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Bayesian Optimization for Identification of Optimal Biological Dose Combinations in Personalized Dose-Finding Trials (2404.11323v1)

Published 17 Apr 2024 in stat.ME

Abstract: Early phase, personalized dose-finding trials for combination therapies seek to identify patient-specific optimal biological dose (OBD) combinations, which are defined as safe dose combinations which maximize therapeutic benefit for a specific covariate pattern. Given the small sample sizes which are typical of these trials, it is challenging for traditional parametric approaches to identify OBD combinations across multiple dosing agents and covariate patterns. To address these challenges, we propose a Bayesian optimization approach to dose-finding which formally incorporates toxicity information into both the initial data collection process and the sequential search strategy. Independent Gaussian processes are used to model the efficacy and toxicity surfaces, and an acquisition function is utilized to define the dose-finding strategy and an early stopping rule. This work is motivated by a personalized dose-finding trial which considers a dual-agent therapy for obstructive sleep apnea, where OBD combinations are tailored to obstructive sleep apnea severity. To compare the performance of the personalized approach to a standard approach where covariate information is ignored, a simulation study is performed. We conclude that personalized dose-finding is essential in the presence of heterogeneity.

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References (44)
  1. One Month Dosing of Atomoxetine Plus Oxybutynin in Obstructive Sleep Apnea: a Randomized, Placebo-Controlled Trial. Annals of the American Thoracic Society, 20(4):584–595.
  2. Cancer Phase I Clinical Trials: Efficient Dose Escalation with Overdose Control. Statistics in Medicine, 17(10):1103–1120.
  3. Patient Specific Dosing in a Cancer Phase I Clinical Trial. Statistics in Medicine, 20(14):2079–2090.
  4. Estimation of the Global Prevalence and Burden of Obstructive Sleep Apnoea: a Literature-Based Analysis. The Lancet Respiratory Medicine, 7(8):687–698.
  5. Bayesian Adaptive Methods for Clinical Trials. CRC Press, Boca Raton, FL.
  6. hetgp: Heteroskedastic Gaussian Process Modeling and Sequential Design in R. Journal of Statistical Software, 98(13):1–44.
  7. A Novel Toxicity Scoring System Treating Toxicity Response as a Quasi-Continuous Variable in Phase I Clinical Trials. Contemporary Clinical Trials, 31(5):473–482.
  8. The Impact of Dichotomization on the Efficiency of Testing for an Interaction Effect in Exponential Family Models. Journal of the American Statistical Association, 99(467):822–831.
  9. Bayesian Optimization with Inequality Constraints. In Proceedings of the 31st International Conference on Machine Learning. 32:937–945.
  10. Garnett, R. (2023). Bayesian Optimization. Cambridge University Press, Cambridge, UK.
  11. Bayesian Optimization with Unknown Constraints. arXiv preprint arXiv:1403.5607.
  12. Monotone Emulation of Computer Experiments. SIAM/ASA Journal on Uncertainty Quantification, 3(1):370–392.
  13. Gramacy, R. B. (2020). Surrogates: Gaussian Process Modeling, Design and Optimization for the Applied Sciences. Chapman Hall/CRC, Boca Raton, FL.
  14. Modeling an Augmented Lagrangian for Blackbox Constrained Optimization. Technometrics, 58(1):1–11.
  15. A Bayesian Phase I/II Biomarker-Based Design for Identifying Subgroup-Specific Optimal Dose for Immunotherapy. Statistical Methods in Medical Research, 31(6):1104–1119.
  16. Utility-Based Optimization of Combination Therapy Using Ordinal Toxicity and Efficacy in Phase I/II Trials. Biometrics, 66(2):532–540.
  17. Global Optimization of Stochastic Black-Box Systems via Sequential Kriging Meta-Models. Journal of Global Optimization, 34:441–466.
