S plus 8

Descriptive statistics were used for continuous and categorical variables separately. Kruskal-Wallis test and either chi-square test or Fisher exact test, as appropriate, were used for the group comparison for continuous and categorical variables, respectively. Kaplan-Meier survival analysis and Cox regression analysis were used to assess the effect of categorical and continuous covariates, respectively, on DDFS. All computations were carried out in SAS 9.3 (SAS Institute Inc., Cary, NC) and Splus 8.2 (TIBCO Software Inc, Palo Alto, CA).

Summary statistics including mean, standard deviation, median, and range for continuous variables and frequency counts and percentages for categorical variables. Fisher exact test or χ² test were used to evaluate the association between two categorical variables. Wilcoxon rank sum test was used to evaluate the difference in continuous variables between groups. We calculated ICU and hospital length of stay using (LOS) as the time interval from admission to discharge or death. LOS was reported with median and range. The Kaplan-Meier method was used to estimate the rate and median overall survival (OS) and progression free survival (PFS). Overall survival time was calculated from CAR T-cell infusion date to death or last follow-up date. Patients were followed up for at least 1 year after infusion and median follow-up time for the censored observations (alive patients) was reported. Progression free survival was calculated from time of CAR T-cell infusion to disease progression or death, whichever happened first. Considering the small amount of events occurring after 1 year after infusion, patients with the last follow up or event occurring after one year post infusion, were censored at one year. Statistical software SAS (version 9.4, Cary, North Carolina) and S-Plus 8.2 (TIBCO Software Inc., Palo Alto, CA) were used for the analyses. A p value <0.05 was considered significant.

The primary objective was to determine the correlation between corrected calcium and ionized calcium in each group using the Spearman correlation coefficient. To illustrate correlation, scatterplots of calcium measurements were fitted with locally-weighted smoothing regression curves [32 ]. Secondary analyses included sensitivity and specificity of corrected calcium in detecting hypercalcemia using the ranges defined above, where a true hypercalcemia was defined by elevated ionized calcium ≥ 5.33mg/dL. Additionally, multiple linear regression was performed to assess the influence of several myeloma-related variables (serum albumin, phosphorus, creatinine, paraprotein, free kappa light chains, free lambda light chains, and MM immunoglobulin type) on corrected calcium measurements. Continuous variables were compared between patient groups via two-sample t-test (or Mann-Whitney test) and discrete variables were evaluated for association via Fisher’s exact test (or Chi-square test). Statistical significance was defined as p-value < 0.05. Statistical software SAS 9.3 (SAS, Cary, NC), R, and S-Plus 8.2 (TIBCO Software Inc., Palo Alto, CA) were used for the analyses.

In this pilot study exploring the utility of early PET/CT, descriptive statistics defined baseline characteristics and treatment response/outcomes. Fisher’s exact test was used to evaluate the association between EOT response and other categorical variables. Kaplan-Meier method was used to estimate time-to-event endpoints. Log-rank test was used to evaluate the difference in time-to-event outcomes between patient groups. Progression free survival (PFS) was defined as time from start of salvage treatment to the first occurrence of progression, relapse, or death due to any cause. Disease specific survival (DSS) was defined as time from start of salvage treatment to death secondary to lymphoma. A two-sided P-value of <0.05 was considered statistically significant. Statistical software used included SAS 9.4 (SAS, Cary, NC), S-Plus 8.2 (TIBCO Software Inc., Palo Alto, CA), and R 4.0.2 (R Core Team, Vienna, Austria).