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. 2024 Jun;18(3):227-242.
doi: 10.1177/20494637231216352. Epub 2023 Nov 26.

Does opioid therapy enhance quality of life in patients suffering from chronic non-malignant pain? A systematic review and meta-analysis

Karl V L Kraft  1 , Teresa Backmund  1 , Leopold Eberhart  1 , Ann-Kristin Schubert  1 , Hanns-Christian Dinges  1 , Maria K Hagen  2 , Markus Gehling  3
Affiliations

Does opioid therapy enhance quality of life in patients suffering from chronic non-malignant pain? A systematic review and meta-analysis

Karl V L Kraft et al. Br J Pain. 2024 Jun.

Abstract

Background and objective: Chronic pain is associated with a poor health-related quality of life (HRQL). Whereas the prescription rate of opioids increased during the last decades, their use in chronic non-malignant pain remains unclear. However, there is currently no clinical consensus or evidence-based guidelines that consider the long-term effects of opioid therapy on HRQL in patients with chronic non-cancer pain. This systematic review aims to address the question of whether opioid therapy improves HRQL in patients with chronic non-malignant pain and provide some guidance to practitioners.

Databases and data treatment: PubMed, EMBASE and CENTRAL were searched in June 2020 for double-blind, randomized trials (RCTs), comparing opioid therapy to placebo and assessed a HRQL questionnaire. The review comprises a qualitative vote counting approach and a meta-analysis of the Short Form Health Survey (SF-36), EQ-5D questionnaire and the pain interference scale of the Brief pain inventory (BPI).

Results: 35 RCTs were included, of which the majority reported a positive effect of opioids for the EQ-5D, the BPI and the physical component score (PCS) of the SF-36 compared to placebo. The meta-analysis of the PCS showed a mean difference of 1.82 [confidence interval: 1.32, 2.32], the meta-analysis of the EQ-5D proved a significant advantage of 0.06 [0.00, 0.12]. In the qualitative analysis of the mental component score (MCS) of the SF-36, no positive or negative trend was seen. No significant differences were seen in the MCS (MD: 0.65 [-0.43, 1.73]). A slightly higher premature dropout rate was found in the opioid group (risk difference: 0.04 [0.00, 0.07], p = .07). The body of evidence is graded as low to medium.

Conclusion: Opioids have a statistically significant, but small and clinical not relevant effect on the physical dimensions of HRQL, whereas there is no effect on mental dimensions of HRQL in patients with chronic non-malignant pain during the initial months of treatment. In clinical practice, opioid prescriptions for chronic non-cancer pain should be individually assessed as their broad efficacy in improving quality of life is not confirmed. The duration of opioid treatment should be determined carefully, as this review primarily focuses on the initial months of therapy.

Keywords: Chronic pain; health related quality of life; opioid; quality of life.

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Conflict of interest statement

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.1.
Figure 1.1.
Summary of the risk of bias assessment of included studies: lalo 2010 - Khoromi.
Figure 1.2.
Figure 1.2.
Summary of the risk of bias assessment of included studies: Kivitz 2006 - Webster.
Figure 2.
Figure 2.
Flowchart of literature search.
Figure 3.
Figure 3.
Risk of Bias of all studies included.
Figure 4.
Figure 4.
Forest Plot of PCS (physical quality of life). Meta-analysis of all PCS datasets. Mean differences between Opioid and Placebo. A generic inverse variance method with random effects was used. Pooled estimates of the weighted mean difference are shown with 95% CIs. Pooled effect estimates are presented as diamonds and lines depict the 95% CIs.
Figure 5.
Figure 5.
Forest Plot of MCS (physical quality of life). Meta-analysis of all MCS datasets. Mean differences between Opioid and Placebo. A generic inverse variance method with random effects was used. Pooled estimates of the weighted mean difference are shown with 95% CIs. Pooled effect estimates are presented as diamonds and lines depict the 95% CIs.
Figure 6.
Figure 6.
Forest Plot of EQ-5D. Mean differences between Opioid and Placebo. A generic inverse variance method with random effects was used. Pooled estimates of the weighted mean difference are shown with 95% CIs. Pooled effect estimates are presented as diamonds and lines depict the 95% CIs.
Figure 7.
Figure 7.
Meta-analysis of premature withdrawals. Pooled Risk Difference of Opioid compared to Placebo. Mantel-Haenszel method with a random effect model was used. Pooled effect estimates are presented as diamonds and lines depict the 95% CIs.
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