BACKGROUND: The purpose of this study was to analyze the relationship between cytologic features, clinical features, and recurrence of papillary thyroid cancer (PTC). We hoped to predict prognosis preoperatively. METHODS: We retrospectively studied cytologic features by using computerized morphometry and clinical data of 118 patients with usual-type PTC without initial metastasis, including 34 patients with cancer recurrence in 10 years after surgery and 84 patients who did not have recurrence for more than 10 years after surgery. Another 24 patients were recruited for validation. RESULTS: Multivariate logistic analysis indicated that nucleus-to-cell ratio, variation of nuclear area, tumor size, and patient age were significantly related to recurrence. Cox regression analysis showed that hazard ratios were 3.34, 1.53, 1.77, and 2.6, respectively. CONCLUSION: Cytologic features of PTC analyzed with computerized morphometry significantly correlated with recurrence. It helped to predict prognosis preoperatively and may be helpful for planning further treatment.
BACKGROUND: The purpose of this study was to analyze the relationship between cytologic features, clinical features, and recurrence of papillary thyroid cancer (PTC). We hoped to predict prognosis preoperatively. METHODS: We retrospectively studied cytologic features by using computerized morphometry and clinical data of 118 patients with usual-type PTC without initial metastasis, including 34 patients with cancer recurrence in 10 years after surgery and 84 patients who did not have recurrence for more than 10 years after surgery. Another 24 patients were recruited for validation. RESULTS: Multivariate logistic analysis indicated that nucleus-to-cell ratio, variation of nuclear area, tumor size, and patient age were significantly related to recurrence. Cox regression analysis showed that hazard ratios were 3.34, 1.53, 1.77, and 2.6, respectively. CONCLUSION: Cytologic features of PTC analyzed with computerized morphometry significantly correlated with recurrence. It helped to predict prognosis preoperatively and may be helpful for planning further treatment.
Authors: Flávia O Valentim; Bárbara P Coelho; Hélio A Miot; Caroline Y Hayashi; Danilo T A Jaune; Cristiano C Oliveira; Mariângela E A Marques; José Vicente Tagliarini; Emanuel C Castilho; Paula Soares; Gláucia M F S Mazeto Journal: Endocr Connect Date: 2018-07-04 Impact factor: 3.335