Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study

Uterine cancer; Cancer risk factors; Endometrial carcinoma

Detalhes bibliográficos
Autores: Reijnen, Casper, Gogou, Evangelia, Engerud, Hilde, Ramjith, Jordache, van der Putten, Louis, Reques Llanos, Armando, Visser, Nicole, Gil-Moreno, Antonio
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:11351/10996
Acesso em linha:https://hdl.handle.net/11351/10996
http://hdl.handle.net/11351/10996
Access Level:acceso abierto
Palavra-chave:Marcadors tumorals
Metàstasi limfàtica
Estadística bayesiana
Endometri - Càncer
DISEASES::Neoplasms::Neoplasms by Site::Urogenital Neoplasms::Genital Neoplasms, Female::Uterine Neoplasms::Endometrial Neoplasms
CHEMICALS AND DRUGS::Biological Factors::Biomarkers::Biomarkers, Tumor
DISEASES::Neoplasms::Neoplastic Processes::Neoplasm Metastasis::Lymphatic Metastasis
ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Probability::Bayes Theorem
ENFERMEDADES::neoplasias::neoplasias por localización::neoplasias urogenitales::neoplasias de los genitales femeninos::neoplasias uterinas::neoplasias endometriales
COMPUESTOS QUÍMICOS Y DROGAS::factores biológicos::biomarcadores::marcadores tumorales
ENFERMEDADES::neoplasias::procesos neoplásicos::metástasis neoplásica::metástasis linfática
TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::técnicas de investigación::métodos epidemiológicos::estadística como asunto::probabilidad::teorema de Bayes
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oai_identifier_str oai:recercat.cat:11351/10996
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study
title Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study
spellingShingle Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study
Reijnen, Casper
Marcadors tumorals
Metàstasi limfàtica
Estadística bayesiana
Endometri - Càncer
DISEASES::Neoplasms::Neoplasms by Site::Urogenital Neoplasms::Genital Neoplasms, Female::Uterine Neoplasms::Endometrial Neoplasms
CHEMICALS AND DRUGS::Biological Factors::Biomarkers::Biomarkers, Tumor
DISEASES::Neoplasms::Neoplastic Processes::Neoplasm Metastasis::Lymphatic Metastasis
ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Probability::Bayes Theorem
ENFERMEDADES::neoplasias::neoplasias por localización::neoplasias urogenitales::neoplasias de los genitales femeninos::neoplasias uterinas::neoplasias endometriales
COMPUESTOS QUÍMICOS Y DROGAS::factores biológicos::biomarcadores::marcadores tumorales
ENFERMEDADES::neoplasias::procesos neoplásicos::metástasis neoplásica::metástasis linfática
TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::técnicas de investigación::métodos epidemiológicos::estadística como asunto::probabilidad::teorema de Bayes
title_short Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study
title_full Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study
title_fullStr Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study
title_full_unstemmed Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study
title_sort Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study
dc.creator.none.fl_str_mv Reijnen, Casper
Gogou, Evangelia
Engerud, Hilde
Ramjith, Jordache
van der Putten, Louis
Reques Llanos, Armando
Visser, Nicole
Gil-Moreno, Antonio
author Reijnen, Casper
author_facet Reijnen, Casper
Gogou, Evangelia
Engerud, Hilde
Ramjith, Jordache
van der Putten, Louis
Reques Llanos, Armando
Visser, Nicole
Gil-Moreno, Antonio
author_role author
author2 Gogou, Evangelia
Engerud, Hilde
Ramjith, Jordache
van der Putten, Louis
Reques Llanos, Armando
Visser, Nicole
Gil-Moreno, Antonio
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Institut Català de la Salut
[Reijnen C] Department of Obstetrics and Gynaecology, Radboud University Medical Center, Nijmegen, The Netherlands. Department of Obstetrics and Gynaecology, Canisius-Wilhelmina Hospital, Nijmegen, The Netherlands. [Gogou E] Department of Computing Sciences, Radboud University, Nijmegen, The Netherlands. [Visser NCM] Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands. [Engerud H] Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway. Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway. [Ramjith J] Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands. [van der Putten LJM] Department of Obstetrics and Gynaecology, Radboud University Medical Center, Nijmegen, The Netherlands. [Gil-Moreno A] Grup de Recerca Biomèdica en Ginecologia, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain. CIBERONC, Barcelona, Spain. Servei de Ginecologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. CIBERONC, Barcelona, Spain. [Reques A] Servei d’Anatomia Patològica, Vall d’Hebron Hospital Universitari, Barcelona, Spain. CIBERONC, Barcelona, Spain
