Development and Validation of a Nomogram Prediction Model for Endometrial Malignancy in Patients with Abnormal Uterine Bleeding.

PURPOSE: This study aimed to identify the risk factors and sonographic variables that could be integrated into a predictive model for endometrial cancer (EC) and atypical endometrial hyperplasia (AEH) in women with abnormal uterine bleeding (AUB). MATERIALS AND METHODS: This retrospective study included 1837 patients who presented with AUB and underwent endometrial sampling. Multivariable logistic regression was developed based on clinical and sonographic covariates [endometrial thickness (ET), resistance index (RI) of the endometrial vasculature] assessed for their association with EC/AEH in the development group (n=1369), and a predictive nomogram was proposed. The model was validated in 468 patients. RESULTS: Histological examination revealed 167 patients (12.2%) with EC or AEH in the development group. Using multivariable logistic regression, the following variables were incorporated in the prediction of endometrial malignancy: metabolic diseases [odds ratio (OR)=7.764, 95% confidence intervals (CI) 5.042-11.955], family history (OR=3.555, 95% CI 1.055-11.971), age ≥40 years (OR=3.195, 95% CI 1.878-5.435), RI ≤0.5 (OR=8.733, 95% CI 4.311-17.692), and ET ≥10 mm (OR=8.479, 95% CI 5.440-13.216). A nomogram was created using these five variables with an area under the curve of 0.837 (95% CI 0.800-0.874). The calibration curve showed good agreement between the observed and predicted occurrences. For the validation group, the model provided acceptable discrimination and calibration. CONCLUSION: The proposed nomogram model showed moderate prediction accuracy in the differentiation between benign and malignant endometrial lesions among women with AUB.

[Fourier transform infrared spectroscopy in detection of breast cancer].

Breast cancer is the most common cancer in women. Later diagnosis of the disease is the leading cause of poor prognosis. Fourier-transform infrared (FTIR) spectroscopy is a novel approach to provide information about the molecular components and metabolic conditions of human tissue; therefore it can detect the early changes caused by cancer cells prior to histological manifestation. FTIR-based diagnosis is rapid, simple and label free, which meets the requirements of an automated and patient-friendly technique. The current article gives an overview of the experimental techniques, data analysis methods and spectral signatures of breast cancer in FTIR-based diagnosis, summarizes the present challenges by focusing on the history of FTIR spectroscopy in breast cancer since 1990s, and highlights some investigations that give a perspective of FTIR-based diagnosis.