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A Lung Cancer Growth and Multi-Modality Treatment Model Based On Clinical Trial Data to Predict In-Vivo Repopulation and Radiation Sensitivity Parameters

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C Geng

C Geng1*,H Paganetti1, C Grassberger1 (1) Massachusetts General Hospital and Harvard Medical School, Boston, MA


WE-G-FS1-1 (Wednesday, August 2, 2017) 4:30 PM - 6:00 PM Room: Four Seasons 1

Purpose: To develop a mathematical model that simulates growth of untreated lung tumors as well as response to radiation or chemotherapy and subsequently can predict the Kaplan–Meier survival curves for chemotherapy combined with radiation in Non-Small Cell Lung Cancer patients.

Methods: 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. To account for repopulation during treatment, we considered two independent methods: 1) kickoff-repopulation using exponential growth with a volume doubling time (VDT) of 3 days after day 28, or 2) Gompertz-repopulation using the gradually accelerating growth rate with tumor shrinkage. Parameters were independently estimated by fitting to the following clinical data: SEER database for untreated tumors, RTOG-8808 for radiation only, RTOG-9410 for chemo-radiation.

Results: Only fitting to SEER data for untreated patients, the median tumor diameter and VDT for stage I/II/III/IV were predicted to be 1.2/3.5/6.9/9.7 cm and 59/89/198/311 days. Based on in-vitro findings, we introduced a correlation between radio-sensitivity and growth rate for the radiation effect, leading to a significantly better fit to the Kaplan–Meier from RTOG-8808. The fitted α for the radiation effect was 0.16 for Gompertz repopulation and 0.17 for kickoff-repopulation. The median alpha-parameter in the log-cell kill model for chemotherapy was 1.14/mg/m², consistent with clinical experiences. The benefit from concurrent chemo-radiation was predicted to be 6.2% and 4.9% OS improvement for 3 and 5-year OS for stage III patients, which compares well to the 5.3% and 4.5% observed in RTOG-9410.

Conclusion: In an effort to improve treatment strategies, a mathematical model was developed for the combined therapy of chemo and radiation. The parameter-less Gompertz-repopulation can naturally account for repopulation during radiation therapy. The model provides a tool for the optimization of combined chemo-radiation scheduling.

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