A comparison between an ultrasound based prediction model (LR2) and the risk of ovarian malignancy algorithm (ROMA) to assess the risk of malignancy in women with an adnexal mass

Prospective external validation of IOTA methods for classifying adnexal masses and retrospective assessment of two-step strategy using benign descriptors and ADNEX model: Portuguese multicenter study

OBJECTIVES

To externally and prospectively validate the International Ovarian Tumor Analysis (IOTA) Simple Rules (SRs), Logistic Regression model 2 (LR2) and Assessment of Different NEoplasias in the adneXa (ADNEX) model in a Portuguese population, comparing these approaches with subjective assessment and the risk-of-malignancy index (RMI), as well as with each other. This study also aimed to retrospectively validate the IOTA two-step strategy, using modified benign simple descriptors (MBDs) followed by the ADNEX model in cases in which MBDs were not applicable.

METHODS

This was a prospective multicenter diagnostic accuracy study conducted between January 2016 and December 2021 of consecutive patients with an ultrasound diagnosis of at least one adnexal tumor, who underwent surgery at one of three tertiary referral centers in Lisbon, Portugal. All ultrasound assessments were performed by Level-II or -III sonologists with IOTA certification. Patient clinical data and serum CA 125 levels were collected from hospital databases. Each adnexal mass was classified as benign or malignant using subjective assessment, RMI, IOTA SRs, LR2 and the ADNEX model (with and without CA 125). The reference standard was histopathological diagnosis. In the second phase, all adnexal tumors were classified retrospectively using the two-step strategy (MBDs + ADNEX). Sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios and overall accuracy were determined for all methods. Receiver-operating-characteristics curves were constructed and corresponding areas under the curve (AUC) were determined for RMI, LR2, the ADNEX model and the two-step strategy. The ADNEX model calibration plots were constructed using locally estimated scatterplot smoothing (LOESS).

RESULTS

Of the 571 patients included in the study, 428 had benign disease and 143 had malignant disease (prevalence of malignancy, 25.0%), of which 42 had borderline ovarian tumor, 93 had primary invasive adnexal cancer and eight had metastatic tumors in the adnexa. Subjective assessment had an overall sensitivity of 97.9% and a specificity of 83.6% for distinguishing between benign and malignant lesions. RMI showed high specificity (95.6%) but very low sensitivity (58.7%), with an AUC of 0.913. The IOTA SRs were applicable in 80.0% of patients, with a sensitivity of 94.8% and specificity of 98.6%. The IOTA LR2 had a sensitivity of 84.6%, specificity of 86.9% and an AUC of 0.939, at a malignancy risk cut-off of 10%. At the same cut-off, the sensitivity, specificity and AUC for the ADNEX model with vs without CA 125 were 95.8% vs 98.6%, 82.5% vs 79.7% and 0.962 vs 0.960, respectively. The ADNEX model gave heterogeneous results for distinguishing between benign masses and different subtypes of malignancy, with the highest AUC (0.991) for discriminating benign masses from primary invasive adnexal cancer Stages II-IV, and the lowest AUC (0.696) for discriminating primary invasive adnexal cancer Stage I from metastatic lesion in the adnexa. The calibration plot suggested underestimation of the risk by the ADNEX model compared with the observed proportion of malignancy. The MBDs were applicable in 26.3% (150/571) of cases, of which none was malignant. The two-step strategy using the ADNEX model in the second step only, with and without CA 125, had AUCs of 0.964 and 0.961, respectively, which was similar to applying the ADNEX model in all patients.

CONCLUSIONS

The IOTA methods showed good-to-excellent performance in the Portuguese population, outperforming RMI. The ADNEX model was superior to other methods in terms of accuracy, but interpretation of its ability to distinguish between malignant subtypes was limited by sample size and large differences in the prevalence of tumor subtypes. The IOTA MBDs are reliable in identifying benign disease. The two-step strategy comprising application of MBDs followed by the ADNEX model if MBDs are not applicable, is suitable for daily clinical practice, circumventing the need to calculate the risk of malignancy in all patients. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

Comparison of Human Epididymis Protein 4, Cancer Antigen 125, and Ultrasound Prediction Model in Differentiating Benign from Malignant Adnexal Masses

Background

This study aimed to compare the diagnostic performance of carcinogenic antigen (CA) 125, (HE)-4 (Human epididymis protein 4), and ultrasound (International Ovarian Tumor Analysis [IOTA]) Simple Rules individually and to derive a composite score in the differentiating ovarian cancer from benign ovarian mass.

Subjects and Methods

Consecutive patients (n = 100) with pelvic mass admitted during February 2018-August 2019 were included prospectively. Patients with either known case of epithelial ovarian cancer (EOC) or metastatic EOC were excluded. The primary outcome was to assess the sensitivity and specificity of CA-125, HE-4, and IOTA Simple Rules in predicting benign from malignant mass independently, while secondary outcome was derivation of a new model incorporating these variables using multivariate logistic regression analysis to predict benign from malignant lesions. Receiver operator curve (ROC) was drawn to redefine the best-performing cutoff values and difference between area under the ROC (AUROC) were compared by DeLong's method.

Results

Out of 100 cases of adnexal mass selected, the sensitivity and specificity of CA-125 were 73.8% and 77.6%, HE-4 were 90.5% and 87.9%, and IOTA Simple Rules were 92.9% and 81.0%. CA-125, HE-4, and IOTA Simple Rules were independently associated with the likelihood of malignancy/borderline (P < 0.001). The area under the curve for the "composite score" (AUC = 0.93) was the highest and was significantly better than that of CA-125 (AUC = 0.786) (P = 0.004 using DeLong's test) and comparable with HE-4 (AUROC = 0.90; P = 0.128 using DeLong's Test).

Conclusion

The sensitivity and specificity of HE-4 and IOTA Simple Rules for predicting malignant ovarian tumor was better than those of CA-125. The diagnostic performance of "composite score" was comparable to those of either HE-4 or IOTA Simple Rules and significantly better than CA-125.

