DEVELOPMENT OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LYMPH NODE INVOLVEMENT IN BLADDER CANCER PATIENTS BASED ON CLINICAL VARIABLES
<p><strong><em>Objective: </em></strong><em>to develop nomogram based on clinical variables, that predicts pathological lymph node involvement (</em><em>р</em><em>N+) in bladder cancer patients.</em></p><p><strong>&l...
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doaj-b8503dc4cca445e1a17e7f3c3df3c0752020-11-25T01:10:26ZrusABV-pressOnkourologiâ 1726-97761996-18122014-07-0181495596DEVELOPMENT OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LYMPH NODE INVOLVEMENT IN BLADDER CANCER PATIENTS BASED ON CLINICAL VARIABLESL. V. Mirylenko0O. G. Sukonko1A. V. Pravorov2A. I. Rolevich3A. S. Mavrichev4N.N. Alexandrov National Cancer Centre of BelarusN.N. Alexandrov National Cancer Centre of BelarusN.N. Alexandrov National Cancer Centre of BelarusN.N. Alexandrov National Cancer Centre of BelarusN.N. Alexandrov National Cancer Centre of Belarus<p><strong><em>Objective: </em></strong><em>to develop nomogram based on clinical variables, that predicts pathological lymph node involvement (</em><em>р</em><em>N+) in bladder cancer patients.</em></p><p><strong><em>Material and methods: </em></strong><em>We used data of 511 patients with bladder cancer, that have undergone radical cystectomy between 1999 and 2008 at N.N. Alexandrov National Cancer Centre. Mono- and multivariate logistic regression analyses were used for pN+ prediction on preoperative data. Coefficients from logistic regression equation were used to construct the nomogram. Nomogram accuracy was evaluated with concordance index and construction of the calibration plot. Internal validation by bootstrap method with 200 variants of dataset was performed.</em></p><p><strong><em>Results: </em></strong><em>We developed nomogram, that includes: clinical stage </em><em>сТ</em><em>, tumor grade, tumor macroscopic appearance, and creatinine level. Bootstrap-corrected prognostic accuracy of nomogram was 71,6%, that was 9,4% better than clinical stage accuracy.</em></p><p><strong><em>Conclusion: </em></strong><em>utilization of developed nomogram can significantly improve pathologic tumor stage prediction accuracy that may be used to select patients for neoadjuvant chemotherapy.</em></p>http://oncourology.abvpress.ru/index.php/oncur/article/view/81bladder cancerradical cystectomyN stagelymph nodespredictionnomogram |
collection |
DOAJ |
language |
Russian |
format |
Article |
sources |
DOAJ |
author |
L. V. Mirylenko O. G. Sukonko A. V. Pravorov A. I. Rolevich A. S. Mavrichev |
spellingShingle |
L. V. Mirylenko O. G. Sukonko A. V. Pravorov A. I. Rolevich A. S. Mavrichev DEVELOPMENT OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LYMPH NODE INVOLVEMENT IN BLADDER CANCER PATIENTS BASED ON CLINICAL VARIABLES Onkourologiâ bladder cancer radical cystectomy N stage lymph nodes prediction nomogram |
author_facet |
L. V. Mirylenko O. G. Sukonko A. V. Pravorov A. I. Rolevich A. S. Mavrichev |
author_sort |
L. V. Mirylenko |
title |
DEVELOPMENT OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LYMPH NODE INVOLVEMENT IN BLADDER CANCER PATIENTS BASED ON CLINICAL VARIABLES |
title_short |
DEVELOPMENT OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LYMPH NODE INVOLVEMENT IN BLADDER CANCER PATIENTS BASED ON CLINICAL VARIABLES |
title_full |
DEVELOPMENT OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LYMPH NODE INVOLVEMENT IN BLADDER CANCER PATIENTS BASED ON CLINICAL VARIABLES |
title_fullStr |
DEVELOPMENT OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LYMPH NODE INVOLVEMENT IN BLADDER CANCER PATIENTS BASED ON CLINICAL VARIABLES |
title_full_unstemmed |
DEVELOPMENT OF THE NOMOGRAM THAT PREDICTS PATHOLOGICAL LYMPH NODE INVOLVEMENT IN BLADDER CANCER PATIENTS BASED ON CLINICAL VARIABLES |
title_sort |
development of the nomogram that predicts pathological lymph node involvement in bladder cancer patients based on clinical variables |
publisher |
ABV-press |
series |
Onkourologiâ |
issn |
1726-9776 1996-1812 |
publishDate |
2014-07-01 |
description |
<p><strong><em>Objective: </em></strong><em>to develop nomogram based on clinical variables, that predicts pathological lymph node involvement (</em><em>р</em><em>N+) in bladder cancer patients.</em></p><p><strong><em>Material and methods: </em></strong><em>We used data of 511 patients with bladder cancer, that have undergone radical cystectomy between 1999 and 2008 at N.N. Alexandrov National Cancer Centre. Mono- and multivariate logistic regression analyses were used for pN+ prediction on preoperative data. Coefficients from logistic regression equation were used to construct the nomogram. Nomogram accuracy was evaluated with concordance index and construction of the calibration plot. Internal validation by bootstrap method with 200 variants of dataset was performed.</em></p><p><strong><em>Results: </em></strong><em>We developed nomogram, that includes: clinical stage </em><em>сТ</em><em>, tumor grade, tumor macroscopic appearance, and creatinine level. Bootstrap-corrected prognostic accuracy of nomogram was 71,6%, that was 9,4% better than clinical stage accuracy.</em></p><p><strong><em>Conclusion: </em></strong><em>utilization of developed nomogram can significantly improve pathologic tumor stage prediction accuracy that may be used to select patients for neoadjuvant chemotherapy.</em></p> |
topic |
bladder cancer radical cystectomy N stage lymph nodes prediction nomogram |
url |
http://oncourology.abvpress.ru/index.php/oncur/article/view/81 |
work_keys_str_mv |
AT lvmirylenko developmentofthenomogramthatpredictspathologicallymphnodeinvolvementinbladdercancerpatientsbasedonclinicalvariables AT ogsukonko developmentofthenomogramthatpredictspathologicallymphnodeinvolvementinbladdercancerpatientsbasedonclinicalvariables AT avpravorov developmentofthenomogramthatpredictspathologicallymphnodeinvolvementinbladdercancerpatientsbasedonclinicalvariables AT airolevich developmentofthenomogramthatpredictspathologicallymphnodeinvolvementinbladdercancerpatientsbasedonclinicalvariables AT asmavrichev developmentofthenomogramthatpredictspathologicallymphnodeinvolvementinbladdercancerpatientsbasedonclinicalvariables |
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1725174774281273344 |