Urinary biomarkers for the non-invasive diagnosis of endometriosis

Endometriosis

Endometriosis is defined as an inflammatory condition characterised by endometrial-like tissue at sites outside the uterus (Johnson and Hummelshoj 2013). Endometriotic lesions can occur at different locations, including the pelvic peritoneum and the ovary; or they can penetrate pelvic structures below the surface of peritoneum (defined as deeply infiltrating endometriosis (DIE)). Each of these types of endometriosis are thought to represent a separate clinical entity, but can coexist in the same woman. Rarely, endometriotic implants can be found at more distant sites, including lung, liver, pancreas and operative scars, with consequent variations in presenting symptoms.

Endometriosis afflicts 10% of reproductive-aged women causing dysmenorrhoea (painful periods), dyspareunia (painful intercourse), chronic pelvic pain and infertility (Vigano 2004). The clinical presentation can vary from asymptomatic and unexplained infertility to severe dysmenorrhoea and chronic pain. These symptoms can occur with bowel or urinary symptoms, an abnormal pelvic examination or the presence of a pelvic mass, however no symptom is specific to endometriosis. The prevalence of endometriosis in symptomatic population is reported as 35-50% (Giudice 2004).

Women with endometriosis are also at increased risk of developing several cancers (Somigliana 2006) and autoimmune disorders (Sinaii 2002). The presence of disease is associated with changes in the immune response, vascularisation, neural function, the peritoneal environment and the eutopic endometrium, suggesting that endometriosis is a systemic, rather than localized, condition (Giudice 2004). Endometriosis has a profound effect on psychological and social well being and imposes a substantial economic burden on society. Women with endometriosis incur significant direct medical costs from diagnostic and therapeutic surgeries, hospital admissions and fertility treatments, however these costs are superseded by the indirect costs of endometriosis including absenteeism and loss of productivity (Gao 2006; Simoens 2012). In the USA, the financial burden of endometriosis is estimated at USD 12,419 per woman (Simoens 2012).

Although the pathogenesis of endometriosis has not been fully elucidated, it is commonly thought that endometriosis occurs when endometrial tissue contained within the menstrual fluid flows back through the fallopian tubes and implants at an ectopic site within the pelvic cavity (Sampson 1927). However, this theory does not explain the fact that although retrograde menstruation is seen in up to 90% of women only 10% of women develop endometriosis (Halme 1984). There is evidence that a variety of environmental, immunological and hormonal factors are associated with endometriosis (Vigano 2004); and genetic loci that confer a risk of endometriosis have been identified (Nyholt 2012). The relative contribution of these and other causal factors needs further elucidation.

Although it is impossible to time the onset of disease, on average women have a 6- to 12-year history of symptoms before obtaining a surgical diagnosis of endometriosis, indicative of considerable diagnostic delay (Matsuzaki 2006). Untreated endometriosis is associated with reduced quality of life and contributes to outcomes such as depression, inability to work, sexual dysfunction and missed opportunity for motherhood (Gao 2006).

Treatment of endometriosis

There is no cure for endometriosis. Treatment options include expectant management, pharmacological (hormonal) therapy and surgery (Johnson and Hummelshoj 2013). Treatment is individualised, taking into consideration the therapeutic goal (pain relief or subfertility) and the location of the disease. Current pharmacological therapies such as the combined oral contraceptive pill, progestogens, weak androgens and GnRH agonists and antagonists act to reduce the effect of oestrogen on endometrial tissues and suppress menstruation. These drugs can ameliorate the symptoms of dysmenorrhoea and chronic pelvic pain, but are associated with side effects such as breast discomfort, irritability, androgenic symptoms and bone loss. Surgical excision of endometriotic lesions can reduce pain symptoms; however it is associated with high recurrence rates of 40% to 50% at 5 years post-surgery (Guo 2009). Early treatment of endometriosis improves pain levels and physical and psychological functioning. Furthermore, improvements in menstrual management (the use of the Mirena coil and the continuous use of the combined contraceptive pill) and fertility preservation (oocyte vitrification) raise the possibility of suppressing the progression of endometriosis and prospectively managing subfertility in endometriosis sufferers. The potential success of these preventative strategies is dependent on an accurate and early diagnosis. A major impediment to earlier and more efficacious treatment of this disease is diagnostic delay due to the invasive nature of standard diagnostic tests (Dmowski 1997).

Diagnosis of endometriosis

Clinical history and pelvic examination can raise the possibility of a diagnosis of endometriosis, but the heterogeneity in clinical presentation, the high prevalence of asymptomatic endometriosis (2% to 50%) and the poor association between presenting symptoms and severity of the disease mean that a reliable diagnosis of endometriosis based solely on presenting symptoms is difficult to obtain (Spaczynski 2003; Fauconnier 2005; Ballard 2008). Although an abnormal pelvic examination correlates with the presence of endometriosis on laparoscopy in 70% to 90% of cases (Ling 1999), there is a wide differential diagnosis for most positive physical findings. Furthermore, a normal clinical examination does not exclude endometriosis, as laparoscopically proven disease has been diagnosed in more than 50% women with a clinically normal pelvic examination (Eskenazi 2001). A variety of tests utilising pelvic imaging, blood markers, eutopic endometrium characteristics, urinary markers or peritoneal fluid components have been suggested as diagnostic measures for endometriosis. Although large numbers of the reported markers distinguish women with and without endometriosis in small pilot studies, many do not show convincing potential as a diagnostic test when they are evaluated in larger studies by different research groups. The diagnostic value of these tests has not previously been fully systematically evaluated and summarised using Cochrane methodologies. Currently, there is no simple non-invasive test for the diagnosis of endometriosis that is routinely implemented in clinical practice.

Surgical diagnostic procedures for endometriosis include laparoscopy (minimal access surgery) or laparotomy (open surgery via an abdominal incision). In the last several decades, laparoscopy has become an increasingly common procedure and has largely replaced traditional open surgery in women suspected of having endometriosis (Yeung 2009). Laparoscopy has significant advantages over laparotomy, creating fewer complications and shorter recovery times. Furthermore a magnified view at laparoscopy allows better visualisation of the peritoneal cavity. Despite continuing controversy in the literature with regard to the superiority of one surgical modality over another in treating pelvic pathology, laparoscopy is the preferred technique to evaluate the pelvis and abdomen and to treat benign conditions such as ovarian endometriomas (Medeiros 2009). Surgery is currently also the only accepted way to determine the extent and severity of endometriosis. Several classification systems have been suggested for endometriosis (Batt 2003; Chapron 2003a; Martin 2006; Adamson 2008), but most researchers and clinicians use the revised American Society for Reproductive Medicine (rASRM) classification, which is internationally accepted as a respected, currently available tool for the objective assessment of the disease (American Society for Reproductive Medicine 1997). The rASRM classification system considers appearance, size and depth of peritoneal or ovarian implants and adhesions visualised during laparoscopy (Table 1) and allows uniform documentation of the extent of disease. Unfortunately this classification system has little value in clinical practice due to the lack of correlation between laparoscopic staging, the severity of symptoms and response to treatment (Vercellini 1996; Guzick 1997; Chapron 2003b).

