Efficacy of Ultrasound-Guided Retrolaminar Block Combined With Standard Multimodal Analgesia for Postoperative Pain Management in Lumbar Spine Surgery: A Randomized Controlled Trial
Phase: NA
Conditions: Postoperative Pain, Lumbar Surgery, Back Pain Lower Back Chronic, Opioid Analgesia, Regional Anaesthesia
Sponsor: Universidad de los Andes, Chile

Study Design and Statistical Analysis Plan
Efficacy of Ultrasound-Guided Retrolaminar Block Combined with Standard Multimodal Analgesia
for Postoperative Pain Management in Lumbar Spine Surgery: A Randomized Controlled Trial
Study Acronym: REALM (Retrolaminar Analgesia for LuMbar Surgery)
Principal Investigator: Dr. Roberto Coloma Díaz
Institution: Clínica Universidad de Los Andes, Santiago, Chile
Department: Anesthesiology
Email: rcoloma@clinicauandes.cl
Phone: +56 9 9337 1413
Document Version: 1.0
Date: November 06, 2025

TABLE OF CONTENTS
1. Study Overview
2. Study Objectives
3. Study Design
4. Sample Size Calculation
5. Statistical Methods
6. Primary Outcome Analysis
7. Secondary Outcomes Analysis
8. Subgroup Analysis
9. Safety Analysis
10. Missing Data Handling
11. Interim Analysis
12. Final Analysis and Reporting

1. STUDY OVERVIEW
This Statistical Analysis Plan (SAP) describes the planned statistical methods for the REALM study
(Retrolaminar Analgesia for LuMbar Surgery), a prospective, randomized controlled trial evaluating the
efficacy of ultrasound-guided retrolaminar nerve block as an adjunct to standard multimodal analgesia
for postoperative pain management in patients undergoing lumbar spine surgery. This document
should be read in conjunction with the study protocol and will guide all statistical analyses to be
performed.
2. STUDY OBJECTIVES
2.1 Primary Objective
To compare the total postoperative opioid consumption (measured as cumulative morphine equivalents
via patient-controlled analgesia) during the first 24 hours between patients receiving ultrasound-guided
retrolaminar block plus standard multimodal analgesia versus patients receiving standard multimodal
analgesia alone.
2.2 Secondary Objectives
a) To evaluate pain intensity (Visual Analog Scale 0-10) at 0, 6, 12, 24, 48, and 72 hours
postoperatively between both groups.
b) To compare cumulative postoperative opioid consumption at 48 and 72 hours between groups.
c) To determine time to first rescue analgesia request postoperatively.
d) To assess duration of sensory block (thermal and tactile testing).
e) To evaluate incidence of postoperative nausea and vomiting (PONV).
f) To compare length of hospital stay, time in post-anesthesia care unit, and total hospitalization costs.
g) To assess time to independent ambulation.
h) To evaluate sleep quality using validated scales.
i) To measure overall patient satisfaction (Likert scale).
j) To record specific adverse events (local anesthetic toxicity, neurological injury, infection, hematoma).
k) To determine incidence of chronic pain at 3 and 6 months postoperatively.

3. STUDY DESIGN
Design Type: Prospective, randomized, controlled trial with blinded outcome assessment
Randomization: Computer-generated randomization using variable block sizes (blocks of 4 and 6) in a
1:1 allocation ratio
Blinding: Single-blind design (outcome assessors blinded to group allocation). The anesthesiologist
performing the block and patients are aware of treatment allocation, but independent evaluators
collecting outcome data remain blinded.
Study Population: Adult patients (≥18 years) with ASA physical status I-III scheduled for elective
lumbar spine surgery (with or without instrumentation) involving ≤3 vertebral levels
Study Groups:
• Intervention Group: Bilateral ultrasound-guided retrolaminar block with levobupivacaine 0.25% (15
ml per side, total 30 ml = 75 mg) performed preoperatively under general anesthesia + standard
multimodal analgesia + morphine PCA (0-1-10 regimen: 0 ml/hr basal, 1 mg bolus, 10-minute lockout)
• Control Group: Standard multimodal analgesia + morphine PCA (0-1-10 regimen) without regional
anesthesia block
Study Duration: Approximately 12-18 months for recruitment and initial follow-up, with extended
follow-up at 3 and 6 months for chronic pain assessment

