Introduction

Fibromyalgia (FM), a chronic centralized pain syndrome, is characterized by widespread musculoskeletal pain, fatigue, sleep disturbances, and cognitive impairment.1 With a global prevalence of 2–8% in the general population and a striking 3:1 female-to-male predominance, FM is most commonly observed in women aged 30–60 years.2 The pathophysiology of FM remains incompletely understood and is likely multifactorial, involving genetic susceptibility, neuroendocrine and immunological dysregulation, and environmental stressors.3 Once regarded as a musculoskeletal pain disorder, FM is currently acknowledged as a multisystem condition that encompasses genitourinary, gastrointestinal, and neuropsychiatric features.4 Women with FM have higher rates of anxiety, depression, headache syndromes, chronic pelvic pain (CPP), and irritable bowel syndrome (IBS) than the general population.5 In response to this complex symptomatology, clinical management has evolved to address fibromyalgia as a systemic illness rather than a localized muscular dysfunction. Current treatment regimens thus integrate pharmacological therapy with non-pharmacological interventions, including physical therapy, structured exercise, patient education, and cognitive behavioral therapy, reflecting a clinical shift toward phenotype-informed management.6

Lower urinary tract pain, including bladder and urethral pain in women, is considered a component of CPP according to the International Continence Society working group.7 Lower urinary tract symptoms (LUTS), a term coined by Paul Abrams in 1994 to avoid organ-specific labeling, include storage (eg, frequency, urgency, nocturia, incontinence), voiding (eg, slow stream, hesitancy), and post-micturition symptoms (eg, incomplete emptying) without reference to pain.8 Previous retrospective studies have reported that LUTS may be associated with IBS, as well as with depression and anxiety.9 Despite these potential connections, no meta-analysis has systematically evaluated the association of FM with lower urinary tract pain and LUTS in women.

This meta-analysis aims to quantitatively synthesize epidemiological evidence for the association between FM and lower urinary tract pain as well as LUTS in women, and to discuss possible pathophysiological explanations proposed in prior literature. By integrating the available evidence, our findings may help to distinguish priorities for future prospective investigation in this population.

Methods

This meta-analysis was prospectively registered with the International Prospective Register of Systematic Reviews (PROSPERO) prior to data extraction (Registration ID: CRD420251073873). The systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 checklist.10

Search Strategy

A systematic search was conducted in the following electronic databases from January 1990 to December 2025: PubMed/MEDLINE, Embase, Web of Science Core Collection, and CINAHL. Reference lists of included studies and relevant reviews were manually screened. No language restrictions were applied. For potentially eligible non-English studies, full texts were translated when necessary for eligibility assessment and data extraction.

The search strategy targeted two conceptual domains: FM, and lower urinary tract pain as well as LUTS. The search combined controlled vocabulary terms (MeSH, Emtree, and CINAHL Headings) with free-text terms in title/abstract fields. For Web of Science Core Collection, which does not have a standardized controlled vocabulary like MeSH or Emtree, only free-text terms were employed. Boolean operators were applied hierarchically: OR within each conceptual domain, AND between domains. The search terms and strategy are reported in Supplementary Material 1.

PECOS Framework Population (P)

Inclusion: Adult women (≥ 18 years) with FM.

Exclusion: Adolescents (<18 years); pregnant women; women with FM secondary to surgical procedures, physical trauma, or specific pathologies (eg, systemic lupus erythematosus).

Exposure (E)/Comparator (C)

Exposure: A diagnosis of FM based on the American College of Rheumatology (ACR) criteria or other clinically applied diagnostic approaches.

Comparator: Women without a diagnosis of FM (for cohort/case-control studies) or age-matched healthy women (for cross-sectional studies).

Outcome (O)

Inclusion: Studies that reported effect estimates of the association between FM and lower urinary tract pain or LUTS. Studies that did not report effect estimates but provided sufficient data to calculate crude odds ratios (ORs) with 95% confidence intervals (CIs) were also included.

Exclusion: Studies were excluded if the reported lower urinary tract pain or LUTS were secondary to surgical procedures, physical trauma, or specific pathologies (eg, urinary tract infection, pelvic neoplasms).

Study Design (S)

Included designs: Cohort studies, case-control studies, and cross-sectional studies.

Excluded designs: Intervention studies, case reports, and animal studies.

Additional exclusion criteria: Non-original research (reviews, editorials, commentaries, letters, and book chapters), conference abstracts, unpublished dissertations/theses, and grey literature sources.

Study Selection

All identified citations were exported from electronic databases to EndNote 21.5 (Clarivate, Philadelphia, PA). Duplicate records were removed using EndNote’s built-in “Find Duplicates” function. Two reviewers (XY Wang and JP Liu) independently screened titles and abstracts against the predefined PECOS criteria. Studies that were clearly irrelevant were excluded. Potentially eligible studies underwent full-text review and were assessed independently by two reviewers. Disagreements were resolved through discussion or by consulting a third reviewer (Y Zhang). The study selection process was documented using a PRISMA flow diagram (Figure 1).

Figure 1 PRISMA flow diagram of the study selection process.

Data Extraction

Two reviewers (XY Wang and JP Liu) independently extracted data from the included studies using a specifically designed form. Discrepancies were resolved through discussion or by consulting a third reviewer (Y Zhang). We contacted the corresponding authors of three studies, but none of them provided the information necessary for our analysis. All extracted data underwent double-entry verification before analysis. The extracted data included:

Study characteristics: First author, publication year, country of study conduct, study design, total sample size, subgroup sizes, and mean age.

Outcome measures: ORs with 95% CIs were reported to assess the association between FM and lower urinary tract pain or LUTS. If studies reported multiple effect estimates, we extracted the most fully adjusted OR. If studies did not report effect estimates, we calculated a crude OR and 95% CI from contingency table data.

Methodological details: FM diagnostic approaches, FM duration, outcome definitions (lower urinary tract pain or LUTS phenotypes), outcome ascertainment, and confounding variables adjusted for in statistical analyses.

Risk of Bias Assessment

Two reviewers (XY Wang and JP Liu) independently assessed risk of bias using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist specific to each study design (Supplementary Material 2).11 Critical domains (selection, measurement, confounding) were predefined as: cross-sectional studies (Item 3, 4, and 5), case-control studies (Item 2, 4, and 6), and cohort studies (Item 3, 4, and 7).11 Each item was scored as “Yes”, “No”, “Unclear”, or “Not applicable”. We prespecified decision rules to categorize studies as low, moderate, or high risk of bias based on critical and non-critical items. Finally, studies were rated as:

Low risk: All critical domains scored “Yes”, and ≤ 1 non-critical issue.

Moderate risk: One critical “Unclear”, and ≤ 1 non-critical issue; or 2–3 non-critical issues only.

High risk: Any critical “No”; ≥ 2 critical “Unclear”; one critical “Unclear”, and ≥ 2 non-critical issues; or ≥ 4 non-critical issues only.

Discrepancies were resolved through discussion or by consulting a third reviewer (Y Zhang).

Statistical Analysis

Meta-analyses were performed using Stata 19 (StataCorp LLC, USA). For dichotomous outcomes, we extracted ORs and 95% CIs, which were then log-transformed for analysis. Random-effects models with restricted maximum likelihood were used throughout, given expected clinical and methodological heterogeneity across studies. All tests were two-sided, with p < 0.05 considered statistically significant. Quantitative synthesis was performed only for outcomes reported by ≥ 3 studies; outcomes with < 3 studies were described narratively.