The European Society of Human Reproduction and Embryology (ESHRE) Special Interest Group for Endometriosis stated in their guidelines for the diagnosis and treatment of endometriosis that for women presenting with symptoms suggestive of endometriosis, a definitive diagnosis of most forms of endometriosis requires visual inspection of the pelvis at laparoscopy as the 'gold standard' investigation (Kennedy 2005). Currently the visual identification of endometriotic tissue in the pelvic cavity during surgery with or without histological confirmation is not just the best available but the only diagnostic test for endometriosis that is used routinely in clinical practice.

The disadvantages of laparoscopic surgery include and are not limited to the high cost, the need for general anaesthesia and the potential for adhesion formation post procedure. Laparoscopy has been associated with a 2% risk of injury to pelvic organs, a 0.001% risk of damaging a major blood vessel and a mortality rate of 0.0001% (Chapron 2003c). Only one third of women who undertake a laparoscopic procedure will receive a diagnosis of endometriosis; therefore many disease-free women are unnecessarily exposed to surgical risk (Frishman 2006).

The validity of laparoscopy as a reference test for endometriosis has been assessed as being highly dependent on the skills of the surgeon. The diagnostic accuracy of laparoscopic visualisation has been compared with histological confirmation in a sole systematic review and is estimated as having a 94% sensitivity and 79% specificity (Wykes 2004). Subsequent studies suggested that incorporation of histological verification in the diagnosis of endometriosis may improve diagnostic accuracy (Marchino 2005; Almeida Filho 2008; Stegmann 2008) but these papers have not been systematically reviewed. The clinical significance of histological verification remains debatable, and a diagnosis based on visual findings can be considered reliable with an accurate inspection of the abdominal cavity by properly trained, experienced surgeons (Redwine 2003). Furthermore, excised potential endometriotic tissues are rarely serially sectioned in clinical practice and small lesions can be missed by pathologists in mild disease. Thus sampling inconsistencies are also likely to influence the accuracy of histological reporting.

Summary

A diagnostic test without the need for surgery would reduce surgical risks, increase accessibility to a diagnostic test and improve treatment outcomes.  A need for an accurate and non-invasive diagnostic test for endometriosis continues to encourage extensive research in the field and was endorsed at the international consensus workshop at the 10th World Congress of Endometriosis in 2008 (Rogers 2009). Although multiple markers and imaging techniques have been explored as diagnostic tests for endometriosis, none of them have been implemented routinely in clinical practice and most of them have not been subject to systematic review.

Prior test(s)

Most women presenting with symptoms suggestive of endometriosis have a full history and examination and a routine gynaecological ultrasound before a decision is made to have diagnostic surgery. However there is no consensus on whether or not ultrasound or any other test should be routinely used as part of a standardised approach.

Role of index test(s)

A new diagnostic test can fulfil one of three roles:

1. Replacement: replacing an existing test by having more accuracy, or a similar accuracy with other advantages.

2. Triage: used as an initial step in a diagnostic pathway to identify the group of individuals who need further testing with an existing test. Although ideally a triage test has a high sensitivity and specificity, it may have a lower sensitivity but higher specificity than the current test or vice versa. The triage test does not aim to improve the diagnostic accuracy of the existing test but rather to reduce the number of individuals having an unnecessary diagnostic test.

3. Add-on: used in addition to existing testing to improve diagnostic performance (Bossuyt 2008).

Ideally a diagnostic test is expected to correctly identify all individuals with a disease and to exclude all those without that disease, in other words it should have a sensitivity and specificity of 100%. A high sensitivity indicates that there are a low number of people who have a negative test and do have the disease (i.e. a low number of false-negative results). High specificity corresponds to a low number of people who have a positive test but do not have the disease (i.e. low false-positive results). In practice, however, it is extremely rare to find a test with equally high sensitivity and specificity. An acceptable replacement test would need to have a similar or higher sensitivity and specificity than the current gold standard of laparoscopy. The only systematic review that determines the accuracy of laparoscopy in diagnosing endometriosis reported a sensitivity of 94%, and a specificity of 79% and we have taken this as a cut off for a replacement test (Wykes 2004).

The purpose of triage tests can vary depending on the clinical context and individuals’ priorities. One reasonable approach is to exclude the diagnosis to avoid further unnecessary and expensive diagnostic investigation. High sensitivity tests have few false-negative results and act to rule conditions out (SnOUT). A negative result from a test with high sensitivity will exclude the disease with high certainty independent of the specificity. As women without disease would be assured of having a negative test, unnecessary invasive interventions can be avoided. However, a positive result has less diagnostic value particularly when the specificity is low. We predetermined that a clinically useful 'SnOUT' triage test should have a sensitivity of 95% or more and a specificity of 50% and above. The sensitivity cutoff for a 'SnOUT' triage test was set at 95% and above, assuming that a 5% false negative rate is statistically and clinically acceptable. The specificity cutoff was set at 50% and above, to avoid diagnostic uncertainty in more than 50% of the population with a positive result.

An alternative approach would be to avoid a missed diagnosis. High specificity tests have few false positive results and act to rule conditions 'in' (SpIN). A positive result for a highly specific triage test indicates a high likelihood of having endometriosis. This information could be used to prioritise these women for surgical treatment. A positive 'SpIN' test could also provide a clinical rationale to start targeted disease-specific medical management in a person without a surgical diagnosis, under the assumption that disease is present. Surgical management could then be reserved for cases when conservative treatment fails. This is particularly relevant in some populations where the therapeutic benefits of surgery for endometriosis have to be carefully balanced with the disadvantages (e.g. young women, women with medical conditions or pain-free women with a history of infertility). In this scenario we considered a sensitivity of 50% and above and a specificity of 95% and higher as suitable cutoffs for a 'SpIN' triage test.

We evaluated urine tests for their potential to replace surgery (replacement test) or to improve the selection of women for surgery (triage test) that can either rule out (SnOUT) or rule in (SpIN) the disease. Both types of triage test are clinically useful, minimising the number of unnecessary interventions. Sequential implementation of SnOUT and SpIN tests can also optimise a diagnostic algorithm (Figure 1). We did not assess any test as an add-on test, as we sought tests that reduce the need for surgery and not tests that improve the accuracy of the currently available surgical diagnosis.

Alternative test(s)

There are no alternative tests for the diagnosis of endometriosis that are in routine clinical practice.

Types of studies

Published peer-reviewed studies that compared the results of one or several types of urinary biomarkers with the results obtained by surgical diagnosis of endometriosis. Studies were included if they were:

• Randomised controlled trials;

• Observational studies of the following designs:

  • ‘Single-gate design’ (studies with a single set of inclusion criteria defined by clinical presentation). All participants had clinically suspected endometriosis.

