lung cancer

Data from: Developing and validating a survival prediction model for NSCLC patients through distributed learning across three countries

Jochems A, Deist TM, Naqa IEl, et al. Data from: Developing and validating a survival prediction model for NSCLC patients through distributed learning across three countries. 2017. doi:10.17195/candat.2017.02.2.

Developing and validating a survival prediction model for NSCLC patients through distributed learning across three countries

Arthur Jochems, Timo M. Deist, Issam El Naqa, Marc Kessler, Chuck Mayo, Jackson Reeves, Shruti Jolly, Martha Matuszak, Randall Ten Haken, Johan van Soest, Cary Oberije, Corinne Faivre-Finn, Gareth Price, Dirk de Ruysscher, Philippe Lambin, Andre Dekker

 

Purpose

Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with (chemo)radiotherapy are of limited quality. In this work, we develop a predictive model of survival at two years based on a large volume of historical patient data, as a proof of concept, using a distributed learning approach.

Patients and methods