Residual β-Cell Function Predicts Clinical Response After Autologous Hematopoietic Stem Cell Transplantation

New strategies of autologous hematopoietic stem cell transplantation (auto-HSCT) have gained much interest for the treatment of type 1 diabetes mellitus. However, assessing the clinical response and residual β-cell function still has limitations. The aim of the study was to select the optimal quantitative index to assess pre-existing β-cell function and to explore its predictive function for clinical response after auto-HSCT therapy. In this study, all of the patients who had undergone auto-HSCT were clustered into a responder group (Δβ-score > 0) and a nonresponder group (Δβ-score ≤ 0). We compared their quantitative metabolic indexes at baseline and performed receiver-operating characteristic (ROC) analysis to analyze the correlations between the indexes and clinical response. Kaplan-Meier analysis was conducted to compare the cumulative response durations in each quartile of the selected indexes. In an average of 15.13 ± 6.15 months of follow-up, 44 of 112 patients achieved a clinical response. The responder group had lower levels of fasting plasma glucose and quantitative insulin sensitivity check index (QUICKI) but higher levels of fasting C-peptide, fasting insulin, and homeostasis model assessments for insulin resistance (HOMA-IR). ROC analysis showed that HOMA-IR had the largest area under the curve (0.756), which was similar to that of QUICKI. Kaplan-Meier analysis further confirmed that the third quartile (1.3371-1.7018) of HOMA-IR or the second quartile (0.3523-0.3657) of QUICKI was preferential for a prolonged response. In conclusion, HOMA-IR and QUICKI could be optimal measurements for β-cell reserves, and they were predictive for the clinical response after auto-HSCT.

The β-score was comprehensive and reliable in evaluating clinical response after autologous hematopoietic stem cell transplantation (HSCT). The homeostasis model assessments for insulin resistance and the quantitative insulin sensitivity check index could serve as precise assessments for residual β-cell function and good predictors of clinical response. They might be used to select optimal clinical trial participants or predict the clinical response after auto-HSCT.