Biological and Clinical Underpinnings of Postoperative Pain - Mastectomy

Overview

Persistent pain after mastectomy remains a significant clinical challenge that can delay recovery, reduce quality of life, and increase long-term healthcare burden. The goal of this study is to gain a deeper understanding of the biological and clinical factors that influence pain severity after mastectomy and contribute to the transition from acute to chronic postoperative pain. Guided by a biopsychosocial framework, this research will address the following aims: 1. We will use standardized experimental pain testing before surgery to evaluate how patients respond to different types of controlled sensory stimuli. These responses may help predict who is more likely to experience severe or prolonged pain after surgery. 2. We will analyze blood samples collected before and after surgery to measure markers of inflammation and other biological responses. These data will help us explore how the body's immune and hormonal systems relate to pain severity in both the short- and longer-term recovery phases. 3. We will assess psychological and clinical factors, such as emotional health, coping style, household income, and life stressors, to understand how they contribute to patients' pain experiences throughout recovery. 4. We will examine whether routinely collected demographic and clinical characteristics can help identify patients at greater risk of experiencing higher levels of pain after surgery. This approach will allow us to better understand which patients may benefit from more tailored perioperative pain management strategies.

The overarching goal of this study is to elucidate the biological, psychological, and clinical factors that are responsible for pain trajectories following mastectomy. Using a biopsychosocial framework, we aim to identify modifiable risk and protective mechanisms that could inform the development of targeted interventions to prevent chronic postsurgical pain. Aim 1: Characterize individual differences in pain processing using standardized experimental pain testing. Participants will complete a battery of quantitative sensory testing (QST) measures preoperatively to assess their sensitivity to mechanical, thermal, and pressure-based stimuli. These standardized tests capture individual differences in nociceptive and central pain modulation. By linking preoperative pain sensitivity profiles to postoperative pain intensity and duration, we will determine whether QST-derived measures can serve as early predictors of maladaptive pain trajectories. Aim 2: Examine biological and inflammatory mechanisms underlying postoperative pain persistence. Peripheral blood samples will be collected at multiple time points before and after surgery to quantify circulating markers of inflammation (e.g., IL-6, CRP), neuroendocrine function (e.g., oxytocin, vasopressin), and immune regulation. These biomarkers will be analyzed in relation to clinical pain outcomes to identify biological signatures associated with resilience versus vulnerability to chronic pain. This aim will provide mechanistic insight into how systemic physiological responses to surgery contribute to prolonged nociceptive signaling. Aim 3: Assess psychosocial determinants of pain and recovery. We will evaluate key psychological and social-contextual variables, including emotional health, coping style, catastrophizing, optimism, perceived stress, and socioeconomic indicators-to determine how these factors influence postoperative pain experiences and recovery. This comprehensive assessment will clarify how psychological resilience and environmental stressors interact with biological processes to shape individual pain outcomes. Aim 4: Develop a multidimensional risk model integrating demographic, clinical, and mechanistic predictors. Using routinely collected demographic and perioperative data (e.g., age, sex, race, comorbidities, analgesic use, surgical approach), combined with the experimental, biological, and psychosocial measures from Aims 1-3, we will construct an integrative predictive model of postoperative pain outcomes. This approach will allow us to identify distinct risk phenotypes and generate clinically actionable profiles for early identification of patients most likely to benefit from personalized perioperative pain management strategies. Together, these efforts will advance our understanding of how biological, psychological, and contextual factors jointly influence pain recovery after surgery, with the long-term goal of informing precision pain medicine and improving postoperative care.