Objective: The value of adjuvant therapy in resected laryngeal cancer remains controversial. This large SEER‐based cohort study aimed to investigate the existing parameters of lymph node status that could predict survival outcomes and the prognostic value of adjuvant treatment in resected laryngeal carcinoma.Methods: Population‐based data from the US Surveillance, Epidemiology, and End Results (SEER‐18) Program on patients after laryngectomy and lymphadenectomy (2004‐2015) were analyzed. The optimal cut‐off values for examined lymph nodes number (ELNs) and metastatic lymph nodes ratio (MLNR) were determined using the X‐tile program. Associations of ELNs and MLNR with overall survival were investigated through Cox regression analysis. A survival‐predicting model was then constructed to stratified patients. The prognostic value of adjuvant therapy was evaluated in different subgroups.Results: A total of 2122 patients with resected laryngeal cancer were analyzed. A novel survival‐predicting model was proposed based on ELNs, MLNR, and other clinicopathological characteristics. Patients were stratified into three subgroups with the increasing risk of death. Only patients in the high‐risk group who receiving adjuvant treatment had a significantly better survival outcome than those receiving surgery alone.Conclusion: A new survival‐predicting model was established in this study, which was superior in assessing the survival outcomes of patients with resected laryngeal cancer. Notably, this model was also able to assist in the decision making of adjuvant therapy for patients and physicians.

Objective: To quantitatively predict the probability of lateral lymph node metastasis (LLNM) for papillary thyroid carcinomas (PTC) patients with central lymph node metastasis (CLNM) in order to guide postoperative adjuvant treatment. Methods: Five hundred and three PTC patients with CLNM from three medical centers were retrospectively analyzed. Results: The LLNM rate for all patients was 23.9% (120 in 503), with 15.5% (45 in 291) and 35.4% (75 in 212) for patients with papillary thyroid microcarcinoma (PTMC) and large papillary thyroid carcinoma (LPTC), respectively. Patients with no fewer than five positive central lymph nodes (CLN) exhibited a higher risk of LLNM. For patients with fewer than five positive CLN, a maximum diameter of positive CLN > 0.5 cm and the presence of ipsilateral nodular goiter were identified as independent risk factors of LLNM for papillary thyroid microcarcinoma (PTMC) patients. The independent risk factors of LLNM for large papillary thyroid carcinoma (LPTC) patients included a tumor located in the upper portion of thyroid, maximum tumor diameter ≥ 2.0 cm, maximum diameter of positive CLN > 0.5 cm, and the presence of thyroid capsular invasion. Predictive nomograms were established based on these risk factors for PTMC and LPTC patients, respectively. The accuracy and validity of our newly built models were verified by C-index and calibration curves. PTMC and LPTC patients with fewer than five positive CLN were each stratified into three subgroups based on their nomogram risk scores, and a detailed risk stratification flow chart was established for a more accurate evaluation of LLNM risk in PTC patients. Conclusions: A detailed stratification flow chart for PTC patients with CLNM to quantitatively assess LLNM risk was established, which may aid in clinical decision-making for those patients.

Background：The submental island flap (SIF) is valuable for head and neck reconstruction, but anatomical variations in submental vasculature pose surgical challenges. Systematic preoperative imaging may optimize planning and minimize vascular injury. Objective：To develop a standardized CT-based protocol for preoperative assessment of submental flap vasculature and characterize common anatomical patterns. Methods：Contrast-enhanced CT images from 109 patients (218 sides) were retrospectively analyzed between January and June 2024. A systematic protocol identified submental artery origin, traced its course relative to mylohyoid and digastric muscles, and determined facial vein drainage patterns using Fang's classification (Type I: internal jugular vein; Type II: external jugular vein; Type III: anterior jugular vein). Results：The submental artery origin was consistently identified within the "submental artery triangle" bounded by the mandible, mylohyoid muscle, and submandibular gland. The main trunk coursed deep to the digastric muscle in 31.1%, superficial in 33.0%, and penetrating through in 35.9%. Facial vein drainage patterns included Type I (56.3%), Type II (32.5%), and Type III (11.2%), with significant gender differences observed (p < 0.001). Conclusion： This standardized CT protocol enables reliable preoperative prediction of submental flap vascular anatomy, facilitating surgical planning and reducing risk of inadvertent vascular injury during flap harvest.