Validation of ADNEX and IOTA two-step strategy and estimation of risk of complications during follow-up of adnexal masses in low-risk population

OBJECTIVES

The aim is to evaluate the ability of the Assessment of Different NEoplasias in the adneXa model (ADNEX) and the International Ovarian Tumour Analysis (IOTA) two-step strategy to predict malignancy in adnexal masses detected in an outpatient low-risk setting, and to estimate the risk of complications in masses with benign ultrasound morphology managed with clinical and ultrasound follow-up.

METHODS

This single center (Hospital Universitari Dexeus Barcelona) study was performed using interim data of the ongoing prospective observational IOTA phase 5 study. The primary aim of the IOTA 5 study is to describe the cumulative incidence of complications during follow-up of adnexal masses classified as benign on ultrasound. Consecutive patients with adnexal masses detected between June 2012 and September 2016 in a private center offering screening for gynecological cancers were included and followed-up until February 2020. Tumors were classified as benign or malignant based on histology (if patients underwent surgery) or outcome of clinical and ultrasound follow-up at 12 (±2) months. Multiple imputation was used when follow-up information was uncertain. The ability of the ADNEX model without CA125 and of the IOTA two-step strategy to distinguish benign from malignant masses was evaluated retrospectively using the prospectively collected data. We describe performance as discrimination (area under the receiver operating characteristic curve, AUC), calibration, classification (sensitivity and specificity) and clinical utility (Net Benefit). In the group of patients with a benign looking mass selected for conservative management we evaluated the occurrence of spontaneous resolution or any mass complication during the first 5 years of follow-up by assessing the cumulative incidence for malignancy, torsion, cyst rupture, or minor mass complications (inflammation, infection, or adhesions) and the time to occurrence of an event.

RESULTS

A total of 2654 patients were recruited to the study. After application of exclusion criteria, 2039 patients with a newly detected mass were included for the model validation. 1684 (82.6%) masses were benign, 49 (2.4%) masses were malignant and for 306 (15.0%) masses the outcome was uncertain and imputed. The AUC was 0.95 (95% CI 0.89-0.98) for ADNEX and 0.94 (95% CI 0.88-0.97) for the two-step strategy. Calibration performance could not be meaningfully interpreted due to few malignancies resulting in very wide confidence intervals. The two-step strategy had better clinical utility than ADNEX at malignancy risk thresholds < 3%. 1472 (72%) patients had a mass judged to be benign based on pattern recognition by an experienced ultrasound examiner and were managed with clinical and ultrasound follow-up. In this group, the 5-year cumulative incidence was 66% for spontaneous resolution of the mass (95% CI 63-69), 0% for torsion (95%CI 0-0.002), 0.1% for cyst rupture (<0.1-0.6), 0.2% for a borderline tumor (<0.1-0.6), and 0.2% (0.1-0.6) for invasive malignancy.

CONCLUSIONS

The ADNEX model and IOTA two-step strategy performed well to distinguish benign from malignant adnexal masses detected in a low-risk population. Conservative management is safe for masses with benign ultrasound appearance in such a population. This article is protected by copyright. All rights reserved.

Updating M6 pregnancy of unknown location risk-prediction model including evaluation of clinical factors

OBJECTIVES

Ectopic pregnancy (EP) is a major high-risk outcome following a pregnancy of unknown location (PUL) classification. Biochemical markers are used to triage PUL as high vs low risk to guide appropriate follow-up. The M6 model is currently the best risk-prediction model. We aimed to update the M6 model and evaluate whether performance can be improved by including clinical factors.

METHODS

This prospective cohort study recruited consecutive PUL between January 2015 and January 2017 at eight units (Phase 1), with two centers continuing recruitment between January 2017 and March 2021 (Phase 2). Serum samples were collected routinely and sent for β-human chorionic gonadotropin (β-hCG) and progesterone measurement. Clinical factors recorded were maternal age, pain score, bleeding score and history of EP. Based on transvaginal ultrasonography and/or biochemical confirmation during follow-up, PUL were classified subsequently as failed PUL (FPUL), intrauterine pregnancy (IUP) or EP (including persistent PUL (PPUL)). The M6 models with (M6P ) and without (M6NP ) progesterone were refitted and extended with clinical factors. Model validation was performed using internal-external cross-validation (IECV) (Phase 1) and temporal external validation (EV) (Phase 2). Missing values were handled using multiple imputation.

