1. Introduction The purpose of this document is to provide sufficient proof that SRA-MMB-301 study results will not be influenced by the randomization method used known as “biased coin method”. Therefore, a re-randomization test was performed. This was performed in two parts. First, the algorithm used for randomization of the study was reconstructed to make sure that the same algorithm is used to construct the empirical cumulative distribution function (cdf) for the statistical test. Second, rerandomization is performed and rerun the statistical test keeping the same outcome for each patient, and the empirical cdf is constructed. The primary objective of the study is to determine the efficacy of Momelotinib (MMB) versus Danazol (DAN) assessed by improvement in Myelofibrosis Symptom Assessment Form v4.0 (MFSAF) total symptom score (TSS) in subjects with PMF, post-polycythemia vera myelofibrosis (MF), or post-essential thrombocythemia MF who were previously treated with approved Janus kinase (JAK) inhibitor therapy. The corresponding primary endpoint is MFSAF TSS response rate at Week 24. TSS response rate is defined as the proportion of subjects who achieved a ≥ 50% reduction in TSS over the 28 days immediately prior to the end of Week 24 compared to baseline. 2. Re-randomization test As outcomes for one particular set of treatment assignment, the randomized one in this case, are observed, it is possible to rerun the statistical tests for any other treatment assignment keeping the same outcome for each patient. This would lead to an empirical cumulative distribution function (cdf) for the statistical test and, based on it, the new corresponding p-value for the observed value in the study. Those new treatment assignments or “re-randomization” should be performed following exactly the same randomization scheme as original randomization and should therefore respect the order of entry into the study for the patient as well as their strata values reported to the system. If biased coin method has no impact on statistical results, one should observe significant but also non-significant results and corresponding p-values would finally just be a random number in [0,1]. For this reason, it is also interesting to provide qq-plots of the sorted p-values result from rerandomization against ordered statistics of a U (0,1) random variable. Under null hypothesis, this plot should follow a line with intercept 0 and slope 1. Further, the empirical p-value obtained from the rerandomization should be equal to the observed p-value. The empirical p-value is the number of test values superior to the observed value in the statistical analysis divided by the number of rerandomizations performed. 2.1.Algorithm implementation The program to generate the same treatment assignment as the one in the randomization file of the study was written in R Studio. Using the randomization file’s random variable, the treatment sequence obtained in R Studio were identical as the one in the study randomization file. This perfect match validates the R program. As described in the previous paragraph the re-randomization tests must follow exactly the scheme as original randomization and analysis. For practical reasons, the re-randomizations were also produced using R Studio. The randomization technique used for the study was a biased coin method with probability of 90% to choose MMB as the actual treatment if MMB is the preferred treatment and choose DAN as the actual treatment with probability of 10%. If the preferred treatment is DAN, then we choose DAN as the actual treatment with probability 80% and MMB as the actual treatment with probability 20%. If the imbalance measures of the two treatment arms are identical, then a weighted coin was flipped with probability of 2/3 for selecting MMB as the preferred treatment and probability of 1/3 for selecting DAN as the preferred treatment. For a new subject, the two measures of imbalance, one if the subject is assigned to MMB (diffmmb) and one if the subject is assigned to DAN (diffdan), were computed as follows: diffmmb = 2|1+nxtm - 2(nxtd)| + 2|1+nysm - 2(nysd)| + 3|1+nzrm - 2(nzrd)| + 1|1+nwim 2(nwid)| diffdan = 2|nxtm - 2(1+nxtd)| + 2|nysm - 2(1+nysd)| + 3|nzrm - 2(1+nzrd)| + 1|nwim 2(1+nwid)| Let nflt = number of subjects in level l of factor f on treatment t at a given point in the study. We have four stratification factors: tss (t), spleen (s), rbc transfusion pre-treatment (r), and investigative site (i). t has levels low (l) and high (h), s has levels small (s) and large (l), r has levels 0 (0), 1-4 (1), and 5+ (5), and investigative site has a finite integer number of levels (1, 2, 3, …). There are two treatments: Momelotinib (MMB) (m) and Danazol (DAN) (d 2.2.Re-randomization Using the validated R program, 10000 re-randomizations were performed. For each time of the rerandomization, the MFSAF TSS response rate was compared between the two new treatment arms assignment using a Cochran-Mantel-Haenszel (CMH) test, stratified by MFSAF TSS baseline score, baseline spleen length, and baseline RBC units transfused, on the ITT analysis set. Twosided test was used at 0.05 significance level. Stratification factors used from the study randomization file: - MFSAF TSS baseline score: High (greater than or equal to 22) vs Low (less than 22) - Baseline spleen length: Large (greater than or equal to 12 cm) vs Small (less than 12 cm) - Baseline RBC units transfused: Zero units vs 1 to 4 units (inclusive) vs 5 or greater units 3. Results The re-randomization test analysis was performed on a database with a snapshot date of 14 January 2022. The database contains 195 subjects, and 38 (19.5%) subjects achieved a ≥50% reduction in TSS at week 24. After the re-randomization, the empirical distribution for the CMH test is presented by the following graph. The red line gives the observed value (6.728) in statistical analysis of the CMH test. The plots of the sorted p-values result from the re-randomization against ordered statistics of a U(0,1) random variable follows a line with intercept 0 and slope 1. Finally, the empirical p-value was estimated as 0.0095 which is equal to the observed p-value (0.0095). This is a sufficient proof to assure that the randomization method used in the SRA-MMB301 study (biased coin method) has no impact on the study’s statistical results.
