Dataset Information

A prospective study to evaluate the risk malignancy index and its diagnostic implication in patients with suspected ovarian mass.

ABSTRACT: There is no universal screening method for discrimination between benign and malignant adnexal masses yet. Various authors have tried tumor markers, imaging studies, cytology but no one yet is a definite method for screening of cancer ovary, for which a combined diagnostic modality has come to practice in form of RMI. With this background we conducted our study "Evaluation of risk malignancy index and its diagnostic value in patients with adnexal masses".The aim of the study was to determine the effectiveness of risk of malignancy index (RMI-3) in preoperative discrimination between benign and malignant masses and also to reveal the most suitable cut off value. We have conducted a prospective study between November 2014 to October 2016. We included the parameters like menopausal status, ultrasound features, and serum levels of tumor marker like CA-125 for calculating RMI 3. Then RMI was compared with the histopathological report which was taken as gold standard.In the present study malignant tumors constitute 54.76% (69/126) & benign tumors 45.24% (57/126). Bilaterality in adnexal masses and multilocularity is higher in malignant tumors than benign tumor, but a P -value >0.005 failed to be proved significant in our study. Solid area is seen in 24.69% (20/81) of benign and 75.30% (61/81) of malignant tumor. Similarly ascites was found in 38.09% (48/126) of cases. Out of which 18.75% (9/48) cases were found to be benign and malignancy was confirmed in 81.25% (39/48) patients. There is statistically significant number of malignant ovarian cancer patients where ascites and solid area is seen in USG findings (p = 0.000). Risk of Malignancy Index compared with individual parameters of Ultrasound score, CA-125 or menopausal score and a cut-off point of 236 shows a very high sensitivity (72.5%), specificity (98.2%), positive predictive value (98.1%), negative predictive value (74.7%) and diagnostic accuracy (84.13%) for discriminating malignant and benign pelvic masses.Simplicity and applicability of the method in the primary evaluation of patients with pelvic masses makes it a good option in daily clinical practice in non-specialized gynecologic departments and also in developing countries where access to a gynaecologist oncologist is limited.

SUBMITTER: Dora SK

PROVIDER: S-EPMC5556625 | biostudies-other | 2017 Aug

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:The study objectives were to determine whether ovarian morphology can distinguish between women with regular menstrual cycles, normo-androgenic anovulation (NA-Anov), and PCOS and whether body mass index (BMI)-specific thresholds improved diagnostic potential. Women with PCOS (biochemical and/or clinical hyperandrogenism and irregular cycles; N = 66), NA-Anov (irregular cycles without clinical and/or biochemical hyperandrogenism; N = 64), or regular cycles (controls; cycles every 21-35 days in the absence of clinical or biochemical hyperandrogenism; N = 51) were evaluated. Participants underwent a reproductive history, physical exam, transvaginal ultrasound, and a fasting blood sample. Linear regression analyses were used to assess the impact of BMI on ovarian morphology across groups. The diagnostic performance of ovarian morphology for anovulatory conditions, and by BMI (lean: <25 kg/m2; overweight: ≥25 kg/m2), was tested using Receiver Operating Characteristic (ROC) curves. Follicle number per ovary (FNPO) and ovarian volume (OV), but not follicle number per cross-section (FNPS), increased across controls, NA-Anov, and PCOS. Overall, FNPO had the best diagnostic performance for PCOS versus controls (AUCROC = 0.815) and NA-Anov and controls (AUCROC = 0.704), and OV to differentiate between PCOS and NA-Anov (AUCROC = 0.698). In lean women, FNPO best differentiated between PCOS and controls (AUCROC = 0.843) and PCOS versus NA-Anov (AUCROC = 0.710). FNPS better distinguished between NA-Anov and controls (AUCROC = 0.687), although diagnostic performance was lower than when thresholds were generated using all participants. In women with overweight and obesity, OV persisted as the best diagnostic feature across all analyses (PCOS versus control, AUCROC = 0.885; PCOS versus NA-Anov, AUCROC = 0.673; NA-Anov versus controls, AUCROC = 0.754). Ovarian morphology holds diagnostic potential to distinguish between NA-Anov and PCOS, with marginal differences in diagnostic potential when participants were stratified by BMI suggesting that follicle number may provide better diagnostic performance in lean women and ovarian size in those with overweight.

Dataset Information

A prospective study to evaluate the risk malignancy index and its diagnostic implication in patients with suspected ovarian mass.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets