A look at the recent oncology literature or a search of the common databases reveals a steadily increasing number of nomograms and other prognostic models. These models may predict the risk of relapse, lymphatic spread of a given malignancy, toxicity, survival, etc. Pathology information, gene signatures, and clinical data may all be used to compute the models. This trend reflects increasingly individualized treatment concepts, the need for approaches that achieve a favorable balance between effectiveness and side-effects, and the goal of optimal resource utilization reflecting prognostic knowledge. In order to avoid misuse, it is important to understand the limits and caveats of prognostic and predictive models. This book provides a comprehensive overview of such decision tools for radiation oncology, stratified by disease site, which will enable readers to make informed choices in daily clinical practice and to critically follow the future development of new tools in the field.>

Prognosis and Predictive Factors for Tumours and Organs at risk: Background and Purpose

Specific issues for prognostic factors related to radiotherapy
Role of ICT in decision models
Statistics of Prediction of survival and toxicity and Nomogram Development
Treatment decisions based on Gene Signatures: Methods and Caveats
Brain tumors
Head and neck cancer
Breast cancer
Lung cancer
Esophageal cancer
Gastric cancer
Pancreas and biliary tract cancer
Liver cancer and metastases
Rectal and anal cancer
Cervix and corpus uteri, vulva and vaginal cancers
Bladder cancer
Prostate cancer
Sarcomas
Lymphomas
Brain metastases
Bone metastases.