  • ‘Two-gate design’ (studies where participants are sampled from distinct populations with respect to clinical presentation). The same study includes participants with a clinical suspicion of having the target condition (e.g. women with pelvic pain) and also participants in whom the target condition is not suspected (e.g. women admitted for tubal ligation). Two-gate studies were eligible only where all cases and controls belonged to the same population in respect to the reference standard (i.e. all the participants were scheduled for laparoscopy) (Rutjes 2005).

• Performed on prospectively collected samples, irrespective of the actual time of the test assay. The timing of sample collection relative to surgery is important because the surgical excision of endometriotic lesions could influence urine biomarker expression and hence bias the results. Therefore, we only included studies where urine was collected before the surgical procedure, i.e. 'prospectively collected'. The studies performed on tissue bank samples collected from prospectively recruited, well-defined populations were considered eligible, which prevented the omission of valuable data from adequately designed studies. The time interval between sample collection and laboratory testing may influence test outcomes which could be dependent on sample storage conditions and the stability of each individual biomarker during storage and freeze/thawing. This information was not readily available for most molecules and was not addressed in this review, but will be considered in future updates if more evidence emerges.

• Performed in any healthcare setting;

• Published in any language;

• We did not impose a minimal limit on the number of participants in the included studies nor the number of studies that have evaluated each index test.

The following studies were excluded:

• Study design:

  • Narrative or systematic reviews;

  • Studies of retrospective design where the sample collection was performed after execution of reference test;

  • Studies of retrospective design where the participants were selected from retrospective review of the case notes/archived samples and information on recruitment methods or study population was not available;

  • Case reports or case series;

• Studies reported only in abstract form or in conference proceedings where the full text was not available. This limitation was applied when we faced substantial difficulty in obtaining the information from the abstracts, which precluded a reliable assessment of eligibility and methodological quality.

Participants

Study participants included reproductive-aged women (puberty to menopause) with suspected endometriosis based on clinical symptoms or pelvic examination, or both, who undertook both the index test and reference standard.

The participants were selected from populations of women undergoing abdominal surgery for the following indications: 1) clinically suspected endometriosis (pelvic pain, infertility, abnormal pelvic examination, or a combination of the above), 2) ovarian mass regardless of symptoms, 3) a mixed group, which consists of women with suspected endometriosis/ovarian mass or women with other benign gynaecological conditions (e.g. surgical sterilisation, fibroid uterus, etc). Asymptomatic women who have an incidental finding of endometriosis at surgery performed for another indication were also included

Articles that included participants of postmenopausal age were eligible when the data for the reproductive age group was available in isolation. Studies were excluded when the study population involved participants who clearly would not undergo the index test in a clinical scenario or would not benefit from the test (e.g. women with ectopic pregnancies, gynaecological malignancy or acute pelvic inflammatory disease). We also excluded publications where only a subset of participants with a positive index test or reference standard were included in the analysis and the data for the whole cohort were not available.

Index tests

Any type of urinary biomarker for endometriosis was assessed either separately or in combination with other urine tests. The assessed index tests are presented in Table 2. We included the tests performed in one or several phases of menstrual cycle.

The combined evaluations of urinary biomarkers with other methods for diagnosing endometriosis (e.g. pelvic examination, imaging, blood or endometrial tests) are beyond the scope of this review and are presented separately in another review 'Combined tests for the non-invasive diagnosis of endometriosis'. The studies that solely assessed specific technical aspects, qualitative descriptions of lesion appearance or inter-observer variability of the index tests without reporting the data on diagnostic performance were excluded from the review. When the evaluated biomarker(s) showed differential expression between the groups of women with and without endometriosis, the publication was considered only if the data were reported with sufficient detail for the construction of 2 x 2 contingency tables. However, when the contingency tables were not available because the expression level of index test did not significantly differ between the groups and the inclusion criteria were otherwise met, a critical appraisal was undertaken and the study was presented in the descriptive part of the review. Thus the adequately designed studies that identified biomarkers without diagnostic value were evaluated as they provide information that is likely to focus future research on other more clinically useful biomarkers. This methodology also identified biomarkers which were associated with endometriosis in some but not other publications. Evaluations of screening or predictive accuracy tests were not included in this review.

The diagnostic performance of an index test was considered to be high when the test reached the criteria for a replacement test (sensitivity of equal or greater than 94% with specificity of equal or greater than 79%) or triage test (sensitivity of equal or greater than 95% with specificity of equal or greater than 50% or vice versa), or approached these criteria (diagnostic estimates within 5% of the set thresholds). All other diagnostic estimates were considered to be low.

Target conditions

Pelvic endometriosis, defined as endometrial tissue located in the pelvic cavity: any of the pelvic organs, peritoneum and pouch of Douglas. Three types of pelvic endometriosis were assessed:

1. Peritoneal endometriosis, defined as endometrial deposits detected on peritoneum covering pelvic organs, pelvic side walls or pouch of Douglas;

2. Ovarian endometriosis (endometrioma), defined as an ovarian cyst lined by endometrial tissue and appearing as an ovarian mass of varying size;

3. Deep infiltrating endometriosis (DIE), defined as subperitoneal infiltration of endometrial implants, i.e. when the endometriotic implants penetrate the retroperitoneal space for a distance of 5 mm or more (Koninckx 1991). DIE may be present in multiple locations, involving either anterior or posterior pelvic compartments, or both.

Certain rare types of endometriosis such as extrapelvic, bladder and ureteric endometriosis were not included in this review because the majority were reported in case reports or case series and laparoscopy or laparotomy are not reliable reference standards for these conditions.

We excluded the studies where diagnosis of endometriosis was not the primary outcome of the trial (e.g. malignant vs benign masses or normal vs. abnormal pelvis) and the separate data for endometriosis were not available.

We also excluded the studies where the findings of the index test formed the basis of selection for the reference standard, because this was likely to distort an assessment of the diagnostic value of index test.

We included studies that recruited selected populations of women with endometriosis (i.e. those with specific rASRM stages), because there is a poor correlation between the rASRM classification and infertility and pain symptoms. Exclusion of these studies could result in a loss of potentially important diagnostic information from otherwise eligible publications. Where possible the impact of these studies was addressed in the assessments of heterogeneity. When a study analysed a large population with a wide spectrum of endometriosis and additionally reported a sub-group analysis of the different stages of disease severity, only estimates for the entire population were considered, because a subgroup analysis does not directly address the review question regarding the clinical utility of the biomarker in detecting the disease.

Reference standards

The reference standard was visualisation of endometriosis at surgery (laparoscopy or laparotomy) with or without histological confirmation, as this is currently the best available test for endometriosis. Information regarding the inter- and intra-observer correlation of the reference standard was reviewed if reported.