RESULTS

Overall, 5473 PUL were recruited over both phases. A total of 709 PUL were excluded because maternal age was < 16 years or initial β-hCG was ≤ 25 IU/L, leaving 4764 (87%) PUL for analysis (2894 in Phase 1 and 1870 in Phase 2). For the refitted M6P model, the area under the receiver-operating-characteristics curve (AUC) for EP/PPUL vs IUP/FPUL was 0.89 for IECV and 0.84-0.88 for EV, with respective sensitivities of 94% and 92-93%. For the refitted M6NP model, the AUCs were 0.85 for IECV and 0.82-0.86 for EV, with respective sensitivities of 92% and 93-94%. Calibration performance was good overall, but with heterogeneity between centers. Net Benefit confirmed clinical utility. The change in AUC when M6P was extended to include maternal age, bleeding score and history of EP was between -0.02 and 0.01, depending on center and phase. The corresponding change in AUC when M6NP was extended was between -0.01 and 0.03. At the 5% threshold to define high risk of EP/PPUL, extending M6P altered sensitivity by -0.02 to -0.01, specificity by 0.03 to 0.04 and Net Benefit by -0.005 to 0.006. Extending M6NP altered sensitivity by -0.03 to -0.01, specificity by 0.05 to 0.07 and Net Benefit by -0.005 to 0.006.

CONCLUSIONS

The updated M6 model offers accurate diagnostic performance, with excellent sensitivity for EP. Adding clinical factors to the model improved performance in some centers, especially when progesterone levels were not suitable or unavailable. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

ADNEX risk prediction model for diagnosis of ovarian cancer: systematic review and meta-analysis of external validation studies

Objectives

To conduct a systematic review of studies externally validating the ADNEX (Assessment of Different Neoplasias in the adnexa) model for diagnosis of ovarian cancer and to present a meta-analysis of its performance.

Design

Systematic review and meta-analysis of external validation studies.

Data sources

Medline, Embase, Web of Science, Scopus, and Europe PMC, from 15 October 2014 to 15 May 2023.

Eligibility criteria for selecting studies

All external validation studies of the performance of ADNEX, with any study design and any study population of patients with an adnexal mass. Two independent reviewers extracted the data. Disagreements were resolved by discussion. Reporting quality of the studies was scored with the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) reporting guideline, and methodological conduct and risk of bias with PROBAST (Prediction model Risk Of Bias Assessment Tool). Random effects meta-analysis of the area under the receiver operating characteristic curve (AUC), sensitivity and specificity at the 10% risk of malignancy threshold, and net benefit and relative utility at the 10% risk of malignancy threshold were performed.

Results

47 studies (17 007 tumours) were included, with a median study sample size of 261 (range 24-4905). On average, 61% of TRIPOD items were reported. Handling of missing data, justification of sample size, and model calibration were rarely described. 91% of validations were at high risk of bias, mainly because of the unexplained exclusion of incomplete cases, small sample size, or no assessment of calibration. The summary AUC to distinguish benign from malignant tumours in patients who underwent surgery was 0.93 (95% confidence interval 0.92 to 0.94, 95% prediction interval 0.85 to 0.98) for ADNEX with the serum biomarker, cancer antigen 125 (CA125), as a predictor (9202 tumours, 43 centres, 18 countries, and 21 studies) and 0.93 (95% confidence interval 0.91 to 0.94, 95% prediction interval 0.85 to 0.98) for ADNEX without CA125 (6309 tumours, 31 centres, 13 countries, and 12 studies). The estimated probability that the model has use clinically in a new centre was 95% (with CA125) and 91% (without CA125). When restricting analysis to studies with a low risk of bias, summary AUC values were 0.93 (with CA125) and 0.91 (without CA125), and estimated probabilities that the model has use clinically were 89% (with CA125) and 87% (without CA125).

Conclusions

The results of the meta-analysis indicated that ADNEX performed well in distinguishing between benign and malignant tumours in populations from different countries and settings, regardless of whether the serum biomarker, CA125, was used as a predictor. A key limitation was that calibration was rarely assessed.

Systematic review registration

PROSPERO CRD42022373182.

Multiclass risk models for ovarian malignancy: an illustration of prediction uncertainty due to the choice of algorithm

BACKGROUND

Assessing malignancy risk is important to choose appropriate management of ovarian tumors. We compared six algorithms to estimate the probabilities that an ovarian tumor is benign, borderline malignant, stage I primary invasive, stage II-IV primary invasive, or secondary metastatic.

