{"paper_id":"2257ea9c-d627-4ed3-bfe0-37f6da9fea5b","body_text":"Computational-Assisted Systematic Review and\nMeta-Analysis (CASMA): Effect of a Subclass of GnRH-a\non Endometriosis Recurrence\nSandro Tsang, PhD\nFaculty of Medicine\nUniversité Paris-Saclay\n@:skf.tsang[at]gmail.com\nhttps://santsang.github.io/\nhttps://orcid.org/0000-0002-5144-9049/\n28 October 2025\nAbstract\nBackground:Medical literature continues to grow at an astonishing rate,\nrendering the traditionally manual, resource-intensive PRISMA guidelines difficult\nto uphold. This bottleneck risks methodological transparency and efficiency,\ndemanding computational solutions.\nObjective:Building on prior work in information retrieval from unstructured\nmedical data, this study introduces a framework, Computational-Assisted\nSystematic Review and Meta-analysis (CASMA), to enhance the efficiency,\ntransparency, and reproducibility of evidence synthesis. Endometriosis recurrence,\nmarked by inconsistent definitions, serves as the ideal clinical case to demonstrate\nthe framework’s application.\nMethods:The CASMA framework integrates standard PRISMA guidelines with\nfuzzy matching and regular expression (regex) search to facilitate deduplication\nand pre-screening of relevant records prior to manual paper selection. A specific\nsubclass of gonadotropin-releasing hormone agonists (referred to as GnRH-a\ninterchangeably) was chosen to avoid confounding from a potential response to an\nintrauterine device. A modified splitting method addressed unit-of-analysis errors\nin multi-arm trials, alongside other sensitivity, subgroup analyses, bias assessment,\nand GRADE.\nResults:This semi-automated process of pre-screening sharply reduced the\nlabour-intensive workflow: From fetching 33,444 records, the computational\npre-screening identified 29 potentially eligible records (including systematic\nreviews and RCTs) for manual assessment in only 11 days. Hand searches were\nperformed on six manually selected meta-analyses to identify seven eligible RCTs\nfor evidence synthesis (841 patients; 152 recurrences). The pooled random-effects\nmodel yielded a statistically significant Risk Ratio (RR) of0.64(95%confidence\ninterval (CI)(0.48to0.86)) (or a36%reduction in recurrence), with non-significant\nheterogeneity (I2 = 0.00%,τ2 = 0.00). The profiling likelihood method confirmed\nτ2 = 0.00, but its95%CI(0.00to0.59)indicates some level of uncertainty.\nSensitivity and subgroup analyses supported the robustness and stability of\narXiv:2509.16599v3  [cs.CL]  27 Oct 2025\n\nthe findings.\nConclusion:The consistency of the results with the existing evidence reinforces\nthat this subclass of GnRH-a is a promising management strategy to reduce\nendometriosis recurrence. The CASMA framework is a validated, efficient,\nand reproducible approach to help deliver medicine backed by the current best\nevidence. This study bridges the gap between medical research and computer\nscience, offering a generalisable solution for managing the rapidly growing medical\nliterature.\nKeywords:Computer and Language; Information Retrieval; Endometriosis;\nDisease Recurrence; Evidence synthesis; Randomised Controlled Trials as Topic;\nGnRH-a.\nIntroduction\nEndometriosis has been documented in the medical literature since the mid-19th\ncentury, yet treating the disease remains a source of considerable clinical\nuncertainty.1,2 Endometriosis is a common gynaecological condition affecting over\n190 million women worldwide,3 and it contributes to the Global Burden of Disease.4\nWhile recurrence was once considered a rare event, it is now recognised as a common\nand complex challenge.5 The rates of recurrence vary across the world, partially due\nto inconsistent definitions.5 Consequently, the observed recurrence rate is a function\nof both biological persistence and methodological definition. Post-operative hormonal\nsuppression is a widely used strategy to manage endometriosis and reduce the risk of\nrecurrence.6,7 The existing evidence reports a wide range of effects for these agents,\nfrom no effect to a significant protective effect,5–8which makes translating evidence\ninto clinical practice difficult. Searching for definitive, confirmatory evidence is\ntherefore a critical research priority.\nThe immense and continuously expanding volume of literature on\nendometriosis presents a substantial challenge to evidence synthesis when\nstrictly compiling with manual, resource-intensive PRISMA guidelines. This is\nexemplified by the exponential growth in endometriosis publications since the\n1960s (see Figures S.1 and S.2). A Computational-Assisted Systematic Review and\nMeta-analysis (CASMA) framework was therefore employed to scale up evidence\nsynthesis with enhanced transparency and reproducibility. Following the standard\nPRISMA guidelines, regular expressions (regex) search and fuzzy matching were\nintroduced to pre-screen the records before a manual selection process, efficiently\nexcluding 812 records in a few days. This paper applies the CASMA framework to\nsynthesise evidence about a specific subclass of GnRH-a (or GnRH-a interchargeably)\n2\n\nwhere the drug delivery does not involve the use of an intrauterine device (IUD). This\narrangement avoids the confounding reaction to a foreign body, leading to clearer\nand more precise results for easier interpretation. The aim was to synthesise robust\nevidence on the efficacy of the GnRH-a subclass in reducing endometriosis recurrence\nby deploying the CASMA framework to achieve validated, reproducible, transparent,\nand efficient evidence synthesis that leverages expert knowledge effectively.\nMethods\nProtocol and Registration\nProspective registration of the review protocol was not feasible due to time\nconstraints. Instead, the protocol was retrospectively registered on the Open Science\nFramework (OSF); DOI: https://doi.org/10.17605/OSF.IO/R2DFA, registered\n5 September 2025.\nSearch Strategy\nFollowing PRISMA guidelines,9 a systematic search was conducted in PubMed,\nScopus, Google Scholar, and CrossRef between 6 and 17 June 2025. A final\nfree-text search was performed on 14 July 2025 after the research direction was\nrefined. Search terms combined controlled vocabulary (e.g., MeSH) and free text\nto capture the population (“endometriosis”), interventions (“GnRH”, “hormonal\ntherapy”), and study designs (“meta-analysis”, “controlled trial”, “clinical trial”),\nwith adaptations for each database. The search terms were derived from several much\ncited reviews1,10,11 and a post by Mayo Clinic.12 The full search syntax is available\nas Supplementary Material.