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      Prognosticating gestational trophoblastic neoplasia: from FIGO 2000 to future models

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          Summary

          The FIGO 2000 Prognostic Scoring System is a global standard for prognostication in patients with gestational trophoblastic neoplasia (GTN). However, the system has not been updated in over 20 years, and in clinical practice it has several critical limitations, including inadequate assessment of single-agent chemotherapy resistance and overuse in unsuitable clinical scenarios. This review critically examines these shortcomings and summarizes recent efforts to refine the system. After identifying its limitations, we propose novel refinements: instead of relying on a single system to address multiple clinical objectives, we advocate for specialized scoring models, each tailored to a specific clinical goal. This approach simplifies and enhances the effectiveness of prognostic assessments. Additionally, biological and genetic markers must be integrated into these models to improve accuracy. Looking ahead, we emphasize the need for advanced technologies and multicentre collaboration to build more personalized and adaptive GTN management frameworks, ultimately improving clinical practice and outcomes.

          Funding

          This work was supported by the National Key R&D Program of China ( 2023YFC2705802) and National High Level Hospital Clinical Research Funding (2022-PUMCH-C-058).

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          Most cited references67

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          2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative.

          The 1987 American College of Rheumatology (ACR; formerly, the American Rheumatism Association) classification criteria for rheumatoid arthritis (RA) have been criticized for their lack of sensitivity in early disease. This work was undertaken to develop new classification criteria for RA. A joint working group from the ACR and the European League Against Rheumatism developed, in 3 phases, a new approach to classifying RA. The work focused on identifying, among patients newly presenting with undifferentiated inflammatory synovitis, factors that best discriminated between those who were and those who were not at high risk for persistent and/or erosive disease--this being the appropriate current paradigm underlying the disease construct "rheumatoid arthritis." In the new criteria set, classification as "definite RA" is based on the confirmed presence of synovitis in at least 1 joint, absence of an alternative diagnosis that better explains the synovitis, and achievement of a total score of 6 or greater (of a possible 10) from the individual scores in 4 domains: number and site of involved joints (score range 0-5), serologic abnormality (score range 0-3), elevated acute-phase response (score range 0-1), and symptom duration (2 levels; range 0-1). This new classification system redefines the current paradigm of RA by focusing on features at earlier stages of disease that are associated with persistent and/or erosive disease, rather than defining the disease by its late-stage features. This will refocus attention on the important need for earlier diagnosis and institution of effective disease-suppressing therapy to prevent or minimize the occurrence of the undesirable sequelae that currently comprise the paradigm underlying the disease construct "rheumatoid arthritis."
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            Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement

            Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). Editors’ note: In order to encourage dissemination of the TRIPOD Statement, this article is freely accessible on the Annals of Internal Medicine Web site (www.annals.org) and will be also published in BJOG, British Journal of Cancer, British Journal of Surgery, BMC Medicine, British Medical Journal, Circulation, Diabetic Medicine, European Journal of Clinical Investigation, European Urology, and Journal of Clinical Epidemiology. The authors jointly hold the copyright of this article. An accompanying Explanation and Elaboration article is freely available only on www.annals.org; Annals of Internal Medicine holds copyright for that article.
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              Endometrial cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up

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                Author and article information

                Contributors
                Journal
                eClinicalMedicine
                EClinicalMedicine
                eClinicalMedicine
                Elsevier
                2589-5370
                07 November 2024
                November 2024
                07 November 2024
                : 77
                : 102890
                Affiliations
                [1]Department of Obstetrics & Gynaecology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Science, National Clinical Research Centre for Obstetric & Gynaecologic Diseases, No. 1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, China
                Author notes
                []Corresponding author. Peking Union Medical College Hospital (Dongdan campus), No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China. jiangfang@ 123456pumch.cn
                [∗∗ ]Corresponding author. Peking Union Medical College Hospital (Dongdan campus), No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China. xiangy@ 123456pumch.cn
                Article
                S2589-5370(24)00469-3 102890
                10.1016/j.eclinm.2024.102890
                11582452
                39583749
                28bbe6eb-3e0c-4710-8509-b3d80d2f14a8
                © 2024 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 21 July 2024
                : 2 October 2024
                : 3 October 2024
                Categories
                Review

                figo 2000,gestational trophoblastic neoplasia,prediction,prognostication,resistance

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