Abstract
Dear Editor,
I congratulate Cooper et al on their research investigating the outcomes in patients with T3-4N0-1 cancer of the larynx using the Surveillance, Epidemiology, and End Results (SEER) database in 1820 advanced laryngeal cancer patients. 1 This retrospective analysis included patients with advanced T-stage nonmetastatic laryngeal cancers (T3-4N0-1) to compare outcomes between those who underwent adjuvant radiation and those who underwent laryngectomy alone. The majority of patients received adjuvant therapy (RT). N0 patients who received laryngectomy and who did not undergo adjuvant radiation had a 47% higher risk of cancer-specific death than patients receiving adjuvant RT. N1 patients who did not undergo adjuvant radiation had a 90% higher risk of cancer-specific death than patients receiving RT after surgery. This study provides real-world data for adjuvant radiation in patients with T3-4N0-1 laryngeal carcinoma. However, concerns require attention to enhance the interpretation of the results, which could offer valuable guidance for future research on this critical subject.
In this study, although the authors mentioned handling missing data by excluding it, this approach may lead to a reduction in sample size and introduce selection bias. To improve data integrity and accuracy, it is recommended to use more advanced methods for handling missing data, such as multiple imputation, which can better maintain sample size and reduce biases caused by missing data. In addition, while the study indicates that adjuvant radiation improves survival rates for patients, it does not sufficiently discuss the side effects of radiation therapy. Side effects can significantly impact a patient’s quality of life, and future studies should consider weighing the treatment benefits against the side effects, clarifying the toxicity and clinical significance of radiation. The omission of a discussion on radiation side effects is due to the limitations of the SEER database used in this study, as it does not provide detailed records of post-treatment side effects. Therefore, future studies should aim to collect comprehensive treatment information, including side effect data, to provide a more holistic basis for clinical decision-making. Furthermore, while the study employed propensity score matching (PSM) to balance baseline characteristics between treatment groups, the specific implementation of this method was not thoroughly explained. The core purpose of PSM is to eliminate treatment selection bias by adjusting for baseline characteristics, so a clearer explanation is needed on how matching variables were selected and how results were analyzed after matching. Future studies could describe the specific steps of PSM in more detail to ensure transparency and reproducibility of the method.
Footnotes
Data Availability Statement
Not applicable.
Declaration of Conflicting Interests
The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
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Ethical Approval
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Declaration of Generative AI and AI-Assisted Technologies in the Writing Process
During the preparation of this work, the authors used ChatGPT to improve language. After using this service, the authors reviewed and edited the content as needed and took full responsibility for the content of the publication.