An Interventional Pain Algorithm for the Treatment of Postmastectomy Pain Syndrome: A Single-Center Retrospective Review. Academic Article uri icon

Overview

abstract

  • OBJECTIVE: Breast cancer is the most common female malignancy worldwide. Breast surgery and adjuvant oncological therapies are often required to increase survival. Treatment-related pain may persist and evolve into postmastectomy pain syndrome (PMPS) in a significant subset of breast cancer survivors. In this retrospective investigation, we will present our experience in applying an interventional algorithmic approach to treat PMPS. DESIGN: A retrospective study. SETTING: An academic cancer hospital. SUBJECTS: Adult females with PMPS diagnosis. METHODS: We reviewed 169 records with the diagnosis of PMPS from 2015 to 2019 within our health system. Pre- and post-injection pain scores, relief duration, and medication usage changes were collected. The decision to perform each procedure was based on the anatomic location of the painful area with the corresponding peripheral sensory innervation. Decision-making flow diagrams were created to present our experience in managing PMPS beyond peripheral nerve blocks. RESULTS: Ultrasound-guided peripheral nerve block results (n=350) were analyzed. The mean baseline pain score was 7, compared with the post-treatment mean score of 3 (95% confidence interval: 3.58 to 3.98, P = 0.0001). Among the responders, the mean pain relief duration was 45 days, with a median of 84 days. Opioid medication consumption was reduced by 11% (t = 0.72, P = 0.47). CONCLUSIONS: Ultrasound-guided nerve blocks of this area could be performed safely and effectively after breast surgeries. We also present our proposed algorithm to provide a stepwise application for selecting the appropriate therapies in the management of more complex PMPS.

publication date

  • March 18, 2021

Research

keywords

  • Breast Neoplasms

Identity

PubMed Central ID

  • PMC7971473

Scopus Document Identifier

  • 85103226958

Digital Object Identifier (DOI)

  • 10.1093/pm/pnaa343

PubMed ID

  • 33155049

Additional Document Info

volume

  • 22

issue

  • 3