\nTo enhance efficiency, accuracy, and reproducibility, semi-automated\ntext-matching techniques – including fuzzy matching and regular expressions (regex)\n– were integrated into the PRISMA workflow. This computational approach, which\nfacilitates a rapid assessment of records prior to manual screening, is inspired by a\npreviously proposed method for analysing unstructured medical data.13 Specifically,\nfuzzy matching was performed on the titles to deduplicate records (an example is\nshown in Table S.2 in the Supplementary section). The nativeR14 functions were\nimplemented to identify MAs of RCTs and to exclude records concerning network\nmeta-analyses, Bayesian studies, or associated diseases such as adenomyosis. An\n3\n\nautomated research tool15 was employed to ensure that conducting an update of\na meta-analysis was an appropriate research direction after the manual selection\nprocess was exhausted.\nEligibility Criteria and Outcome Definition\nThe initial plan was to conduct a meta meta-analyses, which was subsequently refined\nto a meta-analysis of randomised controlled trials (RCTs). Eligible studies were RCTs\nevaluating post-operative hormonal treatment for managing endometriosis, with a\ncontrol arm receiving placebo, expectant management, or no treatment. Studies were\nexcluded if the comparator (in)directly affected sex hormone levels or the hormonal\ntherapy involved intrauterine devices (IUDs), as IUDs might introduce confounding\ndue to the foreign body response.\nThe primary outcome measure was the recurrence of endometriosis. Leading\nmedical associations agreed that recurrence could be diagnosed through four\nestablished methods: symptom-based, image-based, laparoscopic, or histological\ndiagnosis.2 Endometriosis is a complex disease, often presenting with various\nsymptoms and frequently coexisting with adenomyosis, which is often mistakenly\ndiagnosed as endometriosis. 2,16 Studies defining recurrence solely based on the\nresolution or re-emergence of individual symptoms alone were excluded to ensure\nthat synthesised evidence about recurrence fitted the standardised terminology.2\nInter-rater Reliability (IRR)\nReviewer agreement for selecting meta-analysis papers was analysed in two stages.\nA three-point grading system was employed to record the selection decision and for\ncomputing the IRRs after the entire review process. This approach helps to avoid\nselection bias. Discrepancies in paper selection were resolved through discussion.\nThe statistical approach was based on non-parametric bootstrapping with 2000\nreplications.\nFor the title/abstract review, a concordance of 82.76% (24/29 papers) was\nreached, yielding a weighted absolute Kappa (κ) of 0.68 (95% bootstrap bias-corrected\nand accelerated (BCa) confidence interval (CI) (0.396 to 0.884)). The agreement\nis substantial.17 For the full-text review, only slight agreement was achieved; the\nconcordance was 57.14% (8/14 papers), and theκwas 0.05 (95% bootstrap CI\n(-0.286 to 0.588)). A negativeκindicates that the observed agreement was lower than\n4\n\nexpected by chance.17 The true level of agreement could plausibly range from poor\nto moderate.17,18 Table S.2 presents the grading at the meta-analysis selection stage,\nand the bootstrap results of each replication are depicted in Figure S.3(a) and S.3(b).\nData Extraction\nST extracted data on study design, patient characteristics, interventions,\ncomparators, and recurrence outcomes, recording them in a structured spreadsheet\nthat followed the format of well-written publications. A subset of data was\nindependently extracted by another reviewer in the same approach. Discrepancies\nin data extraction and risk of bias (RoB) assessment were resolved by ST after\ncross-checking the data against published systematic reviews, including a Cochrane\nSystematic Review.\nStatistical Analysis\nAnalyses were conducted on a device with a base clock speed of 2.55 GHz, 8 GB\nRAM, and 8 threads.R(version 4.2.2) was the main statistical implementation. 14\ndata.table19 andHmisc 20 were the packages used for data wrangling. Inter-rater\nreliability was computed using thepsy 21 package with weighted absolute Kappa.\nboot22 wasemployedforallbootstrappedstatistics. EffectestimatesforGnRH-awere\ncalculated with themetaforpackage, 23 and risk-of-bias assessments were depicted\nusingrobvis. 24 Risk ratios (RRs) were pooled using a random-effects model to\naccount for between-trial variability. A splitting method was applied to adjust for\nmulti-arm RCTs and mitigate unit-of-analysis errors.25 The method was modified\nby proportionally splitting the control group to match the size of the intervention\narm of interest relative to that of all intervention arms. Truncation was applied to\nensure integer counts. Cumulative recurrence curves were digitised when necessary to\napproximate intention-to-treat (ITT) counts.26 When ITT statistics and a cumulative\nrecurrence curve were not available, loss to follow-up was assumed to be independent\nfrom recurrence.\nA non-parametric bootstrap was performed to ensure robustness. For the\napproximations of the IRRs at the two stages, 2000 replications were applied, and\n10000replicationswereappliedtoverifythestabilityofthepooledRRanditsCI.The\nprofile likelihood method was used to derive a robust 95% CI for the heterogeneity\n5\n\nparameter (τ2), with the estimation performed with 50 steps to ensure numerical\nstability.27\nOther sensitivity and subgroup analyses were performed to check the stability\nand robustness of the primary model. The Cochrane RoB 2 tool was the basis for\nassessing the 5 domains of RoB of the included randomised controlled trials (RCTs).28\nPublication bias was assessed using a Doi plot and LFK index due to the small number\nof included studies (n= 7).29 The certainty of evidence for the primary outcome was\njudged using the GRADE framework. The Summary of Findings table was obtained\nfrom GRADEpro.30\nResults\nOur initial search identified 33444 endometriosis documents from four journal\ndatabases (278 were potentially meta-analyses of RCTs) (see Figure 1). Grey\nliterature records were extracted from Google Scholar and Crossref (the three\ncategories stated in lower panel of the Figure S.2). The workflow followed the\nPRISMA procedure, but introduced a semi-automated pre-screening stage prior to\nmanual screening. With the application of fuzzy matching and regex search, 745\nrecords were eliminated. Combined with the two free-text search records, only 29\nrecords required manual screening. The workflow, including record fetching 33444,\ntook only 11 days to complete. This process ultimately yielded two eligible MAs\nwith incomparable comparators. The decision to perform an update of an older MA7\nwas supported by the finding of an automated research tool15 (see Figure S.4). The\ncomputation-assisted systematic review and meta-analysis (CASMA) process was not\nonly efficient, but also reliable. Following data extraction and discussion, seven RCTs\nwere confirmed as eligible for the evidence synthesis.