Significance of Pelvic Fluid Observed during Ovarian Cancer Screening with Transvaginal Sonogram

The primary objective was to examine the role of pelvic fluid observed during transvaginal ultrasonography (TVS) in identifying ovarian malignancy. A single-institution, observational study was conducted within the University of Kentucky Ovarian Cancer Screening trial from January 1987 to September 2019. We analyzed true-positive (TP), false-positive (FP), true-negative (TN), and false-negative (FN) groups for the presence of pelvic fluid during screening encounters. Measured outcomes were the presence and duration of fluid over successive screening encounters. Of the 48,925 women surveyed, 2001 (4.1%) had pelvic fluid present during a TVS exam. The odds ratio (OR) of detecting fluid in the comparison group (TN screen; OR = 1) significantly differed from that of the FP cases (benign pathology; OR: 13.4; 95% confidence interval (CI): 9.1–19.8), the TP cases with a low malignant potential (LMP; OR: 28; 95% CI: 26.5–29.5), TP ovarian cancer cases (OR: 50.4; 95% CI: 27.2–93.2), and FN ovarian cancer cases (OR: 59.3; 95% CI: 19.7–178.1). The mean duration that pelvic fluid was present for women with TN screens was 2.2 ± 0.05 encounters, lasting 38.7 ± 1.3 months. In an asymptomatic screening population, free fluid identified in TVS exams was more associated with ovarian malignancy than in the control group or benign ovarian tumors. While pelvic free fluid may not solely discriminate malignancy from non-malignancy, it appears to be clinically relevant and warrants thoughtful consideration.

Guideline No. 403: Initial Investigation and Management of Adnexal Masses

OBJECTIVES

To aid primary care physicians, emergency medicine physicians, and gynaecologists in the initial investigation of adnexal masses, defined as lumps that appear near the uterus or in or around ovaries, fallopian tubes, or surrounding connective tissue, and to outline recommendations for identifying women who would benefit from a referral to a gynaecologic oncologist for further management.

INTENDED USERS

Gynaecologists, obstetricians, family physicians, general surgeons, emergency medicine specialists, radiologists, sonographers, nurses, medical learners, residents, and fellows.

TARGET POPULATION

Adult women 18 years of age and older presenting for the evaluation of an adnexal mass.

OPTIONS

Women with adnexal masses should be assessed for personal risk factors, history, and physical findings. Initial evaluation should also include imaging and laboratory testing to triage women for management of their care either by a gynaecologic oncologist or as per SOGC guideline no. 404 on the initial investigation and management of benign ovarian masses.

EVIDENCE

A search of PubMed, Cochrane Wiley, and the Cochrane systematic reviews was conducted in January 2018 for English-language materials involving human subjects published since 2000 using three sets of terms: (i) ovarian cancer, ovarian carcinoma, adnexal disease, ovarian neoplasm, adnexal mass, fallopian tube disease, fallopian tube neoplasm, ovarian cyst, and ovarian tumour; (ii) the above terms in combination with predict neoplasm staging, follow-up, and staging; and (iii) the above two sets of terms in combination with ultrasound, tumour marker, CA 125, CEA, CA19-9, HE4, multivariable-index-assay, risk-of-ovarian-malignancy-algorithm, risk-of-malignancy-index, diagnostic imaging, CT, MRI, and PET. Relevant evidence was selected for inclusion in descending order of quality of evidence as follows: meta-analyses, systematic reviews, guidelines, randomized controlled trials, prospective cohort studies, observational studies, non-systematic reviews, case series, and reports. Additional articles were identified through cross-referencing the identified reviews. The total number of studies identified was 2350, with 59 being included in this review.

VALIDATION METHODS

The content and recommendations were drafted and agreed upon by the authors. The Executive and Board of the Society of Gynecologic Oncology of Canada reviewed the content and submitted comments for consideration. The Board of Directors of the Society of Obstetricians and Gynaecologists of Canada approved the final draft for publication. The quality of evidence was rated using the criteria described in the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology framework (Table A1 of Online Appendix A). See Table A2 of Online Appendix A for the interpretation of strong and weak recommendations. The summary of findings is available upon request.

BENEFITS, HARMS, COSTS

Adnexal masses are common, and guidelines on how to triage them and manage the care of patients presenting with adnexal masses will continue to guide the practice of primary care providers and gynaecologists. Ovarian cancer outcomes are improved when initial surgery is performed by a gynaecologic oncologist, likely as a result of complete surgical staging and optimal cytoreduction. Given these superior outcomes, guidelines to assist in the triage of adnexal masses and the referral and management of the care of patients with an adnexal mass are critical.

SUMMARY STATEMENTS (GRADE RATINGS IN PARENTHESES)

RECOMMENDATIONS (GRADE RATINGS IN PARENTHESES).

Prediction Models of Adnexal Masses: State-of-the-Art Review

Importance

Several predictive models and scoring systems have been developed to differentiate between benign and malignant ovarian masses, in order to guide effective management. These models use combinations of patient characteristics, ultrasound markers, and biochemical markers.

Objective

The aim of this study was to describe, compare, and prioritize, according to their strengths and qualities, all the adnexal prediction models.

Evidence Acquisition

This was a state-of-the-art review, synthesizing the findings of the current published literature on the available prediction models of adnexal masses.

Results

The existing models include subjective assessment by expert sonographers, the International Ovarian Tumor Analysis models (logistic regression models 1 and 2, Simple Rules, 3-step strategy, and ADNEX [Assessment of Different NEoplasias in the adneXa] model), the Risk of Malignancy Index, the Risk of Malignancy Ovarian Algorithm, the Gynecologic Imaging Reporting and Data System, and the Ovarian-Adnexal Reporting and Data System. Overall, subjective assessment appears to be superior to all prediction models. However, the International Ovarian Tumor Analysis models are probably the best available methods for nonexpert examiners. The Ovarian-Adnexal Reporting and Data System is an international approach that incorporates both the common European and North American approaches, but still needs to be validated.