4. SAMPLE SIZE CALCULATION
4.1 Rationale and Assumptions
The sample size calculation is based on the primary outcome: cumulative morphine consumption via
PCA during the first 24 postoperative hours. Based on Singh et al. (2020), the control group is expected
to consume 7.2 ± 2.0 mg of morphine. We hypothesize that the retrolaminar block will reduce
consumption by 50% to approximately 3.6 mg (absolute reduction of 3.6 mg).
4.2 Statistical Parameters
Parameter
Value
Justification
Type I error (α)
0.05 (two-sided)
Standard significance level
Statistical power (1-β)
80%
Standard power for clinical trials
Expected mean difference (∆)
3.6 mg
50% reduction from 7.2 mg to 3.6 mg
Assumed standard deviation (σ)
2.5 mg
Conservative estimate accounting for technique novelty
Effect size (Cohen's d)
1.44
Large effect size
4.3 Sample Size Formula
For comparison of means between two independent groups with normal distribution:
n = 2 × [(Zα/2 + Zβ)2 × σ2] / ∆2
Where:
• n = sample size per group
• Zα/2 = 1.96 (critical value for α = 0.05, two-sided)
• Zβ = 0.84 (critical value for 80% power)
• σ = 2.5 mg (standard deviation)
• ∆ = 3.6 mg (minimum clinically important difference)
Calculation:
n = 2 × [(1.96 + 0.84)2 × (2.5)2] / (3.6)2
n = 2 × [7.84 × 6.25] / 12.96
n = 2 × [49.0] / 12.96
n ≈ 7.6 → 8 patients per group (minimum)

4.4 Final Sample Size Determination
Although the calculation yields a minimum of 8 patients per group, we have increased the sample size
to 25 patients per group (50 total) for the following reasons:
1. Novel Technique: This is the first study evaluating retrolaminar block efficacy in lumbar spine
surgery at our center. The technique is less standardized than erector spinae plane block, warranting
conservative estimates.
2. Enhanced Statistical Power: With 25 patients per group, statistical power increases to >95% for
detecting the expected difference, providing robust evidence.
3. Rare Adverse Event Detection: Larger sample enables detection of adverse events with incidence
≥6%, important for safety profile establishment.
4. Subgroup Analysis: Adequate power for pre-specified subgroup analyses (surgery type, number of
levels, ASA classification).
5. Attrition Buffer: 10% additional participants (approximately 5 patients) to account for potential
losses to follow-up or protocol violations.
6. Feasibility: With our high surgical volume, recruitment of 50 patients is achievable within 12-18
months.
Conclusion: Final sample size of 50 patients (25 per group) provides excellent statistical power,
feasibility, and will generate robust evidence for this novel analgesic technique.

5. STATISTICAL METHODS
5.1 General Principles
All statistical analyses will be performed using R software (RStudio 2025.05.1 Build 513© 2009-2025
Posit Software, PBC). A significance level of α = 0.05 (two-sided) will be used for all hypothesis tests.
The primary analysis will follow the intention-to-treat (ITT) principle, including all randomized patients in
their originally assigned groups regardless of protocol adherence. A per-protocol (PP) analysis will be
conducted as sensitivity analysis.
5.2 Descriptive Statistics
Continuous Variables:
• Normal distribution: Mean ± standard deviation (SD)
• Non-normal distribution: Median with interquartile range (IQR, 25th-75th percentile)
• Distribution assessed using Shapiro-Wilk test (p < 0.05 indicates non-normality)
Categorical Variables:
• Absolute frequencies (n) and percentages (%)
• 95% confidence intervals calculated for proportions where appropriate
5.3 Baseline Characteristics Comparison
Baseline demographic and clinical characteristics will be compared between groups to assess
randomization success:
For continuous variables:
• Normally distributed: Independent samples t-test
• Non-normally distributed: Mann-Whitney U test
For categorical variables:
• Expected frequency ≥5 in all cells: Pearson's chi-square test
• Expected frequency <5 in any cell: Fisher's exact test
Note: p-values for baseline comparisons are descriptive only; significant differences do not invalidate
randomization but may be considered as covariates in adjusted analyses.

