A Phase 1/2 Two-center, Double-blind, Randomized, Placebo-controlled Multi-period Crossover (N-of-1) Study to Evaluable the Feasibility, Safety, and Efficacy of TJ-68 in Patients With Amyotrophic Lateral Sclerosis (ALS) and Muscle Cramps
Phase: PHASE1
Conditions: Amyotrophic Lateral Sclerosis, Muscle Cramp
Sponsor: Hiroshi Mitsumoto

 
 
 
A PHASE 1/2, TWO-CENTER, DOUBLE-BLIND, RANDOMIZED, PLACEBO-
CONTROLLED MULTI-PERIOD CROSSOVER (N-OF-1) STUDY TO EVALUATE THE 
FEASIBILITY, SAFETY, AND EFFICACY OF TJ-68 IN PATIENTS WITH AMYOTROPHIC 
LATERAL SCLEROSIS (ALS) AND MUSCLE CRAMPS 
 
 
 
NCT04998305 
 
June 27, 2024 
 
 
 
 
 
 
 
 
 
 
 
 
 

1. Background 
This is the statistical analysis plan for is a phase 1/2 trial of TJ-68 in participants with 
amyotrophic lateral sclerosis (ALS) and muscle cramps. This trial aims to evaluate the efficacy of 
TJ-68 for improving muscle cramps in the participants using a double-blind, randomized, 
crossover design.  This trial also aims to evaluate safety of TJ-68.  
 
2. Study Design 
2.1. Design Overview 
This is a multi-period crossover study where each participant will receive four 2-week 
treatment periods of TJ-68/placebo.   We plan to randomize a total of 26 participants, with 13 
randomized to Treatment Sequence A: TJ-68-Placebo-Placebo-TJ-68, and another 13 to 
Treatment Sequence B: Placebo-TJ-68-TJ-68-Placebo, with a 1-week washout period between 
treatment periods.   That is, each participant will receive TJ-68 and Placebo each in two 
separate treatment periods.  Assuming 15% attrition, we expect to have 22 evaluable 
participants.  Balanced randomization of the two alternating treatment sequences will 
eliminate linear trend in the primary analysis.   
 
2.2.  Randomization Procedures 
The 22 evaluable participants will be randomized 1:1 to the two treatment sequences based on 
the study schedule, using blocked randomization stratified by site. To ensure power with 
anticipated dropout (15%), we anticipate randomizing up to 2 additional participants to each 
treatment sequence. 
 
2.3.  Analysis Populations and Missing Data 
All efficacy analyses will be performed using the modified intent-to-treat (mITT) population.  
The mITT population consists of all randomized participants with outcomes evaluated in at least 
two (out of four) post-randomization periods with at least one period in TJ-68 and one in 
Placebo.     
 
As sensitivity analyses, we will also perform efficacy analyses in the completers only, that is, 
participants with outcome evaluated in all 4 treatment periods.   
 
Safety analyses will be performed as treated.   
 
Missing data patterns will be compared by treatment sequence as well as by the treatment 
periods.  While the primary analyses will be performed in the mITT population defined above, 
we will perform sensitivity analyses using imputed data sets under different imputation 
approaches: 

(A) Mean imputations: Missing data within a treatment period will be imputed using averages 
from other data points within the same treatment period.  If data in the entire treatment 
period is missing, the observations from the previous period will be carried forward. 
(B) Worst-outcome imputations: All missing data will be imputed using the worst values 
observed in a treatment group. 
3. Primary Efficacy Analysis 
3.1. Primary Outcome 
The primary outcome of the study will be calculated using the Columbia Muscle Cramp Scale 
(MCS).  We will use MCS item #5, visual analog scale (VAS) (0-10) for Muscle Cramps Affecting 
Overall Daily Activity of Columbia MCS as the primary outcome.  The MCS will be assessed on 
the phone twice a week; thus, there will be a total of four MCS assessments per treatment 
period.   However, for the primary analysis, only data in the second week of each treatment 
period will be used to minimize carryover effects.   
 
3.2.  Statistical Analysis for the Primary Outcome 
The primary analysis will be performed using linear mixed effect (LME) model to estimate the 
effect of TJ-68 compared to placebo on MCS VAS.   The LME model will use all available MCS 
VAS measured in the second week of all treatment periods per mITT.   The model will include 
TJ-68 as a main effect with a random participant effect to account for within-individual 
correlation.  While balanced randomization of Treatment Sequences A and B will eliminate 
linear time trend, we will also explore linear and non-linear time effects in the LME model to 
explore the impact on the primary comparison between TJ-68 and Placebo.   
 
3.3.       Sample Size Consideration 
We aim to enroll 22 evaluable participants equally to the two alternating TJ-68/Placebo 
sequences over the four treatment periods, i.e., each participant will have 4 observations.  
Under the LME model, assuming a within-participant standard deviation of 1.4 based on our 
pilot data, this sample size will yield about 85% power to detect a 1-point shift on MCS VAS    
Assuming 15% attrition, we will plan to enroll a total of 22 participants.  
 
4. Safety Analysis 
Adverse events (AE), including the presence of hypokalemia, will be summarized by treatment 
per participant.  The AE will be attributed to the period in which it is observed.  AE rate by 
treatment will be summarized using proportion and 95% confidence intervals and will be 
compared using McNemar test.  Longitudinal AE data will be modeled using generalized linear 
mixed effect model with a logit link.  
 
5. Secondary Outcome Analyses 

5.1.  Additional Analyses of MCS 
Secondary outcomes based on the MCS include (i) total MCS score, (ii) cramp frequency, 
severity, or both measured via the Cramp Diary (CD), (iii) MCS Additional Questions, and (iv) 
VAS of Cramp Pain.   These secondary outcomes will be analyzed using LME in the same manner 
as in the analysis of the primary outcome.  
 
 
5.2.  Other Secondary outcomes 
Other secondary outcomes of the study include ALSFRS-R within each treatment period, clinical 
global impression of changes (CGIC) within each treatment period, qualify of life measured via 
ALSAQ-5 within each treatment period, and goal assessment scale (GAS) within each treatment 
period.  As these outcomes are measured longitudinally, they will be analyzed using LME 
models.  
 
 
5.3.  Heterogeneity of treatment effects and plasma metabolomics 
We will perform exploratory analysis to understand treatment mechanism via heterogeneity of 
treatment effects.  Specifically, plasma metabolomics will be measured longitudinally, and will 
be included as a longitudinal covariate in the LME models.  Its interaction with treatment 
effects will also be explored.