Only studies in which the reference test was performed within 12 months of the urine sample collection were included, on the assumption that disease status could change within a period of one year or longer, either naturally or as a result of treatment. Studies in which the participants did not undergo the reference standard or where the findings of the index test formed the basis of selection for undertaking the reference standard were not included in this review.

Electronic searches

We searched the following databases to identify the published articles that assessed the diagnostic value of urinary biomarkers for endometriosis:

• CENTRAL;

• MEDLINE;

• EMBASE;

• CINAHL;

• PsycINFO;

• Web of Science;

• LILACS;

• OAIster;

• TRIP;

• Databases of the trial registers:

  • ClinicalTrials.gov;

  • World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP);

• Databases to identify reviews and guidelines as sources of references to potentially relevant studies:

  • MEDION;

  • DARE;

  • PubMed, a ‘Systematic Review’ search under the ‘Clinical Queries' link;

• Searches for papers recently published and not yet indexed in the major databases:

  • PubMed (simple search for the last 6 months; the ‘related articles’ feature was used to locate additional relevant studies).

Searching other resources

The reference list of all relevant publications (retrieved full texts of the key articles and identified reviews) was handsearched.

An intended attempt to locate the grey literature (unpublished studies and conference proceedings) was abandoned as we faced substantial difficulty in obtaining full-text publications or further details of studies reported in an abstract form.

Selection of studies

Two authors of this review (EL, VN) and four authors for the other reviews from this series (Devashana Gupta, Rabia Shaikh, Deepika Arora and Lucy Prentice) scanned the titles of studies identified by our search to remove any clearly irrelevant articles. The titles and abstracts of the remaining studies were reviewed to select potentially relevant publications. The relevant articles were then divided into four categories of endometriosis biomarkers: serum, endometrial, urinary, and combined tests. Two of the urinary biomarker review authors (EL, LH, or VN) independently reviewed each of the full-text versions of the articles selected by title and abstract and assessed them for eligibility for inclusion, based on the criteria listed above under Criteria for considering studies for this review. A single failed eligibility criterion was sufficient for a study to be excluded from the review.

The review authors who assessed the relevance of the studies and eligibility for inclusion were not blinded to the information about each article, including the publishing journal, the names of authors, the institution and the results. Any disagreements were resolved by discussion and, if necessary, in consultation with a third review author (CF), who is an expert in methodological aspects of Cochrane systematic reviews.

When papers updated previous publications and were performed on the same study population at different recruitment points, the most complete data set that superseded previous publications was used to avoid double counting participants or studies. Missing data were retrieved by directly contacting authors to clarify study eligibility. When potentially relevant studies were found in languages other than English, a translation was undertaken. For excluded studies, the reasons for exclusion and details of which criteria were not met were documented. The characteristics of included, excluded and awaiting classification studies are presented under Characteristics of included studies, Characteristics of excluded studies and Characteristics of studies awaiting classification, respectively.

Data extraction and management

Data were extracted from eligible studies by two independent review authors (EL, LH) and any disagreement was resolved by the third review author (VN). If required, study investigators were contacted to resolve any questions regarding the data.

To collect details from included studies, a data extraction form was specifically designed for this review and pilot tested on three studies of diagnostic accuracy tests for endometriosis. The following information was recorded for each study:

• General information and study design: first author, year of publication, country, language, setting, objectives, inclusion/exclusion criteria, type of enrolment.

• Characteristics of the study participants: age, symptoms/history/previous tests, type of target condition and its prevalence in the study population, number of participants enrolled and available for analysis, reasons for withdrawal.

• Features of the index test and reference standard: type, diagnostic criteria, number and experience of the operators, blinding of the operators to other tests or clinical data or both, interobserver variability, time interval between index test and reference standard.

• The reported number of true positives (TP), false negatives (FN), true negatives (TN) and false positives (FP) was used to construct a two-by-two (2 x 2) table for each index test. If these values were not reported, we attempted to reconstruct the 2 x 2 tables from the summary estimates presented in the article.

Data were extracted into Review Manager® (RevMan) software, which was used to graphically display the quality assessment, the diagnostic estimates data and the descriptive analyses.

Assessment of methodological quality

We used QUADAS-2, a modified version of the QUADAS tool to assess the quality of each included study (Whiting 2011).

The review-specific QUADAS-2 tool and explanatory document are presented in Table 3. Each paper was judged as having a 'low', 'high' or 'unclear' risk for each of four domains and concerns about applicability were assessed in three domains. We considered studies as having low methodological quality when classified at high or unclear risk of bias or at high concern regarding applicability in at least one domain. The assessment of each included study was performed independently by two reviewers (EL, LH, or VN) and disagreements were settled by a third author (CF) or by consensus. Two review authors (EL, LH) independently piloted the topic-specific tool to rate four of the included studies with a high level of agreement. Modifications specific to the urinary biomarkers review were made to the signalling questions of the original QUADAS-2 tool and were as following:

1) Domain 1: an original signalling question 'Was a case control design avoided?' was rephrased as 'Was a two-gate design avoided?'. The diagnostic studies are cross-sectional in nature, aiming to compare the result of an index test with the result of the reference standard in same group of participants. In these studies the parameters are measured at a single point of time and the groups are classified by the outcome of the reference standard, albeit the analysis is performed retrospectively. Therefore, unlike epidemiological studies, the terminology 'cohort' and 'case-control' is less informative for diagnostic test trials, and was substituted by 'single-gate' and 'two-gate' designs. This question was included because a two-gate design has more potential to introduce selection bias.

2) Domain 2: an additional signalling question 'Was the phase of the menstrual cycle considered in interpreting the index test?' was introduced to assess bias in the interpretation of the test results. Some biochemical markers are sensitive to fluctuations in steroid sex hormones levels across a menstrual cycle, which could result in the differential expression of endometriosis biomarkers at different cycle phases.

The assessment of methodological quality was undertaken for each domain but a summary score to estimate the overall quality of studies was not calculated (Whiting 2005).

Statistical analysis and data synthesis

The estimates of sensitivity and specificity were generated in forest plots and plotted in the receiver operating characteristic (ROC) space for each index test using RevMan. The diagnostic performance of each test was investigated and inter study variation in the performance of each index test was visually explored in relation to participant characteristics, study design, and study quality factors. Two or more tests evaluated in the same cohort were included as separate data sets, since the unit of analysis was the test result, not the participant.

For studies that reported subgroup analyses per phase of the menstrual cycle, we presented the data in a clinically relevant way. For instance, pooled estimates were presented when there was no statistically significant difference in biomarker expression between cycle phases. Alternatively, where putative biomarkers demonstrated cycle-dependent expression or were noted to be modulated by ovarian hormones, we reported the test performance either at several time points across the menstrual cycle or in the phase that demonstrated the most distinct difference between groups.

