Histopathological predictors of lymph node metastasis in oral cavity squamous cell carcinoma: a systematic review and meta-analysis.

Autor:	Alqutub S; Department of Pathology and Laboratory Medicine, King Abdulaziz University, Jeddah, Saudi Arabia., Alqutub A; Department of Otolaryngology-Head and Neck Surgery, King Abdulaziz University, Jeddah, Saudi Arabia., Bakhshwin A; Department of Pathology and Laboratory Medicine, King Abdulaziz University, Jeddah, Saudi Arabia., Mofti Z; Department of Family and Community Medicine, King Abdulaziz University, Jeddah, Saudi Arabia., Alqutub S; Department of Family and Community Medicine, University of Jeddah, Jeddah, Saudi Arabia., Alkhamesi AA; Department of Otolaryngology-Head and Neck Surgery, King Abdulaziz University, Jeddah, Saudi Arabia., Nujoom MA; Department of Otolaryngology-Head and Neck Surgery, King Abdulaziz University, Jeddah, Saudi Arabia., Rammal A; Department of Otolaryngology-Head and Neck Surgery, King Abdulaziz University, Jeddah, Saudi Arabia., Merdad M; Department of Otolaryngology-Head and Neck Surgery, King Abdulaziz University, Jeddah, Saudi Arabia., Marzouki HZ; Department of Otolaryngology-Head and Neck Surgery, King Abdulaziz University, Jeddah, Saudi Arabia.
Jazyk:	angličtina
Zdroj:	Frontiers in oncology [Front Oncol] 2024 May 14; Vol. 14, pp. 1401211. Date of Electronic Publication: 2024 May 14 (Print Publication: 2024).
DOI:	10.3389/fonc.2024.1401211
Abstrakt:	Objectives: Lymph node metastasis (LNM) is the most significant parameter affecting overall survival in patients with oral cavity squamous cell carcinomas (OCSCC). Elective neck dissection (END) is the standard of care in the early management of OCSCC with a depth of invasion (DOI) greater than 2-4 mm. However, most patients show no LNM in the final pathologic report, indicating overtreatment. Thus, more detailed indicators are needed to predict LNM in patients with OCSCC. In this study, we critically evaluate the existing literature about the risk of different histological parameters in estimating LNM. Methods: A systematic review was conducted using PRISMA guidelines. PubMed, Web of Science, Cochrane, and Scopus were searched from inception to December 2023 to collect all relevant studies. Eligibility screening of records was performed, and data extraction from the selected studies was carried out independently. Inclusion in our systematic review necessitated the following prerequisites: Involvement of patients diagnosed with OCSCC, and examination of histological parameters related to lymph node metastasis in these studies. Exclusion criteria included animal studies, non-English articles, non-availability of full text, and unpublished data. Results: We included 217 studies in our systematic review, of which 142 were eligible for the meta-analysis. DOI exceeding 4 mm exhibited higher risk for LNM [Risk ratio (RR) 2.18 (1.91-2.48), p<0.00001], as did perineural invasion (PNI) [RR 2.04 (1.77-2.34), p<0.00001], poorly differentiated tumors [RR 1.97 (1.61-2.42), p<0.00001], lymphovascular invasion (LVI) [RR 2.43 (2.12-2.78), p<0.00001], groups and single pattern of invasion [RR 2.47 (2.11-2.89), p<0.00001], high tumor budding [RR 2.65 (1.99-3.52), p<0.00001], tumor size over 4 cm [RR 1.76 (1.43-2.18), p<0.00001], tumor thickness beyond 4 mm [RR 2.72 (1.91-3.87), p<0.00001], involved or close margin [RR 1.73 (1.29-2.33), p = 0.0003], and T3 and T4 disease [RR 1.98 (1.62-2.41), p <0.00001]. Conclusion: Our results confirm the potential usefulness of many histopathological features in predicting LNM and highlight the promising results of others. Many of these parameters are not routinely incorporated into pathologic reports. Future studies must focus on applying these parameters to examine their validity in predicting the need for elective neck treatment. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2024 Alqutub, Alqutub, Bakhshwin, Mofti, Alqutub, Alkhamesi, Nujoom, Rammal, Merdad and Marzouki.)
Databáze:	MEDLINE
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