Clinical scoring algorithm for the prescription opioid misuse and abuse questionnaire (POMAQ). (3rd June 2022)

• Record Type: Journal Article
• Authors: Coyne, Karin S.; Schnoll, Sidney H.; Butler, Stephen F.; Barsdorf, Alexandra I.; Currie, Brooke M.; Mazière, Jean-Yves; Pierson, Renee F.; Porter, Leslie N.; Franks, CAPT Michael J.; Farrar, John T.
• Is Part Of: Current medical research and opinion. Volume 38:Number 6(2022)
• Page Start: 971
• Page End: 980
• Publication Date: 2022-06-03
• Subjects: Scoring algorithm -- misuse -- abuse -- chronic pain -- opioid -- patient-reported outcome; Clinical medicine -- Periodicals; Therapeutics -- Periodicals; 615.5
• DOI: 10.1080/03007995.2022.2065139
• Languages: English
• ISSNs: 0300-7995

Abstract

Abstract: Objective: The Prescription Opioid Misuse and Abuse Questionnaire (POMAQ) was developed to identify prescription opioid misuse and abuse among patients with chronic pain. A clinical scoring algorithm was developed and refined to align with the patient experience. Methods: This study utilized data from the POMAQ validation study (3033-4, NCT02660606) conducted on a sample of patients with chronic pain living in the United States. The study was carried out in two phases. Two purposefully enriched patient samples, one for each phase, were created based on patient responses to select POMAQ items and the availability of urine and hair samples. Two clinical experts (SHS, SFB) reviewed patient data to classify prescription opioid use behavior. Classification differences were adjudicated by a third clinical expert (JTF). Comparisons were made between the final clinical classification determined by the experts and the proposed classification based on the POMAQ algorithm. Results: Sixty patients were included in Phase I (only POMAQ data) and 52 in Phase II (including POMAQ and ancillary sources [e.g. electronic medical records, urine toxicity screen]). Refinements were made to the POMAQ scoring algorithm following discussions with clinical experts to ensure it was clinically relevant. For both phases, classifications were reviewed and discussed to achieve maximal concordance of classifications across experts. The proposed scoring algorithm was then modified to maximize agreement with the expert interpretation of clinically relevant patient experiences. Conclusion: The clinical scoring algorithm for the POMAQ was developed and refined to reflect clinically relevant patient behaviors identified by expert review. Future testing is needed to determine the sensitivity and specificity of this measure.