We planned to perform the bivariate logit-normal random effects model for all meta-analyses with four studies or more and a fixed effect meta-analysis of sensitivity and specificity for smaller groups of studies (two to three) in the absence of substantial heterogeneity. When the number of studies was less than four, we did not attempt to estimate the covariance, and reported this as zero. The meta-analyses were performed using SAS NLMIXED software. Results from SAS were input into RevMan to provide plots of the estimated summary points and confidence regions, superimposed on the study-specific estimates of sensitivity and specificity. In this review this aspect of the statistical analysis was unable to be performed due to the paucity of data for each biomarker.

The comparative accuracy of index tests was assessed in two ways. In direct, fully paired comparisons where all the study participants received more than one index test as well as the reference standard, the estimates were plotted in RevMan. If a meta-analysis was possible, test-level covariates in the bivariate logit-normal model were used to identify statistically significant differences. Otherwise the available comparative data were reported in a narrative way and illustrated using forest and ROC plots.

When test performance was judged against the predetermined diagnostic criteria, the point estimates of sensitivity and specificity were considered as the most informative presentation of test performance. We acknowledge that tests with point estimates that did not reach the predetermined criteria but confidence intervals (CIs) which contained values above the threshold, could have diagnostic value. Furthermore tests with point estimates that reached the criteria but CIs which contained values below the threshold, could have an overestimated diagnostic value. If the range of the CIs rather than the point estimates of the data are used, the predetermined cut-off becomes meaningless. Therefore we did not consider CIs in qualifying the test performance, but utilised this information in interpreting the reliability of the obtained data.

Investigations of heterogeneity

Heterogeneity was initially assessed by visually examining the forest plots of sensitivities and specificities and the ROC plots for each index test. The potential sources of heterogeneity are stated in the Secondary objectives. For diagnostic tests where there were more than five eligible studies, we initially planned to formally explore heterogeneity by using study level covariates but we were unable to do so, because of the small numbers of studies in each group. We also planned to assess the sensitivity of results to the inclusion and exclusion of outlying studies in all analyses, but refrained from doing so, again because of the small number of studies for most analyses. It is important to use caution when interpreting small meta-analyses (few studies) with a limited total sample size.

Sensitivity analyses

We planned to conduct sensitivity analyses to assess the impact of the methodological quality of included studies on the results of any meta-analyses if sufficient data were available. Low quality studies were defined by the identification of a high risk of bias for one or more QUADAS-2 domains. We also planned to use the ’leave-one-out’ procedure to assess the impact of each study on the meta-analysis results (leading study effect). In the urinary review this was unable to be undertaken due to the paucity of studies evaluating each biomarker.

Assessment of reporting bias

A comprehensive search of multiple sources for eligible studies, a search of trial registers and no language restrictions minimised the risk of reporting bias. However, publication bias generally arises when studies have a higher chance of being published if their results are positive. Therefore unpublished and published study databases and conference proceedings were initially searched and evaluated. During the process of qualifying the studies for inclusion in this review, we faced substantial difficulty in obtaining full-text publications or further details of studies published in an abstract form. This precluded a reliable assessment of eligibility and methodological quality and it was decided not to include these publication sources in this review.

Basic features of the included studies

The list and details of the included studies are presented in Characteristics of included studies. The eight eligible studies included 646 participants, with a median of 73 women per study (range 39 to 147). Of these studies, five assessed urinary biomarker expression in women with and without endometriosis and included enough data to estimate a diagnostic performance of the investigated test (n = 438 participants, median 95, range 39 to 147 women). Each study evaluated one or several biomarkers. Most studies reported diagnostic estimates for biomarkers that demonstrated differential expression between women with and without endometriosis, although in one publication this assessment was undertaken for a test that demonstrated no differential expression (Lessey 2014). In three studies there was no difference in the expression between the women with and without endometriosis and the diagnostic test accuracy of the urinary biomarker was not evaluated (n = 208 participants, median 70, range 62 to 76 women). This set of studies was methodologically eligible and the biomarkers identified are unlikely to be of diagnostic utility and hence may not be worth further study.

Four of the included studies were conducted in Asia, two in Europe and two in North America. All the studies were conducted at university hospitals, of which at least three were referral centres for endometriosis. The earliest article was published in 2004, six articles were published after 2010 and four studies were published after 2013. There were no randomised controlled trials and all the studies were observational of cross-sectional design. Five studies were 'single-gate', where both cases and controls were sampled from the same participant population, all of which included women with suspected endometriosis based on clinical presentation (women presenting with pelvic pain, infertility, ovarian mass, or a combination thereof). Three studies were of a 'two-gate design' and included a wider group of participants who were undergoing surgery for various indications. All the included studies assessed women of reproductive age. Laparoscopy was the predominant surgical modality in the included studies, whereas laparotomy was co-utilised in one study. Seven of the included studies used histopathology to confirm the surgical diagnosis. All the included studies evaluated pelvic endometriosis and the reported prevalence of endometriosis varied from 43% to 66%. Five studies included wide spectrum of endometriosis (rASRM I-IV), two studies included only participants with moderate–severe endometriosis (rASRM stage III-IV) and in one study the information on the severity of the disease was not available. Six studies received financial support, two of which were funded by the pharmaceutical companies, and all the authors declared no conflict of interest. No information was available from the remaining two studies.

Basic features of the excluded studies

The list and descriptions of the excluded studies are presented in Characteristics of excluded studies. Based on a full text assessment, six publications were excluded, of which one was of retrospective design and the urine samples were collected after the surgical procedure. One study reported statistically significant differences in biomarker levels between the study and control groups, but contained insufficient diagnostic accuracy information for the construction of 2 x 2 contingency tables. One excluded paper presented the qualitative evaluation of urinary biomarkers and did not define a specific test for diagnostic assessment. A further three studies were excluded as they evaluated urinary excretion of the environmental toxins and their association with risk of endometriosis. For two studies there was insufficient data to confirm eligibility and these were classified as awaiting classification at the time of publication. These studies are outlined in Characteristics of studies awaiting classification and will be addressed in future updates of this review.

1) Enolase 1 (NNE)

The diagnostic performance of urinary NNE was evaluated in one study (59 women, follicular or luteal cycle phase, only moderate to severe endometriosis, rASRM III-IV) (Yun 2014). Urinary NNE expression was not influenced by cycle phase and was significantly greater (P = 0.026) in women with endometriosis when corrected for creatine excretion (NNE-Cr). Using a cut-off threshold of more than 0.96 ng/mgCr, the sensitivity was 0.56 (95% CI, 0.40 to 0.72), and the specificity 0.70 (95% CI, 0.46 to 0.88) and did not meet the criteria for either replacement or triage tests (Figure 5). Further testing in larger studies including participants with a wider spectrum of endometriosis is needed to confirm the role of NNE in detecting endometriosis.