Conclusions

Many prediction models exist for the assessment of adnexal masses. The adoption of a particular model is based on local guidelines, as well as sonographer's experience. The safety of expectant management of adnexal masses with benign ultrasound morphology is still under investigation.

Microcystic pattern and shadowing are independent predictors of ovarian borderline tumors and cystadenofibromas in ultrasound

OBJECTIVES

To determine the sonographic characteristics of borderline tumors (BoTs) and cystadenofibromas (CAFs).

METHODS

Preoperative sonograms from consecutive patients who had at least one primary epithelial tumor in the adnexa were retrospectively collected. All tumors were described using the International Ovarian Tumor Analysis terminology. Ultrasound variables were tested using multinomial logistic regression after univariate analysis.

RESULTS

A total of 650 patients were included in this study. Of these, 110 had a CAF, 128 had a BoT, 249 had a cystadenoma (CAD), and 163 had a cystadenocarcinoma (CAC). Nearly half of CAFs and more than half of BoTs and CACs appeared to be unilocular and multilocular solid on the ultrasound images, while CADs were predominantly uni- or multilocular (p < 0.001). Overall, shadowing was identified in 82/650 cases. Sixty-five of 110 (59.1%) CAFs exhibited an acoustic shadow, compared with only 4/249 (1.6%) in CADs, 7/128 (5.5%) in BoTs, and 6/163 (3.7%) in CACs (p < 0.001). Furthermore, 112/650 cases demonstrated microcystic pattern (MCP). Sixty-eight of 128 (53.1%) BoTs exhibited MCP, compared with only 5/249 (2.0%) in CADs, 19/163 (11.7%) in CACs, and 20/110 (18.2%) in CAFs (p < 0.001). Logistic regression analysis revealed that shadowing is an independent predictor of CAFs, while MCP is an independent predictor of BoTs.

CONCLUSIONS

Sonographic findings for CAFs and BoTs were complex and partly overlapped with those for CACs. However, proper recognition and utilization of shadowing or MCP may help to correctly discriminate CAFs and BoTs.

KEY POINTS

• Sonographic findings for borderline tumors and cystadenofibromas are complex and mimic malignancy. • Microcystic pattern and shadowing are independent predictors of borderline tumors and cystadenofibromas respectively.

Ovarian-Adnexal Reporting Data System Magnetic Resonance Imaging (O-RADS MRI) Score for Risk Stratification of Sonographically Indeterminate Adnexal Masses

IMPORTANCE

Approximately one-quarter of adnexal masses detected at ultrasonography are indeterminate for benignity or malignancy, posing a substantial clinical dilemma.

OBJECTIVE

To validate the accuracy of a 5-point Ovarian-Adnexal Reporting Data System Magnetic Resonance Imaging (O-RADS MRI) score for risk stratification of adnexal masses.

DESIGN, SETTING, AND PARTICIPANTS

This multicenter cohort study was conducted between March 1, 2013, and March 31, 2016. Among patients undergoing expectant management, 2-year follow-up data were completed by March 31, 2018. A routine pelvic MRI was performed among consecutive patients referred to characterize a sonographically indeterminate adnexal mass according to routine diagnostic practice at 15 referral centers. The MRI score was prospectively applied by 2 onsite readers and by 1 reader masked to clinical and ultrasonographic data. Data analysis was conducted between April and November 2018.

MAIN OUTCOMES AND MEASURES

The primary end point was the joint analysis of true-negative and false-negative rates according to the MRI score compared with the reference standard (ie, histology or 2-year follow-up).

RESULTS

A total of 1340 women (mean [range] age, 49 [18-96] years) were enrolled. Of 1194 evaluable women, 1130 (94.6%) had a pelvic mass on MRI with a reference standard (surgery, 768 [67.9%]; 2-year follow-up, 362 [32.1%]). A total of 203 patients (18.0%) had at least 1 malignant adnexal or nonadnexal pelvic mass. No invasive cancer was assigned a score of 2. Positive likelihood ratios were 0.01 for score 2, 0.27 for score 3, 4.42 for score 4, and 38.81 for score 5. Area under the receiver operating characteristic curve was 0.961 (95% CI, 0.948-0.971) among experienced readers, with a sensitivity of 0.93 (95% CI, 0.89-0.96; 189 of 203 patients) and a specificity of 0.91 (95% CI, 0.89-0.93; 848 of 927 patients). There was good interrater agreement among both experienced and junior readers (κ = 0.784; 95% CI, 0.743-0824). Of 580 of 1130 women (51.3%) with a mass on MRI and no specific gynecological symptoms, 362 (62.4%) underwent surgery. Of them, 244 (67.4%) had benign lesions and a score of 3 or less. The MRI score correctly reclassified the mass origin as nonadnexal with a sensitivity of 0.99 (95% CI, 0.98-0.99; 1360 of 1372 patients) and a specificity of 0.78 (95% CI, 0.71-0.85; 102 of 130 patients).

CONCLUSIONS AND RELEVANCE

In this study, the O-RADS MRI score was accurate when stratifying the risk of malignancy in adnexal masses.

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

OBJECTIVE

To compare the diagnostic accuracy of International Ovarian Tumor Analysis (IOTA) simple rules and risk of malignancy index (RMI 1/RMI 2) scoring to discriminate between benign and malignant adnexal masses.

METHODS

Secondary analysis of a cohort of patients scheduled for surgery for adnexal masses in a tertiary center between April 2010 and March 2018. Ultrasound examinations were performed by general gynecologists within 24 hours prior to surgery to evaluate sonographic features. Demographic data and preoperative CA 125 levels were recorded. IOTA rules and RMI scoring were applied to predict malignancy and prospectively recorded. Final diagnosis was based on pathological or intraoperative diagnosis.

RESULTS

A total of 479 masses met the inclusion criteria and were retrieved from the database: 334 (69.7%) benign and 145 (30.3%) malignant. IOTA rules could be applied to 392 (81.8%) masses and were inconclusive in 87 (18.2%). Sensitivity and specificity of IOTA rules (83.8% and 92.0%, respectively) were significantly higher than RMI 1 (77.2% and 86.8%, respectively) and RMI 2 (82.1% and 82.6%, respectively).