\nA summary of the included studies is presented in Table 1. Four trials were\nconducted in Italy, two in China, and one was in the US or Canada. In these\nstudies, 443 patients received GnRH-a, and 398 received no treatment, a placebo,\nor expectant management. All but one trial31 evaluated the risk of recurrence using\nGnRH-a depots. In one study, 32 the specific drug was not reported; since it was\nadministered subcutaneously, it was classified as a GnRH-a depot. Two trials assessed\nendometriosis recurrence based on symptoms.31,33 Five trials followed patients for 2\nyears, while two had follow-up periods of 1.5 or 5 years. All participants were of\nreproductive age, but the accrual periods varied. The quality of research in two trials\n6\n\nwas undermined by not reporting the accrual period31 or enrolling only 100 patients\nover 4 years.32\nFigure 1 – PRISMA Flow Chart for Study Selection\nPubMed\n(n=66)\nGoogle Scholar (GS)\n(n=140)\nScopus\n(n=68)\nCrossref\n(n=33 168)\nGrey Literature with Full-text\n(n=565)\nFree-text Search\n(n=2)\nDuplicates Excluded\n(fuzzy matching)\n• GS (n=25)\n• Crossref (n=42)\nRegex Search\n(n=772)\nTitles and Abstracts Screened\n(n=29)\nFull-text Records Assessed\n(n=14)\nMeta-analyses Identified\n(n=2)\nDecision\nHandsearch RCT records (n=12)\nFree-text Search (n=1)\nStudies included in\nEvidence Synthesis\n(n=7)\nRecords Excluded from\nManual Screening\n(n=745)\n• Network Meta-analysis\n• Bayesian theorem\n• Fertility only\n• Adenomyosis, etc\nNot Eligible for Review\n(n=15)\n• Not endometriosis\n• Not hormonal therapy\n• Not placebo/expectant\n• Not outcome of interest, etc\nUnmatched Intervention,\nComparator or Design\n(n=12)\nNot Eligible for Meta-analysis\n• Clinical trial (n=1)\n• RCT cohort (n=1)\n• Not GnRH-a (n=1)\n• A comparator affects sex\nhormone levels (n=1)\n• Measure recurrence by each\nsymptom (n=1)\n• Severe attrition bias (n=1)\nMeta-analyses\nIdentificationScreeningEligibilityRCT Records\nIdentification\nEligibility &\nIncluded\nThe primary random-effects (RE) model (Figure 2(a)) pooled data from\n7 papers, including 841 patients and 152 inferred recurrences. The pooled risk ratio\n(RR) was 0.64 (95% CI (0.48 to 0.86)). This was statistically significant as the 95%\nCI excluded the null value (1). The risk reduction was 36% (= (1−0.64)×100)\nfor patients who received this subclass of GnRH-a agents. This analysis included the\n24-month recurrence from a trial that also reported a 12-month recurrence.33 When\nthe analysis was performed with the 12-month outcome, the pooled effect reduced\nto RR = 0.59 (95% CI (0.43 to 0.81)), indicating a slightly stronger protective effect\n(see Figure 3). However, the differences between the two analyses were not practically\nmeaningful, as the 95% CIs overlapped substantially.\n7\n\nTable 1 – Characteristics of Included Studies\nstudy country design accrual baseline age surgery recurrence\ndiagnosis\nintervention medication\nduration\ncontrol follow-up Recurrence\nGnRH-a Control\nHornstein et al. (1997)31 Canada & US Multicentre\n– 2 arms\nunknown stages II-IV I: 30.4±6.0;\nC: 31.1±6.2\nlaser or\nelectrosurgery\nsymptomatic\n– composite\nmeasure\nNafarelin\nnasal 400µg\n6 months Placebo 24 months 17/56 26/53\nVercellini et al. (1999)33 Italy Multicentre\n– 2 arms\n02/92-06/94 stages I-IV I: 30.1±5.4;\nC: 30.0±5.3\nlaparoscopy symptomatic\n– composite\nmeasure\nGoseline SC\n3.6mg\n6 months Expectant 24 months 23/133 32/134\nBusacca et al. (2001)34 Italy Multicentre\n- 2 arms\n01/97-12/99 stages III-IV I: 20-37;\nC: 21-38\nlaparoscopy gynaecological\nexam and/or\npelvic\nechography\nLeuropelin\nacetate SC\n3.75mg\n3 months Expectant 36 months 4/44 4/45\nLoverro et al. (2008)35 Italy 2 arms 01/98-01/99 stages III-IV I: 28.7±4.4;\nC: 28.5±4.5\nlaparoscopic laparoscopic Triptorelin\ndepot 3.75mg\n3 months Placebo 60 months 4/30 2/30\nSesti et al. (2009)36 Italy 4 arms 01/04-08/06 stages III-IV I: 30.8±6.0;\nC: 31.3±5.1\nlaparoscopic\n(uni-) or\n(bil-)ateral\ncystectomy\nEchography\nand\nSecond-look\nlaparoscopy\nGroup 2:\nTryptorelin or\nLeuropelin\n3.75mg\n6 months Placebo 18 months 6/65 3/21\nHuang et al. (2018)32 China 2 arms 01/11-12/14 reclassify\nASRM stages\ninto two\nI: 36.41±5.19;\nC: 36.81±6.92\nlaparoscopy echography GnRH agonist\nSC 3.75mg\n6 months No treatment 12 months 6/50 15/50\nYang et al. (2019)37 China 2 arms 01/15-03/16 stages III-IV 24-35 laparoscopy clinical and\nbiochemical\nassessment\nTriptorelin\n3.75mg IM\n6 months Expectant 24 months 1/65 9/65\n8\n\nBoth analyses (Figures 2(a) and 3) showed negligible heterogeneity, with\nstandard metrics indicatingI 2 = 0.00%and a point estimate ofτ 2 = 0.00.I 2\nexpresses the proportion of variability in a meta-analysis which is explained by\nbetween-trial heterogeneity rather than by sampling error, andτ2 the between-trial\nheterogeneity.9 The complete picture was that the 95% CI forτ2 varied widely\n(0.00 to 3), revealing that the true level of heterogeneity could be highly uncertain.\nThe choice of the random-effects model was, therefore, appropriate to account for this\npotential true heterogeneity, highlighting the limitations of relying on point estimates\nalone when assessing heterogeneity.\nFigure 2 – The Primary Model and Its Leave-One-Out Results\n(a)\n(b)\nThe As-Treated (AT) analysis yielded a pooled effect smaller than the ITT\nanalysis, and the 95% CI was just 0.01 narrower (cf.Figures 2(a) and 4). Although\nthe difference was only at the second decimal place, it suggests that the AT analysis\nslightly overestimates the protective effect of this subclass of GnRH-a agents. At\n9\n\nindividual study level, Nafarelin nasal 400µg for 6 months was shown to be protective\nagainst recurrence after endometriosis surgery in the AT analysis.31\nFigure 3 – Sensitivity Analysis of the 7 papers\nFigure 4 – As-treated Analysis\nThe non-parametric bootstrap analysis failed to converge in only 22 of 10,000\nreplications. It provided a pooled effect estimate, with a 95% BCa CI of(−0.84to\n0.24)onthelog-scale(or(0.43to0.79)ontheRRscale). Thecloseagreementbetween\nthe standard and bootstrap CIs indicates that the pooled effect is robust and not an\n10\n\nartifact of the model’s assumptions. The point estimate forτ2 was0.00, with a 95%\nCI of(0.00to3). The non-parametric bootstrap forτ2 could not provide a reliable CI\ndue to the large number of zero-valued replicates. However, the likelihood function\nofτ2 reinforced that the between-study heterogeneity was low, with0.00as the peak\nof the function (Figure 5). The profiling likelihood 95% CI forτ2 (0.00 to 0.59)\nsignified uncertainty in heterogeneity, although its upper limit was substantially lower\nthan the CI estimated by the standard meta-analysis. A leave-one-out sensitivity\nanalysis (Figure 2b) further confirmed that GnRH-a had a protective effect against\nendometriosis recurrence after surgery; that is, the pooled effect remained statistically\nsignificantandwasnotdisproportionatelyinfluencedbytheremovalofanysingletrial.\nFigure 5 – Between-Study Heterogeneity\nA sensitivity analysis was conducted on a 5-paper model that excluded two trials\nwith severe methodological flaws (see Figure 6(a)).32,36 This model obtained a pooled\nRR of 0.69 (95% CI 0.50, 0.94), which was slightly larger and had a wider 95% CI\nin comparison with the primary model. Although the point estimate ofτ2 remained\n0.00, its 95% CI (0.00, 8.57) was much wider than that of the primary model, whose\nupper limit was 3. As Figure 6(b) illustrates, a leave-one-out analysis showed that\nexcluding the trial by Hornsteinet al.31 from this 5-paper model rendered the pooled\neffect non-significant (p= 0.168). The trial’s substantial difference from the pooled\neffect, combined with the loss of statistical significance, qualifies it as an influential\nstudy or a potential outlier.