Prediction of Treatment Response for Combined Chemo- and Radiation Therapy for Non-Small Cell Lung Cancer Patients Using a Bio-Mathematical Model

• Published in: Scientific reports Vol. 7; no. 1; pp. 13542 - 12
• Main Authors: Geng, Changran, Paganetti, Harald, Grassberger, Clemens
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 19.10.2017; Nature Publishing Group
• Subjects: 631/57/2266; 631/67/1059; 631/67/1612/1350; Chemotherapy; Growth rate; Humanities and Social Sciences; Lung cancer; Mathematical models; multidisciplinary; Non-small cell lung carcinoma; Patients; Radiation therapy; Repopulation; Science; Science (multidisciplinary); Tumors
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-017-13646-z

The goal of this work was to develop a mathematical model to predict Kaplan–Meier survival curves for chemotherapy combined with radiation in Non-Small Cell Lung Cancer patients for use in clinical trial design. The Gompertz model was used to describe tumor growth, radiation effect was simulated by the linear-quadratic model with an α / β -ratio of 10, and chemotherapy effect was based on the log-cell kill model. To account for repopulation during treatment, we considered two independent methods: 1) kickoff-repopulation using exponential growth with a decreased volume doubling time, or 2) Gompertz-repopulation using the gradually accelerating growth rate with tumor shrinkage. The input parameters were independently estimated by fitting to the SEER database for untreated tumors, RTOG-8808 for radiation only, and RTOG-9410 for sequential chemo-radiation. Applying the model, the benefit from concurrent chemo-radiation comparing to sequential for stage III patients was predicted to be a 6.6% and 6.2% improvement in overall survival for 3 and 5-years respectively, comparing well to the 5.3% and 4.5% observed in RTOG-9410. In summary, a mathematical model was developed to model tumor growth over extended periods of time, and can be used for the optimization of combined chemo-radiation scheduling and sequencing.