<b>P</b><b>ost-operative</b><b> </b><b>neutrophil count</b><b> </b><b>and platelet count predict recurrent differentiated thyroid carcinoma</b>

Background Peripheral blood laboratory indicators are used as signs of tumor recurrence. However, few studies have used them to predict the recurrence of differentiated thyroid carcinoma (DTC). Our study aimed to combine pre- and postoperative peripheral blood laboratory indicators with clinicopathological characteristics to predict DTC recurrence. Methods Between June 2013 and December 2020, 488 patients with DTC were admitted to the Second Affiliated Hospital of Guangxi University of Science and Technology. Kaplan–Meier survival analysis and Cox regression analysis were used to assess DTC prognosis based on pre- and postoperative inflammatory marker levels and clinicopathological features. A predictive nomogram was developed and validated. The performance of the prediction model was evaluated using the C-index, area under the curve (AUC), and calibration curves. Results A total of 488 patients with DTC were included, and thirty-six (7.38%) patients developed recurrence during a mean follow-up time of 28.85 months (range: 17.92–41.26). lymph node metastases (LNMs), tumor diameter ≥2 cm, post-operative neutrophil count (post-NEU), and post-operative platelets count (post-PLT) were independent recurrence risk factors for patients with DTC (all <i>P</i>&lt;0.05). The median AUC for the forecast of 2- and 3-year DTC recurrence using the four factors were 0.86 (range: 0.75–0.97) and 0.84 (0.72–0.95). Recurrence-free survival (RFS) in all patients with DTC was estimated using Kaplan–Meier survival curves (low- vs. high-risk group, <i>P</i>&lt;0.001). Conclusion LNMs, tumor diameter ≥2 cm, post-NEU, and post-PLT are risk factors for DTC recurrence. Building a nomogram model combining these four features significantly enhanced the predictive capability for DTC recurrence. This study suggests that postoperative peripheral blood laboratory indicators may serve as novel biomarkers for identifying early DTC recurrence.