Background
1
There was significant BSV in CL (29%), baseline neutrophil count (48%), drug effect slope factor (17%) and mean neutrophil transit time (MTT; 17%). BOV in CL (30%), slope (31%) and MTT (12%) were significant. Predictive performance when based on PD data only was similar to that of full PKPD information, and superior to the use of only PK or baseline data (tab.1). Adding information from more treatment courses Predictive Performance of a Myelosuppression Model for Dose Individualization; Impact of Type and Amount of Information Provided Johan E. Wallin, Lena E. Friberg and Mats O. Karlsson Division of Pharmacokinetics & Drug Therapy, Uppsala University, Sweden A previously published semi-mechanistic model for myelo-suppression (fig.1) has successfully been applied for several cytotoxic drugs [1], among them etoposide. Observed plasma drug concentration and/or neutrophil counts from the previous cycle and a PKPD model of myelosuppression may be used for dose individualization in order to avoid severe neutropenia or a suboptimal tumor effect. Multiple course data of etoposide plasma concentrations and neutrophil counts were available for 44 patients from two previously published studies [2,3]. Data was analysed using NONMEM 6. BSV and BOV, including covariances, were estimated. Model performance was evaluated by goodness- of-fit plots and predictive checks. One thousand patients receiving 5 courses of therapy were simulated from the final model. POSTHOC estimates were obtained providing either - only PK data - neutrophil baseline (BASE) - full course PD profiles - full course PK+PD profiles from one to four previous cycles (fig.2). The POSTHOC estimates were used as input in a set of models designed to find the dose expected to result in a nadir of 1*10 9 cells/L. As a reference, a standard dose reduction of 25% was used when a patient experience severe toxicity. The resulting nadir of adjusted dose when knowing the true parameters was used as outcome. Background Results and Discussion Conclusion PK provided little benefit to predictive performance if PD information was available. The ratio of BSV/BOV is of importance in the precision of PK- or PD-guided dosing, and the etoposide model contains rather large BOV. Model-based dose individualization was shown to decrease the proportion of patients with severe toxicity despite selective dose escalation. [1] Friberg LE et al. J Clin Oncol 20:4713–4721, 2002 The average second course dose was somewhat lower with PD-guided model based dosing compared to standard treatment recommendations, 86 % vs. 90% of first course dose. However with PD-guidance there was selective dose escalation and still the number of patients experiencing severe neutropenia was lowered by 8%. The overall number of patients achieving a nadir in the close range to 1*10 9 cells/l was somewhat increased (tab.2). Table 1. Predictive performance using different levels of information Table 2. Nadir in second course of treatment after different methods of dose adjustment BASE PK PK+BASE PD PKPD Prediction with information from one previous course mpe 0.0048 0.026 0.039 0.042 0.049 rmse 1.25 1.37 1.17 1.09 1.08 Prediction with information from two previous courses mpe 0.048 0.079 0.095 0.078 0.097 rmse 1.22 1.35 1.37 1.09 1.08 Prediction with information from four previous courses mpe 0.005 0.053 0.068 0.037 0.058 rmse 1.21 1.33 1.11 1.04 1.01 no adjustment 25% reduction if Grade 4 BASE PK PD PKPD median 0.741 0.927 0.957 0.911 0.994 0.987 min 0.00002 0.00002 0.0001 2 0.00005 0.0002 2 0.00027 max 6.221 6.221 7.146 6.582 6.532 6.384 stdev 0.960 1.011 1.100 1.024 1.050 1.034 0.75-1.25*10 9 19.1% 21.4% 21.8% 22.9% 22.5% 22.7% <0.5*10 9 ( gr4 tox) 35.8% 28.3% 27.3% 27.9% 25.7% 26.2% One reason for not seeing a more marked difference between the dosing methods is due to the relatively large estimated BOV used for simulating data. If using smaller BOV the difference become more apparent. References Methods The aim was to evaluate the importance of PK- and PD- information on the predictive performance, and improvement with accumulated information with an increased number of administered courses. Aim Fig 2. PK- and/or PD-information is used for prediction of sequential course Fig 1. Depiction of the semi-mechanistic myelosuppression model
description
Predictive Performance of a Myelosuppression Model for Dose Individualization; Impact of Type and Amount of Information Provided Johan E. Wallin, Lena E. Friberg and Mats O. Karlsson Division of Pharmacokinetics & Drug Therapy, Uppsala University, Sweden. Background. - PowerPoint PPT Presentation
Transcript of Background
There was significant BSV in CL (29%), baseline neutrophil count (48%), drug effect slope factor (17%) and mean neutrophil transit time (MTT; 17%). BOV in CL (30%), slope (31%) and MTT (12%) were significant. Predictive performance when based on PD data only was similar to that of full PKPD information, and superior to the use of only PK or baseline data (tab.1). Adding information from more treatment courses improved the performance.