Statistical heterogeneity was evaluated using between-study variance (τ2), the I2 statistic and Cochran’s Q-test (p < 0.10). I2 was interpreted as follows: 0–40% low, 30–60% moderate, 50–90% substantial, and 75–100% considerable heterogeneity.12 Clinical and methodological heterogeneity were assessed qualitatively according to participant characteristics, study design, FM diagnostic approaches, outcome definitions, and extent of confounder adjustment. We explored heterogeneity using three methods: First, a Galbraith plot was used to identify potential outlier studies, defined as those with absolute standardized residuals > 2. Second, subgroup analyses were performed based on study design, FM diagnostic approaches, outcome definitions, and degree of statistical adjustment. Subgroups with < 3 studies were not analyzed. Given that the ACR 2016 criteria are a revised version of the ACR 2010 criteria, they share a diagnostic framework based on the Widespread Pain Index and Symptom Severity Scale. Therefore, studies using these two sets of criteria were combined into a subgroup. Third, meta-regression with the covariates of publication year, sample size, mean age, and geographic region was conducted only when ≥ 10 studies.

For studies reporting multiple related outcomes, we used a structured inclusion approach. Data from mutually exclusive subgroups were all included. For overlapping outcomes, only the most reliable estimate (larger sample size or higher clinical relevance) was used in the primary analysis to avoid duplication bias. All data were included in subgroup analyses without double-counting participants.

Sensitivity analyses were conducted to evaluate the robustness of pooled effect sizes from different perspectives. First, high-risk studies (defined per Risk of Bias Assessment) were excluded to assess the influence of study quality on pooled estimates. Second, outlier studies identified from the Galbraith plot were excluded to recalculate the pooled estimates. Third, the leave-one-out method (sequentially excluding one study at a time) was applied to identify overly influential individual studies and assess the stability of pooled estimates. Fourth, the primary results were re-analyzed using fixed-effects models for comparison with the random-effects model, to assess the impact of model selection on the pooled estimates.

Publication bias was evaluated visually using funnel plots. For outcomes with ≥ 10 included studies, we also assessed publication bias statistically using Egger’s test. If the test was significant (p < 0.10), non-parametric trim-and-fill analysis was used as an exploratory tool to detect and evaluate potential small-study effects contributing to publication bias; findings from this analysis were interpreted cautiously and not used to alter primary conclusions.

The certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework. Evidence from observational studies started at low certainty.13 Evidence was downgraded by one level for each of the following (maximum two levels): high risk of bias (> 50% of studies), inconsistency (unexplained substantial heterogeneity with conflicting effect directions across included studies), imprecision (fewer than 200 events, or 95% CI crossing 1), indirectness (use of surrogate outcomes or non-target populations), or publication bias. Evidence was upgraded by one level if any of the following three conditions was met: large magnitude of effect (OR > 5), dose-response gradient, and residual confounding likely minimizing the effect.

Results Characteristics of Included Studies

A total of 14 studies14–27 were included, comprising seven case-control14,16–19,23,26 and seven cross-sectional15,20–22,24,25,27 designs. Four studies14,22,25,27 reported data for multiple outcomes. The included studies, published between 2007 and 2025, involved 17,139 female participants from nine countries, with a mean age ranging from 33.4 to 59.3 years. Detailed information on participant characteristics, FM diagnostic approaches, and outcome measures for each individual study is summarized in Table 1.

Table 1 Characteristics of the Included Studies

Risk of Bias Assessment

Among the 14 included studies, four (28.57%) were rated as low risk, eight (57.14%) as moderate risk, and two (14.29%) as high risk. Among the seven case-control studies, Nickel 201018 and Warren 200919 met low-risk criteria; Chung 2014,16 Hamed 202023 and Soyupek 200726 met moderate-risk criteria; and Araújo 200814 and Fuoco 201417 were rated high risk. Among the seven cross-sectional studies, Fusco 201922 and Kurtulus 202524 met low-risk criteria, while the remaining five studies15,20,21,25,27 had moderate risk. Detailed risk of bias assessment is provided in Supplementary Table 1 (case-control studies) and Supplementary Table 2 (cross-sectional studies).