\nTherisk-of-bias(RoB)summaryplotispresentedinFigure S.5(a). Themajority\nof the trials were rated as having a high RoB in the domains of deviations from\nintended interventions (D2) and outcome measurement (D4). This suggests potential\n11\n\nissues with intervention consistency and outcome assessment across trials. Conversely,\nlow RoB was most prevalent in the domain of missing data (D3) and that of the\nselection of reported results (D5). No trial scored a high risk in the randomisation\nprocess (D1). Individual study scores are shown in Figure S.5(b), where all trials\nwere assessed as having a high overall RoB. We assessed eight papers in total. One\ntrial was eligible, but its results were not reliable; therefore, only its RoB could be\nassessed. Because of the high overall RoB and serious indirectness, the certainty of\nevidence was downgraded twice in the GRADE assessment (see Table S.3).\nFigure 6 – A 5-paper Model\n(a)\n(b)\nFunnel plot was not performed for this study due to the limited number of\nincluded studies (n<10in the sensitivity analysis).9 Instead, a Doi plot and the LFK\nindex were calculated to assess for asymmetry.29 The LFK index was−0.113, which\nfalls within the accepted interval of[−1,1], indicating a lack of statistical evidence\nfor asymmetry (or publication bias). The Doi plot for the seven papers is presented\nin Figure S.6, which visually suggested that two trials, and to a lesser extent a third,\nappeared as potential outliers.\n12\n\nDiscussion\nThis systematic review and meta-analysis (SRMA) of seven RCTs identified a\npromising direction to address the long-standing clinical and methodological\nquestion concerning the impact of hormonal therapy on reducing post-operative\nendometriosisrecurrence. Thisstudydemonstratesthata specificsubclassofGnRH-a\nagents offers a statistically significant protective effect in reducing post-operative\nrecurrence, a finding that directly addresses prevailing clinical scepticism regarding\nthe use of hormonal therapy for managing endometriosis after surgery. Recognising\nautomated tools for SRMA are increasingly free accessible, this paper details a\nComputational-Assisted Systematic Review and Meta-analysis (CASMA) framework,\nmaking it one of the first papers to open the discussion on the use of computer\ntechnologies to achieve validated, efficient, reproducible, and transparent evidence\nsynthesis without violating the PRISMA guidelines.\nThe findings from the seven trials (including 841 patients and 152 inferred\nrecurrences) were subjected to comprehensive validity checks. External validity was\nestablished by cross-checking the extracted data against data reported in published\nreviews – including a Cochrane Systematic Review, which is widely considered a gold\nstandard in evidence synthesis. While not a gold standard practice, this approach\noffers a pragmatic and methodologically robust alternative under the circumstances.\nThe consistency of the results with those reviews implies the extraction was accurate.\nFor internal validity, the primary analysis yielded a pooled RR of 0.64 (a 36%\nreduction in risk), with a 95% CI (0.48 to 0.86). The close agreement with the\nbootstrap 95% CI (0.43 to 0.79) indicates the result is stable and robust. The\nlikelihood profiling method confirmedτ2 = 0.00to be a valid point estimate and\nprovided a much narrower 95% CI than the standard meta-analysis, clarifying the\nbetween-study heterogeneity. Subgroup analyses were performed by replacing a\ndata point in the primary model with one where the follow-up period was shorter,\nand also on the five papers that had no serious methodological limitations. The\nleave-one-out analysis on this 5-paper model identified an influential paper, yet the\nsame analysis showed that the primary model remained stable. All analyses, including\nthe As-Treated analysis, consistently suggested that GnRH-a had a protective effect,\nand the homogeneity assumption failed to be rejected. These diverse statistical\nmethods were applied to establish internal validity and the robustness of the findings,\nnot for the purposes of data dredging. Publication bias was assessed by the Doi plot\nwith the LFK index rather than a funnel plot to obtain a more reliable measure where\nthe sample size was small.\n13\n\nBy focusing on a specific subclass of GnRH-a, the findings provide a focused\ncomplement to existing reviews with a broader scope. For example, one review\nreported that hormonal therapy reduced endometriosis recurrence at both 12 months\nor less (RR=0.30, 95% CI (0.17 to 0.54)) and at 13-24 months (RR=0.40, 95%\nCI (0.27 to 0.58)), but these findings were coupled with substantial heterogeneity\n(I 2 = 58%and57%respectively). 8 Another review found a protective effect across\na broader range of hormonal therapies (RR=0.44, 95% CI (0.30 to 0.66)), though\nwith low reported heterogeneity (I2 = 3%). 6 A direct comparison of the extent of\nthis reduction is challenging, as the estimations are based on different methodologies\nand the definition of recurrence varies widely across studies.5 A previous review had\na similar scope to this paper,7 but the methodology was prone to unit-of-analysis\nerrors and included studies that deviated from standardised definitions. By applying\ncontrol-group splitting and excluding trials with potential confounding factors, the\npresent analysis provides a more internally consistent assessment of this subclass of\nGnRH-a.\nThis study updates the evidence on endometriosis recurrence through the\napplications of recently standardised definitions2, current methodological standards\nand well-established computational techniques. The CASMA framework adds a\nprocess of pre-screening prior to manual paper selection. It only involves applying a\nsemi-automated text-matching approach – fuzzy matching and regex – to efficiently\nexclude 812 irrelevant records. From fetching 33444 records to completing the\npre-screening, it took less than 11 days to obtain a manageable collection of 29\nrecords. Inspired by a previously proposed semi-automated method for analysing\nunstructured medical data,13 this approach balances expert-driven screening with\nautomated solutions and can be applied to larger or more complex datasets without\nviolating PRISMA standards. The efficiency of the CASMA pre-screening minimised\nthe subsequent manual workload. Crucially, this framework eases the decision-making\nprocess by avoiding overloading experts with information, allowing them to efficiently\nadapt and integrate their clinical and methodological expertise via iterative search\nstring refinement. This approach is preferred to applying fully automated but\nstandardised solutions, where researchers are only given the option of accepting or\nrejecting the proposed evidence.