• Peter D Vu, Ryan S D'Souza, and Saba Javed.
• Department of Physical Medicine and Rehabilitation, McGovern Medical School, The University of Texas Health Science Center at Houston, 1333 B Moursund St., Ste. 114, Houston, TX, 77030, USA. peter.d.vu@uth.tmc.edu.
• Curr Pain Headache Rep. 2025 Jan 27; 29 (1): 3636.

Purpose Of ReviewQuickly referenceable, streamlined, algorithmic approaches for advanced pain management are lacking for patients, trainees, non-pain specialists, and interventional specialists. This manuscript aims to address this gap by proposing a comprehensive, evidence-based algorithm for managing neuropathic, nociceptive, and cancer-associated pain. Such an algorithm is crucial for pain medicine education, offering a structured approach for patient care refractory to conservative management.Recent FindingsA comprehensive literary review with PubMed and regulatory documents from the United States Food and Drug Administration were searched for a variety of interventions. Pain syndromes were categorized into nociceptive and neuropathic pain, and an algorithm was constructed. Serving as an educational tool for patients, trainees, and non-pain specialists, and as an accessible reference for pain specialists, this algorithm bridges knowledge gaps, promotes interdisciplinary collaboration, and streamlines the learning curve for new practitioners. The strength of this algorithm lies in integrating extensive clinical data, emphasizing the latest clinical evidence, and providing a structured decision-making pathway.© 2025. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

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