Association of FM with Lower Urinary Tract Pain and LUTS

The primary random-effects meta-analysis showed that FM was statistically associated with both lower urinary tract pain and LUTS in women. Key findings were as follows (k = number of studies, n = total sample size):

Lower urinary tract pain (Figure 2): k = 6,14–19 n = 3926, OR = 2.92, 95% CI: 1.41–6.06, I2 = 79.07%, p < 0.01.

Figure 2 Forest plot of the association between fibromyalgia and lower urinary tract pain in women (random-effects meta-analysis).

LUTS (Figure 3): k = 9,14,20–27 n = 13314, OR = 2.83, 95% CI: 1.98–4.03, I2 = 79.05%, p < 0.01.

Figure 3 Forest plot of the association between fibromyalgia and lower urinary tract symptoms in women (random-effects meta-analysis).

Heterogeneity Analyses Outlier Exclusion

Removal of outliers identified via Galbraith plots was conducted to assess the impact of outliers on between-study heterogeneity. Key changes in heterogeneity for each outcome were as follows:

Lower urinary tract pain (Supplementary Figure 1): exclusion of two outliers17,18 reduced heterogeneity from substantial (I2 = 79.07%, τ2 = 0.57, p (Q-test) < 0.01) to low (I2 = 28.06%, τ2 = 0.04, p (Q-test) = 0.27).

LUTS (Supplementary Figure 2): exclusion of one outlier22 reduced heterogeneity from substantial (I2 = 79.05%, τ2 = 0.15, p (Q-test) = 0.01) to a lower but still substantial level (I2 = 73.50%, τ2 = 0.10, p (Q-test) = 0.02).

Subgroup Analyses

We conducted predefined subgroup analyses to explore heterogeneity sources, including study design, FM diagnostic approaches, outcome definitions, and adjustment status. Subgroups with fewer than three studies were excluded from subgroup analyses. Q-between and its p-value are reported only when all subgroups contain at least three studies. Key findings were as follows:

Lower urinary tract pain (Table 2): A significant subgroup difference (Q-between = 7.13, p = 0.01) was observed between clinician-based (OR = 1.45, 95% CI: 1.15–1.83; I2 = 0.00%) and self-reported FM (OR = 5.84, 95% CI: 2.16–15.79; I2 = 58.32%). Because the two ascertainment approaches may have different measurement properties, the pooled estimate combining them should be interpreted cautiously. Formal between-subgroup comparisons were not possible for study design, outcome definitions, and adjustment status because at least one subgroup within each variable contained fewer than three studies.

Table 2 Subgroup Analyses of the Association Between Fibromyalgia and Lower Urinary Tract Pain in Women

LUTS (Table 3): A significant subgroup difference (Q-between = 11.60, p < 0.01) was found among overactive bladder (OAB; OR = 2.65, 95% CI: 1.88–3.74; I2 = 77.82%), urge urinary incontinence (UUI; OR = 2.95, 95% CI: 1.05–8.28; I2 = 49.59%), and stress urinary incontinence (SUI; OR = 1.00, 95% CI: 0.63–1.59; I2 = 19.46%). We also observed a significant subgroup difference (Q-between = 4.67, p = 0.03) between crude estimates (OR = 4.48, 95% CI: 2.68–7.49; I2 = 0.00%) and adjusted estimates (OR = 2.27, 95% CI: 1.62–3.20; I2 = 80.18%). For study design and FM diagnostic approaches, no significant subgroup difference was observed. Notably, for studies using the ACR 2010/2016 criteria, the pooled OR was 4.23 (95% CI: 2.77–6.46) with I2 = 0.00%.

Table 3 Subgroup Analyses of the Association Between Fibromyalgia and Lower Urinary Tract Symptoms in Women

Meta-Regression

Meta-regression with the covariates of publication year, sample size, mean age, and geographic region was not conducted because the number of available studies for each outcome was fewer than 10.

Sensitivity Analyses Exclusion of High-Risk Studies

Excluding studies rated at high risk of bias14,17 preserved the positive direction and statistical significance of both associations, although substantial heterogeneity remained. Key findings were as follows:

Lower urinary tract pain: k = 4,15,16,18,19 n = 3774, OR = 2.69, 95% CI: 1.29–5.61, I2 = 70.78%, p = 0.01.

LUTS: k = 8,20–27 n = 13213, OR = 2.74, 95% CI: 1.87–4.00, I2 = 81.42%, p < 0.01.

Exclusion of Outlier Studies

Exclusion of outlying studies preserved the positive direction of association for both outcomes, but materially changed the magnitude of the lower urinary tract pain estimate. The pooled OR decreased from 2.92 to 1.66 after outlier exclusion, representing an approximately 43% reduction. Key findings were as follows:

Lower urinary tract pain: k = 4,14–16,19 n = 3551, OR = 1.66, 95% CI: 1.15–2.40, I2 = 28.06%, p = 0.01.

LUTS: k = 8,14,20,21,23–27 n = 13188, OR = 2.54, 95% CI: 1.83–3.53, I2 = 73.50%, p < 0.01.

Leave-One-Out Analysis

Sequential exclusion of individual studies (leave-one-out analysis) did not change the direction or statistical significance of either pooled association. Key findings were as follows:

Lower urinary tract pain (Supplementary Figure 3): pooled ORs ranged from 2.23 to 3.65 (95% CI: 1.18–8.57) across all leave-one-out iterations, with all associations remaining statistically significant (all p < 0.05).

LUTS (Supplementary Figure 4): pooled ORs varied between 2.54 and 3.16 (95% CI: 1.83–4.83), and all iterations remained statistically significant (all p < 0.01).

Fixed-Effects Model Reanalysis

Reanalysis using fixed-effects models yielded results consistent in direction with the primary random-effects model, but with attenuated pooled ORs and narrower 95% CIs. Key findings were as follows:

Lower urinary tract pain: k = 6,14–19 n = 3926, OR = 1.70, 95% CI: 1.37–2.11, p < 0.01.

LUTS: k = 9,14,20–27 n = 13314, OR = 2.11, 95% CI: 1.89–2.34, p < 0.01.

Publication Bias

Publication bias was assessed visually using funnel plots (Figures 4 and 5). For lower urinary tract pain and LUTS, visual inspection suggested possible asymmetry; however, interpretation was highly limited by the small number of studies, and the possible asymmetry may also reflect between-study heterogeneity or the influence of outlying studies. Egger’s test was not performed because the number of included studies for each outcome was fewer than 10.

Figure 4 Funnel plot of the association between fibromyalgia and lower urinary tract pain in women.

Figure 5 Funnel plot of the association between fibromyalgia and lower urinary tract symptoms in women.

Certainty of Evidence

Following GRADE guidelines for observational studies, all outcomes began at an initial rating of low certainty. No outcomes met the criteria for evidence certainty upgrading. Substantial heterogeneity was present in the primary analyses for lower urinary tract pain (I2 = 79.07%) and LUTS (I2 = 79.05%). In addition, exclusion of two outlying studies reduced the pooled OR for lower urinary tract pain from 2.92 to 1.66, while substantial heterogeneity persisted for LUTS after outlier exclusion (I2 = 73.50%). We therefore downgraded both outcomes by one level for serious inconsistency. The final certainty of evidence was very low for both lower urinary tract pain and LUTS. Complete domain judgments are provided in Supplementary Table 3.

Discussion

To our knowledge, this meta-analysis is the first to quantitatively synthesize epidemiological evidence on the associations of FM with lower urinary tract pain and LUTS in women. The pooled analysis of 14 observational studies involving 17,139 women showed statistically significant associations for lower urinary tract pain (OR = 2.92) and LUTS (OR = 2.83), while the certainty of evidence remained very low. In phenotype-stratified analyses, FM was associated with OAB and UUI but not with SUI; therefore, the pooled LUTS association appeared to be driven predominantly by urgency-related storage symptoms. Statistical heterogeneity was substantial for both outcomes (I2 > 75%), but the direction of association was consistent in the primary analyses. Clinical and methodological heterogeneity was also evident, particularly in FM ascertainment and symptom phenotype, and likely contributed to the observed statistical heterogeneity. Accordingly, the pooled ORs should be interpreted as average associations across heterogeneous settings rather than as uniform effects expected in every clinical population. These findings provide a framework for the detailed discussion of each outcome below.

