OUTCOME: Urinary continence at 6 months ANALYSIS: primary_all_designs STUDIES: 17 TREATMENTS: Conventional, Retzius, Ultra Original data: treat1 treat2 TE seTE Asimakopoulos_2019 Conventional Retzius -1.5500 0.6233 Beyatli_2025 Retzius Ultra 0.3334 0.5159 Feng_2025 Conventional Retzius -1.3824 0.8196 Ficarra_2022 Conventional Retzius -1.2452 0.6738 Golubtsova_2021 Conventional Retzius -0.1542 1.4413 Kwon_2014 Conventional Ultra -2.0496 0.6509 Lambert_2023 Conventional Retzius -2.3691 0.5039 Lin_2025 Conventional Ultra -0.4796 1.6773 Maruyama_2020 Conventional Retzius -0.4321 0.4172 Nagoya_RS_anatomy_OAB Conventional Retzius -1.5198 1.1573 Nanchang_Deng_2021a Conventional Retzius -1.6124 0.5534 Puliatti_2019 Conventional Ultra -0.9478 0.4366 Qian_2024 Conventional Retzius -0.0451 0.2124 Sayyid_2017 Conventional Retzius -1.3863 0.3202 Tan_2024 Conventional Ultra 0.1372 0.7645 Wang_2021 Conventional Retzius -0.8583 1.6464 Yilmaz_2023 Conventional Retzius -0.7472 0.7322 Number of treatment arms (by study): narms Asimakopoulos_2019 2 Beyatli_2025 2 Feng_2025 2 Ficarra_2022 2 Golubtsova_2021 2 Kwon_2014 2 Lambert_2023 2 Lin_2025 2 Maruyama_2020 2 Nagoya_RS_anatomy_OAB 2 Nanchang_Deng_2021a 2 Puliatti_2019 2 Qian_2024 2 Sayyid_2017 2 Tan_2024 2 Wang_2021 2 Yilmaz_2023 2 Results (random effects model): treat1 treat2 OR 95%-CI Asimakopoulos_2019 Conventional Retzius 0.3281 [0.2047; 0.5257] Beyatli_2025 Retzius Ultra 1.2112 [0.5130; 2.8600] Feng_2025 Conventional Retzius 0.3281 [0.2047; 0.5257] Ficarra_2022 Conventional Retzius 0.3281 [0.2047; 0.5257] Golubtsova_2021 Conventional Retzius 0.3281 [0.2047; 0.5257] Kwon_2014 Conventional Ultra 0.3973 [0.1793; 0.8806] Lambert_2023 Conventional Retzius 0.3281 [0.2047; 0.5257] Lin_2025 Conventional Ultra 0.3973 [0.1793; 0.8806] Maruyama_2020 Conventional Retzius 0.3281 [0.2047; 0.5257] Nagoya_RS_anatomy_OAB Conventional Retzius 0.3281 [0.2047; 0.5257] Nanchang_Deng_2021a Conventional Retzius 0.3281 [0.2047; 0.5257] Puliatti_2019 Conventional Ultra 0.3973 [0.1793; 0.8806] Qian_2024 Conventional Retzius 0.3281 [0.2047; 0.5257] Sayyid_2017 Conventional Retzius 0.3281 [0.2047; 0.5257] Tan_2024 Conventional Ultra 0.3973 [0.1793; 0.8806] Wang_2021 Conventional Retzius 0.3281 [0.2047; 0.5257] Yilmaz_2023 Conventional Retzius 0.3281 [0.2047; 0.5257] Number of studies: k = 17 Number of pairwise comparisons: m = 17 Number of observations: o = 2442 Number of treatments: n = 3 Number of designs: d = 3 Random effects model Treatment estimate (sm = 'OR', comparison: other treatments vs 'Conventional'): OR 95%-CI z p-value Conventional . . . . Retzius 3.0483 [1.9021; 4.8852] 4.63 < 0.0001 Ultra 2.5167 [1.1356; 5.5775] 2.27 0.0230 Quantifying heterogeneity / inconsistency: tau^2 = 0.3426; tau = 0.5853; I^2 = 59.8% [30.3%; 76.8%] Tests of heterogeneity (within designs) and inconsistency (between designs): Q d.f. p-value Total 37.29 15 0.0011 Within designs 36.52 14 0.0009 Between designs 0.77 1 0.3792 Details of network meta-analysis methods: - Frequentist graph-theoretical approach - Restricted maximum-likelihood estimator for tau^2 - Calculation of I^2 based on Q --- P-SCORE RANKING --- P-score Retzius 0.8345 Ultra 0.6597 Conventional 0.0058 --- SUCRA RANKING --- SUCRA Retzius 0.8342 Ultra 0.6599 Conventional 0.0059 - based on 20000 simulations --- GLOBAL INCONSISTENCY: DESIGN-BY-TREATMENT --- Q statistics to assess homogeneity / consistency Q df p-value Total 37.29 15 0.0011 Within designs 36.52 14 0.0009 Between designs 0.77 1 0.3792 Design-specific decomposition of within-designs Q statistic Design Q df p-value Conventional:Retzius 31.59 11 0.0009 Conventional:Ultra 4.92 3 0.1775 Between-designs Q statistic after detaching of single designs (influential designs have p-value markedly different from 0.3792) Detached design Q df p-value Conventional:Retzius 0.00 0 -- Conventional:Ultra 0.00 0 -- Retzius:Ultra 0.00 0 -- Q statistic to assess consistency under the assumption of a full design-by-treatment interaction random effects model Q df p-value tau.within tau2.within Between designs 0.03 1 0.8588 0.6822 0.4654 --- LOCAL INCONSISTENCY: NODE SPLITTING/SIDE --- Separate indirect from direct evidence (SIDE) using back-calculation method Random effects model: comparison k prop nma direct indir. RoR z p-value Retzius:Conventional 12 0.93 3.0483 3.0044 3.6961 0.8129 -0.22 0.8261 Ultra:Conventional 4 0.75 2.5167 2.6481 2.1526 1.2302 0.22 0.8261 Retzius:Ultra 1 0.32 1.2112 1.3957 1.1345 1.2302 0.22 0.8261 Legend: comparison - Treatment comparison k - Number of studies providing direct evidence prop - Direct evidence proportion nma - Estimated treatment effect (OR) in network meta-analysis direct - Estimated treatment effect (OR) derived from direct evidence indir. - Estimated treatment effect (OR) derived from indirect evidence RoR - Ratio of Ratios (direct versus indirect) z - z-value of test for disagreement (direct versus indirect) p-value - p-value of test for disagreement (direct versus indirect)