CONCLUSION

IOTA simple rules had higher diagnostic accuracy compared with RMI to discriminate between benign and malignant adnexal masses; however, nearly 20% of IOTA results were inconclusive and needed expert consultation.

Prospective external validation of IOTA three-step strategy for characterizing and classifying adnexal masses and retrospective assessment of alternative two-step strategy using simple-rules risk

OBJECTIVES

To perform an external validation of the diagnostic performance of the three-step strategy proposed by the International Ovarian Tumor Analysis (IOTA) group for classifying adnexal masses as benign or malignant, when ultrasound is performed by non-expert sonographers in the first two steps. The second objective was to assess the diagnostic performance of an alternative strategy using simple-rules risk (SRR), instead of simple rules (SR), in the second step.

METHODS

This was a prospective observational study conducted at two university hospitals, from September 2015 to August 2017, of consecutive patients diagnosed with an adnexal mass. All women were evaluated by ultrasound using the IOTA three-step strategy. Non-expert sonographers performed the first step (use of simple descriptors to classify the masses) and the second step (use of SR if the mass could not be classified in the first step); masses that could not be classified in the first two steps were categorized by an expert sonographer based on their subjective assessment (third step). The reference standard was histological diagnosis in patients who underwent surgery or at least 12 months of follow-up in cases managed expectantly. The sensitivity, specificity, positive (LR+) and negative (LR-) likelihood ratios and overall accuracy of the IOTA three-step strategy were estimated. Furthermore, we evaluated retrospectively an alternative two-step strategy using SRR in the second step to categorize the masses not classifiable with simple descriptors, classifying the lesions as being of low, intermediate or high risk for malignancy. The diagnostic performance of this strategy was estimated by calculating its sensitivity and specificity, assuming surgical intervention for intermediate- or high-risk lesions.

RESULTS

The study included 283 patients (median age, 48 (range, 18-90) years), of whom 165 (58.3%) were premenopausal and 118 (41.7%) postmenopausal. Two hundred and sixteen (76.3%) women underwent surgery (154 benign and 62 malignant masses) and 67 (23.7%) were managed expectantly with serial ultrasound follow-up for at least 12 months. All expectantly managed masses were considered benign because no sonographic changes suggestive of malignancy were observed during follow-up. Simple descriptors could be applied in 126 (44.5%) masses. Of the remaining 157 lesions, 112 (39.6%) could be characterized using SR. Therefore, 238 (84.1%) masses could be classified by non-expert sonographers in the first two steps. Of the remaining 45 (15.9%) masses, all could be classified by an expert sonographer. Overall sensitivity, specificity, LR+ and LR- of the IOTA three-step strategy were 95.2%, 97.7%, 42.1 and 0.05, respectively. The diagnostic accuracy was 97.2%. Following the two-step strategy using SRR in the second step, of the 157 lesions not classified with simple descriptors, 42, 38 and 77 presented low, intermediate or high risk for malignancy, respectively. Based on this method, 210 women would have undergone surgical treatment. The sensitivity and specificity of this two-step strategy were 98.4% and 63.8%, respectively.

CONCLUSIONS

The IOTA three-step strategy shows high accuracy for discriminating between benign and malignant adnexal lesions when used by non-expert sonographers. An alternative strategy using the SRR calculator in the second step might improve on this diagnostic performance by decreasing the number of surgical interventions and increasing sensitivity. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.

The contribution and perspectives of proteomics to uncover ovarian cancer tumor markers

Despite all the advances in understanding the mechanisms involved in ovarian cancer (OC) development, many aspects still need to be unraveled and understood. Tumor markers (TMs) are of special interest in this disease. Some aspects of clinical management of OC might be improved by the use of validated TMs, such as differentiating subtypes, defining the most appropriate treatment, monitoring the course of the disease, or predicting clinical outcome. The Food and Drug Administration (FDA) has approved a few TMs for OC: CA125 (cancer antigen 125; monitoring), HE4 (Human epididymis protein; monitoring), ROMA (Risk Of Malignancy Algorithm; HE4+CA125; prediction of malignancy) and OVA1 (Vermillion's first-generation Multivariate Index Assay [MIA]; prediction of malignancy). Proteomics can help advance the research in the field of TMs for OC. A variety of biological materials are being used in proteomic analysis, among them tumor tissues, interstitial fluids, tumor fluids, ascites, plasma, and ovarian cancer cell lines. However, the discovery and validation of new TMs for OC is still very challenging. The enormous heterogeneity of histological types of samples and the individual variability of patients (lifestyle, comorbidities, drug use, and family history) are difficult to overcome in research protocols. In this work, we sought to gather relevant information regarding TMs, OC, biological samples for proteomic analysis, as well as markers and algorithms approved by the FDA for use in clinical routine.

Risk scores to guide referral decisions for people with suspected ovarian cancer in secondary care: a systematic review and cost-effectiveness analysis

BACKGROUND

Ovarian cancer is the sixth most common cancer in UK women and can be difficult to diagnose, particularly in the early stages. Risk-scoring can help to guide referral to specialist centres.

OBJECTIVES

To assess the clinical and cost-effectiveness of risk scores to guide referral decisions for women with suspected ovarian cancer in secondary care.

METHODS

Twenty-one databases, including MEDLINE and EMBASE, were searched from inception to November 2016. Review methods followed published guidelines. The meta-analysis using weighted averages and random-effects modelling was used to estimate summary sensitivity and specificity with 95% confidence intervals (CIs). The cost-effectiveness analysis considered the long-term costs and quality-adjusted life-years (QALYs) associated with different risk-scoring methods, and subsequent care pathways. Modelling comprised a decision tree and a Markov model. The decision tree was used to model short-term outcomes and the Markov model was used to estimate the long-term costs and QALYs associated with treatment and progression.