2) Vitamin D-binding protein (VDBP)

The diagnostic performance of urinary VDBP was evaluated in one study only, which included 95 women in the follicular or luteal cycle phase (Cho 2012). Even though the study included endometriosis of varying severity (rASRM I-IV), more than 90% of women with endometriosis had moderate to severe disease (52/57). Urinary VDBP levels corrected for creatinine (VDBP-Cr) expression were significantly greater in participants with endometriosis (P = 0.001). However, VDBP-Cr only distinguished women with and without endometriosis in the luteal phase (P = 0.042) of the cycle. The cut-off value of more than 87.83 ng/mgCr demonstrated a sensitivity of 0.58 (95% CI, 0.44 to 0.71) and a specificity of 0.55 (95% CI, 0.38 to 0.71) (Figure 6). The results are discouraging, but further evaluation of VDBP across the spectrum of endometriosis particularly in the luteal phase may help to clarify its diagnostic role in endometriosis.

3) MALDI-TOF-MS proteomics

Two studies, including seven data sets comprising 186 women, assessed the accuracy of proteomic techniques in detecting endometriosis (Figure 7; Figure 8). One study included 39 women in the follicular, peri-ovulatory or luteal phases (El-Kasti 2011). Six significant putative peptide markers distinguished controls from women with moderate to severe endometriosis (rASRM III-IV), four of these in the peri-ovulatory phase and two in the luteal phase. The diagnostic accuracy of two peptides only identified by their mass profile were evaluated. The peri-ovulatory peptide mass of 1767.1 Da using a cut-off of 35.22 or more arbitrary units (a.u.) showed a sensitivity of 0.75 (95% CI, 0.43 to 0.95) and a specificity of 0.87 (95% CI 0.60 to 0.98). The luteal peptide mass of 1824.3 Da using a cut-off of 29.34 or more a.u. showed a sensitivity of 0.77 (95% CI, 0.46 to 0.95) and a specificity of 0.73 (95% CI, 0.45 to 0.92). The diagnostic performance of the other four peptides were not assessed. It was noted that 14 participants with minimal to mild endometriosis were excluded from this analysis. None of the biomarkers met the criteria for a replacement or triage test, but this observation provides too little data to draw conclusions regarding the diagnostic role of these urinary peptides in endometriosis.

Another study (122 women, follicular or luteal cycle phase, rASRM I-IV, unclear histological confirmation) identified 36 peptides that were significantly different between the endometriosis and the control groups (Wang 2014). The peptide pattern did not vary between follicular and luteal phases and four peptides, that were down-regulated in endometriosis, were further evaluated for diagnostic performance. The 2052.3 Da mass peptide demonstrated a sensitivity of 0.83 (95% CI, 0.71 to 0.92) and a specificity of 0.69 (95% CI, 0.56 to 0.80), and the 3393.9 Da mass peptide had a sensitivity of 0.85 (95% CI, 0.73 to 0.93) and a specificity of 0.71 (95% CI, 0.58 to 0.82). The other two peptides were able to be identified by their mass spectra and were a collagen alpha-6(IV) chain precursor fragment (1579.2 Da) with a sensitivity of 0.83 (95% CI, 0.71 to 0.92) and a specificity of 0.69 (95% CI, 0.56 to 0.80) and a type VIII, IX, XV collagen alpha1 chain precursor fragment (891.6 Da) with a sensitivity of 0.82 (95% CI, 0.70 to 0.90) and a specificity of 65 (95% CI, 0.51 to 0.76).The cut-off thresholds were not reported for any of these analyses. Three algorithms were developed using peptide peak clusters in diagnostic models, (the Genetic algorithm (GA), the decision tree algorithm (DTA), and the quick classifier algorithm (QC)). The GA algorithm showed the highest diagnostic estimates comprising five peptides of 1433.9 Da, 1599.4 Da, 2085.6 Da, 6798.0 Da, and 3217.2 Da and was further validated in a blinded test group analysis of 25 randomly selected participants, 11 of which had endometriosis. The estimates of the validation test showed a high sensitivity of 0.91 (95% CI, 0.59 to 1.00) and a high specificity of 0.93 (95% CI, 0.66 to 1.00), which approach the criteria for the replacement of SnOUT and SpIN triage tests. These results require further validation in large, independent, well-defined populations, displaying a wide spectrum of disease, using standardised and reproducible methodologies.

4) Cytokeratin-19 fragments (uCYFRA 21-1)

Two studies that included 174 women assessed the performance of Cytokeratin 19 (CK 19) as a biomarker in detecting endometriosis by measuring urine fragment uCYFRA 21-1. Both studies concluded that CK 19 was not altered by the presence of endometriosis and that their levels were not affected by menstrual cycle phases (Kuessel 2014), by severity of the disease or when the levels were normalised to urine creatinine or urine protein (Lessey 2014). Only one of these studies (98 participants, cycle phase not reported, rASRM I-IV) evaluated the diagnostic accuracy of uCYFRA 21-1 (Lessey 2014), demonstrating a very low sensitivity of 0.11 (95% CI, 0.05 to 0.22) with a high specificity 0.94 (95% CI, 0.81 to 0.99), using a chosen cut-off of more than 5.3 ng/ml (Figure 9). This evidence suggests that the cytokeratin 19 molecule is not reliable as a diagnostic test for endometriosis, but further testing is required to confirm or refute these findings.

5) Vascular endothelial growth factor (VEGF) or vascular endothelial growth factor-A (VEGF-A)

Two studies in 132 women assessed the performance of urinary VEGF in diagnosing endometriosis (Potlog-Naharia 2004; Cho 2007). The levels were corrected to urinary creatinine in both studies, and one study showed no differences in excretion across the menstrual cycle (Potlog-Naharia 2004). There was no significant difference between the control and endometriosis groups seen in either study, and the diagnostic accuracy was not evaluated.

6) Tumour necrosis factor-alpha (TNF-alpha)

Urinary TNF-alpha levels were not significantly different in one study (70 participants, follicular or luteal cycle phase, rASRM I-IV) and the diagnostic accuracy was not evaluated (Cho 2007).

Investigations of heterogeneity and sensitivity analyses

The potential sources of heterogeneity are outlined in Secondary objectives. Although we attempted to assess these sources of heterogeneity, there were not enough studies evaluating each test to make this a meaningful analysis. Furthermore, the sensitivity analyses were not possible due to the small number of studies.

