Papillary thyroid cancer (PTC) is by far the most common thyroid malignancy, reaching a prevalence of about 80%. Furthermore, it represents the unique responsible for the increasing thyroid cancer incidence. Upon thyroid ablation (thyroidectomy with or without iodine-131 administration), PTC has an excellent prognosis with nearly 100% 5-year disease-specific survival.
However, about 25-30% of patients experience disease morbidity, as related to persistent structural disease/recurrence upon initial standard treatment, and 10% die over time, as related to cancer. Furthermore, the latest data from the US Surveillance, Epidemiology, and End Results found that disease-related mortality is slightly increasing over time.
Owing to these issues, to identify the PTC subgroup with the worst outcome represents the prognostic goal. To date, prognostic stratification relies on death-predicting (such as the AJCC/TNM and the MACIS) and persistence/recurrence predicting (such as that provided by the
American Thyroid Association (ATA)) systems, with the latter being the most useful in clinical practice. However, for all such approaches, the long-term risk stratification is suboptimal, due to the low proportion of variance explained (a statistical measure analyzing the capability of a staging system to predict the outcome of interest) and, more importantly, to the low positive predictive value.
To date, despite the deep knowledge of thyroid cancer genetics, any PTC-related molecular alteration has revealed enough specificity to be used in isolation for prognostic purpose. Therefore, current prognostication of DTC relies on a non-standardized multivariable approach, as derived by the combination of clinico-pathological and genetic features.
This Research Topic welcomes contributions of any type (clinical trial, correction, editorial, general commentary, hypothesis & theory, methods, mini review, opinion, original research, perspective, policy and practice reviews, review, study protocol, systematic review, technology and code) on topics around Prognostic Factors and Risk Assessment of PTC. Aim of the present collection is to identify novel prognostic factors (clinical/molecular) and/or innovative prognostic approaches in order to improve PTC management.
Papillary thyroid cancer (PTC) is by far the most common thyroid malignancy, reaching a prevalence of about 80%. Furthermore, it represents the unique responsible for the increasing thyroid cancer incidence. Upon thyroid ablation (thyroidectomy with or without iodine-131 administration), PTC has an excellent prognosis with nearly 100% 5-year disease-specific survival.
However, about 25-30% of patients experience disease morbidity, as related to persistent structural disease/recurrence upon initial standard treatment, and 10% die over time, as related to cancer. Furthermore, the latest data from the US Surveillance, Epidemiology, and End Results found that disease-related mortality is slightly increasing over time.
Owing to these issues, to identify the PTC subgroup with the worst outcome represents the prognostic goal. To date, prognostic stratification relies on death-predicting (such as the AJCC/TNM and the MACIS) and persistence/recurrence predicting (such as that provided by the
American Thyroid Association (ATA)) systems, with the latter being the most useful in clinical practice. However, for all such approaches, the long-term risk stratification is suboptimal, due to the low proportion of variance explained (a statistical measure analyzing the capability of a staging system to predict the outcome of interest) and, more importantly, to the low positive predictive value.
To date, despite the deep knowledge of thyroid cancer genetics, any PTC-related molecular alteration has revealed enough specificity to be used in isolation for prognostic purpose. Therefore, current prognostication of DTC relies on a non-standardized multivariable approach, as derived by the combination of clinico-pathological and genetic features.
This Research Topic welcomes contributions of any type (clinical trial, correction, editorial, general commentary, hypothesis & theory, methods, mini review, opinion, original research, perspective, policy and practice reviews, review, study protocol, systematic review, technology and code) on topics around Prognostic Factors and Risk Assessment of PTC. Aim of the present collection is to identify novel prognostic factors (clinical/molecular) and/or innovative prognostic approaches in order to improve PTC management.
