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A continuous-time multistate Markov model to describe the occurrence and severity of diarrhea events in metastatic breast cancer patients treated with lumretuzumab in combination with pertuzumab and paclitaxel

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Abstract

Purpose

To inform lumretuzumab and pertuzumab dose modifications in order to decrease the incidence, severity, and duration of the diarrhea events in metastatic breast cancer patients treated with a combination therapy of lumretuzumab (anti-HER3) in combination with pertuzumab (anti-HER2) and paclitaxel using quantitative clinical pharmacology modeling approaches.

Methods

The safety and pharmacokinetic (PK) data from three clinical trials (lumretuzumab monotherapy n = 47, pertuzumab monotherapy n = 78, and the combination therapy of lumretuzumab, pertuzumab and paclitaxel n = 35) were pooled together to develop a continuous-time discrete states Markov model describing the dynamics of the diarrhea events.

Results

The model was able to capture the time course of different severities of diarrhea reasonably well. The effect of lumretuzumab and pertuzumab was well described by an Emax function indicating an increased rate of transition from moderate to mild or more severe diarrhea with higher doses. The concentration needed to trigger or worsen diarrhea episodes was estimated to be 120-fold lower in combination therapy compared to monotherapy, suggesting strong synergy between the two monoclonal antibodies. The prophylactic effect of loperamide in a subset of patients was also well captured by the model with a clear tendency to reduce the occurrence of diarrhea events.

Conclusions

This work shows that PK-toxicity modeling provides insight into how the severity of key adverse events evolves over time and highlights the potential use to support decision making in drug development.

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Acknowledgements

The authors thank Dr Ahmed Suleiman (Abbvie Inc.) and Dr. Lena Friberg (Associate professor, Uppsala University) for their valuable inputs in the implementation of the compartmental continuous-time Markov model. We also thank Dr. Francesca Michielin of Roche for having provided the diarrhea dataset and made suggestions to the modeling efforts as well as Dr. Jonathan Wagg of Roche for his input in the overall work. We would like to thank the BP27771, BO16934, and BP28752 study teams for their assistance and support in the preparation of this manuscript. Finally, we would like to express our gratitude to the editor and two anonymous reviewers for their insightful and constructive comments, which made us greatly improve the presentation and content of the article.

Funding

The studies were funded by Hoffmann-La Roche Ltd.

Author information

Author notes

  1. Chao Xu

    Present address: Quantitative Pharmacology and Pharmacometrics, Merck & Co., Inc, Rahway, USA

Authors and Affiliations

  1. Clinical Pharmacology, Pharmaceutical Sciences, Roche Innovation Center New York, New York, USA

    Chao Xu, Patanjali Ravva & Jun Steve Dang

  2. Clinical Pharmacology, Pharmaceutical Sciences, Roche Innovation Center Basel, Basel, Switzerland

    Johann Laurent & François Mercier

  3. Pharma Drug Safety Licensing, Roche Innovation Center Basel, Basel, Switzerland

    Céline Adessi

  4. Clinical Pharmacology, Pharmaceutical Sciences, Roche Innovation Center Welwyn, Welwyn, UK

    Christine McIntyre & Georgina Meneses-Lorente

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  1. Chao Xu
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Corresponding author

Correspondence to François Mercier.

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Conflict of interest

All the authors are employees of F. Hoffmann-La Roche Ltd at the time of data collection and analysis.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

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Informed consent was obtained from all individual participants included in the studies.

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Xu, C., Ravva, P., Dang, J.S. et al. A continuous-time multistate Markov model to describe the occurrence and severity of diarrhea events in metastatic breast cancer patients treated with lumretuzumab in combination with pertuzumab and paclitaxel. Cancer Chemother Pharmacol 82, 395–406 (2018). https://doi.org/10.1007/s00280-018-3621-9

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