ANN as a prognostic tool after treatment of non-seminoma testicular cancer-Reference-Cited by-同舟云学术

ANN as a prognostic tool after treatment of non-seminoma testicular cancer

Published:2012-10-01 Issue:5 Volume:7 Page:672-679
ISSN:2391-5463
Container-title:Open Medicine
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Author:

Marszałł Michał¹,Krysiński Jerzy²,Sroka Wiktor¹,Nyczak Zbigniew³,Stefanowicz Marek⁴,Waśniewski Tomasz⁴,Romaszko Jerzy⁵,Buciński Adam⁶

Affiliation:

1. 1Department of Medicinal Chemistry, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University, ul. Jurasza 2, 85-094, Bydgoszcz, Poland

2. 2Department of Marketing and Pharmaceutical Law, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University, ul. Jurasza 2, 85-094, Bydgoszcz, Poland

3. 3The WCO Greater Poland Cancer Centre, ul. Garbary 15, 61-688, Poznan, Poland

4. 4Gynaecology, Obstetrics and Gynaecological Oncology Ward, Provincial Specialist Hospital in Olsztyn, ul. Żołnierska 18, 10-561, Olsztyn, Poland

5. 5NZOZ Pantamed Sp z o.o. in Olsztyn, ul. Pana Tadeusza 6, 10-461, Olsztyn, Poland

6. 6Department of Biopharmacy, Faculty of Pharmacy, Collegium Medicum, Nicolaus Copernicus University, ul. Jurasza 2, 85-094, Bydgoszcz, Poland

Abstract

AbstractTesticular cancer is rare but is the most common cancer in males between 15 and 34 years of age. Two principal types of testicular cancer are distinguished: seminomas and non-seminomas. If detected early, the overall cure rate for testicular cancer exceeds 90%. In this study, artificial neural network (ANN) analysis as a prognostic tool was demonstrated regard to five year recurrence after the non-seminoma treatment. Data from 202 patients treated for non-seminoma were available for evaluation and comparison. A total of 32 variables were analysed using the ANN. The ANN approach, as an advanced multivariate data processing method, was demon-strated to provide objective prognostic data. Some of these prognostic factors are consistent or even imperceptible with previously evaluated by other statistical methods.

Publisher

Walter de Gruyter GmbH

Subject

General Medicine

Link

http://link.springer.com/content/pdf/10.2478/s11536-012-0027-7.pdf

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