J Cancer 2018; 9(21):3986-3990. doi:10.7150/jca.27579
A nomogram to predict long-time survival for patients with M1 diseases of esophageal cancer
Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University. 241 West Huaihai Road, Shanghai, 200030, China.
Objective: To evaluate the clinicopathologic characteristics of the long-time survivals and construct a clinical nomogram using the Surveilance, Epidemiology, and End Results (SEER) database.
Materials and Methods: Information of patients diagnosed with M1 stage esophageal cancer from 2010-2014 was retrieved from SEER database. Patients with unknown information of AJCC TNM stage or metastatic sites or marital status or surgery or survival were excluded. Demographic and clinicopathologic characteristics were compared between LTS (long time survivals: patients who have survived for no less than 2 years) and STS (shorter time survivals: patients who have survived for less than 2 years). Cox regression analysis was performed to evaluate prognostic factors. A nomogram comprising demographic and clinicopathologic factors was established to predict 1-year survival and 2-year survival for patients with M1 diseases.
Results: A total of 2981 patients from the SEER database were included for analysis. Compared with the STS, married people and patients with well differentiated tumors or oligometastatic site were more likely to be LTS. Also, LTS were associated with significantly less bone metastasis and more surgery. The OS nomogram, which had a c-index of 0.633, was based on the eleven variables: gender, age, marital status, T stage, N stage, histology, grade, number of important metastatic organs and primary surgery.
Conclusions: Married patients, patients with well differentiated tumors, patients with oligometastatic site, patients without bone metastasis or liver metastasis and those who underwent surgery are associated with long time survivals. We developed a nomogram predicting 1- and 2-year OS and CSS for M1 stage esophageal cancer. The prognostic model may improve clinicians' abilities to predict individualized survival and to make treatment recommendations.
Keywords: esophageal cancer, nomogram, long time survivals
Liu M, Wang C, Gao L, Lv C, Cai X. A nomogram to predict long-time survival for patients with M1 diseases of esophageal cancer. J Cancer 2018; 9(21):3986-3990. doi:10.7150/jca.27579. Available from http://www.jcancer.org/v09p3986.htm