Can nomograms be superior to other prediction tools? Journal Article
| Authors: | Shariat, S. F.; Capitanio, U.; Jeldres, C.; Karakiewicz, P. I. |
| Article Title: | Can nomograms be superior to other prediction tools? |
| Abstract: | 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. © 2008 The Authors. |
| Keywords: | controlled study; clinical trial; review; nonhuman; outcome assessment; accuracy; evidence based practice; risk assessment; urologic neoplasms; statistical analysis; probability; nomograms; predictive validity; urology; intermethod comparison; regression analysis; decision making; nomogram; classification and regression trees; decision support techniques; artificial neural networks; probability tables; risk groupings; artificial neural network; neural networks (computer) |
| Journal Title: | BJU International |
| Volume: | 103 |
| Issue: | 4 |
| ISSN: | 1464-4096 |
| Publisher: | Wiley Blackwell |
| Date Published: | 2009-02-01 |
| Start Page: | 492 |
| End Page: | 495 |
| Language: | English |
| PUBMED: | 18990135 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | --- - "Cited By (since 1996): 4" - "Export Date: 30 November 2010" - "CODEN: BJINF" - "Source: Scopus" |
