Nomogram for the Prediction of Biochemical Incomplete Response in Papillary Thyroid Cancer Patients.
Cancer Manag Res
; 13: 5641-5650, 2021.
Article
en En
| MEDLINE
| ID: mdl-34285584
ABSTRACT
PURPOSE:
To develop a nomogram for predicting biochemical incomplete response (BIR) in the dynamic risk stratification (DRS) of papillary thyroid carcinoma (PTC) patients without structural recurrence, and to investigate its validity. PATIENTS ANDMETHODS:
Overall, 1705 (1005 and 700 in the training and validation cohorts, respectively) PTC patients treated with total thyroidectomy without structural recurrence were included. multivariate logistic regression analyses were performed to determine the significant predictors of BIR in the training cohort. A nomogram was subsequently constructed for BIR risk prediction. Assessments for the predictive accuracy, discrimination, and calibration of the nomogram were performed. Subsequently, internal and external validations were conducted.RESULTS:
In the multivariate analysis, age, sex, lymph node metastasis site, extrathyroidal extension, and lymphovascular invasion showed significant predictive value; using these predictive factors and tumor size, a nomogram for BIR risk prediction was constructed. In the training cohort, the nomogram showed good predictive performance and discrimination in the receiver operating characteristic (ROC) curve analysis, with an area under the curve (AUC) of 0.765. In internal validation, the bootstrap-corrected AUC was 0.76. The calibration plot showed good agreement between the predicted and actual observation. The Hosmer-Lemeshow (HL) test did not suggest a lack of fit (p=0.1613). In the external validation, the AUC was 0.828 in the ROC curve analysis; the calibration plot showed good quality, and the HL test did not suggest a lack of fit (p=0.2161).CONCLUSION:
The constructed nomogram may effectively predict the risk of BIR in DRS in PTC patients without structural recurrence. LEVEL OF EVIDENCE Level 4.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Cancer Manag Res
Año:
2021
Tipo del documento:
Article