Database: EMBASE (Ovid) <1980 to 2015 Week 07 (16.02.2015)>

Search strategy:

--------------------------------------------------------------------------------

1 Laboratory Test$.tw. (41662)

2 growth factor$.tw. (318593)

3 scatter factor$.tw. (1388)

4 cytokine$.tw. (322134)

5 hepatocyte growth factor.tw. (9594)

6 (FGF or fibroblast growth factor$).tw. (37191)

7 (PDGF or platelet derived growth factor$).tw. (23530)

8 (EGF or epidermal growth factor$).tw. (69553)

9 (IGF-I or insulin-like growth factor$ or IGF1).tw. (49806)

10 (TGF-a or transforming growth factor alfa or TGFa).tw. (542)

11 (TGF-b or transforming growth factor beta or TGFb).tw. (30820)

12 (EGFR or epidermal growth factor receptor$).tw. (64664)

13 (VEGF or vascular endothelial growth factor$).tw. (73191)

14 exp luteinizing hormone/ec [Endogenous Compound] (21924)

15 leptin$.tw. (32576)

16 exp progesterone blood level/ or exp progesterone urine level/ (6285)

17 Proteolytic enzyme$.tw. (9643)

18 exp matrix metalloproteinase/ (19364)

19 matrix metalloproteinase$.tw. (41445)

20 MMP$.tw. (58466)

21 TIMP$.tw. (14174)

22 exp "tissue inhibitor of metalloproteinase 2"/ (4824)

23 exp "tissue inhibitor of metalloproteinase 1"/ (8779)

24 exp glycoprotein/ec [Endogenous Compound] (246077)

25 (Ca-125 or Ca125 or cancer antigen 125).tw. (9536)

26 (Ca-19-9 or Ca19-9 or cancer antigen 19-9).tw. (6054)

27 (PP 14 or PP14).tw. (244)

28 serum placental protein$.tw. (43)

29 exp follistatin/ (2148)

30 Osteopontin$.tw. (8475)

31 exp intercellular adhesion molecule 1/ (32066)

32 exp selectin/ (3082)

33 soluble intercellular adhesion.tw. (1788)

34 Soluble adhesion molecule$.tw. (919)

35 sICAM.tw. (2888)

36 sVCAM$.tw. (1793)

37 (sEcadherin or soluble E-cadherin).tw. (120)

38 (sEselectin or soluble E-selectin).tw. (822)

39 exp T lymphocyte/ (374675)

40 exp natural killer T cell/ (5800)

41 Immune cells alteration$.tw. (6)

42 (T helper$ or T supressor$ or T helper$ T supressor$ ratio).tw. (24786)

43 Total complement level$.tw. (20)

44 Autoantibodies.tw. (42037)

45 exp phospholipid antibody/ (9920)

46 Anti-endometrial.tw. (23)

47 Antiphospholipid$.tw. (13777)

48 exp HLA antigen/ (81011)

49 exp HLA A1 antigen/ (597)

50 exp HLA A2 antigen/ (3288)

51 (HLA or human leucocyte antigen$).tw. (104497)

52 Anti-laminin-1.tw. (43)

53 Anti-thyroid.tw. (1873)

54 Anti-Thomsen Friedenreich antigen$.tw. (5)

55 Anti-transferrin.tw. (290)

56 Anti-LDL.tw. (186)

57 (Anti-2HSG or Heremans-Schmidt glycoprotein).tw. (4)

58 interleukin$.tw. (199692)

59 (MCP-I or monocyte chemoattractant protein-I).tw. (112)

60 (MIF or migration inhibitory factor$).tw. (5063)

61 (TNF-a or tumour necrosis factor$ alfa).tw. (5998)

62 Fas ligand$.tw. (6708)

63 Endometrial marker$.tw. (18)

64 CAMs.tw. (2100)

65 cell adhesion molecule$.tw. (24039)

66 exp integrin/ (29036)

67 Integrin$.tw. (48293)

68 Selectin$.tw. (67300)

69 Cadherin$.tw. (27150)

70 Aromatase P450.tw. (202)

71 estrogen receptor$.tw. (46656)

72 progesterone receptor$.tw. (19861)

73 MTMMP$.tw. (15)

74 cyr61.tw. (755)

75 exp cysteine rich protein 61/ (753)

76 cysteine-rich heparin-binding protein$.tw. (12)

77 (ANXA 1 or ANXA1).tw. (452)

78 (Annexin 1 or Annexin1).tw. (425)

79 (PGP 9?5 or PGP9?5 or protein gene product$).tw. (2620)

80 serum marker$.tw. (7720)

81 neural marker$.tw. (1119)

82 cell surface marker$.tw. (5851)

83 inflammatory marker$.tw. (17339)

84 microarray$.tw. (101846)

85 microRNA$.tw. (40082)

86 proteomic$.tw. (55191)

87 genomic$.tw. (217184)

88 (endometri$ adj2 biops$).tw. (4369)

89 Follistatin$.tw. (1945)

90 exp vasculotropin/ (69810)

91 Vascular Endothelial Growth Factor A.tw. (2275)

92 exp vitamin D binding protein/ (2064)

93 exp cytokine/ (1034772)

94 exp interleukin derivative/ (2790)

95 exp interleukin 1/ (48499)

96 exp interleukin 6/ (136328)

97 exp interleukin 8/ (48884)

98 exp interleukin 12/ (31842)

99 exp interleukin 13/ (13584)

100 exp epidermal growth factor/ (32130)

101 exp fibroblast growth factor/ (13858)

102 cytokeratin 19/ (3601)

103 platelet derived growth factor/ (18930)

104 cytokeratin-19.tw. (1918)

105 (VDBP or vitamin D-binding protein$).tw. (1413)

106 urinary peptide$.tw. (174)

107 VDBP-Cr.tw. (1)

108 urinary VDBP corrected for creatinine expression.tw. (1)

109 urinary marker$.tw. (830)

110 exp blood analysis/ (118854)

111 exp endometrium biopsy/ (4988)

112 exp urinalysis/ or exp biological marker/ (210153)

113 (biomarker or biomarkers).tw. (159748)

114 or/1-113 (2734501)

115 endometriosis/di [Diagnosis] (4979)

116 114 or 115 (2738583)

117 exp endometriosis/ (25923)

118 Endometriosis.tw. (22110)

119 117 or 118 (27911)

120 116 and 119 (10326)

121 Animal/ not Human/ (1204497)

122 120 not 121 (10279)

Additional search February 2015 - May 2015

Embase <1980 to 2015 Week 35 (3.09.2015)>

Search Strategy:

--------------------------------------------------------------------------------

1 Laboratory Test$.tw. (44290)

2 growth factor$.tw. (335543)

3 scatter factor$.tw. (1407)

4 cytokine$.tw. (343623)

5 hepatocyte growth factor.tw. (10104)

6 (FGF or fibroblast growth factor$).tw. (39159)

7 (PDGF or platelet derived growth factor$).tw. (24591)

8 (EGF or epidermal growth factor$).tw. (73599)

9 (IGF-I or insulin-like growth factor$ or IGF1).tw. (51838)

10 (TGF-a or transforming growth factor alfa or TGFa).tw. (583)

11 (TGF-b or transforming growth factor beta or TGFb).tw. (32580)

12 (EGFR or epidermal growth factor receptor$).tw. (71526)

13 (VEGF or vascular endothelial growth factor$).tw. (79087)

14 exp luteinizing hormone/ec [Endogenous Compound] (22767)

15 leptin$.tw. (34921)

