BACKGROUND: There is no consensus regarding the comparison of staging classifications. Recently, numerous staging classifications for thyroid carcinoma have been described. This study was performed to evaluate the relative discriminating ability of these different staging systems. METHODS: A literature review was conducted to identify the available staging classifications used for thyroid carcinoma. To compare the various staging classifications, cause specific survival data from a retrospective review of 382 patients with papillary and follicular thyroid carcinoma treated at Princess Margaret Hospital were applied to the various staging classifications. The ability of these classifications to distinguish the stage groupings were compared in the following ways: 1) tabulating the numbers of patients within each stage group; 2) collapsing stage groupings into high and low risk groups and calculating mortality rates at 10 and 15 years; 3) summing observed deviations at 5, 10, and 15 years; and 4) calculating the proportion of variance explained (PVE) for each staging classification, using each classification separately as a prognostic factor in a Cox regression model. RESULTS: The application of the PVE model, the only method of the four that used statistical inference, showed no statistically significant superiority of any system over the TNM classification of the American Joint Committee on Cancer (AJCC) and the International Union Against Cancer (UICC) in their ability to discriminate stage groupings. CONCLUSIONS: Because the TNM classification of the AJCC and UICC is universally available and widely accepted for other disease sites, the authors recommend it for all reports of the treatment and outcome of patients with thyroid carcinoma. Individual research groups also may use an alternative, validated classification to report results, provided that the outcomes are also reported using the TNM classification to facilitate comparison between different centers.
BACKGROUND: There is no consensus regarding the comparison of staging classifications. Recently, numerous staging classifications for thyroid carcinoma have been described. This study was performed to evaluate the relative discriminating ability of these different staging systems. METHODS: A literature review was conducted to identify the available staging classifications used for thyroid carcinoma. To compare the various staging classifications, cause specific survival data from a retrospective review of 382 patients with papillary and follicular thyroid carcinoma treated at Princess Margaret Hospital were applied to the various staging classifications. The ability of these classifications to distinguish the stage groupings were compared in the following ways: 1) tabulating the numbers of patients within each stage group; 2) collapsing stage groupings into high and low risk groups and calculating mortality rates at 10 and 15 years; 3) summing observed deviations at 5, 10, and 15 years; and 4) calculating the proportion of variance explained (PVE) for each staging classification, using each classification separately as a prognostic factor in a Cox regression model. RESULTS: The application of the PVE model, the only method of the four that used statistical inference, showed no statistically significant superiority of any system over the TNM classification of the American Joint Committee on Cancer (AJCC) and the International Union Against Cancer (UICC) in their ability to discriminate stage groupings. CONCLUSIONS: Because the TNM classification of the AJCC and UICC is universally available and widely accepted for other disease sites, the authors recommend it for all reports of the treatment and outcome of patients with thyroid carcinoma. Individual research groups also may use an alternative, validated classification to report results, provided that the outcomes are also reported using the TNM classification to facilitate comparison between different centers.
Authors: R Michael Tuttle; Hernan Tala; Jatin Shah; Rebecca Leboeuf; Ronald Ghossein; Mithat Gonen; Matvey Brokhin; Gal Omry; James A Fagin; Ashok Shaha Journal: Thyroid Date: 2010-10-29 Impact factor: 6.568
Authors: Daniel Mankarios; Peter Baade; Pip Youl; Robin H Mortimer; Adedayo A Onitilo; Anthony Russell; Suhail A R Doi Journal: Endocrine Date: 2013-10-31 Impact factor: 3.633
Authors: Aubrey A Carhill; Danielle R Litofsky; Douglas S Ross; Jacqueline Jonklaas; David S Cooper; James D Brierley; Paul W Ladenson; Kenneth B Ain; Henry G Fein; Bryan R Haugen; James Magner; Monica C Skarulis; David L Steward; Mingxhao Xing; Harry R Maxon; Steven I Sherman Journal: J Clin Endocrinol Metab Date: 2015-07-14 Impact factor: 5.958