  18. Efficient Global Optimization of Expensive Black-Box Functions. Journal of Global Optimization, 13:455–492.
  19. Korn, E. L. (2004). Nontoxicity Endpoints in Phase I Trial Designs for Targeted, Non-Cytotoxic Agents. Journal of the National Cancer Institute, 96(13):977–978.
  20. Kushner, H. (1964). A New Method of Locating the Maximum Point of an Arbitrary Multipeak Curve in the Presence of Noise. Journal of Basic Engineering, 86(1):97–106.
  21. Adverse Event Burden Score — a Versatile Summary Measure for Cancer Clinical Trials. Cancers, 12(11):3251.
  22. Dose Escalation Methods in Phase I Cancer Clinical Trials. JNCI: Journal of the National Cancer Institute, 101(10):708–720.
  23. Toxicity Burden Score: a Novel Approach to Summarize Multiple Toxic Effects. Annals of Oncology, 23(2):537–541.
  24. Constrained Bayesian Optimization with Noisy Experiments. Bayesian Analysis, 14(2):495–519.
  25. Toxicity and Efficacy Probability Interval Design for Phase I Adoptive Cell Therapy Dose-Finding Clinical Trials. Clinical Cancer Research, 23(1):13–20.
  26. Bayesian Monotone Regression Using Gaussian Process Projection. Biometrika, 101(2):303–317.
  27. A Dose-Finding Design for Dual-Agent Trials with Patient-Specific Doses for One Agent with Application to an Opiate Detoxification Trial. Pharmaceutical Statistics, 21(2):476–495.
  28. A Flexible Design for Advanced Phase I/II Clinical Trials with Continuous Efficacy Endpoints. Biometrical Journal, 61(6):1477–1492.
  29. An Information Theoretic Phase I–II Design for Molecularly Targeted Agents that does not Require an Assumption of Monotonicity. Journal of the Royal Statistical Society, Series C, 68(2):347–367.
  30. Continual Reassessment Method: a Practical Design for Phase 1 Clinical Trials in Cancer. Biometrics, 46:33–48.
  31. R Core Team (2022). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.
  32. Combination of Atomoxetine with the Novel Antimuscarinic Aroxybutynin Improves Mild to Moderate OSA. Journal of Clinical Sleep Medicine, 18(12):2837–2844.
  33. Trends in CPAP Adherence Over Twenty Years of Data Collection: a Flattened Curve. Journal of Otolaryngology-Head & Neck Surgery, 45(1):43.
  34. Dichotomizing Continuous Predictors in Multiple Regression: a Bad Idea. Statistics in Medicine, 25(1):127–141.
  35. The Combination of Aroxybutynin and Atomoxetine in the Treatment of Obstructive Sleep Apnea (MARIPOSA): a Randomized Controlled Trial. American Journal of Respiratory and Critical Care Medicine, 208(12):1316–1327.
  36. Escalation Strategies for Combination Therapy Phase I Trials. Pharmaceutical Statistics, 11(3):258–266.
  37. Bayesian Optimization Design for Dose-Finding Based on Toxicity and Efficacy Outcomes in Phase I/II Clinical Trials. Pharmaceutical Statistics, 20(3):422–439.
  38. Bayesian Optimization for Estimating the Maximum Tolerated Dose in Phase I Clinical Trials. Contemporary Clinical Trials Communications, 21:100753.
  39. Dose-Finding Based on Efficacy-Toxicity Trade-Offs. Biometrics, 60(3):684–693.
  40. Meta-Analysis of Clinical Dose-Response in a Large Drug Development Portfolio. Statistics in Biopharmaceutical Research, 6(4):302–317.
  41. Reducing Sample Sizes in Two-Stage Phase II Cancer Trials by Using Continuous Tumour Shrinkage End-Points. European Journal of Cancer, 47(7):983–989.
  42. Bayesian Optimization for Personalized Dose-Finding Trials with Combination Therapies. arXiv preprint arXiv:2310.17334. Accessed 2024-02-08.
  43. Bayesian Designs for Phase I-II Clinical Trials. Chapman and Hall, Boca Raton, FL.
  44. Zhilinskas, A. (1975). Single-Step Bayesian Search Method for an Extremum of Functions of a Single Variable. Cybernetics and Systems Analysis, 11(1):160–166.

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