The analysis of different longitudinal biomarkers association with the overall survival in non-small cell lung cancer by means of joint modeling
Poster (download)
[pdf-embedder url=”https://bgrssb.icgbio.ru/wp-content/uploads/2020/07/350.pdf”]
Alina Sofronova1, Sergey Gavrilov2, Oleg Stepanov3, Kirill Peskov4, Kirill Zhudenkov5
1M&S decisions LLC, Moscow, Russia, alina.sofronova@msdecisions.ru
2M&S decisions LLC, Moscow, Russia, sergey.gavrilov@msdecisions.ru
3M&S decisions LLC, Moscow, Russia, oleg.stepanov@msdecisions.ru
4M&S decisions LLC, Moscow, Russia; Computational Oncology Group, I.M. Sechenov First Moscow State Medical University, Moscow, Russia, kirill.peskov@msdecisions.ru
5M&S decisions LLC, Moscow, Russia, kirill.zhudenkov@msdecisions.ru
It is well-known that tumor size is predictive of overall survival for patients with non-small cell lung cancer (NSCLC). Joint modeling is an advanced approach to quantify the association between longitudinal biomarkers and overall survival. The obtained results suggest that assessment of biomarker dynamics improved the accuracy of survival prediction in comparison with consideration of only baseline biomarker values for investigated patients with NSCLC.