6. PRIMARY OUTCOME ANALYSIS
6.1 Primary Outcome Definition
Outcome: Total cumulative morphine consumption (in milligrams) delivered via patient-controlled
analgesia (PCA) pump during the first 24 hours postoperatively.
Measurement: Automatically recorded by PCA pump. Data extracted at exactly 24 hours (±30
minutes) after end of surgery.
Hypothesis: Patients receiving retrolaminar block will have significantly lower opioid consumption
compared to control group.
6.2 Statistical Analysis
Step 1: Distribution Assessment
• Shapiro-Wilk test to assess normality
• Visual inspection using Q-Q plots and histograms
Step 2: Primary Comparison
If normally distributed:
• Independent samples t-test (two-sided)
• Report: mean difference with 95% confidence interval, t-statistic, degrees of freedom, p-value
• Effect size: Cohen's d with 95% CI
If non-normally distributed:
• Mann-Whitney U test (two-sided)
• Report: median difference, U-statistic, p-value
• Effect size: rank-biserial correlation
Step 3: Clinical Significance
• Calculate number needed to treat (NNT) if significant reduction observed
• Assess whether mean/median difference exceeds minimal clinically important difference (MCID = 3.6
mg)
6.3 Graphical Presentation
Primary outcome will be visualized using:
1. Box-and-whisker plots comparing distributions between groups
2. Violin plots showing full distribution shapes
3. Forest plot displaying mean/median difference with 95% CI

7. SECONDARY OUTCOMES ANALYSIS
7.1 Pain Intensity Over Time
Outcome: Visual Analog Scale (VAS) scores (0-10) measured at 0, 6, 12, 24, 48, and 72 hours
postoperatively
Analysis Method:
• Primary approach: Linear mixed-effects model with repeated measures
• Fixed effects: Group (intervention vs. control), Time (as categorical variable), Group×Time interaction
• Random effects: Patient-specific intercepts to account for within-subject correlation
• Covariance structure: Unstructured or AR(1) based on best fit (AIC/BIC criteria)
Alternative approach (if model assumptions violated):
• Repeated measures ANOVA or Friedman test depending on distribution
• Post-hoc pairwise comparisons with Bonferroni correction
Key Analysis Questions:
• Is there a significant Group×Time interaction? (different pain trajectories)
• Are there significant between-group differences at specific time points?
• What is the area under the curve (AUC) for pain over 72 hours?
Graphical Presentation:
• Line graphs with error bars showing mean VAS ± SE at each time point by group
• Spaghetti plots showing individual patient trajectories
7.2 Opioid Consumption at 48 and 72 Hours
Analysis: Similar methodology to primary outcome (t-test or Mann-Whitney U test depending on
distribution) at 48 and 72 hours
Adjustment: Bonferroni correction for multiple comparisons (2 additional time points: adjusted α =
0.025)
7.3 Time to First Rescue Analgesia
Outcome: Time in minutes from end of surgery to first PCA bolus request
Analysis:
• Kaplan-Meier survival curves for each group
• Log-rank test to compare survival distributions
• Cox proportional hazards regression to calculate hazard ratio (HR) with 95% CI
• Median time to event with 95% CI for each group
• Assumption checking: Schoenfeld residuals for proportional hazards assumption
Censoring: Patients who do not request rescue analgesia within observation period (24 hours) will be
censored

