Literature DB >> 23765800

Histologic grade as prognostic indicator for mucoepidermoid carcinoma: a population-level analysis of 2400 patients.

Michelle M Chen1, Sanziana A Roman, Julie A Sosa, Benjamin L Judson.   

Abstract

BACKGROUND: Mucoepidermoid carcinoma (MEC) is an uncommon malignancy. To the best of our knowledge, this is the largest study investigating disease-specific survival (DSS) of parotid MEC and the first population-level study of the distribution of nodal metastases.
METHODS: Patients with MEC of the parotid gland were identified in the Surveillance, Epidemiology, and End Results (SEER) database (1988-2009).
RESULTS: We identified 2400 patients with MEC: 522 low grade, 1137 intermediate grade, and 741 high grade. Five-year DSS rates for low-grade, intermediate-grade, and high-grade MEC were 98.8%, 97.4%, and 67.0%, respectively (p < .001). Negative prognostic factors included high grade, increasing patient age, and tumor size, extraparenchymal extension, nodal metastases, and distant metastases. High-grade MEC was more likely to have lymph node metastases in levels I to III (34.0%) than low-grade (3.3%) and intermediate-grade MEC (8.1%; p < .001).
CONCLUSION: Grade influences the prognosis and distribution of nodal metastases. Results indicate that management guidelines should vary based on grade.
Copyright © 2013 Wiley Periodicals, Inc.

Entities:  

Keywords:  lymph node metastases; mucoepidermoid carcinoma; parotid gland; salivary gland carcinoma; survival

Mesh:

Year:  2013        PMID: 23765800     DOI: 10.1002/hed.23256

Source DB:  PubMed          Journal:  Head Neck        ISSN: 1043-3074            Impact factor:   3.147


  25 in total

1.  Overall and cause-specific survival for mucoepidermoid carcinoma of the major salivary glands: Analysis of 2210 patients.

Authors:  Zachary C Taylor; Erin A Kaya; Jeffrey D Bunn; Zachary D Guss; Brian J Mitchell; Robert K Fairbanks; Wayne T Lamoreaux; Aaron E Wagner; Ben J Peressini; Christopher M Lee
Journal:  World J Clin Oncol       Date:  2020-12-24

2.  Sclerosing Mucoepidermoid Carcinoma: A unique case.

Authors:  Keshava Bhat; Bhavna Pandey; Pushparaja Shetty; Vidya Manohar; M K Shruthilaxmi; Madhvika Patidar
Journal:  Sultan Qaboos Univ Med J       Date:  2014-04-07

3.  Incidence, treatment, and outcome of parotid carcinoma, 1996-2011: a population-based study in Thuringia, Germany.

Authors:  Orlando Guntinas-Lichius; Thomas G Wendt; Jens Buentzel; Dirk Esser; Daniel Böger; Andreas H Mueller; Jörn-Uwe Piesold; Stefan Schultze-Mosgau; Peter Schlattmann; Harald Schmalenberg
Journal:  J Cancer Res Clin Oncol       Date:  2015-03-24       Impact factor: 4.553

4.  Prognostic factors and occult nodal disease in mucoepidermoid carcinoma of the oral cavity and oropharynx: An analysis of the National Cancer Database.

Authors:  Mark A Ellis; Evan M Graboyes; Terry A Day; David M Neskey
Journal:  Oral Oncol       Date:  2017-07-27       Impact factor: 5.337

5.  Immunohistochemical Assessment of BAP1 Protein in Mucoepidermoid Carcinomas.

Authors:  Aanchal Kakkar; Prerna Guleria; Karan Madan; Rajeev Kumar; Sunil Kumar; Deepali Jain
Journal:  Indian J Otolaryngol Head Neck Surg       Date:  2018-12-19

6.  Mucoepidermoid carcinoma: Evaluating the prognostic impact of primary tumor site.

Authors:  Ximena Mimica; Avery Yuan; Ashley Hay; Nora Katabi; Daniella Karassawa Zanoni; Cristina Valero; Jatin P Shah; Richard J Wong; Marc A Cohen; Snehal G Patel; Ian Ganly
Journal:  Oral Oncol       Date:  2021-11-09       Impact factor: 5.337

Review 7.  Salivary mucoepidermoid carcinoma revisited.

Authors:  Andrés Coca-Pelaz; Juan P Rodrigo; Asterios Triantafyllou; Jennifer L Hunt; Alessandra Rinaldo; Primož Strojan; Missak Haigentz; William M Mendenhall; Robert P Takes; Vincent Vander Poorten; Alfio Ferlito
Journal:  Eur Arch Otorhinolaryngol       Date:  2014-04-26       Impact factor: 2.503

Review 8.  Molecular Pathology and Biomarkers.

Authors:  Patrick K Ha; Göran Stenman
Journal:  Adv Otorhinolaryngol       Date:  2016-04-12

9.  Patterns of treatment failure in salivary gland cancers.

Authors:  Mateusz Szewczyk; Paweł Golusiński; Jakub Pazdrowski; Piotr Pieńkowski; Sławomir Marszałek; Jacek Sygut; Wojciech Golusiński
Journal:  Rep Pract Oncol Radiother       Date:  2018-06-23

10.  Machine learning models to predict length of stay and discharge destination in complex head and neck surgery.

Authors:  Khodayar Goshtasbi; Tyler M Yasaka; Mehdi Zandi-Toghani; Hamid R Djalilian; William B Armstrong; Tjoson Tjoa; Yarah M Haidar; Mehdi Abouzari
Journal:  Head Neck       Date:  2020-11-03       Impact factor: 3.147

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