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      Blood biomarkers for the non-invasive diagnosis of endometriosis

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          Abstract

          About 10% of reproductive‐aged women suffer from endometriosis, a costly chronic disease causing pelvic pain and subfertility. Laparoscopy is the gold standard diagnostic test for endometriosis, but is expensive and carries surgical risks. Currently, there are no non‐invasive or minimally invasive tests available in clinical practice to accurately diagnose endometriosis. Although other reviews have assessed the ability of blood tests to diagnose endometriosis, this is the first review to use Cochrane methods, providing an update on the rapidly expanding literature in this field. To evaluate blood biomarkers as replacement tests for diagnostic surgery and as triage tests to inform decisions on surgery for endometriosis. Specific objectives include: 1. To provide summary estimates of the diagnostic accuracy of blood biomarkers for the diagnosis of peritoneal, ovarian and deep infiltrating pelvic endometriosis, compared to surgical diagnosis as a reference standard. 2. To assess the diagnostic utility of biomarkers that could differentiate ovarian endometrioma from other ovarian masses. We did not restrict the searches to particular study designs, language or publication dates. We searched CENTRAL to July 2015, MEDLINE and EMBASE to May 2015, as well as these databases to 20 April 2015: CINAHL, PsycINFO, Web of Science, LILACS, OAIster, TRIP, ClinicalTrials.gov, DARE and PubMed. We considered published, peer‐reviewed, randomised controlled or cross‐sectional studies of any size, including prospectively collected samples from any population of reproductive‐aged women suspected of having one or more of the following target conditions: ovarian, peritoneal or deep infiltrating endometriosis (DIE). We included studies comparing the diagnostic test accuracy of one or more blood biomarkers with the findings of surgical visualisation of endometriotic lesions. Two authors independently collected and performed a quality assessment of data from each study. For each diagnostic test, we classified the data as positive or negative for the surgical detection of endometriosis, and we calculated sensitivity and specificity estimates. We used the bivariate model to obtain pooled estimates of sensitivity and specificity whenever sufficient datasets were available. The predetermined criteria for a clinically useful blood test to replace diagnostic surgery were a sensitivity of 0.94 and a specificity of 0.79 to detect endometriosis. We set the criteria for triage tests at a sensitivity of ≥ 0.95 and a specificity of ≥ 0.50, which 'rules out' the diagnosis with high accuracy if there is a negative test result (SnOUT test), or a sensitivity of ≥ 0.50 and a specificity of ≥ 0.95, which 'rules in' the diagnosis with high accuracy if there is a positive result (SpIN test). We included 141 studies that involved 15,141 participants and evaluated 122 blood biomarkers. All the studies were of poor methodological quality. Studies evaluated the blood biomarkers either in a specific phase of the menstrual cycle or irrespective of the cycle phase, and they tested for them in serum, plasma or whole blood. Included women were a selected population with a high frequency of endometriosis (10% to 85%), in which surgery was indicated for endometriosis, infertility work‐up or ovarian mass. Seventy studies evaluated the diagnostic performance of 47 blood biomarkers for endometriosis (44 single‐marker tests and 30 combined tests of two to six blood biomarkers). These were angiogenesis/growth factors, apoptosis markers, cell adhesion molecules, high‐throughput markers, hormonal markers, immune system/inflammatory markers, oxidative stress markers, microRNAs, tumour markers and other proteins. Most of these biomarkers were assessed in small individual studies, often using different cut‐off thresholds, and we could only perform meta‐analyses on the data sets for anti‐endometrial antibodies, interleukin‐6 (IL‐6), cancer antigen‐19.9 (CA‐19.9) and CA‐125. Diagnostic estimates varied significantly between studies for each of these biomarkers, and CA‐125 was the only marker with sufficient data to reliably assess sources of heterogeneity. The mean sensitivities and specificities of anti‐endometrial antibodies (4 studies, 759 women) were 0.81 (95% confidence interval (CI) 0.76 to 0.87) and 0.75 (95% CI 0.46 to 1.00). For IL‐6, with a cut‐off value of > 1.90 to 2.00 pg/ml (3 studies, 309 women), sensitivity was 0.63 (95% CI 0.52 to 0.75) and specificity was 0.69 (95% CI 0.57 to 0.82). For CA‐19.9, with a cut‐off value of > 37.0 IU/ml (3 studies, 330 women), sensitivity was 0.36 (95% CI 0.26 to 0.45) and specificity was 0.87 (95% CI 0.75 to 0.99). Studies assessed CA‐125 at