7.4 Binary Secondary Outcomes
The following binary outcomes will be analyzed:
• Incidence of postoperative nausea and vomiting (PONV)
• Incidence of chronic pain at 3 months (VAS >3)
• Incidence of chronic pain at 6 months (VAS >3)
Statistical Tests:
• Pearson's chi-square test or Fisher's exact test (if expected frequency <5)
Effect Measures:
• Risk ratio (RR) with 95% confidence interval
• Risk difference (RD) with 95% confidence interval
• Number needed to treat (NNT) or number needed to harm (NNH) when applicable
• Odds ratio (OR) from logistic regression if covariate adjustment needed
7.5 Continuous Secondary Outcomes
The following continuous outcomes will be compared using t-test or Mann-Whitney U test:
• Duration of sensory block (hours)
• Length of hospital stay (days)
• Time in post-anesthesia care unit (hours)
• Time to independent ambulation (hours)
• Sleep quality score
• Patient satisfaction score (Likert scale)
• Total hospitalization costs (USD)
Multiple Testing Adjustment: False discovery rate (FDR) control using Benjamini-Hochberg
procedure for secondary endpoints (critical FDR = 0.05)
Conservative estimate accounting for technique novelty
Conservative estimate due to novel technique
Conservative estimate due to novel technique

8. SUBGROUP ANALYSIS
8.1 Pre-specified Subgroups
The following pre-specified subgroup analyses will be performed for the primary outcome:
1. Surgery Type:
• With instrumentation vs. without instrumentation
2. Number of Vertebral Levels:
• Single level (1) vs. multiple levels (2-3)
3. ASA Physical Status:
• ASA I-II vs. ASA III
4. Age Groups:
• <60 years vs. ≥60 years
5. Sex:
• Male vs. Female
6. Body Mass Index (BMI):
• <30 kg/m² vs. ≥30 kg/m²
8.2 Subgroup Analysis Methodology
Interaction Testing:
• Test for treatment×subgroup interaction using regression models
• Linear regression for continuous outcomes: Y = βI + βI(Group) + βI(Subgroup) +
βI(Group×Subgroup)
• Interaction term (βI) tests whether treatment effect differs across subgroup levels
• Significance threshold for interaction: p < 0.10 (less stringent given exploratory nature)
Within-Subgroup Comparisons:
• Separate treatment effect estimates within each subgroup level
• Forest plot displaying treatment effects and 95% CIs for all subgroups
Interpretation Caution:
• Subgroup analyses are exploratory and hypothesis-generating
• Results should be interpreted with caution due to reduced statistical power
• No adjustment for multiple comparisons in subgroup analyses (report unadjusted p-values with
appropriate caveats)

9. SAFETY ANALYSIS
9.1 Adverse Events
All adverse events (AEs) will be recorded and classified by:
• Type/nature of event
• Severity (mild, moderate, severe)
• Relationship to intervention (unrelated, possibly related, probably related, definitely related)
• Outcome (resolved, ongoing, resulted in discontinuation)
Specific Adverse Events of Interest:
• Local anesthetic systemic toxicity (LAST)
• Neurological injury or deficit
• Infection at injection site
• Hematoma at injection site
• Respiratory depression (respiratory rate <8/min or requiring intervention)
• Severe nausea/vomiting requiring multiple antiemetic doses
• Urinary retention requiring catheterization
• Pruritus
Statistical Analysis:
• Incidence rates with 95% exact confidence intervals (Clopper-Pearson method)
• Between-group comparisons using Fisher's exact test
• Risk ratios with 95% CI for events with sufficient frequency
9.2 Serious Adverse Events (SAEs)
Serious adverse events (SAEs) defined as events that:
• Result in death
• Are life-threatening
• Require hospitalization or prolongation of existing hospitalization
• Result in persistent or significant disability/incapacity
• Are medically significant events
All SAEs will be:
• Reported immediately to the Ethics Committee
• Individually described in the safety analysis
• Assessed for relationship to study intervention
• Summarized by frequency and type

10. MISSING DATA HANDLING
10.1 Missing Data Assessment
Extent of Missing Data:
• Proportion of missing data will be reported for each variable
• Pattern of missingness will be assessed (completely at random, at random, not at random)
• Little's MCAR test will be used to test for missing completely at random (MCAR)
Reasons for Missing Data:
• Withdrawal from study
• Loss to follow-up
• Protocol violations
• Technical/measurement issues
• All reasons will be documented and reported
10.2 Missing Data Handling Strategy
Primary Analysis (ITT):
If missing data ≤5%:
• Complete case analysis (listwise deletion)
• Sensitivity analysis comparing baseline characteristics between complete and incomplete cases
If missing data >5%:
• Multiple imputation (MI) using chained equations (MICE)
• Number of imputations: m = 20 (recommended for proportion of missingness up to 50%)
• Imputation model includes: outcome variable, treatment group, baseline characteristics, and auxiliary
variables correlated with missingness
• Pooled estimates using Rubin's rules
• Sensitivity analysis comparing complete case analysis with multiple imputation
Primary Outcome:
• If PCA data missing due to technical issues but patient remained in study: impute based on rescue
medication use and pain scores
• If patient withdrew: conduct sensitivity analyses under different assumptions (e.g., worst-case,
best-case scenarios)
Missing Follow-up Data (3 and 6 months):
• Attempt to contact patients by phone/email
• If permanently lost: consider as separate category in chronic pain analysis
• Inverse probability weighting to account for differential loss to follow-up

11. INTERIM ANALYSIS
Planned Interim Analysis:
One interim analysis for safety will be conducted after enrollment of 25 patients (50% of total sample)
who have completed the 72-hour primary follow-up period.
Purpose:
• Safety monitoring only
• NOT for efficacy assessment (no early stopping for efficacy)
Stopping Rules for Safety:
The study may be stopped early if:
• Incidence of serious adverse events clearly related to retrolaminar block exceeds 10%
• Two or more cases of local anesthetic systemic toxicity occur
• Ethics Committee recommends stopping based on safety concerns
Review Committee:
• Principal Investigator
• Two independent anesthesiologists not involved in patient care
• Ethics Committee representative (if needed)
Statistical Considerations:
• No alpha spending function needed (no efficacy testing at interim)
• Safety analysis will be purely descriptive
• No formal hypothesis testing at interim analysis

12. FINAL ANALYSIS AND REPORTING
12.1 Analysis Populations
Intention-to-Treat (ITT) Population:
• All randomized patients analyzed according to their assigned treatment group
• Includes patients with protocol violations or deviations
• Primary analysis population
Per-Protocol (PP) Population:
• Subset of ITT population who completed the study without major protocol violations
• Exclusions: patients who did not receive assigned intervention, major protocol deviations affecting
primary outcome
• Used for sensitivity analysis
Safety Population:
• All patients who received any study intervention
• Analyzed according to treatment actually received (as-treated analysis)
• Used for safety and adverse event analyses
12.2 Sensitivity Analyses
The following sensitivity analyses will be performed:
1. Per-Protocol Analysis:
• Compare results with ITT analysis
• Assess impact of protocol violations
2. Adjustment for Baseline Covariates:
• Multiple linear regression adjusting for: age, sex, BMI, ASA status, surgery type, number of levels,
baseline pain score
• Compare adjusted vs. unadjusted treatment effects
3. Missing Data Scenarios:
• Complete case analysis vs. multiple imputation
• Worst-case scenario (missing intervention group = maximum observed value; missing control group =
minimum observed value)
• Best-case scenario (opposite of worst-case)
4. Outlier Analysis:
• Identify extreme outliers (>3 SD from mean)
• Analyze with and without outliers
• Robust regression methods if outliers present

