BioMed research international · 2014
A risk-scoring model for the prediction of endometrial cancer among symptomatic postmenopausal women with endometrial thickness > 4 mm.
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Giannella Luca, Mfuta Kabala, Setti Tiziano, Cerami Lillo Bruno, Bergamini Ezio, Boselli Fausto
Аннотация
OBJECTIVE: To develop and test a risk-scoring model for the prediction of endometrial cancer among symptomatic postmenopausal women at risk of intrauterine malignancy.
METHODS: We prospectively studied 624 postmenopausal women with vaginal bleeding and endometrial thickness > 4 mm undergoing diagnostic hysteroscopy. Patient characteristics and endometrial assessment of women with or without endometrial cancer were compared. Then, a risk-scoring model, including the best predictors of endometrial cancer, was tested. Univariate, multivariate, and ROC curve analysis were performed. Finally, a split-sampling internal validation was also performed.
RESULTS: The best predictors of endometrial cancer were recurrent vaginal bleeding (odds ratio (OR) = 2.96), the presence of hypertension (OR = 2.01) endometrial thickness > 8 mm (OR = 1.31), and age > 65 years (OR = 1.11). These variables were used to create a risk-scoring model (RHEA risk-model) for the prediction of intrauterine malignancy, with an area under the curve of 0.878 (95% CI 0.842 to 0.908; P < 0.0001). At the best cut-off value (score ≥ 4), sensitivity and specificity were 87.5% and 80.1%, respectively.
CONCLUSION: Among symptomatic postmenopausal women with endometrial thickness > 4 mm, a risk-scoring model including patient characteristics and endometrial thickness showed a moderate diagnostic accuracy in discriminating women with or without endometrial cancer. Based on this model, a decision algorithm was developed for the management of such a population.
METHODS: We prospectively studied 624 postmenopausal women with vaginal bleeding and endometrial thickness > 4 mm undergoing diagnostic hysteroscopy. Patient characteristics and endometrial assessment of women with or without endometrial cancer were compared. Then, a risk-scoring model, including the best predictors of endometrial cancer, was tested. Univariate, multivariate, and ROC curve analysis were performed. Finally, a split-sampling internal validation was also performed.
RESULTS: The best predictors of endometrial cancer were recurrent vaginal bleeding (odds ratio (OR) = 2.96), the presence of hypertension (OR = 2.01) endometrial thickness > 8 mm (OR = 1.31), and age > 65 years (OR = 1.11). These variables were used to create a risk-scoring model (RHEA risk-model) for the prediction of intrauterine malignancy, with an area under the curve of 0.878 (95% CI 0.842 to 0.908; P < 0.0001). At the best cut-off value (score ≥ 4), sensitivity and specificity were 87.5% and 80.1%, respectively.
CONCLUSION: Among symptomatic postmenopausal women with endometrial thickness > 4 mm, a risk-scoring model including patient characteristics and endometrial thickness showed a moderate diagnostic accuracy in discriminating women with or without endometrial cancer. Based on this model, a decision algorithm was developed for the management of such a population.