different thresholds, demonstrating the following mean sensitivities and specificities: for cut‐off > 10.0 to 14.7 U/ml: 0.70 (95% CI 0.63 to 0.77) and 0.64 (95% CI 0.47 to 0.82); for cut‐off > 16.0 to 17.6 U/ml: 0.56 (95% CI 0.24, 0.88) and 0.91 (95% CI 0.75, 1.00); for cut‐off > 20.0 U/ml: 0.67 (95% CI 0.50 to 0.85) and 0.69 (95% CI 0.58 to 0.80); for cut‐off > 25.0 to 26.0 U/ml: 0.73 (95% CI 0.67 to 0.79) and 0.70 (95% CI 0.63 to 0.77); for cut‐off > 30.0 to 33.0 U/ml: 0.62 (95% CI 0.45 to 0.79) and 0.76 (95% CI 0.53 to 1.00); and for cut‐off > 35.0 to 36.0 U/ml: 0.40 (95% CI 0.32 to 0.49) and 0.91 (95% CI 0.88 to 0.94). We could not statistically evaluate other biomarkers meaningfully, including biomarkers that were assessed for their ability to differentiate endometrioma from other benign ovarian cysts. Eighty‐two studies evaluated 97 biomarkers that did not differentiate women with endometriosis from disease‐free controls. Of these, 22 biomarkers demonstrated conflicting results, with some studies showing differential expression and others no evidence of a difference between the endometriosis and control groups. Of the biomarkers that were subjected to meta‐analysis, none consistently met the criteria for a replacement or triage diagnostic test. A subset of blood biomarkers could prove useful either for detecting pelvic endometriosis or for differentiating ovarian endometrioma from other benign ovarian masses, but there was insufficient evidence to draw meaningful conclusions. Overall, none of the biomarkers displayed enough accuracy to be used clinically outside a research setting. We also identified blood biomarkers that demonstrated no diagnostic value in endometriosis and recommend focusing research resources on evaluating other more clinically useful biomarkers. Blood biomarkers for the non‐invasive diagnosis of endometriosis Review Question How accurate are blood tests in detecting endometriosis? Can any blood test be accurate enough to replace or reduce the need for surgery in the diagnosis of endometriosis? Background Women with endometriosis have endometrial tissue (the tissue that lines the womb and is shed during menstruation) growing outside the womb within the pelvic cavity. This tissue responds to reproductive hormones, causing painful periods, chronic lower abdominal pain and difficulty conceiving. Currently, the only reliable way of diagnosing endometriosis is to perform keyhole surgery and visualise the endometrial deposits inside the abdomen. Because surgery is risky and expensive, we evaluated whether the results of blood tests (blood biomarkers) can help to detect endometriosis non‐invasively. An accurate blood test could lead to the diagnosis of endometriosis without the need for surgery, or it could reduce the need for diagnostic surgery to a group of women who were most likely to have endometriosis. Separate Cochrane reviews from this series evaluate other non‐invasive ways of diagnosing endometriosis using urine, imaging, endometrial and combination tests. Study characteristics The evidence included in this review is current to July 2015. We included 141 studies involving 15,141 participants. All studies evaluated reproductive‐aged women who were undertaking diagnostic surgery because they were suspected of having one or more of the following target conditions: ovarian, peritoneal or deep infiltrating endometriosis (DIE). Cancer antigen‐125 (CA‐125) was the most common blood biomarker studied. Seventy studies evaluated 47 blood biomarkers that were expressed differently in women with and without endometriosis, and 82 studies identified 97 biomarkers that did not distinguish between the two groups. Twenty‐two biomarkers were in both categories. Key results Only four of the assessed biomarkers (anti‐endometrial Abs (anti‐endometrial autoantibodies), interleukin‐6 (IL‐6), CA‐19.9 and CA‐125) were evaluated by enough studies to provide a meaningful assessment of test accuracy. None of these tests was accurate enough to replace diagnostic surgery. Several studies identified biomarkers that might be of value in diagnosing endometriosis, but there are too few reports to be sure of their diagnostic benefit. Overall, there is not enough evidence to recommend testing for any blood biomarker in clinical practice to diagnose endometriosis. Quality of the evidence Generally, the reports were of low methodological quality, and most blood tests were only assessed by a single or a small number of studies. When the same biomarker was studied, there were significant differences in how studies were conducted, the group of women studied and the cut‐offs used to determine a positive result. Future research More high quality research trials are necessary to accurately assess the diagnostic potential of certain blood biomarkers, whose diagnostic value for endometriosis was suggested by a limited number of studies.

