An improved risk of malignancy index in diagnosis of adnexal mass

Background With the advent of color Doppler flow imaging （CDFI） and technological development of detection of serum tumor markers,new opportunities are presented to the improved risk of malignancy index （RMI） based on Jacobs＇research for predicting ovarian malignancy in patients with adnexal masses.Methods One hundred and eighty women with an adnexal mass admitted for primary laparotomy were studied.Tumor specific growth factor （TSGF） adjusted ultrasound scores and the results of Doppler blood flow analysis were obtained before the operation.Based on the parameters which had been studied in Jacobs＇ research,TSGF levels and the findings of color Doppler flow imaging,the risk of malignancy model was redesigned using a binary Logistic regression model.The diagnostic efficacy of the improved risk of malignancy index （improved RMI） was compared with the Jacobs＇model RMI by receiver operator characteristic （ROC） curve.Results The ROC curve showed a higher sensitivity （Mcnamer＇s test,P 〈0.05） in the discrimination between benign and malignant adnexal masses for the improved RMI than the RMI.Compared with the RMI,the improved RMI had an advantage in prediction of ovarian germ cell tumors and granular cell tumor （28.57% vs.71.43%,P 〈0.05） and the early stage tumors and borderline tumors （33.33% vs.66.67%,P〈0.05）.Conclusion The predictability of the improved RMI is better than the classic Jacobs＇ model,especially in diagnosis of the ovarian germ cell tumors and granular cell tumor and other early stage adnexal tumors.

A risk of malignancy index in preoperative diagnosis of ovarian cancer

Objective To evaluate the ability of a risk of malignancy index (RMI), based on serum CA125 level, ultrasound findings and menopausal status, to discriminate benign from malignant pelvic mass. Methods One hundred and forty women with pelvic masses, at age 30 of years or more were admitted to the Peking Union Medical College Hospital between January 1998 and June 1999. The sensitivity, specificity and positive predictive value of serum CA125 level, ultrasound findings and the menopausal status in diagnosis of ovarian cancer were evaluated separately or combined into the RMI. Results RMI was more accurate than any individual criterion in diagnosing cancer. Using an RMI cutoff level of 200 to indicate malignancy, the RMI derived from this data set gave a sensitivity of 87.3%, a specificity of 84.4%, and a positive predictive value of 82.1%. Conclusions RMI is able to correctly discriminate malignant from benign pelvic mass. It can be introduced easily into clinical practice to facilitate the selection of patients for primary surgery.

Ultrasound Features Improve Diagnostic Performance of Ovarian Cancer Predictors in Distinguishing Benign and Malignant Ovarian Tumors

To determine whether ultrasound features can improve the diagnostic performance of tumor markers in distinguishing ovarian tumors,we enrolled 719 patients diagnosed as having ovarian tumors at Nanfang Hospital from September 2014 to November 2016.Age,menopausal status,histopathology,the International Federation of Gynecology and Obstetrics(FIGO)stages,tumor biomarker levels,and detailed ultrasound reports of patients were collected.The area under the curve(AUC),sensitivity,and specificity of the bellow-mentioned predictors were analyzed using the receiver operating characteristic curve.Of the 719 patients,531 had benign lesions,119 had epithelial ovarian cancers(EOC),44 had borderline ovarian tumors(BOT),and 25 had non-EOC.AUCs and the sensitivity of cancer antigen 125(CAI25),human epididymis-specific protein 4(HE4),Risk of Ovarian Malignancy Algorithm(ROMA),Risk of Malignancy Index(RMI1),HE4 model,and Rajavithi-Ovarian Cancer Predictive Score(R-OPS)in the overall population were 0.792,0.854,0.856,0.872,0.893,0.852,and 70.2%,56.9%,69.1%,60.6%,77.1%,71.3%,respectively.For distinguishing EOC from benign tumors,the AUCs and sensitivity of the above mentioned predictors were 0.888,0.946,0.947,0.949,0.967,0.966,and 84.0%,79.8%,87.4%,84.9%,90.8%,89.1%,respectively.Their specificity in predicting benign diseases was 72.9%,94.4%,87.6%,95.9%,86.3%,90.8%,respectively.Therefore,we consider biomarkers in combination with ultrasound features may improve the diagnostic performance in distinguishing malignant from benign ovarian tumors.

Current diagnostic approach to patients with adnexal masses: which tools are relevant in routine praxis?

Objective： The aim of the study was to investigate which anamnestic, laboratory and ultrasound parameters used in routine practice could predict the nature of adnexal mass, thus enabling referral to relevant specialist. Methods： Study involved the women treated for adnexal tumors throughout a period of 2 years. On admission, detailed anamnestic and laboratory data were obtained, expert ultrasound scan was performed, and power Doppler index （PDI）, risk of malignancy index （RMI） and body mass index （BMI） were calculated for all patients. Obtained data were related to histopathological findings, and statistically analyzed. Results： The study included 689 women （112 malignant, 544 benignant, and 33 borderline tumors）. Malignant and borderline tumors were more frequent in postmenopausal women （P=0.000）. Women who had benignant tumors had the lowest BMI （P=0.000）. There were significant （P〈0.05） differences among tumor types regarding erythrocyte sedimentation rate, CA125 and carcinoembryonic antigen （CEA） levels. Among ultrasound findings, larger tumor diameter and ascites were more frequent in malignant tumors （P=0.000）. Women with malignant tumors had highest values of RMI and PDI （P=0.000）. Conclusions： Anamnestic data, ultrasound parameters and laboratory analyses were all found to be good discriminating factors among malignant, benignant and borderline tumors.