 subjects with OUD and 650 controls without OUD.

The POR tool used phenotypic and genotype information to calculate a risk score that correlated with high- , moderate-, or low-risk stratification of opioid dependence:1

  • Low-risk—opioid therapy may be prescribed
  • Moderate-risk—proceed with caution when prescribing opioids; consider more frequent urine drug testing and possibly limiting the duration of opioid therapy
  • High-risk—consider an alternative analgesic to improve patient outcomes, consider more frequent urine drug testing, limit the duration of opioid therapy, contemplate titrating the patient off opioid therapy, maintain vigilant awareness of patient outcomes, and possibly recommend or refer for medically-assisted treatment for detoxification.

“Compared to ‘low’ risk patients, ‘moderate’ and ‘high’ risk patients were found to have, on average, increased odds of OUD diagnosis of 4.17-fold and 16.5-fold, respectively, and were categorized with 95.7% sensitivity,” Dr. Sharma said.

Strengths and Limitations of the Study

“Strengths of the study include a large number of subjects, but that comes with a weakness of large variability in diagnosis,” commented Gerardo Miranda-Comas, MD, assistant professor of rehabilitation medicine, Icahn School of Medicine at Mount Sinai, New York, NY. In addition, “it is an observational study without objective measures,” he said.

“This study was sponsored by Proove—the company that named the tool—and is involved in genetic testing, which is a promising precision medicine tool, but at the moment still needs further investigation,” Dr. Miranda-Comas told Practical Pain Management. “While the findings look promising, based on this study alone one cannot conclude that it is the best tool out there.”

Dr. Miranda-Comas added that the tool “needs further research and comparison with other tools, such as the Brief Risk Questionnaire (BRQ), Screener and Opioid Assessment for Patients with Pain (SOAPP-R), and Opioid Risk Tool (ORT).” 

“Proove Opioid Risk profile provides a decision-making tool that may improve clinical outcomes, reduce deaths and abuse, and potentially reduce health care costs,” Dr. Miranda-Comas concluded. “Although it looks promising to test for genotype features that could help predict and identify patients at higher risk for addiction, it still needs more scientific evidence.”

Devising the Precision Medicine Tool

“The POR profile was developed by analyzing a combination of genetic markers and non-genetic factors that were independently associated with risk of opioid misuse or abuse, and deriving a predictive algorithm that weighs these factors appropriately,” said Dr. Sharma.

“Each individual component was independently validated to correlate with relevant aberrant behaviors/disorders, and then the accuracy of the combined algorithm was validated by 5 clinical validity and 3 clinical utility studies conducted by Proove Biosciences,” he said.

The research included a “validity study in which the predictive accuracy of the profile was evaluated by comparing results in patients versus control subjects. The clinical utility studies examined the impact on physician decision-making and what the outcomes were for patients,” Dr. Sharma said. “We are seeing that the most common utilization of this tool may be to change the opioid prescribed, with the most benefit to patients arising from either discontinuing or initiating opioids, depending on the patient cohort and risk level,” he said.

“This profile can be integrated into clinical practice by reviewing results when making a change to a patient’s opioid prescription, including initiating opioids, and incorporating that information into clinical decision-making strategies,” he told Practical Pain Management.

Last updated on: June 20, 2017
Continue Reading:
Managing Opioid Use Disorders and Chronic Pain

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1 comment.

By dr on 06/02/2017
Ouch! Once again, Proove is marketing pseudoscience. Dr Sharma has no addiction training; he's an interventional clinician. This is an observational, cherry-picking study. The CEO, a sharp guy needs to get out of the science chair! WTF?! The SNPs are archaic. https://www.ncbi.nlm.nih.gov/pubmed/20520587 In 2010, using GWAS even has SNPs we don't know. The mesocorticolimbic system is isolated; the SNPs are incorrect. The ANKK1 1800497 was excluded from a recent study which these authors might have read (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4399004/) and why not consider HTR3A or B? Why are they still using GABRG2? Try glutamate for protective or BDNF. The science has no prospective proper methodology. And the use of this general data mining garbage? Why have protocols? Come on Brian, when are you going to let scientists direct the science?
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