While previous narrative reviews28,29 have hypothesized the connection between FM and CPP in women, our analysis provides the first quantitative summary estimate of the association between FM and lower urinary tract pain, which is a component of CPP. Although the association with lower urinary tract pain remained positive and statistically significant after outlier exclusion, the reduction in the pooled OR from 2.92 to 1.66 indicates that the full estimate was not robust in magnitude. The outlier-excluded OR of 1.66 may represent a more conservative estimate of the association.

Subgroup analysis based on FM diagnostic approach revealed a marked difference (Q-between = 7.13, p = 0.01): studies using self-reported FM diagnosis yielded a substantially larger pooled estimate (OR = 5.84), whereas those employing clinician-based diagnosis produced a smaller but still significant association (OR = 1.45). This contrast should not be interpreted as proof that self-reported FM invariably produces a stronger association, because several bias pathways could plausibly inflate the self-reported estimate. Women with prominent bladder pain, multiple somatic symptoms, or greater psychological distress may be more likely both to recall or report an FM diagnosis and to endorse lower urinary tract pain, creating correlated recall or common-method bias. False-positive FM classification may also occur when other chronic pain conditions are mistaken for FM in the absence of formal diagnostic evaluation. Symptom hypervigilance, catastrophizing, or broader symptom amplification could further increase reporting of both FM and urinary pain. Finally, differential healthcare-seeking and closer medical surveillance may increase opportunities for both conditions to be recognized and documented. These mechanisms are not mutually exclusive and may operate jointly. The overall lower urinary tract pain estimate may have been inflated by studies using self-reported FM, and the clinician-based estimate may therefore provide a more conservative and potentially more reliable estimate for interpretation. However, each subgroup comprised only three studies, and differences in study design, population characteristics, and outcome ascertainment may also have contributed to the subgroup contrast. The self-reported estimate should therefore be considered exploratory, and neither subgroup should be regarded as definitively unbiased.

Notably, most of the available evidence for lower urinary tract pain was derived from studies of interstitial cystitis/painful bladder syndrome (IC/PBS), which limits the generalizability of the pooled estimate to other pain phenotypes such as isolated urethral pain or dysuria. Dysuria was reported in only one study,14 and no data were available for urethral pain. IC/PBS subgroup15–19 showed a higher pooled OR (3.61) than the overall estimate (OR = 2.92). This pattern raises the possibility that IC/PBS, a more specifically defined pain phenotype, may show a stronger association with FM than broader or less standardized lower urinary tract pain definitions; however, this observation is based on limited data and should be interpreted cautiously.

The present meta-analysis directly supports an epidemiological association, but cannot establish mechanisms. Accordingly, the following mechanisms should be regarded as literature-supported, hypothesis-generating explanations. Previous clinical literature has discussed chronic overlapping pain conditions (COPCs) and central sensitization framework as possible explanatory frameworks. FM, IC/PBS, IBS, and other chronic pain disorders are recognized as overlapping conditions,30 and enhanced pain sensitivity is a shared clinical feature.31 Central sensitization—characterized by dysregulated central nociceptive processing (abnormal integration and amplification of peripheral nociceptive signals in the central nervous system), and impaired descending pain inhibition—has been described in FM and IC/PBS and could plausibly amplify pelvic afferent signaling and bladder pain perception.32–34 Viscerosomatic convergence, whereby overlapping neural pathways between pelvic viscera and somatic structures promote cross-sensitization and widespread nociceptive perception, is compatible with this framework,35–37 while mood, stress, trauma history, and coping patterns may modify pain persistence and symptom burden.38–40 Viscerosomatic convergence and psychosocial modulation remain plausible but more indirect explanations.