Vall d'Hebron Barcelona Hospital Campus
dc.subject.none.fl_str_mv Marcadors tumorals
Metàstasi limfàtica
Estadística bayesiana
Endometri - Càncer
DISEASES::Neoplasms::Neoplasms by Site::Urogenital Neoplasms::Genital Neoplasms, Female::Uterine Neoplasms::Endometrial Neoplasms
CHEMICALS AND DRUGS::Biological Factors::Biomarkers::Biomarkers, Tumor
DISEASES::Neoplasms::Neoplastic Processes::Neoplasm Metastasis::Lymphatic Metastasis
ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Probability::Bayes Theorem
ENFERMEDADES::neoplasias::neoplasias por localización::neoplasias urogenitales::neoplasias de los genitales femeninos::neoplasias uterinas::neoplasias endometriales
COMPUESTOS QUÍMICOS Y DROGAS::factores biológicos::biomarcadores::marcadores tumorales
ENFERMEDADES::neoplasias::procesos neoplásicos::metástasis neoplásica::metástasis linfática
TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::técnicas de investigación::métodos epidemiológicos::estadística como asunto::probabilidad::teorema de Bayes
topic Marcadors tumorals
Metàstasi limfàtica
Estadística bayesiana
Endometri - Càncer
DISEASES::Neoplasms::Neoplasms by Site::Urogenital Neoplasms::Genital Neoplasms, Female::Uterine Neoplasms::Endometrial Neoplasms
CHEMICALS AND DRUGS::Biological Factors::Biomarkers::Biomarkers, Tumor
DISEASES::Neoplasms::Neoplastic Processes::Neoplasm Metastasis::Lymphatic Metastasis
ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Probability::Bayes Theorem
ENFERMEDADES::neoplasias::neoplasias por localización::neoplasias urogenitales::neoplasias de los genitales femeninos::neoplasias uterinas::neoplasias endometriales
COMPUESTOS QUÍMICOS Y DROGAS::factores biológicos::biomarcadores::marcadores tumorales
ENFERMEDADES::neoplasias::procesos neoplásicos::metástasis neoplásica::metástasis linfática
TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::técnicas de investigación::métodos epidemiológicos::estadística como asunto::probabilidad::teorema de Bayes
description Uterine cancer; Cancer risk factors; Endometrial carcinoma
publishDate 2020
dc.date.none.fl_str_mv 2020
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11351/10996
http://hdl.handle.net/11351/10996
url https://hdl.handle.net/11351/10996
http://hdl.handle.net/11351/10996
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv PLOS Medicine;17(5)
https://doi.org/10.1371/journal.pmed.1003111
dc.rights.none.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Public Library Science
publisher.none.fl_str_mv Public Library Science
dc.source.none.fl_str_mv Scientia
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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spelling Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation studyReijnen, CasperGogou, EvangeliaEngerud, HildeRamjith, Jordachevan der Putten, LouisReques Llanos, ArmandoVisser, NicoleGil-Moreno, AntonioMarcadors tumoralsMetàstasi limfàticaEstadística bayesianaEndometri - CàncerDISEASES::Neoplasms::Neoplasms by Site::Urogenital Neoplasms::Genital Neoplasms, Female::Uterine Neoplasms::Endometrial NeoplasmsCHEMICALS AND DRUGS::Biological Factors::Biomarkers::Biomarkers, TumorDISEASES::Neoplasms::Neoplastic Processes::Neoplasm Metastasis::Lymphatic MetastasisANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Probability::Bayes TheoremENFERMEDADES::neoplasias::neoplasias por localización::neoplasias urogenitales::neoplasias de los genitales femeninos::neoplasias uterinas::neoplasias endometrialesCOMPUESTOS QUÍMICOS Y DROGAS::factores biológicos::biomarcadores::marcadores tumoralesENFERMEDADES::neoplasias::procesos neoplásicos::metástasis neoplásica::metástasis linfáticaTÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::técnicas de investigación::métodos epidemiológicos::estadística como asunto::probabilidad::teorema de BayesUterine cancer; Cancer risk factors; Endometrial carcinomaCàncer d'úter; Factors de risc del càncer; Carcinoma d'endometriCáncer de útero; Factores de riesgo del cáncer; Carcinoma de endometrioBackground Bayesian networks (BNs) are machine-learning–based computational models that visualize causal relationships and provide insight into the processes underlying disease progression, closely resembling clinical decision-making. Preoperative identification of patients at risk for lymph