TY - JOUR
T1 - Can nomograms be superior to other prediction tools?
AU - Shariat, Shahrokh F.
AU - Capitanio, Umberto
AU - Jeldres, Claudio
AU - Karakiewicz, Pierre I.
PY - 2009/2
Y1 - 2009/2
N2 - Accurate estimates of the likelihood of treatment success, complications and long-term morbidity are essential for counselling and informed decision-making in patients with urological malignancies. Accurate risk estimates are also required for clinical trial design, to ensure homogeneous patient distribution. Nomograms, risk groupings, artificial neural networks (ANNs), probability tables, and classification and regression tree (CART) analyses represent the available decision aids that can be used within these tasks. We critically reviewed available decision aids (nomograms, risk groupings, ANNs, probability tables and CART analyses) and compared their ability to predict the outcome of interest. Of the available decision aids, nomograms provide individualized evidence-based and highly accurate risk estimates that facilitate management-related decisions. We suggest the use of nomograms for the purpose of evidence-based, individualized decision-making.
AB - Accurate estimates of the likelihood of treatment success, complications and long-term morbidity are essential for counselling and informed decision-making in patients with urological malignancies. Accurate risk estimates are also required for clinical trial design, to ensure homogeneous patient distribution. Nomograms, risk groupings, artificial neural networks (ANNs), probability tables, and classification and regression tree (CART) analyses represent the available decision aids that can be used within these tasks. We critically reviewed available decision aids (nomograms, risk groupings, ANNs, probability tables and CART analyses) and compared their ability to predict the outcome of interest. Of the available decision aids, nomograms provide individualized evidence-based and highly accurate risk estimates that facilitate management-related decisions. We suggest the use of nomograms for the purpose of evidence-based, individualized decision-making.
KW - Artificial neural networks
KW - Classification and regression trees
KW - Nomograms
KW - Probability tables
KW - Risk groupings
UR - http://www.scopus.com/inward/record.url?scp=59249084314&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=59249084314&partnerID=8YFLogxK
U2 - 10.1111/j.1464-410X.2008.08073.x
DO - 10.1111/j.1464-410X.2008.08073.x
M3 - Article
C2 - 18990135
AN - SCOPUS:59249084314
VL - 103
SP - 492
EP - 495
JO - BJU International
JF - BJU International
SN - 1464-4096
IS - 4
ER -