Predictive Performance of a Myelosuppression Model for Dose Individualization; Impact of Type and Amount of Information Provided
Johan E. Wallin, Lena E. Friberg and Mats O. Karlsson Division of Pharmacokinetics & Drug Therapy, Uppsala University, Sweden
A previously published semi-mechanistic model for myelo-suppression (fig.1) has successfully been applied for several cytotoxic drugs [1], among them etoposide. Observed plasma drug concentration and/or neutrophil counts from the previous cycle and a PKPD model of myelosuppression may be used for dose individualization in order to avoid severe neutropenia or a suboptimal tumor effect.
Multiple course data of etoposide plasma concentrations and neutrophil counts were available for 44 patients from two previously published studies [2,3]. Data was analysed using NONMEM 6. BSV and BOV, including covariances, were estimated. Model performance was evaluated by goodness-of-fit plots and predictive checks.
One thousand patients receiving 5 courses of therapy were simulated from the final model. POSTHOC estimates were obtained providing either - only PK data - neutrophil baseline (BASE)- full course PD profiles- full course PK+PD profiles from one to four previous cycles (fig.2).
The POSTHOC estimates were used as input in a set of models designed to find the dose expected to result in a nadir of 1*109 cells/L. As a reference, a standard dose reduction of 25% was used when a patient experience severe toxicity. The resulting nadir of adjusted dose when knowing the true parameters was used as outcome.
Background
Results and Discussion
Conclusion PK provided little benefit to predictive performance if PD information was available. The ratio of BSV/BOV is of importance in the precision of PK- or PD-guided dosing, and the etoposide model contains rather large BOV. Model-based dose individualization was shown to decrease the proportion of patients with severe toxicity despite selective dose escalation.
[1] Friberg LE et al. J Clin Oncol 20:4713–4721, 2002
[2] Ratain MJ, et al:. Clin Pharmacol Ther 45:226-233, 1989
[3] Ratain MJ, et al: J Clin Oncol 9:1480-1486, 1991
The average second course dose was somewhat lower with PD-guided model based dosing compared to standard treatment recommendations, 86 % vs. 90% of first course dose. However with PD-guidance there was selective dose escalation and still the number of patients experiencing severe neutropenia was lowered by 8%. The overall number of patients achieving a nadir in the close range to 1*109 cells/l was somewhat increased (tab.2).
Table 1. Predictive performance using different levels of information
Table 2. Nadir in second course of treatment after different methods of dose adjustment
BASE PK PK+BASE PD PKPD
Prediction with information from one previous course
mpe 0.0048 0.026 0.039 0.042 0.049
rmse 1.25 1.37 1.17 1.09 1.08
Prediction with information from two previous courses
mpe 0.048 0.079 0.095 0.078 0.097
rmse 1.22 1.35 1.37 1.09 1.08
Prediction with information from four previous courses
mpe 0.005 0.053 0.068 0.037 0.058
rmse 1.21 1.33 1.11 1.04 1.01
no adjustment
25% reduction if Grade 4 BASE PK PD PKPD
median 0.741 0.927 0.957 0.911 0.994 0.987
min 0.00002 0.00002 0.00012 0.00005 0.00022 0.00027
max 6.221 6.221 7.146 6.582 6.532 6.384
stdev 0.960 1.011 1.100 1.024 1.050 1.034
0.75-1.25*109 19.1% 21.4% 21.8% 22.9% 22.5% 22.7%
<0.5*109 (gr4 tox) 35.8% 28.3% 27.3% 27.9% 25.7% 26.2%
One reason for not seeing a more marked difference between the dosing methods is due to the relatively large estimated BOV used for simulating data. If using smaller BOV the difference become more apparent.
References
Methods
The aim was to evaluate the importance of PK- and PD- information on the predictive performance, and improvement with accumulated information with an increased number of administered courses.
Aim
Fig 2. PK- and/or PD-information is used for prediction of sequential course
Fig 1. Depiction of the semi-mechanistic myelosuppression model