node metastasis (LNM) is challenging in endometrial cancer, and although several biomarkers are related to LNM, none of them are incorporated in clinical practice. The aim of this study was to develop and externally validate a preoperative BN to predict LNM and outcome in endometrial cancer patients. Methods and findings Within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC), we performed a retrospective multicenter cohort study including 763 patients, median age 65 years (interquartile range [IQR] 58–71), surgically treated for endometrial cancer between February 1995 and August 2013 at one of the 10 participating European hospitals. A BN was developed using score-based machine learning in addition to expert knowledge. Our main outcome measures were LNM and 5-year disease-specific survival (DSS). Preoperative clinical, histopathological, and molecular biomarkers were included in the network. External validation was performed using 2 prospective study cohorts: the Molecular Markers in Treatment in Endometrial Cancer (MoMaTEC) study cohort, including 446 Norwegian patients, median age 64 years (IQR 59–74), treated between May 2001 and 2010; and the PIpelle Prospective ENDOmetrial carcinoma (PIPENDO) study cohort, including 384 Dutch patients, median age 66 years (IQR 60–73), treated between September 2011 and December 2013. A BN called ENDORISK (preoperative risk stratification in endometrial cancer) was developed including the following predictors: preoperative tumor grade; immunohistochemical expression of estrogen receptor (ER), progesterone receptor (PR), p53, and L1 cell adhesion molecule (L1CAM); cancer antigen 125 serum level; thrombocyte count; imaging results on lymphadenopathy; and cervical cytology. In the MoMaTEC cohort, the area under the curve (AUC) was 0.82 (95% confidence interval [CI] 0.76–0.88) for LNM and 0.82 (95% CI 0.77–0.87) for 5-year DSS. In the PIPENDO cohort, the AUC for 5-year DSS was 0.84 (95% CI 0.78–0.90). The network was well-calibrated. In the MoMaTEC cohort, 249 patients (55.8%) were classified with <5% risk of LNM, with a false-negative rate of 1.6%. A limitation of the study is the use of imputation to correct for missing predictor variables in the development cohort and the retrospective study design. Conclusions In this study, we illustrated how BNs can be used for individualizing clinical decision-making in oncology by incorporating easily accessible and multimodal biomarkers. The network shows the complex interactions underlying the carcinogenetic process of endometrial cancer by its graphical representation. A prospective feasibility study will be needed prior to implementation in the clinic.This work was supported by the Dutch Cancer Society (JMAP, Grant: 10616/2016-2). The funder did not play any role in the design and conduct of the study; in the collection, management, analysis, or interpretation of the data; or in the preparation, review, or approval of the manuscript.Public Library ScienceInstitut Català de la Salut[Reijnen C] Department of Obstetrics and Gynaecology, Radboud University Medical Center, Nijmegen, The Netherlands. Department of Obstetrics and Gynaecology, Canisius-Wilhelmina Hospital, Nijmegen, The Netherlands. [Gogou E] Department of Computing Sciences, Radboud University, Nijmegen, The Netherlands. [Visser NCM] Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands. [Engerud H] Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway. Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway. [Ramjith J] Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands. [van der Putten LJM] Department of Obstetrics and Gynaecology, Radboud University Medical Center, Nijmegen, The Netherlands. [Gil-Moreno A] Grup de Recerca Biomèdica en Ginecologia, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain. CIBERONC, Barcelona, Spain. Servei de Ginecologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. CIBERONC, Barcelona, Spain. [Reques A] Servei d’Anatomia Patològica, Vall d’Hebron Hospital Universitari, Barcelona, Spain. CIBERONC, Barcelona, SpainVall d'Hebron Barcelona Hospital Campus202420242020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/11351/10996http://hdl.handle.net/11351/10996Scientiareponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésPLOS Medicine;17(5)https://doi.org/10.1371/journal.pmed.1003111Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:11351/109962026-05-29T05:05:01Z
score 15,812429

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