\nThe certainty of evidence, as assessed with the GRADE framework, was\nrated as “Low” (see Table S.3). This was primarily due to a very serious RoB\nand serious indirectness. Bias arose most prominently from deviations from\nintended interventions and outcome measure, while indirectness reflected variations in\n14\n\nrecurrence definitions, limiting the generalisability of the findings. The small sample\nsize prevented both a formal subgroup analysis and a full Qualitative Comparative\nAnalysis (QCA). Although QCA was a compelling tool to explore necessary and\nsufficient conditions for recurrence, the limited number of studies (N= 7) and high\ndata sparsity precluded a meaningful interpretation. This paper demonstrates a case\nof applying CASMA to synthesise robust evidence from a large body of literature\nwith much ambiguity circulating, offering a promising framework to synthesise the\ncurrent and best evidence to facilitate Evidence-Based Medicine practice.\nCompeting Interests\nThe author declares no competing interests.\nFunding Statement\nThis research received no specific grant from any funding agency in the public,\ncommercial, or not-for-profit sectors.\nAcknowledgements\nI am deeply indebted to Professor Bruno Falissard of Université Paris-Saclay for his\nintellectual guidance on this project and throughout the master degree program. My\nthanks also extend to the dedication of other professors and Mr. Fares Youbi for\nhis generous assistance. I would like to thank Miss Meriem Souici for her assistance\nwith paper selection and some data extraction. I sincerely thank Professor Richard\nF. Heller of Universities of Manchester, UK, and Newcastle, Australia for recruiting\nme as a volunteer tutor for his charity foundation; the experience inspired me to find\nmy knowledge and skills for health-related research.\nThe opinions expressed in this article are those of the author and do not\nnecessarily reflect the views or policies of the affiliated institutions. Authorship is\ndefined by the ICMJE criteria.\n15\n\nEthical Approval\nThis systematic review and meta-analysis was completed as part of the requirements\nfor a Master of Public Health (MPH) degree in Methodology and Biostatistics for\nBiomedical Research, with research directions approved by Professor Bruno Falissard\nat the Faculty of Medicine, Université Paris-Saclay. Since this study did not involve\nany human or animal subjects or identifiable data, it was exempt from further\ninstitutional review.\nProtocol Registration and Data/Code Availability\nThe protocol for this research is registered on OSF. The DOI is https://doi.org/10.\n17605/OSF.IO/R2DFA. The timestamp is 5 September 2025.\nAll data used were extracted from published studies. The data needed to\nreproduce the results are included in the main content. Other data and theRcodes\nwill be deposited in the public OSF repository when this manuscript is published in\na peer-reviewed journal.\nReferences\n1. Koninckx, P. R., Ussia, A., Adamyan, L., Tahlak, M., Keckstein, J., Martin,\nD. C.et al.(2021) The epidemiology of endometriosis is poorly known as the\npathophysiology and diagnosis are unclear,Best Practice & Research Clinical\nObstetrics & Gynaecology, 71, 14–26.\n2. Tomassetti, C., Johnson, N. P., Petrozza, J., Abrao, M. S., Einarsson, J. I.,\nHorne, A. W., Lee, T. T., Missmer, S., Vermeulen, N., Zondervan, K. T.,\nGrimbizis, G., De Wilde, R. L., International Working Group of AAGL, E., ESGE\nand WES (2021) An international terminology for endometriosis, 2021,Human\nReproduction Open, 2021(4), hoab029.\n3. 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(2018) Clinical efficacy\nand safety of gonadotropin-releasing hormone agonist combined with laparoscopic\nsurgery in the treatment of endometriosis,Int J Clin Exp Med, 11(4), 4132–4137.\n33. Vercellini, P., Crosignani, P. G., Fadini, R., Radici, E., Belloni, C. and Sismondi,\nP. (1999) A gonadotrophin-releasing hormone agonist compared with expectant\nmanagement after conservative surgery for symptomatic endometriosis,BJOG\nAn International Journal of Obstetrics & Gynaecology, 106(7), 672–677.\n34. Busacca, M., Somigliana, E., Bianchi, S., De Marinis, S., Calia, C., Candiani,\nM. and Vignali, M. (2001) Post-operative GnRH analogue treatment after\nconservative surgery for symptomatic endometriosis stage III–IV: a randomized\ncontrolled trial,Human Reproduction, 16(11), 2399–2402.\n35. Loverro, G., Carriero, C., Rossi, A. C., Putignano, G., Nicolardi, V. and Selvaggi,\nL. (2008) A randomized study comparing triptorelin or expectant management\nfollowing conservative laparoscopic surgery for symptomatic stage III–IV\nendometriosis,European journal of obstetrics & gynecology and reproductive\nbiology, 136(2), 194–198.\n36. Sesti, F., Capozzolo, T., Pietropolli, A., Marziali, M., Bollea, M. R. and Piccione,\nE. (2009) Recurrence rate of endometrioma after laparoscopic cystectomy:\na comparative randomized trial between post-operative hormonal suppression\ntreatment or dietary therapy vs. placebo,European journal of obstetrics &\ngynecology and reproductive biology, 147(1), 72–77.\n37. Yang, Y., Zhu, W., Chen, S., Zhang, G., Chen, M. and Zhuang, Y. (2019)\nLaparoscopic surgery combined with GnRH agonist in endometriosis,J Coll\nPhysicians Surg Pak, 29(4), 313–316.\n38. Hair, J. F., Hult, G. T. M., Ringle, C. M. and Sarstedt, M. (2022)Partial least\nsquares structural equation modeling. Thousand Oaks, CA: Sage.\n19\n\nSupplementary Material\nA Research Domain Grows Exponentially\nFigure S.1 – The Growth of the Publications in\nEndometriosis\nFigure S.2 – An Approximation of Endometriosis\nResearch in the Pipeline†\n†Due to limited computational resources, the records\ncould only be deduplicated using the prefixes of the\nDOIs. Thismethodisnotasaccurateas fuzzymatching.\n20\n\nExtracting Records and Selection Process\nSearch terms were mutually agreed upon by ST and MS. The primary literature\nsearch (for meta-analyses of RCTs) was conducted from 6 June to 14 July 2025.\nRecords were collected from multiple sources: PubMed yielded 37602 documents\non 6 June 2025; Google Scholar (GS) retrieved 583000 documents on 10 June 2025;\nCrossref retrieved 33169 documents on 17 June 2025; and Scopus retrieved 52561\ndocuments on 17 June 2025.