12.3 Reporting Standards
The final study report will adhere to:
• CONSORT 2010 Statement for reporting randomized controlled trials
• CONSORT extension for non-pharmacologic treatments
• ICH E9 Statistical Principles for Clinical Trials
Required Elements:
• CONSORT flow diagram showing patient enrollment, randomization, follow-up, and analysis
• Baseline characteristics table (Table 1) comparing groups
• Primary outcome results with point estimates, 95% CI, and p-values
• Secondary outcome summary tables
• Forest plots for treatment effects across subgroups
• Safety and adverse event tables
• Sensitivity analysis results
Statistical Reporting:
• All p-values reported to 3 decimal places (except p<0.001)
• 95% confidence intervals for all effect estimates
• Exact p-values preferred over "p<0.05" statements
• Effect sizes (Cohen's d, risk ratios, hazard ratios) with interpretations
• Statistical software and package versions documented
12.4 Timeline
Data Lock: Upon completion of 6-month follow-up for all patients
Statistical Analysis: Within 4 weeks of data lock
Draft Report: Within 8 weeks of data lock
Final Report: Within 12 weeks of data lock
Manuscript Submission: Within 6 months of data lock
ClinicalTrials.gov Results: Within 12 months of primary completion date (as required by law)

REFERENCES
1. Singh S, Choudhary NK, Lalin D, Verma VK. Bilateral Ultrasound-guided Erector Spinae Plane Block
for Postoperative Analgesia in Lumbar Spine Surgery: A Randomized Control Trial. J Neurosurg
Anesthesiol. 2020;32(4):330-334.
2. Lemeshow S, Hosmer DW Jr, Klar J, Lwanga SK. Adequacy of Sample Size in Health Studies. John
Wiley & Sons; 1990.
3. Julious SA. Sample sizes for clinical trials with Normal data. Statistics in Medicine.
2004;23(12):1921-1986.
4. Schulz KF, Altman DG, Moher D, for the CONSORT Group. CONSORT 2010 Statement: updated
guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c332.
5. ICH Harmonised Tripartite Guideline. Statistical Principles for Clinical Trials E9. International
Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for
Human Use; 1998.
6. Little RJA. A test of missing completely at random for multivariate data with missing values. J Am
Stat Assoc. 1988;83:1198-1202.
7. Rubin DB. Multiple Imputation for Nonresponse in Surveys. New York: John Wiley & Sons; 1987.
8. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence
Erlbaum Associates; 1988.

APPENDIX A: DEFINITIONS AND ABBREVIATIONS
Term
Definition
AE
Adverse Event
AIC
Akaike Information Criterion
ANOVA
Analysis of Variance
AR(1)
Autoregressive structure of order 1
ASA
American Society of Anesthesiologists
AUC
Area Under the Curve
BIC
Bayesian Information Criterion
BMI
Body Mass Index (kg/m²)
CI
Confidence Interval
FDR
False Discovery Rate
HR
Hazard Ratio
IQR
Interquartile Range
ITT
Intention-to-Treat
LAST
Local Anesthetic Systemic Toxicity
MCAR
Missing Completely At Random
MCID
Minimal Clinically Important Difference
MI
Multiple Imputation
MICE
Multiple Imputation by Chained Equations
NNH
Number Needed to Harm
NNT
Number Needed to Treat
OR
Odds Ratio
PCA
Patient-Controlled Analgesia
PONV
Postoperative Nausea and Vomiting
PP
Per-Protocol
RCT
Randomized Controlled Trial
RD
Risk Difference
RR
Risk Ratio
SAE
Serious Adverse Event
SAP
Statistical Analysis Plan
SD
Standard Deviation
SE
Standard Error
VAS
Visual Analog Scale (0-10)

DOCUMENT APPROVAL
The study design, ethical considerations, and statistical analysis plan were approved by the Ethics Committee.
Dr. Roberto Coloma Díaz
Principal Investigator
Dr. Nicolas Valls Jiménez
Study Director
Dr. Duniel Ortuño Borroto
Chair, Ethics Committee