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How low is low enough? Evaluation of various risk-assessment models for lymph node metastasis in endometrial cancer: a Korean multicenter study
OBJECTIVE: The aim of this study was to identify a standard for the evaluation of future models for prediction of lymph node metastasis in endometrial cancer through estimation of performance of well-known surgicopathological models. METHODS: Using the medical records of 947 patients with endometria...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society of Gynecologic Oncology and Colposcopy
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3469860/ https://www.ncbi.nlm.nih.gov/pubmed/23094128 http://dx.doi.org/10.3802/jgo.2012.23.4.251 |
Sumario: | OBJECTIVE: The aim of this study was to identify a standard for the evaluation of future models for prediction of lymph node metastasis in endometrial cancer through estimation of performance of well-known surgicopathological models. METHODS: Using the medical records of 947 patients with endometrial cancer who underwent surgical management with lymphadenectomy, we retrospectively assessed the predictive performances of nodal metastasis of currently available models. RESULTS: We evaluated three models included: 1) a model modified from the Gynecologic Oncology Group (GOG) pilot study; 2) one from the GOG-33 data; and 3) one from Mayo Clinic data. The three models showed similar negative predictive values ranging from 97.1% to 97.4%. Using Bayes' theorem, this can be translated into 2% of negative post-test probability when 10% of prevalence of lymph node metastasis was assumed. In addition, although the negative predictive value was similar among these models, the proportion that was classified as low-risk was significantly different between the studies (56.4%, 44.8%, and 30.5%, respectively; p<0.001). CONCLUSION: The current study suggests that a false negativity of 2% or less should be a goal for determining clinical usefulness of preoperative or intraoperative prediction models for low-risk of nodal metastasis. |
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