In a single-center retrospective study of 440 women with FM, McClain et al41 reported that 37.0% of patients had at least one documented LUTS. The most common diagnoses were SUI (17.0%), UUI (15.2%), mixed incontinence (10.9%), and OAB (6.8%). In this context, the pooled estimate of this meta-analysis showed a positive association between FM and LUTS that appeared to be driven predominantly by urgency-related storage symptoms. This finding remained positive and statistically significant across multiple sensitivity analyses, although substantial heterogeneity persisted. When the largest study (Altman 2016,20 n = 11,731) was excluded in a leave-one-out analysis, the pooled OR increased from 2.83 to 3.13 (95% CI: 2.12–4.70). This suggests that the very large study, which reported a relatively modest effect size (OR = 1.83), attenuated the overall estimate.

Subgroup analysis based on outcome definition detected an important source of heterogeneity (Q-between = 11.60, p < 0.01): the association was significant for OAB (OR = 2.65) and UUI (OR = 2.95), but not for SUI (OR = 1.00). The positive associations for OAB and UUI and the null association for SUI indicate phenotype heterogeneity but do not identify its biological basis. Previous literature has often distinguished structural and pelvic-floor contributors to SUI from sensory and urgency-related pathways discussed in OAB and UUI, although a degree of phenotypic overlap has also been acknowledged.41,42 Adjustment for confounders appeared to attenuate the crude estimate: the pooled OR for crude estimates was 4.48 versus 2.27 for adjusted estimates, with a significant subgroup difference (Q-between = 4.67, p = 0.03). This may suggest that some of the observed association could be influenced by measured confounders (eg, anxiety, depression). Although studies using the ACR 2010/2016 criteria showed a numerically higher pooled OR (4.23) than those using the ACR 1990 criteria (OR = 3.10), no significant between-subgroup difference was observed (Q-between = 0.59, p = 0.44). The ACR 1990 criteria relied heavily on tender point examination, a physical examination-based approach that emphasizes musculoskeletal tenderness and may preferentially identify patients with more pronounced somatic pain features.43 The ACR 2010 and 2016 criteria were combined into a single subgroup for this analysis because they share a diagnostic framework based on the Widespread Pain Index and Symptom Severity Scale, which incorporates a broader array of symptoms, including fatigue, sleep disturbance, and cognitive complaints.43 This shift may influence the strength of associations with extra-musculoskeletal conditions such as LUTS. Our subgroup analysis may reflect broader symptom capture for the ACR 2010/2016 criteria, but should be interpreted cautiously.

A previous meta-analysis reported a non-significant pooled estimate (OR = 1.96, 95% CI: 0.85–3.06) for the association between FM and OAB.44 The discrepancy with this meta-analysis likely arises from methodological differences: our analysis incorporated more recent data (eg, Kurtulus 202524), applied stricter inclusion criteria, and distinguished LUTS phenotypes through prespecified subgroup analyses. Thus, our study provides a more detailed and phenotype-specific estimate of the FM-LUTS association.

Importantly, the available LUTS evidence was concentrated in storage symptoms, whereas voiding and post-micturition symptoms were underrepresented. Our findings are compatible with neurogenic mechanisms but do not provide direct evidence for them. Existing clinical literature links central sensitization with OAB symptom severity.42,45 Previous studies have hypothesized that central sensitization may amplify afferent signals from the bladder, leading to heightened bladder sensation, urgency perception, and urgency-related symptoms.46 In contrast, more specific pathways—including visceral cross-sensitization,47,48 autonomic dysfunction,49 neurotransmitter imbalance (eg, serotonin, norepinephrine),50 low-grade neuroinflammation,51 or hormonal modulation52—remain more speculative in this context.

