Annals of Surgical Oncology

, Volume 23, Issue 3, pp 975–988 | Cite as

Predictive Modeling: A New Paradigm for Managing Endometrial Cancer

  • Sofiane BendifallahEmail author
  • Emile Daraï
  • Marcos Ballester
Gynecologic Oncology


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.


Overall Survival Endometrial Cancer Myometrial Invasion Cervical Stromal Invasion External Validation Study 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors declare no conflict of interest.


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Copyright information

© Society of Surgical Oncology 2015

Authors and Affiliations

  • Sofiane Bendifallah
    • 1
    • 2
    Email author
  • Emile Daraï
    • 1
    • 3
  • Marcos Ballester
    • 1
    • 3
  1. 1.Department of Gynecology and Obstetrics, Tenon University Hospital, Assistance Publique des Hôpitaux de Paris (AP-HP), University Pierre and Marie CurieInstitut Universitaire de Cancérologie (IUC)Paris 6France
  2. 2.INSERM UMR S 707, “Epidemiology, Information Systems, Modeling,”University Pierre and Marie CurieParis 6France
  3. 3.INSERM UMR S 938University Pierre et Marie CurieParis 6France

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