Related Experiment Video
Updated: Jan 3, 2026

A Model for Perineural Invasion in Head and Neck Squamous Cell Carcinoma
Published on: January 5, 2017
Prognostic Implication of Histopathologic Indicators in Salivary Duct Carcinoma: Proposal of a Novel Histologic Risk
Masato Nakaguro1, Yukiko Sato2, Yuichiro Tada3
1Department of Pathology and Laboratory Medicine, Nagoya University Hospital.
Abstract:
Salivary duct carcinoma (SDC) is a rare, aggressive malignancy that histologically resembles high-grade mammary duct carcinoma. Because of the rarity of this entity, data verifying the association between histologic features and patient survival are limited. We conducted a comprehensive histologic review of 151 SDC cases and performed an analysis of the association between various histomorphologic parameters and the clinical outcome with the aim of developing a histologic risk stratification model that predicts the prognosis of SDC patients. A multivariate analysis revealed that prominent nuclear pleomorphism (overall survival [OS]: P=0.013; progression-free survival [PFS]: P=0.019), ≥30 mitoses/10 HPF (PFS: P=0.013), high tumor budding (OS: P=0.011; PFS: P<0.001), and high poorly differentiated clusters (OS: P<0.001; PFS: P<0.001) were independent prognostic factors. Patients with vascular invasion demonstrated a marginally significant association with shorter PFS (P=0.064) in a multivariate analysis. We proposed a 3-tier histologic risk stratification model based on the total number of positive factors among 4 prognostically relevant parameters (prominent nuclear pleomorphism, ≥30 mitoses/10 HPF, vascular invasion, and high poorly differentiated clusters). The OS and PFS of patients with low-risk (0 to 1 point) (23% of cases), intermediate-risk (2 to 3 points) (54% of cases), and high-risk (4 points) (23% of cases) tumors progressively deteriorated in this order (hazard ratio, 2.13 and 2.28, and 4.99 and 4.50, respectively; Ptrend<0.001). Our histologic risk stratification model could effectively predict patient survival and may be a useful aid to guide clinical decision-making in relation to the management of patients with SDC.
More Related Videos
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
03:05Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors
Published on: February 16, 2024