title: EUCLID: an outcome analysis tool for high-dimensional clinical studies.
abstract: Treatment management decisions in three-dimensional conformal radiation therapy (3DCRT) and intensity-modulated radiation therapy (IMRT) are usually made based on the dose distributions in the target and surrounding normal tissue. These decisions may include, for example, the choice of one treatment over another and the level of tumour dose escalation. Furthermore, biological predictors such as tumour control probability (TCP) and normal tissue complication probability (NTCP), whose parameters available in the literature are only population-based estimates, are often used to assess and compare plans. However, a number of other clinical, biological and physiological factors also affect the outcome of radiotherapy treatment and are often not considered in the treatment planning and evaluation process. A statistical outcome analysis tool, EUCLID, for direct use by radiation oncologists and medical physicists was developed. The tool builds a mathematical model to predict an outcome probability based on a large number of clinical, biological, physiological and dosimetric factors. EUCLID can first analyse a large set of patients, such as from a clinical trial, to derive regression correlation coefficients between these factors and a given outcome. It can then apply such a model to an individual patient at the time of treatment to derive the probability of that outcome, allowing the physician to individualize the treatment based on medical evidence that encompasses a wide range of factors. The software's flexibility allows the clinicians to explore several avenues to select the best predictors of a given outcome. Its link to record-and-verify systems and data spreadsheets allows for a rapid and practical data collection and manipulation. A wide range of statistical information about the study population, including demographics and correlations between different factors, is available. A large number of one- and two-dimensional plots, histograms and survival curves allow for an easy visual analysis of the population. Several visual and analytical methods are available to quantify the predictive power of the multivariate regression model. The EUCLID tool can be readily integrated with treatment planning and record-and-verify systems.
authors.affiliation: Department of Radiation Oncology, Allegheny General Hospital, Pittsburgh, PA 15212, USA. ogayou@wpahs.org
authors.forename: Olivier
authors.initials: O
authors.lastname: Gayou
authors.forename: David S
authors.initials: DS
authors.lastname: Parda
authors.forename: Moyed
authors.initials: M
authors.lastname: Miften
mesh_terms: D000465:Algorithms; D006801:Humans; D016015:Logistic Models; D008495:Medical Oncology / Q000379:methods; D015233:Models, Statistical; D008962:Models, Theoretical; D015999:Multivariate Analysis; D011336:Probability; D018787:Radiation Oncology / Q000379:methods; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*; D012044:Regression Analysis; D012984:Software; D016896:Treatment Outcome