Comparison of the diagnostic accuracy of International Ovarian Tumor Analysis simple rules and the risk of malignancy index to discriminate between benign and malignant adnexal masses

2019 ◽  
Vol 146 (3) ◽  
pp. 364-369 ◽  
Author(s):  
Rapeepat Auekitrungrueng ◽  
Dangcheewan Tinnangwattana ◽  
Charuwan Tantipalakorn ◽  
Cholaros Charoenratana ◽  
Thitikarn Lerthiranwong ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Ovarian Tumor ◽  
Adnexal Masses ◽  
Simple Rules ◽  
Risk Of Malignancy ◽  
Risk Of Malignancy Index

scholarly journals Role of human epididymis protein 4 for detection of ovarian carcinoma in adnexal masses: A pilot study

2016 ◽  
Author(s):  
Nidhi Bansal ◽  
A. Suneja ◽  
K. Guleria ◽  
N. B. Vaid ◽  
K. Mishra ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Cross Sectional Study ◽  
Ca 125 ◽  
Serum Samples ◽  
Cross Sectional ◽  
Adnexal Masses ◽  
Good Discriminator ◽  
Risk Of Malignancy ◽  
Risk Of Malignancy Index ◽  
Benign Tumours

Introduction: HE4 is a novel tumour biomarker used for early diagnosis of ovarian cancer. This study evaluated the diagnostic accuracy of HE4 alone and in combination with CA125, risk of malignancy index (RMI), risk of malignancy algorithm (ROMA). Methods: It was a cross sectional study conducted recruiting 88 women with adnexal masses who were planned for surgery. After baseline work up and ultrasound examination, serum samples were collected for estimation of CA 125 and HE4 levels. Serum HE4 levels were estimated using ELISA kit. RMI and ROMA score were calculated and diagnostic accuracy of HE4, CA 125, RMI, ROMA and their combination were compared. Cut off for HE4 and ROMA score were calculated using ROC curve. Results: Of 88 subjects, 66 were analyzed with 19 malignant (including 5 LMP) and 47 benign cases. The median value of HE4 among malignant cases was found to be significantly higher than among the benign cases. PPV and NPV of HE4 at a cut off 130.8 pMol/ml was 85.7% and 77.9% respectively. Highest PPV (88.9%) with acceptable NPV (80.7%) was found with ROMA followed by HE4 (PPV 85.7%; NPV 77.97%), RMI (PPV 76.92%; NPV 83%) and CA125 (PPV 52%; NPV 80.85%). Conclusion: HE4 levels were lower in Indian population both in malignant and benign tumours as compared to other studies. HE4 is a good discriminator and gives best accuracy when it is combined with CA125 in a logistic algorithm, ROMA.

Comparison of the diagnostic performances of the Assessment of Different NEoplasias in the adneXa model, Simple Rules model, and Risk of Malignancy Index for adnexal masses in a gynecological oncology centre  in China

2020 ◽  
Author(s):  
Le Qian ◽  
Qinwen Du ◽  
Meijiao Jiang ◽  
Fei Yuan ◽  
Hui Chen ◽  
...  
Keyword(s):  
Prediction Models ◽  
Roc Curves ◽  
Chinese Patients ◽  
Malignant Tumours ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
Adnexal Masses ◽  
Simple Rules ◽  
Risk Of Malignancy ◽  
Risk Of Malignancy Index

Abstract Background This study aimed to compare different ultrasound-based International Ovarian Tumor Analysis (IOTA) prediction models, namely, the Simple Rules (SRs) the Assessment of Different NEoplasias in the adneXa (ADNEX) models, and the Risk of Malignancy Index (RMI), for the pre-operative diagnosis of adnexal mass. Methods This single-centre, retrospective study of diagnostic accuracy involved 486 patients. All ultrasound examinations were analyzed and the prediction models were applied. Pathology was the clinical reference standard. The diagnostic performances of prediction models were measured by evaluating receiver-operating characteristic (ROC) curves, sensitivities, specificities, positive and negative predictive values, positive and negative likelihood ratios, and diagnostic odds ratios. Results To discriminate benign and malignant tumours, areas under the ROC curves (AUCs) for ADNEX models were 0.94 (95% CI: 0.92–0.96) with CA125 and 0.94 (95% CI: 0.91–0.96) without CA125, which were significantly higher than the AUCs for RMI I-III: 0.87 (95% CI: 0.83–0.90), 0.83 (95% CI: 0.80–0.86), and 0.82 (95% CI: 0.78–0.86), (all P < 0.0001). At a cut-off of 10%, the ADNEX model with CA125 had the highest sensitivity (0.93; 95% CI: 0.87–0.97) compared with the other models. The SRs model achieved a sensitivity of 0.93 (95% CI: 0.86–0.97) and a specificity of 0.86 (95% CI: 0.82–0.89) when inconclusive diagnoses (11.7%) were classified as malignant. Conclusion ADNEX and SRs models were excellent at characterising adnexal masses which were superior to the RMI in Chinese patients.

