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2012 | 7 | 5 | 672-679
Tytuł artykułu

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

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Testicular 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.
Wydawca

Czasopismo
Rocznik
Tom
7
Numer
5
Strony
672-679
Opis fizyczny
Daty
wydano
2012-10-01
online
2012-07-28
Twórcy
  • Department of Medicinal Chemistry, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University, ul. Jurasza 2, 85-094, Bydgoszcz, Poland
  • Department of Marketing and Pharmaceutical Law, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University, ul. Jurasza 2, 85-094, Bydgoszcz, Poland
autor
  • Department of Medicinal Chemistry, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University, ul. Jurasza 2, 85-094, Bydgoszcz, Poland
  • The WCO Greater Poland Cancer Centre, ul. Garbary 15, 61-688, Poznan, Poland
  • Gynaecology, Obstetrics and Gynaecological Oncology Ward, Provincial Specialist Hospital in Olsztyn, ul. Żołnierska 18, 10-561, Olsztyn, Poland
  • Gynaecology, Obstetrics and Gynaecological Oncology Ward, Provincial Specialist Hospital in Olsztyn, ul. Żołnierska 18, 10-561, Olsztyn, Poland
  • NZOZ Pantamed Sp z o.o. in Olsztyn, ul. Pana Tadeusza 6, 10-461, Olsztyn, Poland
  • Department of Biopharmacy, Faculty of Pharmacy, Collegium Medicum, Nicolaus Copernicus University, ul. Jurasza 2, 85-094, Bydgoszcz, Poland, kizbiofarmacji@cm.umk.pl
Bibliografia
  • [1] Masters J.R.W., Köberle B., Curing metastatic cancer: lessons from testicular germ-cell tumors, Nat. Rev. Cancer, 2003, 3, 517–525 http://dx.doi.org/10.1038/nrc1120[Crossref]
  • [2] Hameed A., White B., Chinegwundoh F., Thwaini A., Pahuja A., A review in management of testicular cancer: single center review, World Journal of Oncology, 2011, 2, 94–101 http://dx.doi.org/10.5306/wjco.v2.i2.94[Crossref]
  • [3] Schmelz H.U., Port M., Hauck E.W., Schwerer M.J., Weidner W., Sparwasser Ch., Abend M., Apoptosis: a key effector mechanism of lymphocyte action in human nonseminomatous testicular carcinoma? BJU International, 2005, 96, 158–163 http://dx.doi.org/10.1111/j.1464-410X.2005.05587.x[Crossref]
  • [4] Aschim E.L, Haugen T.B., Tretli S., Daltveit A.K., Grotmol T. Risk factors for testicular cancer - differences between pure non-seminoma and mixed seminoma/non-seminoma?, INT. J. ANDROL., 2006, 29, 458–467 http://dx.doi.org/10.1111/j.1365-2605.2005.00632.x[Crossref]
  • [5] Robertson A.G., Read G., The value of lactate dehydrogenase as a nonspecific tumour marker for seminoma of the testis, Br. J. Cancer, 1982, 46, 994 http://dx.doi.org/10.1038/bjc.1982.315[Crossref]
  • [6] Testis. In: Edge S.B., Byrd D.R., Compton C.C., et al., eds.: AJCC Cancer Staging Manual. 7th ed. New York, NY: Springer, 2010, 469–478
  • [7] Daugaard G., Petersen P.M., Rorth M., Surveillance in stage I testicular cancer, APMIS, 2003, 111, 76–85 http://dx.doi.org/10.1034/j.1600-0463.2003.11101111.x[Crossref]
  • [8] Fossa S.D., Chen J., Schonfeld S.J., McGlynn K.A., McMaster M.L., Gail M.H., Travis L.B., Risk of contralateral testicular cancer: a population based study of 29515 U.S. men, J. Natl. Caner. Inst., 2005 97, 1056–1066 http://dx.doi.org/10.1093/jnci/dji185[Crossref]
  • [9] Bray F., Ferlay Devesa S.S., McGlynn K.A., øller H., Interpreting the international trends in testicular seminoma and nonseminoma incidence, Nat. Clin. Pract. Urol., 2006, 3, 532–543 http://dx.doi.org/10.1038/ncpuro0606[Crossref]
  • [10] Bradburn M.J., Clark T.G., Love S.B., Altman D.G., Survival analysis part II: Multivariate data analysis - an introduction to concepts and methods, Br. J. Cancer., 2003, 89, 431–436 http://dx.doi.org/10.1038/sj.bjc.6601119[Crossref]
  • [11] Niederberger C.S., Commentary on the use of neuronal networks in clinical urology, J. Urol., 1995, 153, 1362 http://dx.doi.org/10.1016/S0022-5347(01)67405-6[Crossref]
  • [12] Cai T., Conti G., Lorenzini M., Bartoletti R., Artificial intelligences in urological practice: the key to success?, Ann. Oncol., 2007, 18, 604–605 http://dx.doi.org/10.1093/annonc/mdl411[Crossref][WoS]
  • [13] Abbod M.F., Catto J.W.F., Linkens D.A., Hamdy F.C., Application of artificial intelligence to the management of urological cancer, J. Urol., 2007, 178, 1150–1156 http://dx.doi.org/10.1016/j.juro.2007.05.122[Crossref]
  • [14] Schwarzer G., Schumacher M., Artificial neural networks for diagnosis and prognosis in prostate cancer, Semin. Urol. Oncol., 2002, 20, 89–95 http://dx.doi.org/10.1053/suro.2002.32492[Crossref]
