EQUSUM: Endometriosis QUality and grading instrument for SUrgical performance: proof of concept study for automatic digital registration and classification scoring for r-ASRM, EFI and Enzian

Gastrointestinal Myoelectrical Activity (GIMA) Biomarker for Noninvasive Diagnosis of Endometriosis

Background/Objectives: Endometriosis represents substantial direct and indirect healthcare costs impacted by an absence of uniformly accurate, non-invasive diagnostic tools. We endeavored to demonstrate gastrointestinal myoelectrical activity (GIMA) biomarkers, unique to endometriosis, will allow non-invasive, uniformly accurate diagnosis or exclusion of endometriosis. Methods: Prospective open-label comparative study of 154 patients, age ≥ 18, with or without diagnosed endometriosis. Population included 62 non-endometriosis controls (Cohort 1), 43 subjects with surgically/histologically confirmed endometriosis (Cohort 2), and 49 subjects with abdominal pain and negative imaging (Cohort 3). Non-invasive electroviscerography (EVG) recorded GIMA biomarkers from three abdominal electrodes before and 30 min post water load protocol. Cohort 2 had postoperative EVG and Cohort 3 had preoperative EVG. Calculated specificity, sensitivity, negative predictive value (NPV), positive predictive value (PPV), and predictive probability or C-statistic used univariate, multivariate, linear, and logistical regression analyses of the area under the curve (AUC) at all frequency and time points, including age and pain covariants. Results: The non-endometriosis cohort differed significantly from the endometriosis cohorts (p < 0.001) for median (IQR) and AUC percent frequency distribution of power at baseline, 10 min, 20 min, and 30 min post water load at all frequency ranges: 15-20 cpm, 30-40 cpm, and 40-50 cpm. The endometriosis cohorts were statistically similar (p > 0.05). GIMA biomarker threshold scoring demonstrated 95%/91% sensitivity and PPV, 96%/95% specificity and NPV, and a C-statistic of >99%/98%, respectively, for age subsets. GIMA biomarkers in Cohort 3 predicted 47/49 subjects positive and 2/49 negative for endometriosis, confirmed surgically. Hormonal therapy, surgical stage, nor pain score affected diagnostic accuracy. Conclusions: EVG with GIMA biomarker detection distinguished participants with and without endometriosis based upon endometriosis-specific GIMA biomarkers threshold scoring.

Discoid excision for colorectal endometriosis associated infertility: A balance between fertility outcomes and complication rates

OBJECTIVE

The objective of our study was to study the impact of discoid excision for deep endometriosis (DE) with colorectal involvement on fertility outcomes.

METHODS

49 patients with a desire for pregnancy treated with discoid excision for colorectal endometriosis in our endometriosis expert center between January 2015 and August 2020 were selected from our prospectively maintained database. Indications for surgery were either infertility and / or pelvic pain. Postoperative complications were graded according to the Clavien-Dindo classification. Fertility outcomes, both spontaneous and post-ART pregnancies, were analyzed.

RESULTS

Among the 49 patients who underwent discoid excision exclusively (no other digestive resection) with a desire to conceive, 25 had a pregnancy after surgery and 24 did not. Double discoid excision was performed in 6.1 % of the cases (3/49). A colpectomy was performed in 12.2 % of the patients (6/49), and a protective stoma in 12.2 % (6/49). Fenestration of endometriomas was performed in 28.6 % of the patients (14/49), and parametrectomy in 40.8 % (20/49). The postoperative complication rate was 24.5 % (12/49) including 10.2 % (5/49) grade I, 12.2 % (6/49) grade II, and 2 % (1/49) grade III. Prior to surgery, 28 (57.1 %) patients had infertility including 13 (52 %) that successfully conceived following surgery and 15 (62.5 %) that remain infertile. Spontaneous pregnancy was achieved in 60 % (15/25) of infertile patients' prior surgery. The live-birth rate in patients conceiving spontaneously was 75 % (12/16).

