Hyams grading system

Low and high-grade esthesioneuroblastoma display distinct patterns at presentation and relapse, leading to different prognoses. Therefore, they may be regarded as distinct entities 1).


The only histological grading system available for ENB was proposed by Hyams in 1988 on the basis of the Armed Forces Institute of Pathology experience

Hyams grading, a system used to define all upper respiratory tract carcinomas, is utilized to assess nuclear pleomorphism, mitotic activity, rosette presence, and necrosis, and summates these to produce Hyams 1–4 classification 2) It has been shown in the meta-analysis, as well as in large series, that Hyams grade 1 and 2 predict benign disease course, as compared to Hyams 3 and 4, which predict poor disease course. It is recommended that grading be performed in all cases 3) 4).


Vuong et al. verified that the Hyams grading system appears to be a reliable prognostic indicator to assess esthesioneuroblastoma outcomes. Consolidating the Hyams grading system into a three-tier system based on similar clinical outcomes of grades I and II may simplify this classification schema 5).


1)
Malouf GG, Casiraghi O, Deutsch E, Guigay J, Temam S, Bourhis J. Low- and high-grade esthesioneuroblastomas display a distinct natural history and outcome. Eur J Cancer. 2013 Apr;49(6):1324-34. doi: 10.1016/j.ejca.2012.12.008. Epub 2013 Jan 10. PMID: 23312882.
2)
Hyams V. Tumors of the upper respiratory tract and ear. Washington, D.C.: Armed Forces Institute of Pathology; 1988
3)
Van Gompel JJ, Giannini C, Olsen KD, et al. Long- term outcome of esthesioneuroblastoma: Hyams grade predicts patient survival. J Neurol Surg B Skull Base. 2012; 73:331–336
4)
Kane AJ, Sughrue ME, Rutkowski MJ, et al. Posttreatment prognosis of patients with esthesioneuroblastoma. J Neurosurg. 2010; 113:340–351
5)
Vuong HG, Ngo TNM, Dunn IF. Consolidating the Hyams grading system in esthesioneuroblastoma - an individual participant data meta-analysis. J Neurooncol. 2021 Mar 26. doi: 10.1007/s11060-021-03746-2. Epub ahead of print. PMID: 33770323.
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