Accuracy of papillary thyroid cancer prognostic nomograms: a systematic review

Abstract

Objective: To perform a systematic review to evaluate the predictive performance of available nomograms for thyroid cancer patients. Design and methods: PROSPERO registration: CRD42022327028. A systematic search was conducted without time and language restrictions. PICOT question: (Population): patients with papillary thyroid cancer; (Comparator Prognostic Factor): single-arm studies; (Outcomes): Overall survival, disease-free survival, cancer-specific survival, recurrence, central lymph node metastases, or lateral lymph node metastases; (Timing): all periods; (Setting): Hospital setting. Risk of Bias was assessed through PROBAST tool. Results: Eighteen studies with a total of 20 prognostic models were included in the systematic review (90,969 PTC patients). Fourteen models were at high risk of bias and four were at unclear risk of bias. The greatest concerns arose in the analysis domain. The accuracy of nomograms for overall survival was assessed in only one study and appeared limited (0.77, 95%CI: 0.75-0.79). The accuracy of nomograms for disease-free survival ranged from 0.65 (95% CI: 0.55-0.75) to 0.92 (95%CI: 0.91-0.95). The C-index for predicting lateral lymph node metastasis ranged from 0.72 to 0.92 (95%CI: 0.86-0.97). For central lymph node metastasis, the C-index of externally validated studies ranged from 0.706 (95%CI: 0.685-0.727) to 0.923 (95%CI: 0.893-0.946). Conclusions: Our work highlights the extremely high heterogeneity among nomograms and the critical lack of external validation studies that limit the applicability of nomograms in clinical practice. Further studies, ideally using commonly adopted risk factors as backbone to develop nomograms are required.

Using nomograms to predict the presence of papillary thyroid carcinoma

“…Nomograms are pictorial representations of a multifactorial mathematical model aimed at predicting a specific endpoint based on statistical methods ( 20 ). By including statistically significant factors, nomograms can provide an estimated probability of an event (such as cancer-related death), based on the combinations of various factors in the individual patient.…”

“…By including statistically significant factors, nomograms can provide an estimated probability of an event (such as cancer-related death), based on the combinations of various factors in the individual patient. In patients with PTC, numerous reports exist in literature on predicting survival and recurrence, but also regarding the presence of lymph node metastases ( 20 ). Next to this, also US-based nomograms for differentiating benign and malignant thyroid nodules have been created [e.g.…”