DoseFinding

Comparing dose-finding designs by simulation

A simple, efficient method for comparing dose-finding designs described in preprint and implemented in escalation v0.1.8

New phase I methods in escalation

Introducing new methods in `escalation` for TPI, mTPI and Neuenschwander et al.'s design for phase I trials, plus MCMC-based CRM methods.

trialr and escalation

The `trialr` package, the `escalation` package, how they work together, and how they will grow.

Fitting the Emax Model in R

Emax is an awesome, flexible non-linear model for estimating dose-response curves. Come learn how to fit it in R.

Real data on lots of dose-finding trials

We collected efficacy and toxicity outcomes from 122 published dose-finding trials. This project introduces the data and our insights.

Sample sizes in phase I

Empirically, what sample size is used in dose-escalation trials?

Dataset containing outcomes from dose-finding trials in cancer

Descriptive data and dose-level outcomes from 122 manuscripts reporting results of dose-finding clinical trials in cancer.

Simulation or enumeration with dose-finding designs?

Simulation is the popular approach but brute-force enumeration is more accurate and can even be quicker.

Dose-paths in the escalation package

Enumerate every possible dose selection decision for all dose-finding models implemented in the escalation package.

The escalation package

_escalation_ is an R package for dose-escalation clinical trials, providing a consistent, extensible, modular approach.