Quantitative Spatial Characterization of Lymph Node Tumor for N Stage Improvement of Nasopharyngeal Carcinoma Patients.
Jiang ZhangXinzhi TengSaikit LamJiachen SunAndy Lai-Yin CheungSherry Chor-Yi NgFrancis Kar-Ho LeeKwok-Hung AuCelia Wai-Yi YipVictor Ho Fun LeeZhongshi LinYongyi LiangRuijie YangYing HanYuanpeng ZhangSpring Feng-Ming KongJing CaiPublished in: Cancers (2022)
This study aims to investigate the feasibility of improving the prognosis stratification of the N staging system of Nasopharyngeal Carcinoma (NPC) from quantitative spatial characterizations of metastatic lymph node (LN) for NPC in a multi-institutional setting. A total of 194 and 284 NPC patients were included from two local hospitals as the discovery and validation cohort. Spatial relationships between LN and the surrounding organs were quantified by both distance and angle histograms, followed by principal component analysis. Independent prognostic factors were identified and combined with the N stage into a new prognostic index by univariate and multivariate Cox regressions on disease-free survival (DFS). The new three-class risk stratification based on the constructed prognostic index demonstrated superior cross-institutional performance in DFS. The hazard ratios of the high-risk to low-risk group were 9.07 (p < 0.001) and 4.02 (p < 0.001) on training and validation, respectively, compared with 5.19 (p < 0.001) and 1.82 (p = 0.171) of N3 to N1. Our spatial characterizations of lymph node tumor anatomy improved the existing N-stage in NPC prognosis. Our quantitative approach may facilitate the discovery of new anatomical characteristics to improve patient staging in other diseases.
Keyphrases
- lymph node
- prognostic factors
- end stage renal disease
- newly diagnosed
- ejection fraction
- neoadjuvant chemotherapy
- chronic kidney disease
- free survival
- sentinel lymph node
- small cell lung cancer
- squamous cell carcinoma
- small molecule
- peritoneal dialysis
- healthcare
- pet ct
- radiation therapy
- single cell
- virtual reality
- patient reported
- data analysis