The Expected Toxicity Rate at the Maximum Tolerated Dose in the Standard Phase I Cancer Clinical Trial Design

被引:0
|
作者
Seung-Ho Kang
Chul Ahn
机构
[1] Ewha Womens University,Department of Statistics
[2] University of Texas Medical School,Clinical Epidemiology, UT
关键词
Dose finding studies; Cancer; Toxicity; Continual reassessment method;
D O I
暂无
中图分类号
学科分类号
摘要
A main purpose of Phase I cancer clinical trials is to identify the maximum tolerated dose (MTD) of a new agent for experimentation in Phase II and III studies. The continual reassessment method has been shown to be superior to the standard design. However, in practice, the standard design has still been widely used. Therefore, it is important to investigate the performance of the standard design accurately. In this paper, we develop an algorithm to compute the exact distribution of the recommended dose level in the standard design. The algorithm is a better tool than simulation in the investigation of the operating characteristics of the standard design, because it does not involve any sampling error and computing time is much shorter than simulation. With the algorithm, the expected toxicity rate at the MTD in the standard design is investigated extensively for some dose-toxicity curves in a certain range.
引用
收藏
页码:1189 / 1199
页数:10
相关论文
共 50 条
  • [31] Maximum tolerated dose - Results of Phase I trial of weekly paclitaxel and cisplatin with radiation therapy in carcinoma cervix
    Prasad, E.
    Viswanathan, P. N.
    Rangad, V. Faith
    Pavamani, S.
    Ram, T. S.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2008, 72 (01): : S361 - S361
  • [32] Maximum tolerated dose-Results of a phase I trial of paclitaxel and cisplatin with radiation therapy in carcinoma of the cervix
    Prasad, E.
    JOURNAL OF CLINICAL ONCOLOGY, 2008, 26 (15)
  • [33] Adaptive design for identifying maximum tolerated dose early to accelerate dose-finding trial
    Kojima, Masahiro
    BMC MEDICAL RESEARCH METHODOLOGY, 2022, 22 (01)
  • [34] Adaptive design for identifying maximum tolerated dose early to accelerate dose-finding trial
    Masahiro Kojima
    BMC Medical Research Methodology, 22
  • [35] Adaptive Estimation of Personalized Maximum Tolerated Dose in Cancer Phase I Clinical Trials Based on All Toxicities and Individual Genomic Profile
    Chen, Zhengjia
    Li, Zheng
    Zhuang, Run
    Yuan, Ying
    Kutner, Michael
    Owonikoko, Taofeek
    Curran, Walter J.
    Kowalski, Jeanne
    PLOS ONE, 2017, 12 (01):
  • [36] ESTIMATING THE PROBABILITY OF TOXICITY AT THE RECOMMENDED DOSE FOLLOWING A PHASE-I CLINICAL-TRIAL IN CANCER
    OQUIGLEY, J
    BIOMETRICS, 1992, 48 (03) : 853 - 862
  • [37] Adaptive Bayesian phase I clinical trial designs for estimating the maximum tolerated doses for two drugs while fully utilizing all toxicity information
    Zhang, Yuzi
    Kutner, Michael
    Chen, Zhengjia
    BIOMETRICAL JOURNAL, 2021, 63 (07) : 1476 - 1492
  • [38] Phase I Study of Rucaparib in Combination with Bevacizumab in Ovarian Cancer Patients: Maximum Tolerated Dose and Pharmacokinetic Profile
    Domenica Lorusso
    Giuseppa Maltese
    Ilaria Sabatucci
    Sara Cresta
    Cristina Matteo
    Tommaso Ceruti
    Maurizio D’Incalci
    Massimo Zucchetti
    Francesco Raspagliesi
    Cristina Sonetto
    Valentina Sinno
    Dominique Ronzulli
    Serena Giolitto
    Filippo de Braud
    Targeted Oncology, 2021, 16 : 59 - 68
  • [39] Maximum Tolerated Dose and Early Response - Results of a Phase I Trial of Paclitaxel and Cisplatin with Radiation Therapy in Carcinoma of the Cervix
    Prasad, E.
    Viswanathan, P. N.
    Rangad, V. F.
    Pavamani, S.
    Ram, T. S.
    CLINICAL ONCOLOGY, 2009, 21 (06) : 488 - 493
  • [40] Phase I Study of Rucaparib in Combination with Bevacizumab in Ovarian Cancer Patients: Maximum Tolerated Dose and Pharmacokinetic Profile
    Lorusso, Domenica
    Maltese, Giuseppa
    Sabatucci, Ilaria
    Cresta, Sara
    Matteo, Cristina
    Ceruti, Tommaso
    D'Incalci, Maurizio
    Zucchetti, Massimo
    Raspagliesi, Francesco
    Sonetto, Cristina
    Sinno, Valentina
    Ronzulli, Dominique
    Giolitto, Serena
    de Braud, Filippo
    TARGETED ONCOLOGY, 2021, 16 (01) : 59 - 68