Incorporating a Patient Dichotomous Characteristic in Cancer Phase I Clinical Trials Using Escalation with Overdose Control
We describe a design for cancer phase I clinical trials that takes into account patients heterogeneity thought to be related to treatment susceptibility. The goal is to estimate the maximum tolerated dose (MTD) given patient’s specific dichotomous covariate value. The design is Bayesian adaptive and...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Journal of Probability and Statistics |
| Online Access: | http://dx.doi.org/10.1155/2012/567819 |
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| author | Mourad Tighiouart Galen Cook-Wiens André Rogatko |
| author_facet | Mourad Tighiouart Galen Cook-Wiens André Rogatko |
| author_sort | Mourad Tighiouart |
| collection | DOAJ |
| description | We describe a design for cancer phase I clinical trials that takes into account patients heterogeneity thought to be related to treatment susceptibility. The goal is to estimate the maximum tolerated dose (MTD) given patient’s specific dichotomous covariate value. The design is Bayesian adaptive and is an extension of escalation with overdose control (EWOC). We will assess the performance of this method by comparing the following designs via extensive simulations: (1) design using a covariate; patients are accrued to the trial sequentially and the dose given to a patient depends on his/her baseline covariate value, (2) design ignoring the covariate; patients are accrued to the trial sequentially and the dose given to a patient does not depend on his/her baseline covariate value, and (3) design using separate trials; in each group, patients are accrued to the trial sequentially and EWOC is implemented in each group. These designs are compared with respect to safety of the trial and efficiency of the estimates of the MTDs via extensive simulations. We found that ignoring a significant baseline binary covariate in the model results in a substantial number of patients being overdosed. On the other hand, accounting for a nonsignificant covariate in the model has practically no effect on the safety of the trial and efficiency of the estimates of the MTDs. |
| format | Article |
| id | doaj-art-e2e20428e56d489c9d7974bec74febd0 |
| institution | OA Journals |
| issn | 1687-952X 1687-9538 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Probability and Statistics |
| spelling | doaj-art-e2e20428e56d489c9d7974bec74febd02025-08-20T02:21:14ZengWileyJournal of Probability and Statistics1687-952X1687-95382012-01-01201210.1155/2012/567819567819Incorporating a Patient Dichotomous Characteristic in Cancer Phase I Clinical Trials Using Escalation with Overdose ControlMourad Tighiouart0Galen Cook-Wiens1André Rogatko2Biostatistics and Bioinformatics Research Center, Samuel Oschin Comprehensive Cancer Institute, 8700 Beverly Boulevard, PACT, Suite 900C, Los Angeles, CA 90048, USABiostatistics and Bioinformatics Research Center, Samuel Oschin Comprehensive Cancer Institute, 8700 Beverly Boulevard, PACT, Suite 900C, Los Angeles, CA 90048, USABiostatistics and Bioinformatics Research Center, Samuel Oschin Comprehensive Cancer Institute, 8700 Beverly Boulevard, PACT, Suite 900C, Los Angeles, CA 90048, USAWe describe a design for cancer phase I clinical trials that takes into account patients heterogeneity thought to be related to treatment susceptibility. The goal is to estimate the maximum tolerated dose (MTD) given patient’s specific dichotomous covariate value. The design is Bayesian adaptive and is an extension of escalation with overdose control (EWOC). We will assess the performance of this method by comparing the following designs via extensive simulations: (1) design using a covariate; patients are accrued to the trial sequentially and the dose given to a patient depends on his/her baseline covariate value, (2) design ignoring the covariate; patients are accrued to the trial sequentially and the dose given to a patient does not depend on his/her baseline covariate value, and (3) design using separate trials; in each group, patients are accrued to the trial sequentially and EWOC is implemented in each group. These designs are compared with respect to safety of the trial and efficiency of the estimates of the MTDs via extensive simulations. We found that ignoring a significant baseline binary covariate in the model results in a substantial number of patients being overdosed. On the other hand, accounting for a nonsignificant covariate in the model has practically no effect on the safety of the trial and efficiency of the estimates of the MTDs.http://dx.doi.org/10.1155/2012/567819 |
| spellingShingle | Mourad Tighiouart Galen Cook-Wiens André Rogatko Incorporating a Patient Dichotomous Characteristic in Cancer Phase I Clinical Trials Using Escalation with Overdose Control Journal of Probability and Statistics |
| title | Incorporating a Patient Dichotomous Characteristic in Cancer Phase I Clinical Trials Using Escalation with Overdose Control |
| title_full | Incorporating a Patient Dichotomous Characteristic in Cancer Phase I Clinical Trials Using Escalation with Overdose Control |
| title_fullStr | Incorporating a Patient Dichotomous Characteristic in Cancer Phase I Clinical Trials Using Escalation with Overdose Control |
| title_full_unstemmed | Incorporating a Patient Dichotomous Characteristic in Cancer Phase I Clinical Trials Using Escalation with Overdose Control |
| title_short | Incorporating a Patient Dichotomous Characteristic in Cancer Phase I Clinical Trials Using Escalation with Overdose Control |
| title_sort | incorporating a patient dichotomous characteristic in cancer phase i clinical trials using escalation with overdose control |
| url | http://dx.doi.org/10.1155/2012/567819 |
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