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

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Abstract

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.

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Acknowledgments

The study was supported by an unrestricted grant from Norpharma A/S. Mech-Sense, Aalborg University Hospital has received funding from Innovation Fund Denmark for Strategic Research in Individuals, Disease and Society.

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    Authors and Affiliations

    1. Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Jagtvej 160, DK-2100, Copenhagen, Denmark

      Rasmus V Juul, Katrine R Knøsgaard, Anne E Olesen, Mads Kreilgaard, Lona L Christrup & Trine M Lund

    2. Mech-Sense, Department of Gastroenterology & Hepatology, Aalborg University Hospital, Aalborg, Denmark

      Anne E Olesen & Asbjørn M Drewes

    3. Urological Research Center, Lillebaelt Hospital, University of Southern Denmark, Fredericia, Denmark

      Katja V Pedersen & Palle J Osther

    4. Department of Clinical Genetics, Odense University Hospital, Odense, Denmark

      Katja V Pedersen

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    1. Rasmus V Juul
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    2. Katrine R Knøsgaard
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    3. Anne E Olesen
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    4. Katja V Pedersen
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    5. Mads Kreilgaard
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    6. Lona L Christrup
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    7. Palle J Osther
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    8. Asbjørn M Drewes
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    9. Trine M Lund
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    Correspondence to Trine M Lund.

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    Conflicts of Interest

    Asbjørn Mohr Drewes has received unrestricted research grants from Mundipharma, AstraZeneca, Lundbeck, and Pfizer and served as a Consultant/Advisory Board member for Mundipharma, AstraZeneca, Almirall, and Shire. Palle Jørn Sloth Osther has received an unrestricted research grant from Norpharma A/S. Rasmus Vestergaard Juul, Katrine Rørbæk Knøsgaard, Anne Estrup Olesen, Katja Venborg Pedersen, Mads Kreilgaard, Lona Louring Christrup, and Trine Meldgaard Lund have no conflict of interest to declare.

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    Rasmus V Juul and Katrine R Knøsgaard contributed equally to this work.

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    Juul, R.V., Knøsgaard, K.R., Olesen, A.E. et al. A Model-Based Approach for Joint Analysis of Pain Intensity and Opioid Consumption in Postoperative Pain. AAPS J 18, 1013–1022 (2016). https://doi.org/10.1208/s12248-016-9921-2

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    • DOI: https://doi.org/10.1208/s12248-016-9921-2

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