<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The best effective dose of a chemotherapy is defined using the maximum tolerated dose (MTD) of toxicity. It is possible that the toxicity of a dose may increase when the dose-response curve is not monotonic. In the case of metronomic chemotherapy (MC) a 1/10th level of MC dose is considered as a targeted dose of therapy and is safer in terms of toxicity levels. The objective of this study is to develop an algorithm based on the dose response model of MC to evaluate the best effective dose based on the molecular target agent. The molecular target agent is defined as the optimal biological dose achieved by the best effective dose, as the lowest dose with the highest rate of safety and efficacy. The first proposed design is parametric and assumes a logistic dose-efficacy curve for dose determination, and the second design uses quadratic regression to identify the optimal biological dose. We conducted extensive simulation studies to investigate the operating characteristics of the proposed designs. Simulation studies provide a possible way to decide on the best effective dose of MC to be considered in further phases through the finding of the optimal biological dose. The proposed design is assumed, with the threshold value of optimum biological dose (OBD), to detect the best dose of MC. This consistent design with specific dose response models can be recommended for practice.</p></abstract>

The best effective dose of a chemotherapy is defined using the maximum tolerated dose (MTD) of toxicity. It is possible that the toxicity of a dose may increase when the dose-response curve is not monotonic. In the case of metronomic chemotherapy (MC) a 1/10th level of MC dose is considered as a targeted dose of therapy and is safer in terms of toxicity levels. The objective of this study is to develop an algorithm based on the dose response model of MC to evaluate the best effective dose based on the molecular target agent. The molecular target agent is defined as the optimal biological dose achieved by the best effective dose, as the lowest dose with the highest rate of safety and efficacy. The first proposed design is parametric and assumes a logistic dose-efficacy curve for dose determination, and the second design uses quadratic regression to identify the optimal biological dose. We conducted extensive simulation studies to investigate the operating characteristics of the proposed designs. Simulation studies provide a possible way to decide on the best effective dose of MC to be considered in further phases through the finding of the optimal biological dose. The proposed design is assumed, with the threshold value of optimum biological dose (OBD), to detect the best dose of MC. This consistent design with specific dose response models can be recommended for practice.

An Algorithm to Define the Optimum Biological Dose of Metronomic Chemotherapy

Biometrical Letters

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"An Algorithm to Define the Optimum Biological Dose of Metronomic Chemotherapy"}

The best effective dose of a chemotherapy is defined using the maximum tolerated dose (MTD) of toxicity. It is possible that the toxicity of a dose may...

An Algorithm to Define the Optimum Biological Dose of Metronomic Chemotherapy

Online veröffentlicht: 22. Juni 2018

Seitenbereich: 1 - 15

DOI: https://doi.org/10.2478/bile-2018-0001

Schlüsselwörter
OBD, bayesian algorithm, metronomic, MTD, CEC

© 2018 Atanu Bhattacharjee, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

An Algorithm to Define the Optimum Biological Dose of Metronomic Chemotherapy

Online veröffentlicht: 22. Juni 2018

Seitenbereich: 1 - 15

DOI: https://doi.org/10.2478/bile-2018-0001

SchlüsselwörterOBD, bayesian algorithm, metronomic, MTD, CEC

© 2018 Atanu Bhattacharjee, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
OBD, bayesian algorithm, metronomic, MTD, CEC