\name{chemo}
\alias{chemo}
\docType{data}
\title{Response to chemotherapy data
}
\description{
This \code{data.frame} contains the data from a study on large primary breast cancer, in which the aim was to evaluate the use of PET/CT imagining in predicting response to neoadjuvant chemotherapy. The study recruited 50 patients. The following variables have been collected:

\itemize{
  \item{\code{id}   Patient identifier}
  \item{\code{SUV}    percent change in maximum standardised uptake value (SUV) (\%) between the baseline evaluation (before treatment) and the evaluation after two cycles of neoadjuvant chemotherapy, quantified using PET/CT imaging. The following formula was used to calculate this variable: \deqn{\frac{\mbox{SUV}_b-\mbox{SUV}_2}{\mbox{SUV}_b} \cdot 100,} where \eqn{\mbox{SUV}_b} is the maximum SUV in the baseline evaluation and \eqn{\mbox{SUV}_2} is the maximum SUV after two cycles}
  \item{\code{resp}   Response evaluated after the completion of the neoadjuvant chemotherapy, in accordance with the RECIST guidelines: complete response (lesions completely disappeared), partial response (lesions showed at least a 30\% decrease in size), stable disease (otherwise)}
}
}
\usage{data("chemo")}

\references{
Duch J, Fuster D, Munoz M, Fernandez P, Paredes P, Fontanillas M, Guzman F, Rubi S, Lomena F, Pons F. (2009). 18 F-FDG PET/CT for Early Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer. European Journal of Nuclear Molecular Imaging, 36, 1551-1557.

Skaltsa K, Jover L, Fuster D, Carrasco JL. (2012). Optimum threshold estimation based on cost function in a multistate diagnostic setting. Statistics in Medicine, 31:1098-1109.
}

\keyword{datasets}
