OUTCOME: Overall positive surgical margins 
ANALYSIS: sensitivity_rct_only 
STUDIES: 3 
TREATMENTS: Conventional, Retzius, Ultra 

Original data:

                                   treat1  treat2      TE   seTE
Dalela_Detroit_RCT_2015_2016 Conventional Retzius -0.7732 0.4828
Ratanapornsompong_2020       Conventional   Ultra -0.0945 0.4349
Siltari_2021                 Conventional   Ultra -0.2144 0.3445

Number of treatment arms (by study):
                             narms
Dalela_Detroit_RCT_2015_2016     2
Ratanapornsompong_2020           2
Siltari_2021                     2

Results (random effects model):

                                   treat1  treat2     OR           95%-CI
Dalela_Detroit_RCT_2015_2016 Conventional Retzius 0.4615 [0.1792; 1.1890]
Ratanapornsompong_2020       Conventional   Ultra 0.8452 [0.4978; 1.4350]
Siltari_2021                 Conventional   Ultra 0.8452 [0.4978; 1.4350]

Number of studies: k = 3
Number of pairwise comparisons: m = 3
Number of observations: o = 370
Number of treatments: n = 3
Number of designs: d = 2

Random effects model

Treatment estimate (sm = 'OR', comparison: other treatments vs 'Conventional'):
                 OR           95%-CI    z p-value
Conventional      .                .    .       .
Retzius      2.1667 [0.8410; 5.5818] 1.60  0.1093
Ultra        1.1832 [0.6969; 2.0087] 0.62  0.5335

Quantifying heterogeneity / inconsistency:
tau^2 < 0.0001; tau < 0.0001; I^2 = 0%

Tests of heterogeneity (within designs) and inconsistency (between designs):
                   Q d.f. p-value
Total           0.05    1  0.8289
Within designs  0.05    1  0.8289
Between designs 0.00    0      --

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
Conventional  0.8393
Ultra         0.5648
Retzius       0.0959

--- SUCRA RANKING ---
              SUCRA
Conventional 0.8394
Ultra        0.5666
Retzius      0.0940

- based on 20000 simulations

--- GLOBAL INCONSISTENCY: DESIGN-BY-TREATMENT ---
Q statistics to assess homogeneity / consistency

                   Q df p-value
Total           0.05  1  0.8289
Within designs  0.05  1  0.8289
Between designs 0.00  0      --

Design-specific decomposition of within-designs Q statistic

             Design    Q df p-value
 Conventional:Ultra 0.05  1  0.8289

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 0.00  0      --          0           0

--- 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 1 1.00 2.1667 2.1667      .   . .       .
   Ultra:Conventional 2 1.00 1.1832 1.1832      .   . .       .
        Retzius:Ultra 0    0 1.8313      . 1.8313   . .       .

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)