The bidirectional relationship between depression and chronic pain is well-recognized, but their clinical management remains challenging. Here we characterize the shared risk factors and outcomes for their comorbidity in the Australian Genetics of Depression cohort study (N = 13,839). Participants completed online questionnaires about chronic pain, psychiatric symptoms, comorbidities, treatment response and general health. Logistic regression models were used to examine the relationship between chronic pain and clinical and demographic factors. Cumulative linked logistic regressions assessed the effect of chronic pain on treatment response for 10 different antidepressants. Chronic pain was associated with an increased risk of depression (OR = 1.86 [1.37–2.54]), recent suicide attempt (OR = 1.88 [1.14–3.09]), higher use of tobacco (OR = 1.05 [1.02–1.09]) and misuse of painkillers (e.g., opioids; OR = 1.31 [1.06–1.62]). Participants with comorbid chronic pain and depression reported fewer functional benefits from antidepressant use and lower benefits from sertraline (OR = 0.75 [0.68–0.83]), escitalopram (OR = 0.75 [0.67–0.85]) and venlafaxine (OR = 0.78 [0.68–0.88]) when compared to participants without chronic pain. Furthermore, participants taking sertraline (OR = 0.45 [0.30–0.67]), escitalopram (OR = 0.45 [0.27–0.74]) and citalopram (OR = 0.32 [0.15–0.67]) specifically for chronic pain (among other indications) reported lower benefits compared to other participants taking these same medications but not for chronic pain. These findings reveal novel insights into the complex relationship between chronic pain and depression. Treatment response analyses indicate differential effectiveness between particular antidepressants and poorer functional outcomes for these comorbid conditions. Further examination is warranted in targeted interventional clinical trials, which also include neuroimaging genetics and pharmacogenomics protocols. This work will advance the delineation of disease risk indicators and novel aetiological pathways for therapeutic intervention in comorbid pain and depression as well as other psychiatric comorbidities.
Background: The bidirectional relationship between depression and chronic pain is well recognized but their clinical management remains challenging. Here we characterize the shared aetiology and risk factors for their comorbidity using large population cohorts to advance understanding of pharmacological treatment outcomes. Methods: Participants completed online questionnaires about chronic pain, psychiatric symptoms, comorbidities, treatment response and general health (N=13,839). Logistic regression models were used to examine the relationship between chronic pain and clinical and demographic factors. Cumulative linked logistic regressions assessed the effect of chronic pain on treatment response for 10 different antidepressants. Findings: Chronic pain was associated with an increased risk of depression (OR=1.86 [1.37-2.54]), recent suicide attempt (OR=1.88[1.14-3.09]), higher use of alcohol, tobacco and painkiller misuse. Participants with comorbid chronic pain and depression reported fewer functional benefits from antidepressant use and lower benefits from sertraline (OR=0.75[0.68-0.83]), escitalopram (OR=0.75[0.67-0.85]) and venlafaxine (OR=0.78[0.68-0.88]) when compared to participants without chronic pain. Furthermore, participants taking sertraline (OR=0.45[0.30-0.67]), escitalopram (OR=0.45[0.27-0.74]) and citalopram (OR=0.32[0.15-0.67]) specifically for chronic pain reported lower benefits compared to other participants taking these same medications but not for chronic pain. Interpretation: The findings reveal novel insights into the complex relationship between chronic pain and depression. Treatment response analyses indicate differential effectiveness between particular antidepressants and poorer functional outcomes for these comorbid conditions. Further assessment is warranted in targeted interventional trials. This approach will advance precision psychiatry and assist in clinical management by choosing the most suitable treatment for patients, informed by specific symptoms and comorbidities.
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