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Yin A, van Hasselt JGC, Guchelaar HJ, Friberg LE, Moes DJAR. Anti-cancer treatment schedule optimization based on tumor dynamics modelling incorporating evolving resistance. Sci Rep 2022; 12:4206. [PMID: 35273301 PMCID: PMC8913638 DOI: 10.1038/s41598-022-08012-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 02/17/2022] [Indexed: 12/18/2022] Open
Abstract
Quantitative characterization of evolving tumor resistance under targeted treatment could help identify novel treatment schedules, which may improve the outcome of anti-cancer treatment. In this study, a mathematical model which considers various clonal populations and evolving treatment resistance was developed. With parameter values fitted to the data or informed by literature data, the model could capture previously reported tumor burden dynamics and mutant KRAS levels in circulating tumor DNA (ctDNA) of patients with metastatic colorectal cancer treated with panitumumab. Treatment schedules, including a continuous schedule, intermittent schedules incorporating treatment holidays, and adaptive schedules guided by ctDNA measurements were evaluated using simulations. Compared with the continuous regimen, the simulated intermittent regimen which consisted of 8-week treatment and 4-week suspension prolonged median progression-free survival (PFS) of the simulated population from 36 to 44 weeks. The median time period in which the tumor size stayed below the baseline level (TTS<TS0) was prolonged from 52 to 60 weeks. Extending the treatment holiday resulted in inferior outcomes. The simulated adaptive regimens showed to further prolong median PFS to 56–64 weeks and TTS<TS0 to 114–132 weeks under different treatment designs. A prospective clinical study is required to validate the results and to confirm the added value of the suggested schedules.
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Affiliation(s)
- Anyue Yin
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.,Leiden Network for Personalized Therapeutics, Leiden University Medical Center, Leiden, The Netherlands
| | - Johan G C van Hasselt
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research (LACDR), Leiden University, Leiden, The Netherlands
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.,Leiden Network for Personalized Therapeutics, Leiden University Medical Center, Leiden, The Netherlands
| | - Lena E Friberg
- Department of Pharmacy, Uppsala University, Uppsala, Sweden
| | - Dirk Jan A R Moes
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands. .,Leiden Network for Personalized Therapeutics, Leiden University Medical Center, Leiden, The Netherlands.
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