A personalized approach to assessing and managing pain in patients with cancer

Abstract

Pain is one of the most common and distressing symptoms in patients with cancer. In this review, we discuss an evidence-based approach to personalized pain assessment and management. Recent insights into the pain expression pathway have led to a paradigm shift in pain management, allowing clinicians to deliver personalized treatments tailored to the individual's needs. Personalized pain management begins with systematic screening, followed by comprehensive pain assessment. Impeccable characterization of pain informs its etiology and the mechanism to guide treatment choices. Identification of modulators of pain expression such as psychological distress, alcoholism, substance use, and delirium allow clinicians to further tailor treatment recommendations. Documentation of a personalized pain goal provides an individualized response criterion. A multidimensional treatment plan is then formulated targeting the pain mechanism, etiologic factors, and modulators. Finally, longitudinal monitoring customized to the individual's needs allows clinicians to improve adherence and, ultimately, to optimize pain control over time.

Conflict of interest statement

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

© 2014 by American Society of Clinical Oncology.

Figures

Fig 1.

The pain expression pathway. Progressive cancer, cancer treatments, and nonmalignant pathologies can all contribute to tissue injury and inflammation, leading to generation of pain signals peripherally. These signals are then transmitted through afferent pathways and perceived in the somatosensory cortex. The level of pain perceived is further filtered before it is expressed. Multiple modulators may increase or decrease the level of pain expression, including depression, anxiety, spiritual distress, chemical coping, and cognitive impairment. Importantly, we cannot reliably measure pain generation and perception. Pain expression can only be assessed in clinical practice with the use of patient-reported outcomes.

Fig 2.

Personalized management based on pain modulators. Two patients with the same level of pain expression may have different modulators. In patient 1, increased nociception as a result of tumor compression is the dominant factor contributing to pain, and an increase in the dose of analgesia may help alleviate the pain. This is in contrast to patient 2, in whom delirium and hyperalgesia from opioid-induced neurotoxicity is contributing to an increased pain expression. For this patient, prompt opioid rotation, rather than increasing the dose of opioid, would be the most appropriate management. This example highlights the importance of recognizing pain modulators and targeting treatment recommendations based on these predictors.

Fig 3.

Personalized pain assessment and management. Personalized pain management involves systematic screening, detailing of pain characteristics, identification of potential modulators, documentation of a personalized pain goal, formulation of a multidimensional treatment plan, and longitudinal monitoring.