  • [15] Schwarzer G., Vach W., Schumacher M., On the misuses of artificial neural networks for prognostic and diagnostic classification in oncology, Stat. Med., 2002, 19, 541–561 http://dx.doi.org/10.1002/(SICI)1097-0258(20000229)19:4<541::AID-SIM355>3.0.CO;2-V[Crossref]
  • [16] Clark T.G., Bradburn M.J., Love S.B., Altman D.G., Survival analysis part IV: Further concepts and methods in survival analysis, Br. J. Cancer, 2003, 89, 781–786 http://dx.doi.org/10.1038/sj.bjc.6601117[Crossref]
  • [17] Sargent D.J., Comparison of artificial neural networks with other statistical approaches: results from medical data sets, Cancer, 2001, 91, 1636–1642 http://dx.doi.org/10.1002/1097-0142(20010415)91:8+<1636::AID-CNCR1176>3.0.CO;2-D[Crossref]
  • [18] Bączek T., Buciński A., Ivanov A.R., Kaliszan R., Artificial neural network analysis for evaluation of peptide MS/MS spectra in proteomics, Anal. Chem., 2004, 76, 1726–1732 http://dx.doi.org/10.1021/ac030297u[Crossref]
  • [19] Buciński A., Markuszewski M.J., Wiktorowicz W., Krysiński J., Kaliszan R., Artificial neural networks for prediction of antibacterial activity in series of imidazole derivatives, Comb. Chem. High Throughpu. Screen, 2004, 7, 327–336
  • [20] Buciński A., Nasal A., Kaliszan R., Pharmacological classification of drugs based on neural network processing of molecular modeling data, Comb. Chem. High Throughput Screen, 2000, 3, 525–533
  • [21] Moul J.W., Snow P.B., Fernandez B., Maher P.D., Sesterhenn I.A., Neural Network Analysis of quantitative histological factors to predict pathological stage in clinical stage I nonseminomatous testicular cancer, J. Urol., 1995, 153, 1674–1677 http://dx.doi.org/10.1016/S0022-5347(01)67502-5[Crossref]
  • [22] Samili M.M., Dogan I., An artificial neural network for predicting the presence of spermatozoa in the testes of men with nonobstructive azoospermia, J. Urol., 2004, 171, 2354–2357 http://dx.doi.org/10.1097/01.ju.0000125272.03182.c3[Crossref]
  • [23] Snow P.B., Rodvold D.M., Brandt J.M., Artificial neural networks in clinical urology, Urology, 1999, 54, 787–790 http://dx.doi.org/10.1016/S0090-4295(99)00327-1[Crossref]
  • [24] Wei T.J., Tewari A., Artificial neural networks in urology: PRO, Urology, 1995, 54, 945–948 http://dx.doi.org/10.1016/S0090-4295(99)00341-6[Crossref]
  • [25] Djavan B., Remzi M., Zlotta A., Seitz C., Snow P., Marberger M., Novel artificial neural network for early detection of prostate cancer, J. Clin. Oncol., 2002, 20, 921–929 http://dx.doi.org/10.1200/JCO.20.4.921[Crossref]
  • [26] Snow P.B., Smith D.S., Catalona W.J., Artificial neural networks in the diagnosis and prognosis of prostate cancer: a pilot study, J. Urol., 1994, 152, 1923–1926
  • [27] Tawari A. Narayan, P., Novel staging tool for localized prostate cancer: a pilot study using genetic neural network, J. Urol., 1998, 160, 443–444 http://dx.doi.org/10.1016/S0022-5347(01)62920-3[Crossref]
  • [28] Feleppa E.J., Ennis R.D., Schiff P.B., Wuu C.S., Kalisz A., Ketterling J., Urban S., Liu T., Fair W.R., Porter C.R., Gillespie J.R., Ultrasonic spectrum-analysis and neural-network classification as a basis for ultrasonic imaging to target brachytherapy of prostate cancer, Brachytherapy, 2002, 1, 48–53. http://dx.doi.org/10.1016/S1538-4721(02)00002-8[Crossref]
  • [29] Prater J.S., Richard W.D. Segmenting ultrasound images of the prostate using neural networks, Ultrason. Imag.,1992, 4, 159–185 http://dx.doi.org/10.1016/0161-7346(92)90005-G[Crossref]
  • [30] Han M., Snow P.B., Brandt J.M., Partin A.W., Evaluation of artificial neural networks for the prediction of pathologic stage in prostate carcinoma, Cancer, 2001, 91, 1661–1666 http://dx.doi.org/10.1002/1097-0142(20010415)91:8+<1661::AID-CNCR1180>3.0.CO;2-5[Crossref]
  • [31] Khan J., Wei J.S., Ringner M., Saal L.H., Ladanyi M., Wastermann F., Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat. Med., 2001, 7, 673–679 http://dx.doi.org/10.1038/89044[Crossref]
  • [32] Wells D.M., Niederer, J., A medical expert system approach using artificial neural networks for standardized treatment planning, Int. J. Radiat. Oncol. Biol. Phys., 1998, 41, 173–182 http://dx.doi.org/10.1016/S0360-3016(98)00035-2[Crossref]
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.-psjd-doi-10_2478_s11536-012-0027-7
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