Stress and Pain. Predictive (Neuro)Pattern Identification for Chronic Back Pain: A Longitudinal Observational Study - Wippert, Pia-Maria; Puerto Valencia, Laura; Drießlein, David (Frontiers in Medicine, 2022)
Introduction: Low back pain (LBP) leads to considerable impairment of quality of life worldwide and is often accompanied by psychosomatic symptoms. Objective: First, to assess associations between stress and chronic low back pain (CLBP) and its simultaneous appearance with fatigue and depression as a symptom triad. Second, to identify the most predictive stress-related pattern set for CLBP for a one-year diagnosis. Methods: In a one-year observational study with four measurement points, a total of 140 volunteers (aged 18-45 years with intermittent pain) were recruited. Primary outcomes were pain (intensity (CPI), disability (DISS)), fatigue and depressive mood. Stress was assessed as chronic stress, perceived stress, effort reward imbalance, life events and physiological markers (Allostatic-Load-Index (ALI), Hair-Cortisol (HCC)). Multiple linear regression models and selection procedures for model shrinkage and variable selection [LASSO] were applied. Prediction accuracy was calculated by RMSE and ROC curves. Results: 110 participants completed baseline assessments (28.2 ±7.5 years, 38.1% female), including HCC, further 46 agreed to ALI laboratory measurements. Different stress types were associated with LBP, CLBP, fatigue and depressive mood and its joint occurrence as a symptom triad at baseline; mainly social-related stress types were of relevance. Work-related stress (“Excessive Demands at Work” (b=0.51 [95%CI -0.23, 1.25] p=0.18) played a role for upcoming chronic pain disability. “Social Overload" (b=0.45 [95%CI -0.06, 0.96, p=0.080) and "Over-commitment at Work" (b=0.28 [95% -0.39, 0.95], p=0.42) were associated with upcoming depressive mood within one-year. Finally, seven psychometric (CPI: RMSE=12.63; DISS: RMSE=9.81) and five biomarkers (CPI: RMSE=12.21; DISS: RMSE=8.94) could be derived as most predictive pattern set for a one-year prediction of CLBP. The biomarker set showed an apparent AUC of 0.88 for CPI and 0.99 for DISS. Conclusion: Stress disrupts allostasis and favors the development of chronic pain, fatigue, and depression and the emergence of a "hypocortisolemic symptom triad.", whereby social-related stressors play a significant role. For translational medicine a predictive pattern set could be derived which enables to diagnose individuals at higher risk for upcoming pain disorders and can be used in practice.