The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
권호 표지
DOI QR코드

DOI QR Code

Adaptive continual reassessment method: A maximum tolerated dose estimation method in phase I clinical trial

MTD 추정법: 적응형 연속 재평가 방법

  • EunKyung Park (Department of Biomedicine & Health Sciences, The Catholic University Graduate School) ;
  • Eun Jeong Min (Department of Biomedicine & Health Sciences, The Catholic University Graduate School)
  • 박은경 (가톨릭대학교 의생명.건강과학과) ;
  • 민은정 (가톨릭대학교 의생명.건강과학과)
  • Received : 2024.02.06
  • Accepted : 2024.04.02
  • Published : 2024.08.31
Download PDF
⟨ Previous Next ⟩

Abstract

The objective of Phase I clinical trials is to ascertain the maximum tolerated dose (MTD) that is safe for human administration. Accurately determining the MTD within an acceptable safety margin is imperative, necessitating evaluations up to sufficiently high doses. To estimate the MTD, a plethora of methods have been developed, encompassing algorithm-based, model-based, and model-assisted techniques. In this paper, a new dose exploration method based on continual reassessment method (CRM) is proposed to address for the shortcomings of existing dose exploration methods. Through a comprehensive simulation study, this method's efficacy was compared against that of existing methodologies across a variety of scenarios. The findings from this study underscore its enhanced precision and safety in estimating the MTD, alongside a reduction in the number of subjects required for testing.

제 1상 임상시험의 목적은 사람이 견딜 수 있는 최대 허용 용량(maximum tolerated dose; MTD)을 결정하여 안전성이 허용되는 범위하에 충분히 높은 용량까지 올바르게 평가하는 것이 중요하다. MTD를 추정하는 방법은 알고리즘 기반, 모델 기반 및 모델 보조방법을 포함한 여러 가지 방법이 고안되었다. 본 논문에서는 기존 용량 탐색 방법의 단점을 보완하기 위해 연속 재평가 방법(continual reassessment method; CRM)에 기반한 새로운 용량 탐색 방법을 제안하여 다양한 문제 상황에서 기존 용량 탐색 방법들과의 성능을 비교하기 위해 시뮬레이션 연구를 수행하였다. 연구의 결과 MTD 추정에서의 정확도와 안전성을 높일 수 있고, 적은 시험대상자를 사용한다는 점에서 가장 우월한 성능을 보임을 확인하였다.

Keywords

References

  1. Ahn C (1998). An evaluation of phase I cancer clinical trial designs, Statistics in Medicine, 17, 1537-1549.
  2. Dixon WJ and Mood AM (1948). A method for obtaining and analyzing sensitivity data, Journal of the American Statistical Association, 43, 109-126.
  3. Faries D (1994). Practical modifications of the continual reassessment method for phase i cancer clinical trials, Journal of Biopharmaceutical Statistics, 4, 147-164.
  4. Garrett-Mayer E (2006). The continual reassessment method for dose-finding studies: A tutorial, Clinical Trials, 3, 57-71.
  5. Goodman SN, Zahurak ML, and Piantadosi S (1995). Some practical improvements in the continual reassessment method for phase I studies, Statistics in Medicine, 14, 1149-1161.
  6. Guo W, Wang SJ, Yang S, Lynn H, and Ji Y (2017). A Bayesian interval dose-finding design addressingOckham's razor: mTPI-2, Contemporary Clinical Trials, 58, 23-33.
  7. He W, Liu J, Binkowitz B, and Quan H (2006). A model-based approach in the estimation of the maximum tolerated dose in phase I cancer clinical trials, Statistics in Medicine, 25, 2027-2042.
  8. Heyd JM and Carlin BP (1999). Adaptive design improvements in the continual reassessment method for phase I studies, Statistics in Medicine, 18, 1307-1321.
  9. Jang E and Kim D (2014). Maximum tolerated dose estimation with dose de-escalation design in a phase I clinical trials, The Korean Journal of Applied Statistics, 27, 1115-1123.
  10. Ji Y, Liu P, Li Y, and Nebiyou Bekele B (2010). A modified toxicity probability interval method for dose-finding trials, Clinical Trials, 7, 653-663.
  11. Ji Y and Wang SJ (2013). Modified toxicity probability interval design: A safer and more reliable method than the 3 + 3 design for practical phase I trials, Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology, 31, 1785.
  12. Kang SH (2002). Investigation on the modified continual reassessment method in phase I clinical trial, The Korean of Applied Statistics, 15, 323-336.
  13. Kwon D and Kim D (2019). Maximum tolerated dose estimation using continual reassessment method in phase I clinical trial, The Korean Journal of Applied Statistics, 32, 741-752.
  14. Lee NM and Kim DJ (2012). Two-stage maximum tolerated dose estimation by stopping rule in a phase I clinical trial, The Korean Journal of Applied Statistics, 19, 57-64.
  15. Lee JH and Song HH (2011). Continual reassessment method in phase I clinical trials for Leukemia patients, The Korean Journal of Applied Statistics, 18, 581-594.
  16. Leung E, Crass RL, Jorgensen SC, Raybardhan S, Langford BJ, Moore WJ, and Rhodes NJ (2022). Pharmacokinetic/pharmacodynamic considerations of alternate dosing strategies of tocilizumab in COVID-19, Clinical Pharmacokinetics, 61, 155-165.
  17. Liu S and Yuan Y (2015). Bayesian optimal interval designs for phase I clinical trials, Journal of the Royal Statistical Society: Series C: Applied Statistics, 64, 507-523.
  18. O'Quigley J, Pepe M, and Fisher L (1990). Continual reassessment method: A practical design for phase 1 clinical trials in cancer, Biometrics, 46, 33-48.
  19. O'Quigley J and Shen LZ (1996). Continual reassessment method: A likelihood approach, Biometrics, 52, 673-684.
  20. O'Quigley J and Zohar S (2006). Experimental designs for phase I and phase I/II dose-finding studies, British Journal of Cancer, 94, 609-613.
  21. Park SJ, Kim Y, and Choi S (2021). A comparative study on the accuracy and safety of Bayesian CRM-Based MTD estimation method, The Korean Data and Information Science Society, 32, 337-350.
  22. Storer BE (1989). Design and analysis of phase I clinical trials, Biometrics, 45, 925-937.
  23. Tank A, Peterson HM, Pera V, Tabassum S, Leproux A, O'Sullivan T, and Roblyer D (2020). Diffuse optical spectroscopic imaging reveals distinct early breast tumor hemodynamic responses to metronomic and maximum tolerated dose regimens, Breast Cancer Research, 22, 1-10.
  24. Tleyjeh IM, Kashour Z, Damlaj M, Riaz M, Tlayjeh H, Altannir M, and Kashour T (2021). Efficacy and safety of tocilizumab in COVID-19 patients: A living systematic review and meta-analysis, Clinical Microbiology and Infection, 27, 215-227.
  25. Yan F, Mandrekar SJ, and Yuan Y (2017). Keyboard: A novel Bayesian toxicity probability interval design for phase I clinical trials, Clinical Cancer Research, 23, 3994-4003.
  26. Yuan Y, Hess KR, Hilsenbeck SG, and Gilbert MR (2016). Bayesian optimal interval design: A simple and well-performing design for phase I oncology trials, Clinical Cancer Research, 22, 4291-4301.
  27. Zhu Y, Hwang WT, and Li Y (2019). Evaluating the effects of design parameters on the performances of phase I trial designs, Contemporary Clinical Trials Communications, 15, 100379.