### Calculator and Simulator for Escalation With Overdose Control – Normalized Estimated Toxicity Score (EWOC-NETS)

Dear all,

We present our software for calculating operating characteristics and simulation of phase I clinical trials with EWOC-NETS design. Our software is user-friendly and straightforward to use. Simply access the dropbox link down below and unzip the compressed folder. Inside the folder, you will find a script file named run.vbs. Double click to open our software.

Calculator:

Input parameters consist of 3 pages. Xmin, Xmax, γ, ρ0  and equivalent TTL for the calculation for EWOC on page 1, α, β values for calculating NETS on page 2 as well as new patient toxicity input on page 3. In addition, batches of data from previously enrolled patients can be imported from existing data, therefore allowing for more efficient workflow.

Simulator:

All the parameters that must be defined in the EWOC-NETS calculator must be defined for the EWOC-NETS simulator on page 1, with the exception of coefficients for NETS calculation α and β. The second page of the simulator enables users to input the Average NETS (ANETS) expected at each dose level as well as the dosage for the corresponding dose level.

Thank you,

Dr. Zhengjia Chen & Youyun Zheng

Abstract:

Phase I clinical trials signify the first stage experimentation of a new drug in human use. Because cancer patients who respond poorly to conventional treatment usually resort to experimental treatment options such as phase I cancer clinical trials, additional concerns arise in the design of such trials. A combination of accuracy of Maximum Tolerated Dose (MTD) prediction and rapidity of dose escalation is required to maximize the therapeutic effect and minimize the toxic effect for enrolled patients. It is with such considerations that Escalation With Overdose Control – Normalized Equivalent Toxicity Score (EWOC-NETS) was created. Incorporating Bayesian statistics and a novel quasi-continuous toxicity grading system, EWOC-NETS has been shown to outperform various rule-based and adaptive models. However, due to its statistical complexity, it is exceedingly difficult to implement. Because of that, its usage in clinical settings has been significantly hindered. Here, we introduce a user-friendly, standalone software that enables both MTD calculation during trial progress and trial simulations. Our software enables clinicians to both implement and simulate EWOC-NETS clinical trials. It is our hope that the prevalent usage of EWOC-NETS resulting from the development of our software can facilitate and catalyze the efforts in cancer drug development worldwide.

### Chen-Zheng Calculator for Operating Characteristics of Phase I Clinical Trials

Dear all,

We present our software for calculating operating characteristics of phase I clinical trials. Our software is user-friendly and straightforward to use. Simply access the dropbox link down below and unzip the compressed folder. Inside the folder, you will find a script file named run.vbs. Double click to open our software.

To use our software, first input parameters such as dose de-escalation (with vs. without), dose levels, true probability of DLT at each dose level as well as corresponding dosages (optional). Table and graphic outputs will be produced and made downloadable for further editing purposes.

Thank you,

Dr. Zhengjia Chen & Youyun Zheng

Abstract:

Among various Phase I clinical trial designs, rule-based standard 3+3 design is still the most widely utilized one for its simplicity and robustness. It is necessary to have crucial operating characteristics of the Phase I clinical trial before it starts. Based on assumed probability of Dose Limiting Toxicity (DLT) of each tested dose level, Lin and Shih had elaborated the formulas to calculate the 5 key operating characteristics of Phase I clinical trial using the two subtypes of Standard 3+3 designs (with vs without dose de-escalation): Probability of each dose level being chosen as Maximum Tolerated Dose (MTD); Expected number of patients treated at each dose level; Expected number of patients experiencing DLT at each dose level; Target Toxicity Level (TTL) (expected probability of DLT at MTD); Expected total number of patients experiencing DLT. But understanding the formulas requires advanced statistical knowledge and the formulas are also too complicated to be used directly. To facilitate the application, we develop stand-alone interactive software for the convenient calculations. The calculated results are presented in tables and plots that can be saved and easily edited for further usages.