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Common Pitfalls of Head and Neck Research Using Cancer Registries
Author(s) -
Jones Evan A.,
Shuman Andrew G.,
Egleston Brian L.,
Liu Jeffrey C.
Publication year - 2019
Publication title -
otolaryngology–head and neck surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.232
H-Index - 121
eISSN - 1097-6817
pISSN - 0194-5998
DOI - 10.1177/0194599819838823
Subject(s) - medicine , univariate , cancer , disease , medline , inclusion (mineral) , research design , head and neck , data science , computer science , pathology , surgery , statistics , psychology , multivariate statistics , social psychology , mathematics , machine learning , political science , law
Objective To highlight common pitfalls observed in scientific research derived from national cancer registries, predominantly the Survival, Epidemiology, and End Results Program and the National Cancer Database. Data Sources Literature review and expert opinion. Review Methods This state‐of‐the‐art review consolidates the literature with editorial experiences describing how and why statistically flawed studies are usually rejected for publication, highlighting common errors in submitted articles employing national cancer registries. Conclusions Pitfalls were identified in 2 major areas—design and data analysis. Design pitfalls included unbalanced cohorts, uncontrolled covariates, and flawed oncologic variables. Analytical pitfalls included incorrect application of univariate analyses, inclusion of inaccurate data, and inclusion of stage IVc disease in curative survival analysis. Additional limitations of database studies were identified, including absence of patient‐related outcomes, hypothesis‐generating vs practice‐changing implications, and inability to differentiate between overall survival and disease‐specific survival. Implications for Practice Methodological strategies are suggested to ensure careful analytical design and appropriate interpretation. Although national cancer registries provide a wealth of data, researchers must remain vigilant when designing studies and analyzing these data sets. Inherent design flaws raise considerable problems with interpretation; however, when analyzed judiciously, registries can lead to a better understanding of cancer outcomes.

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