Optimizing Management Strategies for Vocal Cord Nodules: A Systematic Review

声带小结管理策略优化:系统性综述

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Abstract

Vocal cord nodules (VCNs) can be treated with a variety of therapeutic approaches, with controversy regarding the optimal management. This review provides an overview of the most commonly used management strategies and their outcomes to enhance decision making. We conducted a systematic literature search on PubMed, Web of Science, and Scopus to include relevant original articles published in peer-reviewed journals from inception through April 2024. We used a broad search strategy including the following search keywords: "Vocal" AND "Nodules" OR "Lesions." All interventions were included, such as speech or voice therapy, medication, surgery, and other therapies. Two authors independently conducted initial screening, full-text screening, inclusion, and data collection. Disagreements were settled by consensus or, if persistent, by a senior author. A total of 18 articles were included in the current scoping review. Voice therapy is highlighted as the preferred non-invasive treatment; however, it requires a longer duration to show results. In children, voice therapy is further limited by non-compliance, which may result in delayed recovery and increased psychological and economic burden. Surgery offers immediate improvements but necessitates postoperative voice therapy to prevent recurrence. In hard or mature nodules, surgery showed superior efficacy compared to voice therapy. Pharmacotherapy is principally indicated to treat an underlying disease and is often prescribed as an adjunct to voice therapy. Patient age, duration of the disorder, morphological features of VCNs, and compliance with voice therapy are significant prognostic factors in determining the success or failure of different treatment modalities. We propose a management algorithm that incorporates these key factors to assist in effective management and decision making. In addition, the management of VCNs requires a methodical approach that considers the prognostic factors associated with each treatment modality. We propose a key-factor-based algorithm that incorporates these factors to assist in therapeutic decision making and guide future research toward establishing definitive guidelines.

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