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          Most cited references 337

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          QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies.

          In 2003, the QUADAS tool for systematic reviews of diagnostic accuracy studies was developed. Experience, anecdotal reports, and feedback suggested areas for improvement; therefore, QUADAS-2 was developed. This tool comprises 4 domains: patient selection, index test, reference standard, and flow and timing. Each domain is assessed in terms of risk of bias, and the first 3 domains are also assessed in terms of concerns regarding applicability. Signalling questions are included to help judge risk of bias. The QUADAS-2 tool is applied in 4 phases: summarize the review question, tailor the tool and produce review-specific guidance, construct a flow diagram for the primary study, and judge bias and applicability. This tool will allow for more transparent rating of bias and applicability of primary diagnostic accuracy studies.
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            Case-control and two-gate designs in diagnostic accuracy studies.

            In some diagnostic accuracy studies, the test results of a series of patients with an established diagnosis are compared with those of a control group. Such case-control designs are intuitively appealing, but they have also been criticized for leading to inflated estimates of accuracy. We discuss similarities and differences between diagnostic and etiologic case-control studies, as well as the mechanisms that can lead to variation in estimates of diagnostic accuracy in studies with separate sampling schemes ("gates") for diseased (cases) and nondiseased individuals (controls). Diagnostic accuracy studies are cross-sectional and descriptive in nature. Etiologic case-control studies aim to quantify the effect of potential causal exposures on disease occurrence, which inherently involves a time window between exposure and disease occurrence. Researchers and readers should be aware of spectrum effects in diagnostic case-control studies as a result of the restricted sampling of cases and/or controls, which can lead to changes in estimates of diagnostic accuracy. These spectrum effects may be advantageous in the early investigation of a new diagnostic test, but for an overall evaluation of the clinical performance of a test, case-control studies should closely mimic cross-sectional diagnostic studies. As the accuracy of a test is likely to vary across subgroups of patients, researchers and clinicians might carefully consider the potential for spectrum effects in all designs and analyses, particularly in diagnostic accuracy studies with differential sampling schemes for diseased (cases) and nondiseased individuals (controls).
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              Endometriosis: epidemiology and aetiological factors.

              Estimates of the frequency of endometriosis vary widely. Based on the few reliable data, the prevalence of the condition can reasonably be assumed to be around 10%. Although no consistent information is available on the incidence of the disease, temporal trends suggest an increase among women of reproductive age. This could be explained-at least in part-by changing reproductive habits. Numerous epidemiological studies have indicated that nulliparous women and women reporting short and heavy menstrual cycles are at increased risk of developing endometriosis; data on other risk factors are less consistent. These epidemiological findings strongly support the menstrual reflux hypothesis. Additional evidence in favour of this theory includes the demonstration of viable endometrial cells in the menstrual effluent and peritoneal fluid, experimental implantation and growth of endometrium within the peritoneal cavity, observation of some degree of retrograde menstruation in most women undergoing laparoscopy during menses, and an association between obstructed menstrual outflow and endometriosis.
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                Author and article information

                Journal
                146518
                Cochrane Database of Systematic Reviews
                Wiley
                14651858
                May 01 2016
                Affiliations
                [1 ]The University of Adelaide; Discipline of Obstetrics and Gynaecology, School of Medicine, Robinson Research Institute; Level 6, Medical School North, Frome Rd Adelaide SA Australia 5005
                [2 ]Academic Medical Center, University of Amsterdam; Department of Clinical Epidemiology, Biostatistics and Bioinformatics; Room J1b-217, PO Box 22700 Amsterdam Netherlands 1100 DE
                [3 ]IVF Australia; Westmead Fertility Clinic; Level 2 20-22 Mons Road, Westmead Sydney Victoria Australia 2145
                [4 ]University of Auckland; Department of Obstetrics and Gynaecology; FMHS Park Road Grafton Auckland New Zealand 1003
                [5 ]University of Groningen; Wenckebachlaan 53 Groningen Groningen Netherlands 9728 JL
                Article
                10.1002/14651858.CD012179
                7076288
                27132058
                © 2016
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