The influence of age on disease outcome in 2015 ATA high-risk differentiated thyroid cancer patients
| Autor: | Folkert J. van Kemenade, Tessa M van Ginhoven, Frederik A. Verburg, Robin P. Peeters, Evert F S van Velsen, W. Edward Visser, Merel T Stegenga |
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| Přispěvatelé: | Internal Medicine, Pathology, Surgery, Radiology & Nuclear Medicine |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Male
medicine.medical_specialty Endocrinology Diabetes and Metabolism Population Disease Kaplan-Meier Estimate Logistic regression Endocrinology SDG 3 - Good Health and Well-being Internal medicine medicine Humans Thyroid Neoplasms Risk factor Follicular thyroid cancer education Thyroid cancer Aged Retrospective Studies education.field_of_study Proportional hazards model business.industry Thyroid Age Factors General Medicine Middle Aged medicine.disease medicine.anatomical_structure Female business |
| Zdroj: | European Journal of Endocrinology, 185(3), 421-429. Bioscientifica Ltd |
| ISSN: | 0804-4643 |
| DOI: | 10.1530/eje-21-0365 |
| Popis: | 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 5 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. |
| Databáze: | OpenAIRE |
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