Hansen Johan Liseth, Wangen Knut Reidar
University of Oslo, Oslo, Norway.
Quantify Research, Stockholm, Sweden.
Eur J Pain. 2025 Jan;29(1):e4706. doi: 10.1002/ejp.4706. Epub 2024 Aug 2.
Low back pain (LBP) is a leading reason for opioid use and a closer examination of opioid use and productivity losses among these patients is needed. We identify opioid use trajectories using a group-based trajectory model (GBTM) and estimate productivity losses across the trajectories.
Patients diagnosed with LBP in Swedish specialty care between 2011 and 2015, between the ages of 20 and 60, were included. Two GBTMs were estimated on monthly opioid use (converted to oral morphine equivalents) during the two 12-month periods preceding and following diagnosis. Productivity losses were estimated using the human-capital approach.
In total, 147,035 patients were included. The mean age at diagnosis was 43 years of age and 49% of the patients were male. A qualitative assessment of the identified groups in the GBTM models was made based on the patterns of opioid use. We chose three pre-diagnosis groups characterized as 'Pre-low' (N = 109,492), 'Pre-increase' (N = 27,336) and 'Pre-high' (N = 10,207). Similarly, four post-diagnosis groups were chosen and characterized as 'Post-low' (N = 73,287), 'Post-decrease' (N = 39,446), 'Post-moderate' (N = 20,001) and 'Post-high' (N = 13,595). Only 50% of the patients in the 'Pre-high' group were in the 'Post-high' group. The total productivity losses by the pre-diagnosis groups were more than 2.7 billion Euros over the total 6-year study period.
This study highlights how patients with LBP and high use of opioids are highly correlated before and after diagnosis. Patients with high use of opioids also exhibit high work absence and productivity losses.
This was the first study to estimate trajectories of opioids in the two time periods before and after a diagnosis of low back pain. For the first time, productivity losses were also estimated across the identified opioid use trajectories.
腰痛(LBP)是使用阿片类药物的主要原因,需要对这些患者的阿片类药物使用情况和生产力损失进行更深入的研究。我们使用基于群体的轨迹模型(GBTM)来识别阿片类药物使用轨迹,并估计各轨迹的生产力损失。
纳入2011年至2015年在瑞典专科护理中诊断为LBP、年龄在20至60岁之间的患者。在诊断前后的两个12个月期间,根据每月阿片类药物使用量(换算为口服吗啡当量)估计两个GBTM。使用人力资本方法估计生产力损失。
共纳入147,035名患者。诊断时的平均年龄为43岁,49%的患者为男性。根据阿片类药物使用模式对GBTM模型中识别出的组进行定性评估。我们选择了三个诊断前组,分别为“诊断前低用量组”(N = 109,492)、“诊断前增加组”(N = 27,336)和“诊断前高用量组”(N = 10,207)。同样,选择了四个诊断后组,分别为“诊断后低用量组”(N = 73,287)、“诊断后减少组”(N = 39,446)、“诊断后中等用量组”(N = 20,001)和“诊断后高用量组”(N = 13,595)。“诊断前高用量组”中只有50%的患者属于“诊断后高用量组”。在整个6年的研究期间,诊断前组的总生产力损失超过27亿欧元。
本研究强调了LBP患者和高阿片类药物使用情况在诊断前后高度相关。高阿片类药物使用的患者也表现出高缺勤率和生产力损失。
这是第一项估计腰痛诊断前后两个时间段内阿片类药物轨迹的研究。首次还对识别出的阿片类药物使用轨迹的生产力损失进行了估计。