scholarly journals Diagnostic accuracy of the risk of malignancy index 1 compared to the more recent IOTA ADNEX model in discriminating benign from malignant adnexal masses: a multi-centric study

2019 ◽  
Vol 8 (3) ◽  
pp. 1001
Author(s):  
Amita Ray ◽  
Divya S. ◽  
B. N. Kumar Guru ◽  
A. S. Ramaswamy ◽  
Bharat Kumar
Keyword(s):  
Diagnostic Accuracy ◽  
Likelihood Ratio ◽  
Predictive Value ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Adnexal Masses ◽  
Medical College ◽  
Risk Of Malignancy ◽  
Risk Of Malignancy Index ◽  
Almost All

Background: Identification of the nature of an adnexal mass can ensure optimum management. Single parameters as well as diagnostic models using a combination of several parameters are in use. The International Ovarian Tumor Analysis (IOTA) consortium has developed and published the Assessment of Different NEoplasias in the adneXa (ADNEX) model, which differentiates between benign and malignant masses. Authors conducted this study with the aim of finding a cut off value for this model in the study population and comparing the diagnostic accuracy of this model to that of the risk of malignancy (RMI).Methods: Women with adnexal masses admitted to the 3 medical college affiliated hospitals for surgical management were included in this study. Appropriate investigations were done to calculate the RMI-I and ADNEX score for each participant. A cut off score for the ADNEX model was determined and diagnostic accuracy tests were done for comparison.Results: At a cut-off of 29 for the ADNEX model and 200 for RMI model the sensitivity was 75% and 77.8, specificity 100% and 80.6%; Positive Predictive Value (PPV) 100%and 60%; Negative Predictive Value (NPV) 91% and 90.6%; Positive Likelihood ratio of infinity and 4 and a negative Likelihood Ratio of 2.8 and 2.5 respectively.Conclusions: The ADNEX model rates higher than the RMI in almost all tests of diagnostic accuracy and can be used for triaging, framing a referral policy and prioritizing surgery.

scholarly journals Predicting the risk of malignancy in adnexal masses based on the Simple Rules from the International Ovarian Tumor Analysis group

2016 ◽  
Vol 214 (4) ◽  
pp. 424-437 ◽  
Author(s):  
Dirk Timmerman ◽  
Ben Van Calster ◽  
Antonia Testa ◽  
Luca Savelli ◽  
Daniela Fischerova ◽  
...  
Keyword(s):  
Ovarian Tumor ◽  
Adnexal Masses ◽  
Analysis Group ◽  
Simple Rules ◽  
Risk Of Malignancy

External validation of Risk of Malignancy Index compared to IOTA Simple Rules

2020 ◽  
pp. 028418512093399
Author(s):  
Esmee E Mulder ◽  
Malou E Gelderblom ◽  
Dick Schoot ◽  
Tineke FM Vergeldt ◽  
Donna L Nijssen ◽  
...  
Keyword(s):  
Cohort Study ◽  
Ovarian Tumor ◽  
External Validation ◽  
Ovarian Tumors ◽  
Ca 125 ◽  
Diagnostic Model ◽  
Histopathological Diagnosis ◽  
Simple Rules ◽  
Risk Of Malignancy ◽  
Risk Of Malignancy Index

Background Mathematical predictive models for ovarian tumors have an advantage over subjective assessment due to their relative simplicity, and therefore usefulness for less experienced sonographers. It is currently unclear which predictive model is best at predicting the nature of an ovarian tumor. Purpose To compare the diagnostic predictive accuracy of the International Ovarian Tumour Analysis Simple Rules (IOTA SR) with Risk of Malignancy Index (RMI), to differentiate between benign and malignant ovarian tumors. Material and Methods A total of 202 women diagnosed with ovarian tumor(s) were included. Preoperatively, patients were examined through transvaginal ultrasonography and CA-125 (U/mL) levels were measured. RMI and IOTA SR were determined, and where possible compared to definitive histopathological diagnosis. Results Of the 202 women with ovarian tumors, 168 women were included in this cohort study. Of these tumors, 118 (70.2%) were benign, 17 (10.1%) were borderline, and 33 (19.7%) were malignant. The sensitivity, specificity, and area under the curve for the RMI were 72.0%, 90.7%, and 0.896, respectively. For the IOTA SR, these were 90.0%, 68.6%, and 0.793, respectively. Conclusion This cohort study shows that the RMI is a relatively useful diagnostic model in characterizing ovarian tumors, compared to the IOTA SR. However, due to the relatively low sensitivity of the RMI and high rate of inconclusive results of the IOTA SR, both diagnostic tests do not seem discriminative enough. Therefore, alternative diagnostic models are necessary.

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