Abstract
We read with great interest the study by Moharrami et al (2026) regarding the heterogeneity of preradiotherapy tooth extraction. While identifying impaired performance status and severe periodontitis as key predictors is valuable, we believe 3 critical points warrant further discussion.
First, recording bias in retrospective data. Standardized dental records are typically mandatory for oral cavity cancers but often sparse for non-oral head and neck cancers (Abed 2023). If missing periodontal or decayed, missing, and filled surfaces (DMFS) data were imputed, it might introduce nonrandom classification bias. We suggest disclosing data completeness across different primary sites to ensure reliability.
Second, the secondary impact of surgical intervention on the bone microenvironment. Patients receiving surgery + radiotherapy (RT) possess vastly different bone vascularity than those receiving RT alone. Surgical devascularization significantly lowers the healing ceiling of extraction sockets (Kubota et al 2021). Treating surgery as a binary variable may oversimplify this complexity.
Finally, the net benefit of extraction is heavily contingent on the healing interval prior to RT and alternative interventions (Watson et al 2021). Clinicians often favor preventive restoration over extraction for patients with non-oral head and neck cancer (HNC). If the model fails to account for RT delays caused by extraction or fails to isolate the contribution of successful nonsurgical shielding in the no-extraction group, it may lead to overoptimism regarding the no-extraction strategy (Goh et al 2023).
In conclusion, future models should integrate anatomic dosimetry, surgical history, and healing time windows to achieve true precision medicine.
Author Contributions
Y.M. Zhou, X. Meng, contributed to conception, data acquisition and interpretation, drafted and critically revised manuscript. All authors gave their final approval and agreed to be accountable for all aspects of the work.
Footnotes
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported in part by the Japan-China Sasakawa Medical Fellowship.
Declaration of generative AI-assisted technologies in preparation process
During the preparation of this manuscript, the authors used Gemini for language editing. The authors reviewed and approved the final content and take full responsibility for the manuscript.
Data Availability
Data sharing is not applicable to this article as no new datasets were generated or analyzed during the current study.