Development of a New Clinical Severity Staging System for Patients With Nonmetastatic Papillary Thyroid Carcinoma

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Abstract

Importance

The inclusion of patient features in addition to tumor morphology provides a more holistic staging system.

Objective

To identify prognostically important variables in papillary thyroid carcinoma (PTC) to incorporate into a comprehensive functional severity staging system (FSSS) and clinical severity staging system (CSSS) and to validate the model using a multi-institutional database.

Design, Setting, and Participants

Retrospective cohort study of adults 18 years or older newly diagnosed or treated for nonmetastatic PTC at the Siteman Cancer Center from 1995 through 2012. Binary logistic regression was used to explore the association between 5-year survival and age, comorbidities, and tumor morphologic features. Conjunctive consolidation was used to create staging systems that incorporated important patient and tumor information. The created FSSS and CSSS were compared with the current AJCC staging system and externally validated using the National Cancer Database (NCDB).

Main Outcomes and Measures

Five-year survival.

Results

The cohort consisted of 774 eligible patients with PTC. There were 119 (15%) deaths in the cohort and a 90% 5-year survival rate. The median age of the patients was 51 years (range, 18-91); 562 (73%) were women. Conjunctive consolidation combined age, comorbidity, and T stage to create a new CSSS with 3 categories where 5-year survival rates (95% CI) were as follows: stage A (n = 612), 95% (94%-97%); stage B (n = 131), 74% (67%-82%); and stage C (n = 31), 58% (41%-75%). The performance of the FSSS and CSSS was validated using the NCDB data. The new staging system indicates that patients with nonmetastatic disease, patients younger than 40 years, or patients without comorbidity regardless of age have a very high 5-year survival rate.

Conclusions and Relevance

The FSSS and CSSS had better predictive results than the current AJCC staging system. The addition of patient features to tumor morphology provides a more comprehensive staging system that improves prognostic accuracy. These comprehensive staging systems can improve scientific reporting of disease outcomes, support comparative effectiveness studies, and guide clinical care by defining prognosis for newly diagnosed patients.

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