RESULTS

Fifty-one diagnostic cohort studies were included in the systematic review. The Risk of Ovarian Malignancy Algorithm (ROMA) score did not offer any advantage over the Risk of Malignancy Index 1 (RMI 1). Patients with borderline tumours or non-ovarian primaries appeared to account for disproportionately high numbers of false-negative, low-risk ROMA scores. (Confidential information has been removed.) To achieve similar levels of sensitivity to the Assessment of Different NEoplasias in the adneXa (ADNEX) model and the International Ovarian Tumour Analysis (IOTA) group's simple ultrasound rules, a very low RMI 1 decision threshold (25) would be needed; the summary sensitivity and specificity estimates for the RMI 1 at this threshold were 94.9% (95% CI 91.5% to 97.2%) and 51.1% (95% CI 47.0% to 55.2%), respectively. In the base-case analysis, RMI 1 (threshold of 250) was the least effective [16.926 life-years (LYs), 13.820 QALYs] and the second cheapest (£5669). The IOTA group's simple ultrasound rules (inconclusive, assumed to be malignant) were the cheapest (£5667) and the second most effective [16.954 LYs, 13.841 QALYs], dominating RMI 1. The ADNEX model (threshold of 10%), costing £5699, was the most effective (16.957 LYs, 13.843 QALYs), and compared with the IOTA group's simple ultrasound rules, resulted in an incremental cost-effectiveness ratio of £15,304 per QALY gained. At thresholds of up to £15,304 per QALY gained, the IOTA group's simple ultrasound rules are cost-effective; the ADNEX model (threshold of 10%) is cost-effective for higher thresholds.

LIMITATIONS

Information on the downstream clinical consequences of risk-scoring was limited.

CONCLUSIONS

Both the ADNEX model and the IOTA group's simple ultrasound rules may offer increased sensitivity relative to current practice (RMI 1); that is, more women with malignant tumours would be referred to a specialist multidisciplinary team, although more women with benign tumours would also be referred. The cost-effectiveness model supports prioritisation of sensitivity over specificity. Further research is needed on the clinical consequences of risk-scoring.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42016053326.

FUNDING DETAILS

The National Institute for Health Research Health Technology Assessment programme.

Ultrasound-based logistic regression model LR2 versus magnetic resonance imaging for discriminating between benign and malignant adnexal masses: a prospective study

BACKGROUND

The diagnostic performances of the International Ovarian Tumor Analysis (IOTA) ultrasound-based logistic regression model (LR2) and magnetic resonance imaging (MRI) in discriminating between benign and malignant adnexal masses have not been directly compared in a single study.

METHODS

Using the IOTA LR2 model and subjective interpretation of MRI findings by experienced radiologists, 265 consecutive patients with adnexal masses were preoperatively evaluated in two hospitals between February 2014 and December 2015. Definitive histological diagnosis of excised tissues was used as a gold standard.

RESULTS

From the 265 study subjects, 54 (20.4%) tumors were histologically diagnosed as malignant (including 11 borderline and 3 metastatic tumors). Preoperative diagnoses of malignant tumors showed 91.7% total agreement between IOTA LR2 and MRI, with a kappa value of 0.77 [95% confidence interval (CI), 0.68-0.86]. Sensitivity of IOTA LR2 (0.94, 95% CI, 0.85-0.98) for predicting malignant tumors was similar to that of MRI (0.96, 95% CI, 0.87-0.99; P = 0.99), whereas specificity of IOTA LR2 (0.98, 95% CI, 0.95-0.99) was significantly higher than that of MRI (0.91, 95% CI, 0.87-0.95; P = 0.002). Combined IOTA LR2 and MRI results gave the greatest sensitivity (1.00, 95% CI, 0.93-1.00) and had similar specificity (0.91, 95% CI, 0.86-0.94) to MRI.

CONCLUSIONS

The IOTA LR2 model had a similar sensitivity to MRI for discriminating between benign and malignant tumors and a higher specificity compared with MRI. Our findings suggest that the IOTA LR2 model, either alone or in conjunction with MRI, should be included in preoperative evaluation of adnexal masses.

Clinical Utility of Risk Models to Refer Patients with Adnexal Masses to Specialized Oncology Care: Multicenter External Validation Using Decision Curve Analysis

Purpose: To evaluate the utility of preoperative diagnostic models for ovarian cancer based on ultrasound and/or biomarkers for referring patients to specialized oncology care. The investigated models were RMI, ROMA, and 3 models from the International Ovarian Tumor Analysis (IOTA) group [LR2, ADNEX, and the Simple Rules risk score (SRRisk)].Experimental Design: A secondary analysis of prospectively collected data from 2 cross-sectional cohort studies was performed to externally validate diagnostic models. A total of 2,763 patients (2,403 in dataset 1 and 360 in dataset 2) from 18 centers (11 oncology centers and 7 nononcology hospitals) in 6 countries participated. Excised tissue was histologically classified as benign or malignant. The clinical utility of the preoperative diagnostic models was assessed with net benefit (NB) at a range of risk thresholds (5%-50% risk of malignancy) to refer patients to specialized oncology care. We visualized results with decision curves and generated bootstrap confidence intervals.Results: The prevalence of malignancy was 41% in dataset 1 and 40% in dataset 2. For thresholds up to 10% to 15%, RMI and ROMA had a lower NB than referring all patients. SRRisks and ADNEX demonstrated the highest NB. At a threshold of 20%, the NBs of ADNEX, SRrisks, and RMI were 0.348, 0.350, and 0.270, respectively. Results by menopausal status and type of center (oncology vs. nononcology) were similar.Conclusions: All tested IOTA methods, especially ADNEX and SRRisks, are clinically more useful than RMI and ROMA to select patients with adnexal masses for specialized oncology care. Clin Cancer Res; 23(17); 5082-90. ©2017 AACR.

