Overall survival (OS) and Progression-free survival (PFS) curves for the entire cohort.

<p>Complete follow-up.</p

3-year overall survival (OS) curves for the entire cohort stratified by the ECOG score.

<p>The hazard rates of groups 1, 2, 3, 4 relative to group ECOG = 0 are 2.85, 3.89, 3.82, 24.58, respectively. Notice the clear separation of the group ECOG = 4 from the rest of the population. However, group ECOG = 4 contains only 8 patients. Optimal stratification of the population into two groups thus separates group ECOG = 0 (109 patients) from the rest of the population (334 patients).</p

Multivariate model results.

<p><i>Results of the final multivariate 3-year overall survival (OS) model: Hazard rate (HR) with its 95% confidence interval (CI) and P-value based on the Cox regression model.</i></p

Summary of all the prognostic factors.

<p><i>Results of the univariate 3-year overall survival (OS) analyses: hazard rate (HR) with its 95% confidence interval (CI) and P-value based on the Cox regression model. Descriptive statistics of all the prognostic factors.</i></p

Overall survival (OS) curves for the entire cohort stratified by the 4-level scoring systems: the proposed novel ABE4-Score, and the classical IPI, AA-IPI, and E-IPI scores.

<p>Overall survival (OS) curves for the entire cohort stratified by the 4-level scoring systems: the proposed novel ABE4-Score, and the classical IPI, AA-IPI, and E-IPI scores.</p

Overall survival (OS) curves for the entire cohort stratified by the 3-level scoring systems: the proposed novel ABE3-Score, and the classical R-IPI, and ALC/RIPI scores.

<p>Overall survival (OS) curves for the entire cohort stratified by the 3-level scoring systems: the proposed novel ABE3-Score, and the classical R-IPI, and ALC/RIPI scores.</p

Summary of the scoring systems.

<p><i>Distribution and outcome of patients according to the compared risk scoring systems. Results of the univariate 3-year overall survival analysis: estimated 3-year overall survival (OS) with its 95% confidence interval (CI), hazard rate (HR) with its 95% CI and P-value based on the Cox regression model. Reference group in all regression models is the lowest risk group.</i></p

Summary of the validation of the ABE scoring systems.

<p><i>Results of the univariate 3-year overall survival analysis in the training and the validation data sets: hazard rate (HR) with its 95% CI and P-value based on the Cox regression model. Reference group in all regression models is the lowest risk group. The measure of concordance compares the model discrimination.</i></p

Comparison of the novel scores with the existing ones.

<p><i>Results from comparison of newly constructed scores (ABE4-Score and ABE3-Score) with several existing scoring systems. The measure of concordance compares the model discrimination, the Akaike Information Criterion (AIC) compares the model fit.</i></p

DataSheet1_Characterization of the input material quality for the production of tisagenlecleucel by multiparameter flow cytometry and its relation to the clinical outcome.pdf

Tisagenlecleucel (tisa-cel) is a CD19-specific CAR-T cell product approved for the treatment of relapsed/refractory (r/r) DLBCL or B-ALL. We have followed a group of patients diagnosed with childhood B-ALL (n = 5), adult B-ALL (n = 2), and DLBCL (n = 25) who were treated with tisa-cel under non-clinical trial conditions. The goal was to determine how the intensive pretreatment of patients affects the produced CAR-T cells, their in vivo expansion, and the outcome of the therapy. Multiparametric flow cytometry was used to analyze the material used for manufacturing CAR-T cells (apheresis), the CAR-T cell product itself, and blood samples obtained at three timepoints after administration. We present the analysis of memory phenotype of CD4/CD8 CAR-T lymphocytes (CD45RA, CD62L, CD27, CD28) and the expression of inhibitory receptors (PD-1, TIGIT). In addition, we show its relation to the patients’ clinical characteristics, such as tumor burden and sensitivity to prior therapies. Patients who responded to therapy had a higher percentage of CD8+CD45RA+CD27+ T cells in the apheresis, although not in the produced CAR-Ts. Patients with primary refractory aggressive B-cell lymphomas had the poorest outcomes which was characterized by undetectable CAR-T cell expansion in vivo. No clear correlation of the outcome with the immunophenotypes of CAR-Ts was observed. Our results suggest that an important parameter predicting therapy efficacy is CAR-Ts’ level of expansion in vivo but not the immunophenotype. After CAR-T cells’ administration, measurements at several timepoints accurately detect their proliferation intensity in vivo. The outcome of CAR-T cell therapy largely depends on biological characteristics of the tumors rather than on the immunophenotype of produced CAR-Ts.</p