Post-Mastectomy Pain: An Updated Overview on Risk Factors, Predictors, and Markers.
Marco CalapaiEmanuela EspositoLuisa PuzzoDaniele Alfio VecchioRosario BlandinoGiuseppe BovaDomenico QuattroneCarmen MannucciIlaria AmmendoliaCristina MondelloSebastiano GangemiGioacchino CalapaiLuigi CardiaPublished in: Life (Basel, Switzerland) (2021)
After breast surgery, women frequently develop chronic post-mastectomy pain (PMP). PMP refers to the occurrence of pain in and around the area of the mastectomy lasting beyond three months after surgery. The nature of factors leading to PMP is not well known. When PMP is refractory to analgesic treatment, it negatively impacts the lives of patients, increasing emotional stress and disability. For this reason, optimizing the quality of life of patients treated for this pathology has gained more importance. On the basis of the findings and opinions above, we present an overview of risk factors and predictors to be used as potential biomarkers in the personalized management of individual PMP. For this overview, we discuss scientific articles published in peer-reviewed journals written in the English language describing risk factors, predictors, and potential biomarkers associated with chronic pain after breast surgery. Our overview confirms that the identification of women at risk for PMP is fundamental to setting up the best treatment to prevent this outcome. Clinical practice can be planned through the interpretation of genotyping data, choosing drugs, and tailoring doses for each patient with the aim to provide safer and more effective individual analgesic treatment.
Keyphrases
- chronic pain
- risk factors
- neuropathic pain
- pain management
- minimally invasive
- systematic review
- clinical practice
- end stage renal disease
- polycystic ovary syndrome
- risk assessment
- multiple sclerosis
- gene expression
- chronic kidney disease
- spinal cord injury
- spinal cord
- metabolic syndrome
- pregnant women
- replacement therapy
- insulin resistance
- case report
- big data
- atrial fibrillation
- patient reported outcomes
- artificial intelligence