Σφακιανάκης Αλέξανδρος
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5 Άγιος Νικόλαος
Κρήτη 72100
00302841026182
00306932607174
alsfakia@gmail.com

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Σάββατο 15 Δεκεμβρίου 2018

Refining the tumor-node-metastasis staging system for individualized treatment of differentiated thyroid carcinoma

Publication date: February 2019

Source: Oral Oncology, Volume 89

Author(s): Young Nam Kim, Mijin Kim, Hyeon Seon Ahn, Kyunga Kim, So Young Park, Hye In Kim, Min Ji Jeon, Won Gu Kim, Sun Wook Kim, Won Bae Kim, Jae Hoon Chung, Young Kee Shong, Tae Yong Kim, Tae Hyuk Kim

Abstract
Background

Patients with differentiated thyroid carcinoma (DTC) are staged according to the single age cut point in addition to anatomic extent. A novel staging system is needed to properly show the character and prognosis of DTC by considering age as a continuous variable. We aimed to refine stage and prognostic groups of the eighth edition tumor-node-metastasis (TNM-8) staging system for DTC and to suggest a possible revision.

Methods

We conducted a retrospective data abstraction study of patients with newly diagnosed DTC who were treated at one of two tertiary referral centres in Seoul, Korea between 1994 and 2005. We used recursive partitioning analysis to derive a new staging classification (TNM-RPA) and compared its prediction of cancer-specific survival with that of TNM-8.

Results

The cohort comprised 6342 patients with DTC who were followed up for a median of 11.4 years. Higher TNM-RPA groups were associated with increased risk of death (10-year cancer-specific survival for stages IA, IB, IIA, IIB, III, and IV: 99.6%, 98.1%, 93.0%, 92.4%, 75.1%, and 56.6%, respectively; P < 0.001). The C-index values were 0.869 (95% CI, 0.833–0.905) for the TNM-RPA and 0.819 (0.789–0.850) for TNM-8. The proportions of variance explained for the ability of the TNM-RPA and TNM-8 stages to predict cancer-specific survival were 7.1% and 5.7%, respectively.

Conclusion

This study presents a RPA-based TNM stage groupings that incorporate multiple age cutoffs and essential anatomic information, which can be conveniently used to facilitate the individual prediction of long-term cancer-specific survival in patients with DTC.



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