Ultrasound Monitoring of Extant Adnexal Masses in the Era of Type 1 and Type 2 Ovarian Cancers: Lessons Learned From Ovarian Cancer Screening Trials

Women that are positive for an ovarian abnormality in a clinical setting can have either a malignancy or a benign tumor with probability favoring the benign alternative. Accelerating the abnormality to surgery will result in a high number of unnecessary procedures that will place cost burdens on the individual and the health delivery system. Surveillance using serial ultrasonography is a reasonable alternative that can be used to discover if changes in the ovarian abnormality will occur that favor either a malignant or benign interpretation. Several ovarian cancer screening trials have had extensive experiences with changes in subclinical ovarian abnormalities in normal women that can define growth, stability or resolution and give some idea of the time frame over which changes occur. The present report examines these experiences and relates them to the current understanding of ovarian cancer ontology, presenting arguments related to the benefits of surveillance.

Diagnostic usefulness of the Risk of Ovarian Malignancy Algorithm using the electrochemiluminescence immunoassay for HE4 and the chemiluminescence microparticle immunoassay for CA125

The present study aimed to investigate the usefulness of the Risk of Ovarian Malignancy Algorithm (ROMA) in the preoperative stratification of patients with ovarian tumors using a novel combination of laboratory tests. The study group (n=619) consisted of 354 premenopausal and 265 postmenopausal patients. The levels of carbohydrate antigen 125 (CA125) and human epididymis protein 4 (HE4) were determined, and ROMA calculations were performed for each pre- and postmenopausal patient. HE4 levels were determined using an electrochemiluminescence immunoassay, while CA125 levels were determined by a chemiluminescence microparticle immunoassay. A contingency table was applied to calculate the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Receiver operating characteristic curves were also constructed, and areas under the curves (AUCs) were compared between the marker determinations and ROMA algorithms. In terms of distinguishing between ovarian cancer and benign disease, the sensitivity of ROMA was 88.3%, specificity was 88.2%, PPV was 75.3% and NPV was 94.9% among all patients. The respective parameters were 71.1, 90.1, 48.2 and 91.1% in premenopausal patients and 93.6, 82.9, 86.6 and 91.6% in postmenopausal patients. The AUC value for the ROMA algorithm was 0.926 for the ovarian cancer vs. benign groups in all patients, 0.813 in premenopausal patients and 0.939 in postmenopausal patients. The respective AUC values were 0.911, 0.879 and 0.934 for CA125; and 0.879, 0.783 and 0.889 for HE4. In this combination, the ROMA algorithm is characterized by an extremely high sensitivity of prediction of ovarian cancer in women with pelvic masses, and may constitute a precise tool with which to support the qualification of patients to appropriate surgical procedures. The ROMA may be useful in diagnosing ovarian endometrial changes in young patients.

Value of serum human epididymis secretory protein 4 as a marker for differential diagnosis of malignant and benign gynecological diseases of patients in southern China

BACKGROUND

This study investigated the clinical value of HE4 in distinguishing malignant and benign gynecological diseases of patients in southern China.

METHODS

Preoperative serum CA125 and HE4 concentrations were tested in samples of women with malignant or benign gynecological diseases using fully automated methods (Abbott ARCHITECT) and validated cutoff values.

RESULTS

For the discrimination of ovarian cancer from benign gynecological diseases, in premenopausal women, the sensitivity and specificity were 89.8% and 67.5% for CA125, 68.5% and 97.8% for HE4, and 88.9% and 78.6% for ROMA, whereas in postmenopausal women, the sensitivity and specificity were 86.6% and 88.9% for CA125, 57.3% and 100% for HE4, and 85.4% and 94.4% for ROMA. For the discrimination of endometrial cancer from benign gynecological diseases, in premenopausal women, the sensitivity and specificity were 20.3% and 67.5% for CA125, 56.8% and 97.8% for HE4, and 74.3% and 78.6% for ROMA, whereas in postmenopausal women, the sensitivity and specificity were 17.8% and 88.9% for CA125, 31.5% and 100% for HE4, and 32.9% and 94.4% for ROMA.

CONCLUSIONS

We showed that HE4 had better specificity than CA125 in discriminating ovarian cancer, and endometrial cancer from benign gynecological diseases in southern China population.

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

BACKGROUND

Accurate methods to preoperatively characterize adnexal tumors are pivotal for optimal patient management. A recent metaanalysis concluded that the International Ovarian Tumor Analysis algorithms such as the Simple Rules are the best approaches to preoperatively classify adnexal masses as benign or malignant.

OBJECTIVE

We sought to develop and validate a model to predict the risk of malignancy in adnexal masses using the ultrasound features in the Simple Rules.

STUDY DESIGN

This was an international cross-sectional cohort study involving 22 oncology centers, referral centers for ultrasonography, and general hospitals. We included consecutive patients with an adnexal tumor who underwent a standardized transvaginal ultrasound examination and were selected for surgery. Data on 5020 patients were recorded in 3 phases from 2002 through 2012. The 5 Simple Rules features indicative of a benign tumor (B-features) and the 5 features indicative of malignancy (M-features) are based on the presence of ascites, tumor morphology, and degree of vascularity at ultrasonography. Gold standard was the histopathologic diagnosis of the adnexal mass (pathologist blinded to ultrasound findings). Logistic regression analysis was used to estimate the risk of malignancy based on the 10 ultrasound features and type of center. The diagnostic performance was evaluated by area under the receiver operating characteristic curve, sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), positive predictive value (PPV), negative predictive value (NPV), and calibration curves.

RESULTS

Data on 4848 patients were analyzed. The malignancy rate was 43% (1402/3263) in oncology centers and 17% (263/1585) in other centers. The area under the receiver operating characteristic curve on validation data was very similar in oncology centers (0.917; 95% confidence interval, 0.901-0.931) and other centers (0.916; 95% confidence interval, 0.873-0.945). Risk estimates showed good calibration. In all, 23% of patients in the validation data set had a very low estimated risk (<1%) and 48% had a high estimated risk (≥30%). For the 1% risk cutoff, sensitivity was 99.7%, specificity 33.7%, LR+ 1.5, LR- 0.010, PPV 44.8%, and NPV 98.9%. For the 30% risk cutoff, sensitivity was 89.0%, specificity 84.7%, LR+ 5.8, LR- 0.13, PPV 75.4%, and NPV 93.9%.