From a clinical perspective, these findings suggest that clinicians may consider targeted symptom inquiry, pending confirmation in prospective studies, rather than routine or universal screening. Future prospective studies could evaluate whether phenotype-specific instruments improve symptom characterization, diagnostic yield, or patient outcomes in women with FM: the International Consultation on Incontinence Questionnaire-Overactive Bladder (ICIQ-OAB) for urgency, frequency, nocturia, and UUI;53 the International Consultation on Incontinence Questionnaire-Urinary Incontinence Short Form (ICIQ-UI SF) for the severity and impact of urinary incontinence;54 and the O’Leary-Sant Interstitial Cystitis Symptom and Problem Index for prominent bladder pain or IC/PBS features.55 Bidirectional assessment strategies in this population require separate prospective evaluation.

This meta-analysis has several limitations. First, although subgroup analyses explained part of the observed heterogeneity, residual heterogeneity persisted. Even after outlier exclusion, heterogeneity remained substantial for LUTS (I2 = 73.50%). Meta-regression could not be conducted because fewer than 10 studies were available for either outcome. Residual heterogeneity may be partly attributable to unmeasured confounding variables (eg, FM severity, FM duration, socioeconomic status, psychological comorbidity burden) that could not be adequately controlled for in the included studies. Second, publication bias cannot be ruled out, and Egger’s test was not performed because each outcome included fewer than 10 studies. Visual funnel-plot asymmetry was possible for both outcomes, but its interpretation was limited by the small number of studies, substantial heterogeneity, and the influence of outlying studies. Third, the potential for ascertainment bias should be considered. Patients with FM are typically under closer medical surveillance due to their underlying chronic condition, making them more likely to have symptoms systematically documented compared to control populations. Additionally, recall bias may be present in case-control studies, particularly those relying on self-reported FM diagnosis. Fourth, the limited number of studies for lower urinary tract pain (k = 6) and LUTS (k = 9) reduces the precision and reliability of the pooled estimates. The pooled estimate for lower urinary tract pain was materially dependent on two outlying studies, decreasing by approximately 43% from 2.92 to 1.66 after their exclusion. Finally, half of the included studies were cross-sectional, precluding temporal or causal inference. Collectively, these limitations suggest that the findings are hypothesis‑generating and require confirmation in well‑designed prospective cohort studies with standardized outcome assessments and adequate confounder adjustment.

Conclusion

This meta-analysis indicates that FM in women may be associated with higher odds of lower urinary tract pain and LUTS. The association with lower urinary tract pain was consistently observed across studies using a validated diagnosis of IC/PBS; the clinician-based FM subgroup yielded a more conservative estimate, whereas the larger self-reported estimate may have inflated the overall pooled estimate. The overall LUTS association appeared to be driven predominantly by urgency-related storage symptoms (OAB and UUI); no significant association was found for SUI. These findings are preliminary and hypothesis-generating; prospective studies with standardized outcome assessments are needed to confirm the associations and guide clinical implementation.

Abbreviations

ACR, the American College of Rheumatology; CIs, confidence intervals; CPP, chronic pelvic pain; FM, fibromyalgia; IBS, irritable bowel syndrome; ICIQ, International Consultation on Incontinence Questionnaire; IC/PBS, interstitial cystitis/painful bladder syndrome; ICS, the International Continence Society; IUGA, International Urogynecological Association; LUTS, lower urinary tract symptoms; MUI, mixed urinary incontinence; OAB, overactive bladder; ORs, odds ratios; SUI, stress urinary incontinence; GRADE, the Grading of Recommendations Assessment, Development and Evaluation; PROSPERO, the International Prospective Register of Systematic Reviews; PRISMA, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses; UUI, urge urinary incontinence.

Data Sharing Statement

All data are available upon reasonable request to the corresponding author.

Consent for Publication

The details of any images, videos, recordings, etc. can be published, and the person(s) providing consent have been shown the article contents to be published.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Disclosure

The authors report no conflicts of interest in this work.

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