\nBased on repeated attempts, it was determined by ST that the following syntax\nwas the most reliable for screening out relevant records from PubMed:\n“((((endometriosis) AND ((((((((((((((Hormonal contraceptive) OR (Progestin\ntherapy)) OR (Gonadotropin-releasing hormone)) OR (Aromatase inhibitor)) OR\n(add-back therapy)) OR (non-steroidal anti-inflammatory drug)) OR (steroid))\nOR (androgen))) OR (hormone replacement)) OR (hormone therapy)) OR\n(hormone-related therapy)) OR (hormone suppression)) OR (hormonal alteration)))\nAND ((randomised controlled trial) OR (clinical trial))) AND (meta analysis))”\nSubsequently, ST adapted this keyword set to search Google Scholar (GS). GS\nretrieved over 4160 records with these keywords. Given that itsrobots.txtfile\nrestricts web scraping, a maximum of 100 records could be obtained. To heighten\nthe chance of retrieving relevant manuscripts within that limit, ST included outcome\nkeywords in the search. The record count dropped from 4160 to 1470. ST fetched\n140 webpages and prioritised the extraction of the most relevant records. The applied\nkeyword set was as follows:\n“((((endometriosis) AND ((((((((((((((Hormonal contraceptive) OR (Progestin\ntherapy)) OR (Gonadotropin-releasing hormone)) OR (Aromatase inhibitor)) OR\n(add-back therapy)) OR (non-steroidal anti-inflammatory drug)) OR (steroid))\nOR (androgen))) OR (hormone replacement)) OR (hormone therapy)) OR\n(hormone-related therapy)) OR (hormone suppression)) OR (hormonal alteration)))\nAND ((randomised controlled trial) OR (clinical trial))) AND (meta-analysis)) AND\n((cancer) OR (recurrence) OR (adverse effect))”\nData from the 140 records were extracted using anRprogramme written by ST. A\ndissimilarity matrix of all the titles was computed using fuzzy matching. Levenshtein\ndistance was the computational basis for this process. It yielded results similar to\nthose obtained by the nativeagrep() Rfunction. Any count smaller than 5, but\nnot on the diagonal of the matrix, was considered a potentially duplicated pair. The\n21\n\nthreshold was set to 5 because, on average, an English word contains 5 letters. The\nresults suggested the elimination of 25 records. This approach was applied to check\nfor duplicates both within and across databases. A manual review of the records\nsuggested that the relevance of subsequent entries was low, indicating a low chance\nof having missed crucial records.\nCrossref only allowed case-insensitive searches with the exact word,\n“endometriosis.” When more terms were added, many more titles were retrieved\nthan were relevant to the term “endometriosis.” The system did not allow fetching\nthe titles and abstracts of records with full-text. ST first fetched the title, creation\ndate, DOI, publisher, type, and indexed information for each of 33169 records. ST\nthen fetched titles and DOIs for the records with full text. Of the27 886records\nwith full-text,565fell into the categories of posted-content, proceedings, and reports\n(referred to as grey literature).42duplicated records were eliminated. Regex\nsearches were performed on388abstracts and their respective titles. For titles\nwithout abstracts, ST reviewed the abstracts of the records indexed by the chosen\nsyntaxes. A variation of this approach was applied to the records obtained from\nother databases. Figure S.2 shows the research trend after records with unique DOI\nprefixes. This only gave an approximate view about the trend, because a single\nrecord could be registered on different platforms. A more accurate view could not\nbe obtained due to insufficient computational power to apply fuzzy matching to the\ntitles.\nOnly six meta-analyses that fitted the research topic were identified. Of these,\nonly three reviewed RCT primary papers where the interventions were Diegogest, a\nGnRH-a, and a GnRH-a with Chinese medicine. The latter was not considered a\npotential topic because Chinese medicine is a broad field, which effectively tested an\nunknown agent. Due to a tight timeline, the decision was made to hand-search the\nRCTs within meta-analyses from a related domain and perform a free-text search.\nThe eligibility was confirmed during data extraction rather than independent review.\n22\n\nManual Process of Paper Selection\nTable S.1 – The 29 Records Shortlisted Following the Computational-Assisted Process\ndatabase author title round 1 assess round 2 potential action note\nMS ST MS ST\ncrossref Shen et al.\n(2020)\nFertility outcomes of deep\ninfiltrating endometriosis with\nfertility desire—a meta\nanalysis\n0 -1 0 -1 -1 -1 Studied fertility desire only\n– Outside research scope\nexcluded\ncrossref Qing et al.\n(2004)\nSystematic Review and\nMeta-analysis on the Effect of\nAdjuvant\nGonadotropin-releasing\nHormone Agonist (GnRH-a)\non Pregnancy Outcomes in\nWomen with Endometriosis\nFollowing Conservative\nSurgery.\n-1 -1 -1 -1 -1 -1 Studied fertility desire only\n– outside research scope\nexcluded at round 1\nGS Yang (2024) Endometriosis and aspirin: a\nsystematic review\n-1 -1 -1 -1 -1 -1 The study compared\nnon-human samples.\nexcluded at round 1\nGS Mikuš et al.\n(2022)\nState of the art, new treatment\nstrategies, and emerging drugs\nfor non-hormonal treatment of\nendometriosis: a systematic\nreview of randomized control\ntrials\n-1 1 -1 -1 -1 -1 Three subgroups:\nantiangiogenic agents,\nimmunomodulators, and\nnatural components. Pelvic\npain is not a chosen research\ntopic.\nexcluded at round 1\nPubMed Johnstone\net al.\n(2015)\nControversies in the\nManagement of\nEndometrioma: To Cure\nSometimes, to Treat Often, to\nComfort Always?\n-1 -1 -1 -1 -1 -1 Its abstract is unstructured.\nThe MeSH terms indicated\nthat it is a meta-analysis.\nThe abstract suggests that\nrecurrence was not an\noutcome measure.\nexcluded at round 1\nPubMed Chen et al.\n(2020)\nEffect of melatonin for the\nmanagement of endometriosis:\nA protocol of systematic\nreview and meta-analysis.\n0 0 0 -1 -1 -1 The study focuses on the\neffect of melatonin; it is\nunclear if both beneficial\nand adverse effects were\nexamined.\nexcluded\nPubMed Deng et al.\n(2020)\nChinese herbal medicine for\nprevious cesarean scar defect:\nA protocol for systematic\nreview and meta-analysis.\n-1 -1 -1 -1 -1 -1 The study focuses on\nChinese herbal medicine for\nprevious Caesarean scar\ndefect, not endometriosis.\nexcluded at round 1\nPubMed Zhang et al.\n(2021)\nThe efficacy and safety of\nKuntai capsule combined with\nleuprorelin acetate in the\ntreatment of endometriosis: A\nprotocol for systematic review\nand meta-analysis.\n1 1 1 -1 -1 -1 Multiple, heterogeneous\ninterventions. Translating\nthe evidence into clinical\npractice would be difficult..\nexcluded\nPubMed Gao et al.\n(2022)\nSalvia miltiorrhiza-Containing\nChinese Herbal Medicine\nCombined With GnRH\nAgonist for Postoperative\nTreatment of Endometriosis:\nA Systematic Review and\nmeta-Analysis.\n1 1 1 -1 1 1 Chinese Herbal Medicine is\na broad area. It is akin to\nstudying the relationship\nbetween an unspecified\nagent of unspecified\nquantity and endometriosis\nrecurrence.\nexcluded\nPubMed Allahqoli et\nal. (2024)\nNeuropelveology for\nEndometriosis Management:\nA Systematic Review and\nMultilevel Meta-Analysis.\n-1 -1 -1 -1 -1 -1 The focus is on a surgical\nmethod (Neuropelveology)\nexcluded at round 1\nPubMed Piacenti et\nal. (2025)\nDienogest vs. combined oral\ncontraceptive: A systematic\nreview and meta-analysis of\nefficacy and side effects to\ninform evidence-based\nguidelines.\n1 1 1 -1 -1 -1 The author analysed RCT\nand observational studies\ntogether.