Predictors of Opioid Resistance: An Investigation in Cancer Pain. (3rd April 2022)

• Record Type: Journal Article
• Authors: Ogawa, Yasuha; Kurihara, Tatsuya; Sakurai, Mami; Momma, Megumi; Nakayama, Hirofumi; Higuchi, Hitomi; Kogo, Mari; Kiuchi, Yuji
• Is Part Of: Journal of pain & palliative care pharmacotherapy. Volume 36:Number 2(2022)
• Page Start: 79
• Page End: 87
• Publication Date: 2022-04-03
• Subjects: Pain relief -- opioid resistance -- cancer pain -- risk factor; Pain -- Treatment -- Periodicals; Analgesia -- Periodicals; Palliative treatment -- Periodicals; Analgesics -- Therapeutic use -- Periodicals; Pain -- drug therapy -- Periodicals; Pain -- prevention & control -- Periodicals; Palliative Care -- Periodicals; Analgesics -- therapeutic use -- Periodicals; 616.994
• DOI: 10.1080/15360288.2022.2064033
• Languages: English
• ISSNs: 1536-0288

Abstract

Abstract: Appropriate use of opioid analgesics according to the World Health Organization pain relief ladder has provided pain relief to many patients with cancer pain. However, a proportion of patients fail to achieve sufficient pain relief and develop opioid resistance. Individual risk factors may relate to opioid resistance. Therefore, we conducted a historical cohort study to identify risk factors for opioid resistance and to construct an index to predict it. We investigated salient factors at the time of opioid initiation in the medical records of 233 patients. The outcome was the achievement of stable pain at 14 days after opioid introduction. We identified factors contributing to opioid resistance by multivariate analysis (p < 0.05). We created a resistance score from the regression equation of the identified factors to predict opioid resistance. Forty-nine (21.0%) patients were opioid resistant without achieving the outcome. Age, neuropathic pain, and alkaline phosphatase were extracted as significant factors for opioid resistance (p < 0.05). A resistance score was created from these factors and classified into binary values, the sensitivity was 80.6% and the negative predictive value was 91.6%. The findings suggest that the resistance score could be a sensitive predictor of opioid resistance before opioid initiation.