Ovarian Tumors
| Autor: | Demetrios Tziortziotis, D. Aravantinos, Christina Tsionou, Stylianos Michalas, Demetrios Minaretzis |
|---|---|
| Rok vydání: | 1995 |
| Předmět: |
Adult
Oncology Pathology medicine.medical_specialty Ovary Logistic regression Malignancy Ovarian tumor Internal medicine Statistics Carcinoma medicine Humans Aged Probability Retrospective Studies Ultrasonography Ovarian Neoplasms Epithelioma business.industry Age Factors Obstetrics and Gynecology General Medicine Middle Aged medicine.disease medicine.anatomical_structure Logistic Models Reproductive Medicine Cohort Female Ovarian cancer business Forecasting |
| Zdroj: | Obstetrical & Gynecological Survey. 50:287-289 |
| ISSN: | 0029-7828 |
| DOI: | 10.1097/00006254-199504000-00019 |
| Popis: | An attempt was made to predict the probability of malignancy of a given ovarian tumor in a certain patient by using the age and simple morphologic features of the tumor. A cohort of 959 patients with ovarian tumors was analysed retrospectively according to the patient's age and tumor characteristics such as greatest diameter, consistency, bilaterality and diagnosis as malignant (271 patients) or benign (688 patients). All variables were entered unconditionally in a logistic regression. The presence of solid/multilocular elements has a 9.6-fold increased risk of malignancy, where a bilateral tumor has a 2.8-fold increase. Significant increase in risk of malignancy was observed in ages under 20 and over 40 years, as well as in tumors with a diameter larger than 9 cm. All variables were highly significant associated with the discrimination between benign and malignant. A formula including all variables has been developed so that the probability of malignancy can be estimated by a scientific calculator. In conclusion, simple, easily determined by ultrasound and reproducible criteria such as patient's age, tumor size, consistency and bilaterality were assembled in a logistic model in order to predict the probability of malignancy for a given ovarian tumor, in an individual patient. |
| Databáze: | OpenAIRE |
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