\nexcluded\nScopus Lata and\nSarwar\n(2014)\nEffectiveness of conservative\nsurgery and adjunctive\nhormone suppression therapy\nversus surgery alone in the\ntreatment of symptomatic\nendometriosis: A systematic\nreview with meta-analysis\n-1 1 -1 -1 -1 -1 The study compares\nadjunctive hormone\nsuppression therapy to\nsurgery alone, measuring\npelvic pain and recurrence.\nexcluded at round 1\nContinued on the next page\n23\n\ndatabase author title round 1 assess round 2 potential action note\nMS ST MS ST\nScopus Chen (2014) Effectiveness and safety of\npostoperative GnRH-a versus\nlaparoscopy alone for\nendometriosis: A\nmeta-analysis\n0 0 0 -1 -1 -1 Full-text paper was\nunavailable; excluded due to\nan inability to contact the\nauthors.\nexcluded\nScopus Liu (2021) Dienogest as a Maintenance\nTreatment for Endometriosis\nFollowing Surgery: A\nSystematic Review and\nMeta-Analysis\n1 1 1 -1 -1 -1 Comparators:\nLevonorgestrel-releasing\nintrauterine system\n(LNG-IUS) and\ngonadotropin-releasing\nhormone analogs (GnRH-a),\nor non-treatment (NT).\nRecurrence is an outcome.\nexcluded\nScopus Whelan\n(2022)\nRisk Factors for Ovarian\nCancer: An Umbrella Review\nof the Literature\n-1 -1 -1 -1 -1 -1 It is a meta-analysis of\ncohort studies, which is not\nthe study design of interest.\nexcluded at round 1\nScopus Ivanov\n(2023)\nThe issues of endometriosis\nhormonal treatment in\nreproductive age women\n-1 -1 -1 -1 -1 -1 The full text is written in\nRussian\nexcluded at round 1\nScopus de Souza\nGaio et al.\n(2025)\nClinical effectiveness of\nprogestogens compared to\ncombined oral contraceptive\npills in the treatment of\nendometriosis: A systematic\nreview and meta-analysis\n1 1 1 1 1 1 All studies are RCTs. The\nstudy compares\nProgestogens vs OC, and\nmeasures pelvic pain,\ndysmenorrhea, and\npsychological symptoms.\nindependent topic\nScopus Li (2024) Efficacy and safety of\ndienogest in the treatment of\nendometriosis: a meta-analysis\n-1 -1 -1 -1 -1 -1 The full text is written excluded at round 1\nScopus Thiel (2024) The Effect of Hormonal\nTreatment on Ovarian\nEndometriomas: A Systematic\nReview and Meta-Analysis\n-1 -1 -1 -1 -1 -1 Mixed study types excluded at round 1\nScopus Shi (2022) Effect and safety of\ndrospirenone and\nethinylestradiol tablets (II) for\ndysmenorrhea: A systematic\nreview and meta-analysis\n-1 -1 -1 -1 -1 -1 Dysmenorrhea is not\nendometriosis\nexcluded at round 1\nScopus Peng (2021) Dydrogesterone in the\ntreatment of endometriosis:\nevidence mapping and\nmeta-analysis\n-1 -1 -1 -1 -1 -1 Mixed study types excluded at round 1\nScopus Chen (2020) Pre- and postsurgical medical\ntherapy for endometriosis\nsurgery\n-1 -1 -1 -1 -1 -1 The study states hormonal\nsuppression is effective but\nmost studies are covered by\nother review papers.\nHormonal suppression is a\nbroad topic. It does not suit\na project with a tight\ntimeline.\nexcluded at round 1\nScopus Zakhari\n(2020)\nDienogest and the Risk of\nEndometriosis Recurrence\nFollowing Surgery: A\nSystematic Review and\nMeta-analysis\n1 1 1 -1 -1 -1 The paper compares\ndienogest to expectant\nmanagement, but analyses\nobservational studies.\nexcluded\nScopus Jeng (2014) A comparison of progestogens\nor oral contraceptives and\ngonadotropin-releasing\nhormone agonists for the\ntreatment of endometriosis: A\nsystematic review\n-1 -1 -1 -1 -1 -1 The author noted that\nproceeding to a\nmeta-analysis was\nimpossible.\nexcluded at round 1\nScopus Wu et al.\n(2014)\nClinical efficacy of add-back\ntherapy in treatment of\nendometriosis: A\nmeta-analysis\n-1 1 0 -1 1 1 The study compares\nGnRH-a with add-back\ntherapy versus GnRH-a\nalone and addresses side\neffects such as osteoporosis\nand menopausal syndrome.\nmay match Gao et\nal.\nScopus Wu, Wu\nand Liu\n(2013)\nOral contraceptive pills for\nendometriosis after\nconservative surgery: A\nsystematic review and\nmeta-analysis\n-1 1 0 -1 1 1 The study compares OC to\nno OC and other drugs\nincluding gestrinone,\nmifepristone, or GnRH-a,\nmeasuring recurrence and\nremission.\nstudied recurrence,\nbut can’t match\nZheng et al. (2016)\nContinued on the next page\n24\n\ndatabase author title round 1 assess round 2 potential action note\nMS ST MS ST\nScopus Wong and\nLim (2011)\nHormonal treatment for\nendometriosis associated\npelvic pain\n1 1 1 -1 1 1 It is a review of RCTs that\nsynthesizes evidence from\nthree trial groups. The trials\nthat compared combined\noral contraceptives with\nprogestogen might align\nwith another meta-analysis.\nHowever, the outcome\nmeasures were\ndysmenorrhea, not\nendometriosis recurrence.\nexcluded\nKeyword\nsearch\nZheng et al.\n(2016)\nCan postoperative GnRH\nagonist treatment prevent\nendometriosis recurrence? A\nmeta-analysis?\n1 1 1 -1 1 1 It reviewed RCTs and\nrecurrence of managing\noperated endometriosis\npatient with GnRH agonist.\nindependent topic\nKeyword\nsearch\nZakhari et\nal. (2021)\nEndometriosis recurrence\nfollowing post-operative\nhormonal suppression: a\nsystematic review and\nmeta-analysis\n1 1 1 1 -1 -1 The paper compares\nhormonal therapies with\nexpectant management, and\nrecurrence is an outcome. It\nanalyses both RCTs and\nobservational studies\ntogether.\nIt is of reference\nvalue (mixed study\ntypes)\nN.B. A three-point scoring system was applied for records during the screening process:−1for rejected, 0\nfor unclear, and 1 for included (full-text retrieval). In both screening stages, records with a score of 0 were\nre-evaluated.\n25\n\nInter-Rater Reliability Plots\nFigure S.3 – Distribution of Bootstrapped Inter-Rater Reliability at Two Stages\n(a)\n (b)\nThe two density graphs show the distribution of the weighted absolute Kappa (κ)\nobtained from2 000non-parametric bootstrap replications. For Title/Abstract\nscreening, the distribution exhibited slight left skew (−0.23) and was mesokurtic\n(−0.373). The meanκwas0.68, and the medianκwas0.69. For Full-text screening,\nthe distribution was right skewed (0.46), mesokurtic (0.65), and visually exhibited\nbimodality. The meanκwas0.04, and the medianκwas0.00. Both distributions\nare characterized by having skewness in an excellent range ([−1,+1]) and kurtosis\nin a generally acceptable range ([−2,+2]).38 The agreement for the Title/Abstract\nreview was substantial, but that for the Full-text review was poor.17\n26\n\nDeduplication through Fuzzy Matching\nTable S.2 – An Example of Identifying String Dissimilarities\nPost-operative GnRH analogue treatment\nafter conservative surgery for symptomatic\nendometriosis stage III–IV: a randomized\ncontrolled trial\nUse of nafarelin versus placebo after\nreductive laparoscopic surgery for\nendometriosis.