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- Janssen, Julie M, et al.
(författare)
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Longitudinal nonlinear mixed effects modeling of EGFR mutations in ctDNA as predictor of disease progression in treatment of EGFR-mutant non-small cell lung cancer.
- 2022
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Ingår i: Clinical and Translational Science. - : John Wiley & Sons. - 1752-8054 .- 1752-8062. ; 15:8, s. 1916-1925
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Tidskriftsartikel (refereegranskat)abstract
- Correlations between increasing concentrations of circulating tumor DNA (ctDNA) in plasma and disease progression have been shown. A nonlinear mixed effects model to describe the dynamics of epidermal growth factor receptor (EGFR) ctDNA data from patients with non-small cell lung cancer (NSCLC) combined with a parametric survival model were developed to evaluate the ability of these modeling techniques to describe ctDNA data. Repeated ctDNA measurements on L858R, exon19del, and T790M mutants were available from 54 patients with EGFR mutated NSCLC treated with erlotinib or gefitinib. Different dynamic models were tested to describe the longitudinal ctDNA concentrations of the driver and resistance mutations. Subsequently, a parametric time-to-event model for progression-free survival (PFS) was developed. Predicted L858R, exon19del, and T790M concentrations were used to evaluate their value as predictor for disease progression. The ctDNA dynamics were best described by a model consisting of a zero-order increase and first-order elimination (19.7/day, 95% confidence interval [CI] 14.9-23.6/day) of ctDNA concentrations. In addition, time-dependent development of resistance (5.0 × 10-4 , 95% CI 2.0 × 10-4 -7.0 × 10-4 /day) was included in the final model. Relative change in L858R and exon19del concentrations from baseline was identified as most significant predictor of disease progression (p = 0.001). The dynamic model for L858R, exon19del, and T790M concentrations in ctDNA and time-to-event model adequately described the observed concentrations and PFS data in our clinical cohort. In addition, it was shown that nonlinear mixed effects modeling is a valuable method for the analysis of longitudinal and heterogeneous biomarker datasets obtained from clinical practice.
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| 2. |
- Molenaar-Kuijsten, Laura, et al.
(författare)
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Everolimus Concentration in Saliva to Predict Stomatitis : A Feasibility Study in Patients with Cancer.
- 2022
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Ingår i: Therapeutic Drug Monitoring. - : Ovid Technologies (Wolters Kluwer Health). - 0163-4356 .- 1536-3694. ; 44:4, s. 520-526
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Most patients with cancer treated with everolimus experience stomatitis, which seriously affects the quality of life. The salivary concentrations of everolimus may predict the incidence and severity of stomatitis. The authors aimed to examine whether it was feasible to quantify the everolimus concentration in saliva and subsequently use it to predict stomatitis.METHODS: Saliva and whole blood samples were taken from patients with cancer, who were treated with everolimus in the dosage of either 10 mg once a day or 5 mg twice a day. Everolimus concentrations in saliva samples were measured by liquid chromatography-tandem mass spectrometry. A published population pharmacokinetic model was extended with the everolimus concentration in saliva to assess any association between everolimus in the blood and saliva. Subsequently, the association between the occurrence of stomatitis and the everolimus concentration in saliva was studied.RESULTS: Eleven patients were included in this study; saliva samples were available from 10 patients, including 3 patients with low-grade stomatitis. Everolimus concentrations were more than 100-fold lower in saliva than in whole blood (accumulation ratio 0.00801 and relative standard error 32.5%). Interindividual variability (67.7%) and residual unexplained variability (84.0%) were high. The salivary concentration of everolimus tended to be higher in patients with stomatitis, 1 hour postdose ( P = 0.14).CONCLUSIONS: Quantification of the everolimus concentration in saliva was feasible and revealed a nonsignificant correlation between everolimus concentration in the saliva and the occurrence of stomatitis. If future research proves this relationship to be significant, the everolimus concentration in the saliva may be used as an early predictor of stomatitis without invasive sampling. Thereby, in patients with high salivary everolimus concentrations, precautions can be taken to decrease the incidence and severity of stomatitis.
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