Risk Stratification Using a Novel Genetic Classifier Including PLEKHS1 Promoter Mutations for Differentiated Thyroid Cancer with Distant Metastasis

Thyroid ◽  
2020 ◽  
Vol 30 (11) ◽  
pp. 1589-1600 ◽  
Author(s):  
Chan Kwon Jung ◽  
Seung-Hyun Jung ◽  
Sora Jeon ◽  
Young Mun Jeong ◽  
Yourha Kim ◽  
...  
2017 ◽  
Vol 102 (5) ◽  
pp. 1757-1764 ◽  
Author(s):  
Tae Hyuk Kim ◽  
Chang-Seok Ki ◽  
Hye Seung Kim ◽  
Kyunga Kim ◽  
Jun-Ho Choe ◽  
...  

Abstract Context: Currently, no recurrence or mortality risk systems consider molecular testing when predicting thyroid cancer outcomes. Objective: We developed an integrative prognostic system that incorporates telomerase reverse transcription (TERT) promoter mutations into the recently proposed risk reclassification system after initial therapy [dynamic risk stratification (DRS)] to better categorize and predict outcomes. Design: A total of 357 differentiated thyroid cancer (DTC) patients without initial distant metastasis were enrolled. Among patients with mutated TERT and wild-type, recurrence-free survival (RFS) was compared according to DRS grouping. Cox regression was used to calculate adjusted hazard ratios (AHRs) to derive AHR groups. Performance of the AHR grouping system with respect to prediction of structural recurrence and cancer-specific survival (CSS) was assessed against the current DRS system and the tumor/node/metastasis (TNM) classification. Results: Among 357 patients, there were 90 recurrences and 15 cancer-related deaths during a median of 14 years of follow-up. Patients in higher AHR groups were at higher risk of recurrence (10-year RFS for AHR 1, 2, 3, and 4: 94.9%, 82.7%, 50.2%, and 23.1%; P < 0.001) and cancer-related death (10-year CSS: 100.0%. 98.7%, 94.2%, and 76.9%; P < 0.001). The proportions of variance explained (PVEs) for the ability of AHR and DRS grouping to predict recurrence were 22.4% and 18.5%. PVEs of AHR and TNM system to predict cancer-related deaths were 11.5% and 7.4%. Conclusions: The AHR grouping system, a simple two-dimensional prognostic system, is as effective as DRS at predicting structural recurrence and provides clinical implication for long-term CSS in patients with nonmetastatic DTC.


Endocrine ◽  
2017 ◽  
Vol 58 (1) ◽  
pp. 167-175 ◽  
Author(s):  
Seo Young Sohn ◽  
Young Nam Kim ◽  
Hye In Kim ◽  
Tae Hyuk Kim ◽  
Sun Wook Kim ◽  
...  

2021 ◽  
Author(s):  
Evert F.s. van Velsen ◽  
Robin P. Peeters ◽  
Merel T. Stegenga ◽  
F.j. van Kemenade ◽  
Tessa M. van Ginhoven ◽  
...  

Objective Recent research suggests that the addition of age improves the 2015 American Thyroid Association (ATA) Risk Stratification System for differentiated thyroid cancer (DTC). The aim of our study was to investigate the influence of age on disease outcome in ATA High Risk patients with a focus on differences between patients with papillary (PTC) and follicular thyroid cancer (FTC). Methods We retrospectively studied adult patients with High Risk DTC from a Dutch university hospital. Logistic regression and Cox proportional hazards models were used to estimate the effects of age (at diagnosis) and several age cutoffs (per five years increment between 20 and 80 years) on (i) response to therapy, (ii) developing no evidence of disease (NED), (iii) recurrence, and (iv) disease specific mortality (DSM). Results We included 236 ATA High Risk patients (32% FTC) with a median follow-up of 6 years. Age, either continuously or dichotomously, had a significant influence on having an excellent response after initial therapy, developing NED, recurrence, and DSM for PTC and FTC. For FTC, an age cutoff of 65 or 70 years showed the best statistical model performance, while this was 50 or 60 years for PTC. Conclusions In a population of patients with High Risk DTC, older age has a significant negative influence on disease outcomes. Slightly different optimal age cutoffs were identified for the different outcomes, and these cutoffs differed between PTC and FTC. Therefore, the ATA Risk Stratification System may further improve should age be incorporated as an additional risk factor.


Author(s):  
Gonzalo Díaz-Soto ◽  
Beatriz Torres Torres ◽  
Juan José López ◽  
Susana García ◽  
María Álvarez Quiñones ◽  
...  

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