\nClinical efficacy and safety of\ngonadotropin-releasing hormone agonist\ncombined with laparoscopic surgery in the\ntreatment of endometriosis\nA randomized study comparing triptorelin\nor expectant management following\nconservative laparoscopic surgery for\nsymptomatic stage III–IV endometriosis\nRecurrence rate of endometrioma after\nlaparoscopic cystectomy: a comparative\nrandomized trial between post-operative\nhormonal suppression treatment or dietary\ntherapy vs. placebo\nA gonadotrophin-releasing hormone\nagonist compared with expectant\nmanagement after conservative surgery\nfor symptomatic endometriosis\nA gonadotrophin-releasing hormone\nagonist compared with expectant\nmanagement after conservative surgery\nfor symptomatic endometriosis\nLaparoscopic surgery combined with\nGnRH agonist in endometriosis\nPost-operative GnRH analogue treatment\nafter conservative surgery for\nsymptomatic endometriosis stage III–IV:\na randomized controlled trial\n0 98 114 105 134 99 99 107\nUse of nafarelin versus placebo after\nreductive laparoscopic surgery for\nendometriosis.\n98 0 84 93 136 86 86 58\nClinical efficacy and safety of\ngonadotropin-releasing hormone agonist\ncombined with laparoscopic surgery in\nthe treatment of endometriosis\n114 84 0 92 129 84 84 95\nA randomized study comparing triptorelin\nor expectant management following\nconservative laparoscopic surgery for\nsymptomatic stage III–IV endometriosis\n105 93 92 0 137 76 76 112\nRecurrence rate of endometrioma after\nlaparoscopic cystectomy: a comparative\nrandomized trial between post-operative\nhormonal suppression treatment or\ndietary therapy vs. placebo\n134 136 129 137 0 136 136 138\nA gonadotrophin-releasing hormone\nagonist compared with expectant\nmanagement after conservative surgery\nfor symptomatic endometriosis\n99 86 84 76 136 0 0 90\nA gonadotrophin-releasing hormone\nagonist compared with expectant\nmanagement after conservative surgery\nfor symptomatic endometriosis\n99 86 84 76 136 0 0 90\nLaparoscopic surgery combined with\nGnRH agonist in endometriosis\n107 58 95 112 138 90 90 0\nN.B. The 6th and 7th titles exemplify the results of applying fuzzy matching to identify duplicated\ntitles. Where the number of titles is enormously large, any score below 5 and located off the diagonal\nof the matrix represents a pair of titles with close similarity and may be further inspected.\n27\n\nNetwork of Publications\nFigure S.4 – The Findings of an AI Research Tool15\nN.B. A targeted search was conducted on 14 July 2025 to verify that the meta-analysis\nby Zhenget al.7 was the most recent meta-analysis of RCTs on our chosen topic. The\ntwo other meta-analyses published around 2020 included one that synthesised both\nRCTsandobservationalstudies 6 andanotherthatfocusedonsurgeries. Consequently,\nthe decision to perform a targeted search rather than running another full selection\nprocess was appropriate and not driven solely by the project timeline.\n28\n\nRisk of Bias\nFigure S.5 – Summary of Risk of Bias (RoB2)\n(a)\n(b)\nPublication Bias\nFigure S.6 – Less Restrictive Measures of Publication Bias\n29\n\nNon-parametric Bootstrap Analysis\nThe following code was applied to obtain the non-parametric bootstrap results to\nverify the pooled risk ratio, between-study heterogeneity and the corresponding 95%\nCIs.\n1# Non - P a r a m e t r i c\nboot . func<- function( dat , indices ) {\nsel<-dat [ indices ,]\nres<- try( s u p p r e s s W a r n i n g s ( rma ( yi ,vi,data= sel ) ) , silent = TRUE )\n5if(inherits( res , \" try - error \" ) ) {\nNA\n}else{\nc(coef( res ) , vcov ( res ) , res$tau2 , res$ se. tau2 ^2)\n}\n10}\nset. seed (print( seed . nbr<- sample(2^16 ,1) ) ) # 14453\n( res . boot<-boot :: boot ( dat , boot . func , parallel = \" m ul ti c or e \" ,R=10000) )\nrange( res . boot$ t[ ,3][! is.na( res . boot$ t[ ,3]) ])\nattr( res . boot , \" seed . nbr \" )<-seed . nbr\n15saveRDS ( res . boot , \" MA - Result_bo ot st ra p_np . rds \" )\n30\n\nGRADE Assessment\nTable S.3 – Summary of Findings†‡\nA subclass of GnRH compared to placebo/expectant for patients who were operated for endometriosis\nBibliography:\nCertainty assessment Summary of findings\nParticipants\n(studies)\nFollow-up\nRisk of bias Inconsistency Indirectness Imprecision Publication\nbias\nOverall certainty\nof evidence\nStudy event rates (%)\nRelative\neffect\n(95%\nCI)\nAnticipated absolute effects\nWith\nplacebo/expectant\nWith a\nsubclass\nof GnRH\nRisk with\nplacebo/expectant\nRisk\ndifference\nwith a\nsubclass\nof GnRH\nThe risk of endometriosis recurrence in patients managed by a subclass of GnRH after surgery (follow-up: range 12 months to 60\nmonths; assessed with: objective, subjective or mixed assessment)\n841\n(7 RCTs)\nvery\nserious1,2,3,4,5,6,7,a,b\nnot serious serious not serious all plausible\nresidual\nconfounding\nwould\nsuggest\nspurious\neffect, while\nno effect\nwas\nobserved\n⨁ ⨁ ◯ ◯\nLow1,2,3,4,5,6,7,a,b\n91/398 (22.9%) 61/443\n(13.8%)\nRR 0.64\n(0.48 to\n0.86)\n91/398 (22.9%) 82 fewer\nper 1,000\n(from 119\nfewer to 32\nfewer)\nCI: confidence interval; RR: risk ratio\nExplanations\na. The overall risk of bias of each paper is high.\nb. One eligible paper was excluded from the main synthesis and only assessed for risk of bias due to substantial loss to follow-up after randomization.\nReferences\n1.Busacca et al. Post-operative GnRH analogue treatment after conservative surgery for symptomatic endometriosis stage III--IV: a randomized controlled trial .Human Reproduction; 2001.\n2. Hornstein et al. Use of nafarelin versus placebo after reductive laparoscopic surgery for endometriosis.; 1997.\n3.Huang et al. Clinical efficacy and safety of gonadotropin-releasing hormone agonist combined with laparoscopic surgery in the treatment of endometriosis.Int J Clin Exp Med; 2018.\n4.Loverro et al. A randomized study comparing triptorelin or expectant management following conservative laparoscopic surgery for symptomatic stage III--IV endometriosis.European journal of obstetrics &\ngynecology and reproductive biology ; 2008.\n5.Sesti et al. Recurrence rate of endometrioma after laparoscopic cystectomy: a comparative randomized trial between post-operative hormonal suppression treatment or dietary therapy vs. placebo .European\njournal of obstetrics & gynecology and reproductive biology; 2009.\n6.Vercellini et al. A gonadotrophin-releasing hormone agonist compared with expectant management after conservative surgery for symptomatic endometriosis .BJOG: An International Journal of Obstetrics &\nGynaecology; 1999.\n7.Yang et al. Laparoscopic surgery combined with GnRH agonist in endometriosis.J Coll Physicians Surg Pak; 2019.\n†The table was obtained from GRADEpro;30\n‡Endometriosis treatment outcome is affected by surgical skills.1 Since the studies were conducted at different times and in different countries, skills might vary, and spurious confounding\nmay exist;\na. Risk of bias: Downgraded for the prevalent high/unclear risk of bias in included studies;\nb. Risk of bias: Downgraded because one eligible paper was excluded due to substantial loss to follow-up after randomization, but before the study started;\nc. Risk difference: Estimated from the RR by the application automatically. It was estimated that 82 fewer per1 000patients who were managed by this subclass of GnRH-a after endometriosis\nsurgery would develop recurrence, compared with those who were not on any GnRH-a therapy. The estimated 95% CI ranged from 119 fewer to 32 fewer per1 000patients.\n31","source_license":"CC0","license_restricted":false}