16 exp progesterone blood level/ or exp progesterone urine level/ (6534)

17 Proteolytic enzyme$.tw. (9903)

18 exp matrix metalloproteinase/ (20462)

19 matrix metalloproteinase$.tw. (44380)

20 MMP$.tw. (63208)

21 TIMP$.tw. (15146)

22 exp "tissue inhibitor of metalloproteinase 2"/ (5136)

23 exp "tissue inhibitor of metalloproteinase 1"/ (9381)

24 exp glycoprotein/ec [Endogenous Compound] (260024)

25 (Ca-125 or Ca125 or cancer antigen 125).tw. (10051)

26 (Ca-19-9 or Ca19-9 or cancer antigen 19-9).tw. (6446)

27 (PP 14 or PP14).tw. (243)

28 serum placental protein$.tw. (44)

29 exp follistatin/ (2283)

30 Osteopontin$.tw. (9173)

31 exp intercellular adhesion molecule 1/ (33492)

32 exp selectin/ (3217)

33 soluble intercellular adhesion.tw. (1865)

34 Soluble adhesion molecule$.tw. (944)

35 sICAM.tw. (3049)

36 sVCAM$.tw. (1924)

37 (sEcadherin or soluble E-cadherin).tw. (125)

38 (sEselectin or soluble E-selectin).tw. (861)

39 exp T lymphocyte/ (394405)

40 exp natural killer T cell/ (6310)

41 Immune cells alteration$.tw. (6)

42 (T helper$ or T supressor$ or T helper$ T supressor$ ratio).tw. (26082)

43 Total complement level$.tw. (20)

44 Autoantibodies.tw. (44153)

45 exp phospholipid antibody/ (10362)

46 Anti-endometrial.tw. (25)

47 Antiphospholipid$.tw. (14399)

48 exp HLA antigen/ (83748)

49 exp HLA A1 antigen/ (622)

50 exp HLA A2 antigen/ (3409)

51 (HLA or human leucocyte antigen$).tw. (109332)

52 Anti-laminin-1.tw. (43)

53 Anti-thyroid.tw. (2059)

54 Anti-Thomsen Friedenreich antigen$.tw. (7)

55 Anti-transferrin.tw. (297)

56 Anti-LDL.tw. (191)

57 (Anti-2HSG or Heremans-Schmidt glycoprotein).tw. (4)

58 interleukin$.tw. (210083)

59 (MCP-I or monocyte chemoattractant protein-I).tw. (114)

60 (MIF or migration inhibitory factor$).tw. (5342)

61 (TNF-a or tumour necrosis factor$ alfa).tw. (6488)

62 Fas ligand$.tw. (6895)

63 Endometrial marker$.tw. (18)

64 CAMs.tw. (2198)

65 cell adhesion molecule$.tw. (25207)

66 exp integrin/ (30330)

67 Integrin$.tw. (50938)

68 Selectin$.tw. (71624)

69 Cadherin$.tw. (29496)

70 Aromatase P450.tw. (207)

71 estrogen receptor$.tw. (49530)

72 progesterone receptor$.tw. (21068)

73 MTMMP$.tw. (16)

74 cyr61.tw. (822)

75 exp cysteine rich protein 61/ (829)

76 cysteine-rich heparin-binding protein$.tw. (12)

77 (ANXA 1 or ANXA1).tw. (500)

78 (Annexin 1 or Annexin1).tw. (440)

79 (PGP 9?5 or PGP9?5 or protein gene product$).tw. (2760)

80 serum marker$.tw. (8158)

81 neural marker$.tw. (1234)

82 cell surface marker$.tw. (6222)

83 inflammatory marker$.tw. (19492)

84 microarray$.tw. (110181)

85 microRNA$.tw. (47554)

86 proteomic$.tw. (60599)

87 genomic$.tw. (233444)

88 (endometri$ adj2 biops$).tw. (4589)

89 Follistatin$.tw. (2081)

90 exp vasculotropin/ (74115)

91 Vascular Endothelial Growth Factor A.tw. (2526)

92 exp vitamin D binding protein/ (2196)

93 exp cytokine/ (1094317)

94 exp interleukin derivative/ (3281)

95 exp interleukin 1/ (50850)

96 exp interleukin 6/ (147379)

97 exp interleukin 8/ (52281)

98 exp interleukin 12/ (33479)

99 exp interleukin 13/ (14685)

100 exp epidermal growth factor/ (33057)

101 exp fibroblast growth factor/ (14499)

102 cytokeratin 19/ (3886)

103 platelet derived growth factor/ (19655)

104 cytokeratin-19.tw. (2030)

105 (VDBP or vitamin D-binding protein$).tw. (1520)

106 urinary peptide$.tw. (189)

107 VDBP-Cr.tw. (1)

108 urinary VDBP corrected for creatinine expression.tw. (1)

109 urinary marker$.tw. (883)

110 exp blood analysis/ (124468)

111 exp endometrium biopsy/ (5197)

112 exp urinalysis/ or exp biological marker/ (232619)

113 (biomarker or biomarkers).tw. (182609)

114 or/1-113 (2911073)

115 endometriosis/di [Diagnosis] (5173)

116 114 or 115 (2915302)

117 exp endometriosis/ (27433)

118 Endometriosis.tw. (23449)

119 117 or 118 (29532)

120 116 and 119 (10922)

121 Animal/ not Human/ (1261620)

122 120 not 121 (10862)

123 (201501$ or 201502$ or 201503$ or 201504$).em. (49200)

124 122 and 123 (34)

Search for clinical studies

Database: Web of Science Core Collection (Thomson Reuters) <1900 to Present (20.04.2015)>

Search strategy:

1. Topic=(endometrio*) AND Topic=(diagnos* OR test* OR marker* OR biomarker*); Timespan=All Years (7425)

Database: PsycINFO (Ovid) <1806 to April Week 2 2015 (20.04.2015)>

Search strategy:

1. endometriosis.tw. (174)

Database: LILACS <20.04.2015>

Search strategy:

1. (tw:(endometriosis)) AND (tw:(diagnos*)) (420)

Database: OAIster (WorldCat.org) <20.04.2015>

Search strategy:

1. endometriosis and (marker* or biomarker*) (11)

2. endometriosis and diagnos* (446)

Database: TRIP <20.04.2015>

Search strategy:

1. (endometriosis and diagnos*) (1648)

Searches of trial registers for ongoing and registered trials

Database: 'ClinicalTrials.gov', a service of the US national Institute of Health

Search strategy:

1. endometriosis (220)

2. endometriosis AND diagnosis (22)

Database: WHO International Clinical Trials Registry Platform (ICTRP) <20.04.2015>

Search strategy:

1. endometriosis (523)

Searches for the reviews as potential source of references

Searches for the papers recently published and not yet indexed in the major databases

Search engine: PubMed <20.10.2014 to 20.04.2015>

Search strategy: