The main patient characteristics are described in Table2. Type of tumor and mobilization were similar between the groups.

Based on AIC minimization, the combined variability structure was selected. The equation of the estimated base model was AP-CD34+=1.63+1.02 (PB-CD34+)+e where e had a zero-mean normal distribution N (0, s2 (k+prediction)2).

The parameter values for intercept, PB-CD34+, k, and were 1.63 (SE=0.72), 0.12 (SE=0.01), 1.76 and 0.49, respectively.

The base model showed a satisfactory goodness-of-fit plot. In the predicted vs the observed scatterplot, the dots were well scattered around the identity line indicating unbiased model predictions. Additionally, the plot of residual values confirmed non-homogeneous variance with greater residual variability for larger predicted values of the AP-CD34+ cell counts. In terms of predictive accuracy, the base model was able to properly predict the percentage of patients achieving both 2 106 and 5 106 AP-CD34+ cells/kg (Fig.2).

AP-CD34+ cluster of differentiation 34+ cells on the first day of apheresis, CI confidence interval.

The base model can be used to characterize the necessary counts of PB-CD34+ to achieve thresholds of 2 106 and 5 106 AP-CD34+ cells/kg (Fig.3).

AP-CD34+ cluster of differentiation 34+ cells on the first day of apheresis, PB-CD34+ peripheral blood-cluster of differentiation 34.

According to the base model, an estimated PB-CD34+ counts of 57.01 (90% CI: 21.76130.76) and 125.24 (90% CI: 72.09330.71) 106/L were necessary to reach thresholds of 2 106 and 5 106 AP-CD34+ cells/kg, respectively, with a probability of 0.90.

Based on AIC minimization, the best model includes the tumor type (neuroblastoma and other) as covariate. The equation of the estimated final model was as follows:

$${{{{{{{mathrm{Neuroblastoma}}}}}}}}:{{{{{{{mathrm{AP}}}}}}}} {mbox{-}} {{{{{{{mathrm{CD}}}}}}}}34^ + = 3.01 + 0.13 times left( {{{{{{{{mathrm{PB}}}}}}}} {mbox{-}} {{{{{{{mathrm{CD}}}}}}}}34^ + } right) + e$$

$${{{{{{{mathrm{Other}}}}}}}};{{{{{{{mathrm{tumor}}}}}}}};{{{{{{{mathrm{types}}}}}}}}:{{{{{{{mathrm{AP}}}}}}}} {mbox{-}} {{{{{{{mathrm{CD}}}}}}}}34^ + = 0.01 + 0.13 times left( {{{{{{{{mathrm{PB}}}}}}}} {mbox{-}} {{{{{{{mathrm{CD}}}}}}}}34^ + } right) + e$$

where e had a zero-mean normal distribution N (0, s2 (k+prediction)2).

The parameter values for intercept-neuroblastoma, intercept-other, PB-CD34+, and were 3.01 (SE=1.10), 0.01 (SE=0.006), 0.13 (SE=0.01), (simeq) 0.00 and 0.54, respectively.

According to the model, the predicted count of AP-CD34+ cells was slightly larger for neuroblastoma tumor types than for the other tumor types. It should be noted that the final model was selected considering the type of tumor as an additional covariate (in addition to PB-CD34+) based on statistical information criterion (AIC), and that the tumor type was correlated with the age of the patients - the patients with Neuroblastoma tumor type, with mean age of 3.7 years (standard deviation, SD=2.1 years), being younger than the others with mean age of 8.9 years (SD=4.8 years). However, the choice of considering tumor type in the final model instead of age was driven by the fact that the fit of the data was improved when tumor type was considered as predictor, as compared to age, which reflected in lower value of the statistical information criterion with tumor type (AIC=288.6) than with age (AIC=310.1).

The final model also showed a good predictive property in terms of goodness-of-fit plot and prediction of the percentages of patients achieving both 2 106 and 5 106 AP-CD34+ cells/kg (Fig.4). The model predicts that a smaller PB-CD34+ cell count was needed to reach 2 106 and 5 106 AP-CD34+ cells/kg with a probability of 0.90 in patients with neuroblastoma tumor type than in those with other tumor types (Fig.5). According to the final model, in patients with neuroblastoma tumor type, the estimated PB-CD34+ counts necessary to reach apheresis thresholds of 2 106 and 5 106 AP-CD34+ cells/kg with a probability of 0.90 were 27.32 (90% CI: 0.1650.51) and 103.20 (90% CI: 56.15165.18) 106/L, respectively. The estimated PB-CD34+ counts necessary to reach thresholds of 2 106 and 5 106 AP-CD34+ cells/kg with a probability of 0.90 in patients with other tumor type were 50.51 (90% CI: 29.3079.12) and 126.39 (90% CI: 77.25198.28) 106/L, respectively.

AP-CD34+ cluster of differentiation 34+ cells on the first day of apheresis, CI confidence interval.

AP-CD34+ cluster of differentiation 34+ cells on the first day of apheresis, PB-CD34+, peripheral blood-cluster of differentiation 34+.

The uncertainty related to these PB-CD34+ estimated values with the final model was slightly less in comparison to the base model probably due to a reduced residual variability.

The physiological process of stem cell mobilization via CXCR4 is comparably the same in subjects of all ages, and when adult data on CXCR4 is extrapolated into children it should closely mirror that seen in children [19]. We complemented our analyses with data from the adult NHL and MM patients who participated in the two plerixafor studies [15, 16], focusing on the first day of apheresis similar to the MOZAIC study. The details of the analyses can be found in theSupplementary section.

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Development and validation of a predictive model to guide the use of plerixafor in pediatric population | Bone Marrow Transplantation - Nature.com