CONCLUSION

Our results support that discoid excision is safe and associated with good fertility outcomes. Whether first-line surgery using discoid excision is superior to first-line ART remains to be determined.

Validation of a Salivary miRNA Signature of Endometriosis - Interim Data

BACKGROUND: The discovery of a saliva-based micro–ribonucleic acid (miRNA) signature for endometriosis in 2022 opened up new perspectives for early and noninvasive diagnosis of the disease. The 109-miRNA saliva signature is the product of miRNA biomarkers and artificial intelligence (AI) modeling. We designed a multicenter study to provide external validation of its diagnostic accuracy. We present here an interim analysis. METHODS: The first 200 patients included in the multicenter prospective ENDOmiRNA Saliva Test study (NCT05244668) were included for interim analysis. The study population comprised women from 18 to 43 years of age with a formal diagnosis of endometriosis or with suspected endometriosis. Epidemiologic, clinical, and saliva sequencing data were collected between November 2021 and March 2022. Genomewide miRNA expression profiling by small RNA sequencing using next-generation sequencing (NGS) was performed, and a random forest algorithm was used to assess the diagnostic accuracy. RESULTS: In this interim analysis of the external validation cohort, with a population prevalence of 79.5%, the 109-miRNA saliva diagnostic signature for endometriosis had a sensitivity of 96.2% (95% confidence interval [CI], 93.7 to 97.3%), specificity of 95.1% (95% CI, 85.2 to 99.1%), positive predictive value of 95.1% (95% CI, 85.2 to 99.1%), negative predictive value of 86.7% (95% CI, 77.6 to 90.3%), positive likelihood ratio of 19.7 (95% CI, 6.3 to 108.8), negative likelihood ratio of 0.04 (95% CI, 0.03 to 0.07), and area under the receiver operating characteristic curve of 0.96 (95% CI, 0.92 to 0.98). CONCLUSIONS: The use of NGS and AI in the sequencing and analysis of miRNA provided a saliva-based miRNA signature for endometriosis. Our interim analysis of a prospective multicenter external validation study provides support for its ongoing investigation as a diagnostic tool. (Funded by Ziwig and the Conseil Régional d’Ile de France [Grant EX024087]; ClinicalTrials.gov number, NCT05244668.)

Clavien-Dindo, comprehensive complication index and classification of intraoperative adverse events: a uniform and holistic approach in adverse event registration for (deep) endometriosis surgery

STUDY QUESTION

What is the additional value of the comprehensive complication index (CCI) and ClassIntra system (classification for intraoperative adverse events (ioAEs)) in adverse event (AE) reporting in (deep) endometriosis (DE) surgery compared to only using the Clavien-Dindo (CD) system?

SUMMARY ANSWER

The CCI and ClassIntra are useful additional tools alongside the CD system for a complete and uniform overview of the total AE burden in patients with extensive surgery (such as DE), and with this uniform data registration, it is possible to provide greater insight into the quality of care.

WHAT IS KNOWN ALREADY

Uniform comparison of AEs reported in the literature is hampered by scattered registration. In endometriosis surgery, the usage of the CD complication system and the CCI is internationally recommended; however, the CCI is not routinely adapted in endometriosis care and research. Furthermore, a recommendation for ioAEs registration in endometriosis surgery is lacking, although this is vital information in surgical quality assessments.

STUDY DESIGN SIZE DURATION

A prospective mono-center study was conducted with 870 surgical DE cases from a non-university DE expertise center between February 2019 and December 2021.

PARTICIPANTS/MATERIALS SETTING METHODS

Endometriosis cases were collected with the EQUSUM system, a publicly available web-based application for registration of surgical procedures for endometriosis. Postoperative adverse events (poAEs) were classified with the CD complication system and CCI. Differences in reporting and classifying AEs between the CCI and the CD were assessed. ioAEs were assessed with the ClassIntra. The primary outcome measure was to assess the additional value toward the CD classification with the introduction of the CCI and ClassIntra. In addition, we report a benchmark for the CCI in DE surgery.

MAIN RESULTS AND THE ROLE OF CHANCE

A total of 870 DE procedures were registered, of which 145 procedures with one or more poAEs, resulting in a poAE rate of 16.7% (145/870), of which in 36 cases (4.1%), the poAE was classified as severe (≥Grade 3b). The median CCI (interquartile range) of patients with poAEs was 20.9 (20.9-31.7) and 33.7 (33.7-39.7) in the group of patients with severe poAEs. In 20 patients (13.8%), the CCI was higher than the CD because of multiple poAEs. There were 11 ioAEs reported (11/870, 1.3%) in all procedures, mostly minor and directly repaired serosa injuries.

LIMITATIONS REASONS FOR CAUTION

This study was conducted at a single center; thus, trends in AE rates and type of AEs could differ from other centers. Furthermore, no conclusion could be drawn on ioAEs in relation to the postoperative course because the power of this database is not robust enough for that purpose.

WIDER IMPLICATIONS OF THE FINDINGS

From our data, we would advise to use the Clavien-Dindo classification system together with the CCI and ClassIntra for a complete overview of AE registration. The CCI appeared to provide a more complete overview of the total burden of poAEs compared to only reporting the most severe poAEs (as with CD). If the use of the CD, CCI, and ClassIntra is widely adapted, uniform data comparison will be possible at (inter)national level, providing better insight into the quality of care. Our data could be used as a first benchmark for other DE centers to optimize information provision in the shared decision-making process.

STUDY FUNDING/COMPETING INTERESTS

No funding was received for this study. The authors have no conflicts of interest to declare.

TRIAL REGISTRATION NUMBER

N/A.

Endometriosis-associated infertility diagnosis based on saliva microRNA signatures

RESEARCH QUESTION

Can a saliva-based miRNA signature for endometriosis-associated infertility be designed and validated by analysing the human miRNome?

DESIGN

The prospective ENDOmiARN study (NCT04728152) included 200 saliva samples obtained between January 2021 and June 2021 from women with pelvic pain suggestive of endometriosis. All patients underwent either laparoscopy, magnetic resonance imaging, or both. Patients diagnosed with endometriosis were allocated to one of two groups according to their fertility status. Data analysis consisted of identifying a set of miRNA biomarkers using next-generation sequencing, and development of a saliva-based miRNA signature of infertility among patients with endometriosis based on a random forest model.

RESULTS

Among the 153 patients diagnosed with endometriosis, 24% (n = 36) were infertile and 76% (n = 117) were fertile. Small RNA-sequencing of the 153 saliva samples yielded approximately 3712 M raw sequencing reads (from ∼13.7 M to ∼39.3 M reads/sample). Of the 2561 known miRNAs, the feature selection method generated a signature of 34 miRNAs linked to endometriosis-associated infertility. After validation, the most accurate signature model had a sensitivity, specificity and area under the curve of 100%.

CONCLUSION

A saliva-based miRNA signature for endometriosis-associated infertility is reported. Although the results still require external validation before using the signature in routine practice, this non-invasive tool is likely to have a major effect on care provided to women with endometriosis.

MicroRNome analysis generates a blood-based signature for endometriosis

Endometriosis, characterized by endometrial-like tissue outside the uterus, is thought to affect 2–10% of women of reproductive age: representing about 190 million women worldwide. Numerous studies have evaluated the diagnostic value of blood biomarkers but with disappointing results. Thus, the gold standard for diagnosing endometriosis remains laparoscopy. We performed a prospective trial, the ENDO-miRNA study, using both Artificial Intelligence (AI) and Machine Learning (ML), to analyze the current human miRNome to differentiate between patients with and without endometriosis, and to develop a blood-based microRNA (miRNA) diagnostic signature for endometriosis. Here, we present the first blood-based diagnostic signature obtained from a combination of two robust and disruptive technologies merging the intrinsic quality of miRNAs to condense the endometriosis phenotype (and its heterogeneity) with the modeling power of AI. The most accurate signature provides a sensitivity, specificity, and Area Under the Curve (AUC) of 96.8%, 100%, and 98.4%, respectively, and is sufficiently robust and reproducible to replace the gold standard of diagnostic surgery. Such a diagnostic approach for this debilitating disorder could impact recommendations from national and international learned societies.

Salivary MicroRNA Signature for Diagnosis of Endometriosis

BACKGROUND

Endometriosis diagnosis constitutes a considerable economic burden for the healthcare system with diagnostic tools often inconclusive with insufficient accuracy. We sought to analyze the human miRNAome to define a saliva-based diagnostic miRNA signature for endometriosis.

METHODS

We performed a prospective ENDO-miRNA study involving 200 saliva samples obtained from 200 women with chronic pelvic pain suggestive of endometriosis collected between January and June 2021. The study consisted of two parts: (i) identification of a biomarker based on genome-wide miRNA expression profiling by small RNA sequencing using next-generation sequencing (NGS) and (ii) development of a saliva-based miRNA diagnostic signature according to expression and accuracy profiling using a Random Forest algorithm.

RESULTS

Among the 200 patients, 76.5% (n = 153) were diagnosed with endometriosis and 23.5% (n = 47) without (controls). Small RNA-seq of 200 saliva samples yielded ~4642 M raw sequencing reads (from ~13.7 M to ~39.3 M reads/sample). Quantification of the filtered reads and identification of known miRNAs yielded ~190 M sequences that were mapped to 2561 known miRNAs. Of the 2561 known miRNAs, the feature selection with Random Forest algorithm generated after internally cross validation a saliva signature of endometriosis composed of 109 miRNAs. The respective sensitivity, specificity, and AUC for the diagnostic miRNA signature were 96.7%, 100%, and 98.3%.

CONCLUSIONS

The ENDO-miRNA study is the first prospective study to report a saliva-based diagnostic miRNA signature for endometriosis. This could contribute to improving early diagnosis by means of a non-invasive tool easily available in any healthcare system.

Structured report for dynamic ultrasonography in patients with suspected or known endometriosis: Recommendations of the International Society for Gynecologic Endoscopy (ISGE)

OBJECTIVE

The International Society for Gynecologic Endoscopy (ISGE) developed this project to establish the recommendations for structured reporting of dynamic ultrasound findings, promoting on this manner the practice of standardized, comprehensive and systematic evaluation and reporting of endometriosis in pelvic structures, in correlation with the #Enzian classification.

STUDY DESIGN

A non-systematic review was done through a search on the following databases: MEDLINE, EMBASE, Global Health, The Cochrane Library (Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Cochrane Methodology Register), Health Technology Assessment Database and Web of Science, using the medical subject heading (MeSH) term "endometriosis" (MeSH Unique ID: D004715) in combination with "diagnostic imaging" (MeSH Unique ID Q000000981) and "consensus" (MeSH Unique ID D032921). The information extracted from the articles of interest, written in English and published from inception of the above-mentioned databases until May 2021, was graded by the level of evidence using the American College of Chest Physicians (ACCP) classification system. The recommendations for a structured reporting of ultrasound findings were developed through multiple cycles of literature analysis and expert discussion following the Delphi method.

RESULTS

The ISGE recommends the adoption of the terms, definitions and methods proposed by the International Deep Endometriosis Analysis (IDEA) Group for ultrasound assessment of patients with suspected or known endometriosis (grade 1C), since this is the most comprehensive and systematic concept currently available. This paper provides the ISGE structured reporting template for presenting quantitative and qualitative information upon the IDEA consensus-based sonographic assessment of the uterus, adnexa, anterior and posterior compartment. The #Enzian classification is recommended to summarize the findings in a standard fashion (grade 1B).

CONCLUSION

Mapping of pelvic endometriosis by ultrasound is accurate when trained sonographers perform the technique. Structured reporting of the lesions may improve patient counseling and treatment planning, including the organization of multidisciplinary teams and the selection of the most appropriate medical or surgical therapeutic strategy.