Jul 2026· The American surgeon· pp.
31348261472872
· 0 citations· 21 references
Medicine
TL;DR
This nomogram provides a population-level estimate of DSS in advanced FTC and may support preliminary risk stratification using readily available registry variables, but its clinical interpretation should consider the absence of key biologic and treatment-response factors not captured in SEER, including vascular invasion, molecular alterations, and systemic therapy data.
Abstract
BackgroundAdvanced follicular thyroid carcinoma (FTC) represents a clinically heterogeneous subgroup of differentiated thyroid cancer with variable long-term outcomes. We aimed to develop and internally validate a population-based nomogram for predicting 3-, 5-, and 10-year disease-specific survival (DSS) in patients with stage III-IV FTC using SEER registry data.Materials and MethodsThis retrospective cohort study utilized data from the SEER 17 registry (2010-2022). A total of 1027 patients with stage III-IV FTC were included and randomly assigned to training (n = 718) and validation (n = 309) cohorts. Clinical and demographic variables were analyzed. Univariable and multivariable Cox proportional hazards regression analyses were performed to identify independent prognostic factors. A nomogram was constructed based on the final multivariable model. Predictive performance was assessed using ROC and calibration analyses.ResultsThe mean age of the cohort was 63.5 years (±11.7), and 59.3% of patients were female. Multivariable analysis identified age, stage IV disease, N1 nodal status, unmarried status, and surgical treatment category as independent predictors of DSS. The nomogram demonstrated strong discriminative performance, with AUC values of 0.953, 0.966, and 0.903 for predicting 3-, 5-, and 10-year DSS, respectively. Calibration analyses showed acceptable agreement.ConclusionThis nomogram provides a population-level estimate of DSS in advanced FTC. While the model may support preliminary risk stratification using readily available registry variables, its clinical interpretation should consider the absence of key biologic and treatment-response factors not captured in SEER, including vascular invasion, molecular alterations, and systemic therapy data.
An innovative clinical prediction model specifically designed to assess the risk of recurrence in residual thyroid tissue is developed and validated and serves as a valuable tool for clinicians, facilitating personalized decision-making and representing a significant advancement in the postoperative management of papil...
Ruohan Shi, Lisen Zhu, Jia Liu et al.· Frontiers in Oncology· 0 citations
Two nomograms incorporating lipid and clinicopathological factors were developed and validated, which effectively predict OS and DFS in OCRC patients with good discrimination, calibration, and clinical utility, providing new tools for individualized risk prediction.
Hanwenchen Wang, Falong Zou, Denglong Cheng et al.· Frontiers in Medicine· 0 citations
This prognostic model provides accurate individualized survival prediction for ECC and facilitates objective risk stratification and facilitates objective risk stratification in palliative settings.
Guan-Jun Zhang, Ya-Qi Zhai, Ke Meng et al.· Journal of Gastrointestinal...· 0 citations
A prognostic nomogram developed and validated exclusively in a large cohort of non-metastatic Asian American BC patients from the SEER database, incorporating modern molecular subtypes to improve prognostic stratification for this understudied population is presented.
This novel nomogram provides better risk stratification for 3-, 5- and 8-year survival in GBC, with moderate discrimination, good calibration, and clinical utility, suggesting its potential usefulness in clinical decision‑making.
Hao Song, Zuo-Biao Li, Qin-Wen Tai et al.· Journal of Gastrointestinal...· 0 citations
A clinical predictive model was established to estimate 3-, 4-, and 5-year survival rates for LACSC patients and exhibited significantly poorer overall survival in both cohorts (P < 0.05).
Ting-Ting Zou, Xu-Peng Wang, Hai-Xia Wu et al.· Frontiers in Oncology· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.