PROSTATE CANCER

An adaptive approach to therapy

Analysis of a mathematical model of an evolution-based strategy for two-drug therapy has shown it could improve outcomes in men with metastatic castration-resistant prostate cancer (mCRPC).

In this study, the authors developed an evolution-based approach in which therapies are divided into primary and secondary roles, termed primary–secondary therapy. In this approach, the drug that has the highest efficacy and/or the lowest toxic effects is the primary therapy. The only role of the secondary drug is to reduce the population of cells resistant to the primary drug. Specifically, the investigators considered the context of a clinical trial of treatment of mCRPC in which the administration of abiraterone was dependent on patient response and informed by an evolution-based mathematical model. The addition of docetaxel was investigated to reduce proliferation of androgen-independent, abiraterone-resistant cells. Thus, the primary–secondary strategy in this context comprised abiraterone as the primary drug and docetaxel as the secondary therapy. Using this context, the authors quantitatively investigated the hypothesized evolutionary dynamics of this strategy using mathematical modelling.

Simulations derived from a virtual patient using the mathematical model showed that time to progression was increased in circumstances in which the primary–secondary therapy approach was used compared with administration of treatment with no regard for evolutionary dynamics. The investigators then retrospectively applied the mathematical model to an ongoing adaptive therapy trial of abiraterone treatment for mCRPC using an evolution-based approach. Data from two patients included in this trial who had experienced progression were used as the model parameters. Simulations derived using these data suggested that administration of docetaxel according to the primary–secondary strategy would result in a considerably increased time to progression.

These results show that using mathematical models could improve patient outcomes in clinical trials of multidrug therapy by integration of evolutionary dynamics.

References

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  1. West, J. B. et al. Multidrug cancer therapy in metastatic castrate-resistant prostate cancer: an evolution-based strategy. Clin. Cancer Res. https://doi.org/10.1158/1078-0432.CCR-19-0006 (2019)

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Correspondence to Louise Stone.

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Stone, L. An adaptive approach to therapy. Nat Rev Urol 16, 388 (2019). https://doi.org/10.1038/s41585-019-0197-z

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