title: Predictive Modeling: A New Paradigm for Managing Endometrial Cancer.
abstract: With the abundance of new options in diagnostic and treatment modalities, a shift in the medical decision process for endometrial cancer (EC) has been observed. The emergence of individualized medicine and the increasing complexity of available medical data has lead to the development of several prediction models. In EC, those clinical models (algorithms, nomograms, and risk scoring systems) have been reported, especially for stratifying and subgrouping patients, with various unanswered questions regarding such things as the optimal surgical staging for lymph node metastasis as well as the assessment of recurrence and survival outcomes. In this review, we highlight existing prognostic and predictive models in EC, with a specific focus on their clinical applicability. We also discuss the methodologic aspects of the development of such predictive models and the steps that are required to integrate these tools into clinical decision making. In the future, the emerging field of molecular or biochemical markers research may substantially improve predictive and treatment approaches.
authors.affiliation: Department of Gynecology and Obstetrics, Tenon University Hospital, Assistance Publique des Hôpitaux de Paris (AP-HP), University Pierre and Marie Curie, Institut Universitaire de Cancérologie (IUC), Paris 6, France. sofiane.bendifallah@yahoo.fr.|INSERM UMR S 707, "Epidemiology, Information Systems, Modeling,", University Pierre and Marie Curie, Paris 6, France. sofiane.bendifallah@yahoo.fr.
authors.forename: Sofiane
authors.initials: S
authors.lastname: Bendifallah
authors.affiliation: Department of Gynecology and Obstetrics, Tenon University Hospital, Assistance Publique des Hôpitaux de Paris (AP-HP), University Pierre and Marie Curie, Institut Universitaire de Cancérologie (IUC), Paris 6, France.|INSERM UMR S 938, University Pierre et Marie Curie, Paris 6, France.
authors.forename: Emile
authors.initials: E
authors.lastname: Daraï
authors.affiliation: Department of Gynecology and Obstetrics, Tenon University Hospital, Assistance Publique des Hôpitaux de Paris (AP-HP), University Pierre and Marie Curie, Institut Universitaire de Cancérologie (IUC), Paris 6, France.|INSERM UMR S 938, University Pierre et Marie Curie, Paris 6, France.
authors.forename: Marcos
authors.initials: M
authors.lastname: Ballester
mesh_terms: D003657:Decision Making; D019468:Disease Management; D018450:Disease Progression; D016889:Endometrial Neoplasms / Q000517:prevention & control*; D005260:Female; D006801:Humans; D015233:Models, Statistical; D049451:Nomograms; D018570:Risk Assessment