A Model-Based Approach for Joint Analysis of Pain Intensity and Opioid Consumption in Postoperative Pain

Joint analysis of pain intensity and opioid consumption is encouraged in trials of postoperative pain. However, previous approaches have not appropriately addressed the complexity of their interrelation in time. In this study, we applied a non-linear mixed effects model to simultaneously study pain intensity and opioid consumption in a 4-h postoperative period for 44 patients undergoing percutaneous kidney stone surgery. Analysis was based on 748 Numerical Rating Scale (NRS) scores of pain intensity and 51 observed morphine and oxycodone dosing events. A joint model was developed to describe the recurrent pattern of four key phases determining the development of pain intensity and opioid consumption in time; (A) Distribution of pain intensity scores which followed a truncated Poisson distribution with time-dependent mean score ranging from 0.93 to 2.45; (B) Probability of transition to threshold pain levels (NRS ≥ 3) which was strongly dependent on previous pain levels ranging from 2.8–15.2% after NRS of 0–2; (C) Probability of requesting opioid when allowed (NRS ≥ 3) which was strongly correlated with the number of previous doses, ranging from 89.8% for requesting the first dose to 26.1% after three previous doses; (D) Reduction in pain scores after opioid dosing which was significantly related to the pain intensity at time of opioid request (P < 0.001). This study highlights the importance of analyzing pain intensity and opioid consumption in an integrated manner. Non-linear mixed effects modeling proved a valuable tool for analysis of interventions that affect pain intensity, probability of rescue dosing or the effect of opioids in the postoperative pain period.