CONCLUSION

Quantification of the risk of malignancy based on the Simple Rules has good diagnostic performance both in oncology centers and other centers. A simple classification based on these risk estimates may form the basis of a clinical management system. Patients with a high risk may benefit from surgery by a gynecological oncologist, while patients with a lower risk may be managed locally.

Usefulness of diagnostic indices comprising clinical, sonographic, and biomarker data for discriminating benign from malignant ovarian masses

The objective of this study was to review the accuracy of indices combining several diagnostic variables, in comparison to other models, sonography alone, and biomarker assays, for predicting benign or malignant ovarian lesions. Different single modalities were reviewed. The most useful complex models were International Ovarian Tumor Analysis (IOTA) sonographic logistic regression model 2 (area under the curve, 0.949), risk of malignancy index-cancer antigen 125-human epididymis protein 4 (0.950), risk of malignancy algorithm (0.953), pelvic mass score (0.960), non-IOTA logistic regression model (0.970), and histoscanning score logistic regression model (0.970). None of the indices was superior to an expert subjective sonographic assessment (0.968). For women with adnexal tumors, indices with high accuracy are available that are applicable in clinical practice and comparable to an expert subjective sonographic assessment for discriminating benign from malignant masses.

Distinguishing benign from malignant pelvic mass utilizing an algorithm with HE4, menopausal status, and ultrasound findings

Objective

The purpose of this study was to develop a risk prediction score for distinguishing benign ovarian mass from malignant tumors using CA-125, human epididymis protein 4 (HE4), ultrasound findings, and menopausal status. The risk prediction score was compared to the risk of malignancy index and risk of ovarian malignancy algorithm (ROMA).

Methods

This was a prospective, multicenter (n=6) study with patients from six Asian countries. Patients had a pelvic mass upon imaging and were scheduled to undergo surgery. Serum CA-125 and HE4 were measured on preoperative samples, and ultrasound findings were recorded. Regression analysis was performed and a risk prediction model was developed based on the significant factors. A bootstrap technique was applied to assess the validity of the HE4 model.

Results

A total of 414 women with a pelvic mass were enrolled in the study, of which 328 had documented ultrasound findings. The risk prediction model that contained HE4, menopausal status, and ultrasound findings exhibited the best performance compared to models with CA-125 alone, or a combination of CA-125 and HE4. This model classified 77.2% of women with ovarian cancer as medium or high risk, and 86% of women with benign disease as very-low, low, or medium-low risk. This model exhibited better sensitivity than ROMA, but ROMA exhibited better specificity. Both models performed better than CA-125 alone.

Conclusion

Combining ultrasound with HE4 can improve the sensitivity for detecting ovarian cancer compared to other algorithms.

In 2014, can we do better than CA125 in the early detection of ovarian cancer?

Ovarian cancer is a lethal gynecologic malignancy with greater than 70% of women presenting with advanced stage disease. Despite new treatments, long term outcomes have not significantly changed in the past 30 years with the five-year overall survival remaining between 20% and 40% for stage III and IV disease. In contrast patients with stage I disease have a greater than 90% five-year overall survival. Detection of ovarian cancer at an early stage would likely have significant impact on mortality rate. Screening biomarkers discovered at the bench have not translated to success in clinical trials. Existing screening modalities have not demonstrated survival benefit in completed prospective trials. Advances in high throughput screening are making it possible to evaluate the development of ovarian cancer in ways never before imagined. Data in the form of human “-omes” including the proteome, genome, metabolome, and transcriptome are now available in various packaged forms. With the correct pooling of resources including prospective collection of patient specimens, integration of high throughput screening, and use of molecular heterogeneity in biomarker discovery, we are poised to make progress in ovarian cancer screening. This review will summarize current biomarkers, imaging, and multimodality screening strategies in the context of emerging technologies.

Strategies to diagnose ovarian cancer: new evidence from phase 3 of the multicentre international IOTA study

Background:

To compare different ultrasound-based international ovarian tumour analysis (IOTA) strategies and risk of malignancy index (RMI) for ovarian cancer diagnosis using a meta-analysis approach of centre-specific data from IOTA3.

Methods:

This prospective multicentre diagnostic accuracy study included 2403 patients with 1423 benign and 980 malignant adnexal masses from 2009 until 2012. All patients underwent standardised transvaginal ultrasonography. Test performance of RMI, subjective assessment (SA) of ultrasound findings, two IOTA risk models (LR1 and LR2), and strategies involving combinations of IOTA simple rules (SRs), simple descriptors (SDs) and LR2 with and without SA was estimated using a meta-analysis approach. Reference standard was histology after surgery.

Results:

The areas under the receiver operator characteristic curves of LR1, LR2, SA and RMI were 0.930 (0.917–0.942), 0.918 (0.905–0.930), 0.914 (0.886–0.936) and 0.875 (0.853–0.894). Diagnostic one-step and two-step strategies using LR1, LR2, SR and SD achieved summary estimates for sensitivity 90–96%, specificity 74–79% and diagnostic odds ratio (DOR) 32.8–50.5. Adding SA when IOTA methods yielded equivocal results improved performance (DOR 57.6–75.7). Risk of Malignancy Index had sensitivity 67%, specificity 91% and DOR 17.5.

Conclusions:

This study shows all IOTA strategies had excellent diagnostic performance in comparison with RMI. The IOTA strategy chosen may be determined by clinical preference.

Presurgical diagnosis of adnexal tumours using mathematical models and scoring systems: a systematic review and meta-analysis

BACKGROUND Characterizing ovarian pathology is fundamental to optimizing management in both pre- and post-menopausal women. Inappropriate referral to oncology services can lead to unnecessary surgery or overly radical interventions compromising fertility in young women, whilst the consequences of failing to recognize cancer significantly impact on prognosis. By reflecting on recent developments of new diagnostic tests for preoperative identification of malignant disease in women with adnexal masses, we aimed to update a previous systematic review and meta-analysis. METHODS An extended search was performed in MEDLINE (PubMed) and EMBASE (OvidSp) from March 2008 to October 2013. Eligible studies provided information on diagnostic test performance of models, designed to predict ovarian cancer in a preoperative setting, that contained at least two variables. Study selection and extraction of study characteristics, types of bias, and test performance was performed independently by two reviewers. Quality was assessed using a modified version of the QUADAS assessment tool. A bivariate hierarchical random effects model was used to produce summary estimates of sensitivity and specificity with 95% confidence intervals or plot summary ROC curves for all models considered. RESULTS Our extended search identified a total of 1542 new primary articles. In total, 195 studies were eligible for qualitative data synthesis, and 96 validation studies reporting on 19 different prediction models met the predefined criteria for quantitative data synthesis. These models were tested on 26 438 adnexal masses, including 7199 (27%) malignant and 19 239 (73%) benign masses. The Risk of Malignancy Index (RMI) was the most frequently validated model. The logistic regression model LR2 with a risk cut-off of 10% and Simple Rules (SR), both developed by the International Ovarian Tumor Analysis (IOTA) study, performed better than all other included models with a pooled sensitivity and specificity, respectively, of 0.92 [95% CI 0.88-0.95] and 0.83 [95% CI 0.77-0.88] for LR2 and 0.93 [95% CI 0.89-0.95] and 0.81 [95% CI 0.76-0.85] for SR. A meta-analysis of centre-specific results stratified for menopausal status of two multicentre cohorts comparing LR2, SR and RMI-1 (using a cut-off of 200) showed a pooled sensitivity and specificity in premenopausal women for LR2 of 0.85 [95% CI 0.75-0.91] and 0.91 [95% CI 0.83-0.96] compared with 0.93 [95% CI 0.84-0.97] and 0.83 [95% CI 0.73-0.90] for SR and 0.44 [95% CI 0.28-0.62] and 0.95 [95% CI 0.90-0.97] for RMI-1. In post-menopausal women, sensitivity and specificity of LR2, SR and RMI-1 were 0.94 [95% CI 0.89-0.97] and 0.70 [95% CI 0.62-0.77], 0.93 [95% CI 0.88-0.96] and 0.76 [95% CI 0.69-0.82], and 0.79 [95% CI 0.72-0.85] and 0.90 [95% CI 0.84-0.94], respectively. CONCLUSIONS An evidence-based approach to the preoperative characterization of any adnexal mass should incorporate the use of IOTA Simple Rules or the LR2 model, particularly for women of reproductive age.

[Ovarian tumor markers of presumed benign ovarian tumors]

Cancer Antigen 125 (CA125) and Human Epididymis Protein 4 (HE4) are the most studied ovarian tumor markers. Their diagnostic performance for identification of ovarian cancer are superior to CA19-9, CA72-4, and carcinoembryonic antigen, which are no more recommended for the diagnosis of presumed benign ovarian tumor. HE4 (>140 pmol/L) is superior to CA125 (>30 U/mL) in terms of specificity and positive likelihood ratio. CA125 and HE4 can be combined into an algorithm ROMA, or associated to clinical information (composite index), biological data (OVA1) or imaging (Risk for Malignancy Index (RMI), LR2). ROMA algorithm is an exponential equation combining plasmatic concentrations of HE4 and CA125. ROMA is more sensitive and less specific than HE4 in predicting epithelial ovarian cancer. ROMA is more accurate in post-menopausal women. The performance of ROMA is lower than the ultrasound model LR2 in differentiating malignant from benign ovarian tumors, whatever the hormonal status. The composite index combining CA125 with a symptoms index (pain, abdominal distension, bloating, difficulty eating) has a good sensitivity in a screening program, but because of a 12% false positive rate, ultrasound is required before management. The RMI algorithm is based on serum CA125, ultrasound findings (septation, solid zones, metastases, ascite, bilaterality) and menopausal status. RMI is less sensitive, but more specific than ROMA or OVA1 for the classification of ovarian masses. The addition of HE4 to RMI seems to be the most accurate. The subjective evaluation of ovarian cysts by sonography and color Doppler is better than ROMA and RMI algorithms, and not affected by the hormonal status.

[Sonographic diagnosis of presumed benign ovarian tumors]

To discriminate ovarian lesions is of particular importance in gynecological practice. Two main problems need answers: discrimination of benign and malignant adnexal masses and choice of the appropriate surgical treatment if necessary. Nearly 2% of the adnexal masses are ovarian carcinomas or borderline tumors. It is now, well established that ultrasonography is the gold standard for ovarian cyst diagnosis. The purpose of this data was to review the literature and to establish, with the evidence base medicine model, which parameters and existing diagnostic models using ultrasound and Doppler perform best in the evaluation of adnexal masses. Transvaginal sonography has demonstrated considerable advantage over conventional transabdominal sonography. However, transparietal sonography is still useful in large tumors. Definition of the nomenclature and classification was done and should be used. Unilocular ovarian cyst characterization seems easy using sonography and Doppler. In front of complication, discrimination of such functional cyst may be difficult but spontaneous regression confirms usually the expectative management. Dermoid cysts and endometriomas seem to be easier to discriminate from other adnexal masses. Ultrasound and morphologic parameters have a sensitivity of about 90% and a specificity of 80%; that makes this exam the gold standard for ovarian masses diagnosis. Only 50% of ovarian masses are characterized by sonography. Scoring systems help to differentiate benign from malignant masses (sensitivity of about 90%). Logistic regression and models are good methods especially for LR1 and 2 and RMI and may be useful for malignancy prediction but are difficult to use in current practice. Expert diagnosis is a subjective but most important performing parameter. Any suspicious ovarian mass or not easily diagnosed mass requires sonography by an expert, which can first use all the techniques and the different parameters to discriminate benign and malignant tumors. An explicit report will help the physician to define the right attitude for an appropriate management. Six to 16% of adnexial masses are complex or not classified and will result in MRI prescription or surgery.