METHODS

This retrospective cohort study used 5909 patients recruited from 1999 to 2012 for model development, and 3199 patients recruited from 2012 to 2015 for model validation. Patients were recruited at oncology referral or general centers and underwent an ultrasound examination and surgery ≤ 120 days later. We developed models using standard multinomial logistic regression (MLR), Ridge MLR, random forest (RF), XGBoost, neural networks (NN), and support vector machines (SVM). We used nine clinical and ultrasound predictors but developed models with or without CA125.

RESULTS

Most tumors were benign (3980 in development and 1688 in validation data), secondary metastatic tumors were least common (246 and 172). The c-statistic (AUROC) to discriminate benign from any type of malignant tumor ranged from 0.89 to 0.92 for models with CA125, from 0.89 to 0.91 for models without. The multiclass c-statistic ranged from 0.41 (SVM) to 0.55 (XGBoost) for models with CA125, and from 0.42 (SVM) to 0.51 (standard MLR) for models without. Multiclass calibration was best for RF and XGBoost. Estimated probabilities for a benign tumor in the same patient often differed by more than 0.2 (20% points) depending on the model. Net Benefit for diagnosing malignancy was similar for algorithms at the commonly used 10% risk threshold, but was slightly higher for RF at higher thresholds. Comparing models, between 3% (XGBoost vs. NN, with CA125) and 30% (NN vs. SVM, without CA125) of patients fell on opposite sides of the 10% threshold.

CONCLUSION

Although several models had similarly good performance, individual probability estimates varied substantially.

Implementation of robot-assisted myomectomy in a large university hospital: a retrospective descriptive study

Background

Background: Myomectomy is often the preferred treatment for symptomatic patients with myomas who wish to preserve their fertility, with a shift from open surgery towards minimally invasive techniques.

Objectives

Retrospective study assessing patient and surgery characteristics, follow-up, and outcomes of robot-assisted myomectomy (RAM) and abdominal myomectomy (AM) in women treated between January 1, 2018, and February 28, 2022, in a Belgian tertiary care hospital.

Materials and Methods

A descriptive analysis was conducted on consecutive patients who underwent myomectomies. 2018 was considered the learning curve for RAM.

Main outcome measures

We assessed rate of open surgery, operation time, postoperative hospital stay, and operative complications.

Results

In total, 94 RAMs and 15 AMs were performed. The rate of AMs was 56.5% in 2018 versus 2.3% after the learning curve. The median operation time for RAM was 136.5 minutes and 131 minutes for AM. Conversion rate for RAM was 0%. The median postoperative hospital stay after RAM was 1 night and 4 nights for AM. Postoperative complication rate was low, with only 14.9% and 33.3% of patients requiring pharmacological treatment of complications after RAM or AM, respectively. No surgical re-intervention was needed in any group.

Conclusions

Implementation of RAM at our centre resulted in a significant reduction of open surgery rate. RAM demonstrated shorter hospital stays and a lower incidence of complications compared to AM.

What is new?

Our study highlights the successful adoption of RAM, showcasing its potential to replace AM even in complex cases. The findings affirm the safety and feasibility of RAM, supporting its use as a valuable technique for minimally invasive myomectomy.

Use of real-time qPCR to quantify members of the unculturable heterotrophic bacterial community in a deep sea marine sponge, Vetulina sp

In this report, real-time quantitative PCR (TaqMan qPCR) of the small subunit (SSU) 16S-like rRNA molecule, a universal phylogenetic marker, was used to quantify the relative abundance of individual bacterial members of a diverse, yet mostly unculturable, microbial community from a marine sponge. Molecular phylogenetic analyses of bacterial communities derived from Caribbean Lithistid sponges have shown a wide diversity of microbes that included at least six major subdivisions; however, very little overlap was observed between the culturable and unculturable microbial communities. Based on sequence data of three culture-independent Lithistid-derived representative bacteria, we designed probe/primer sets for TaqMan qPCR to quantitatively characterize selected microbial residents in a Lithistid sponge, Vetulina, metagenome. TaqMan assays included specificity testing, DNA limit of detection analysis, and quantification of specific microbial rRNA sequences such as Nitrospira-like microbes and Actinobacteria up to 172 million copies per microgram per Lithistid sponge metagenome. By contrast, qPCR amplification with probes designed for common previously cultured sponge-associated bacteria in the genera Rheinheimera and Marinomonas and a representative of the CFB group resulted in only minimal detection of the Rheiheimera in total DNA extracted from the sponge. These data verify that a large portion of the microbial community within Lithistid sponges may consist of currently unculturable microorganisms.