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Contains fulltext : 288319.pdf (Publisher’s version ) (Open Access), 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.

Item does not contain fulltext, PURPOSE: We studied EGFR mutations in circulating tumor DNA (ctDNA) and explored their role in predicting the progression-free survival (PFS) of non-small cell lung cancer (NSCLC) patients treated with erlotinib or gefitinib. METHODS: The L858R, T790M mutations and exon 19 deletions were quantified in plasma using digital droplet polymerase chain reaction (ddPCR). The dynamics of ctDNA mutations over time and relationships with PFS were explored. RESULTS: In total, 249 plasma samples (1-13 per patient) were available from 68 NSCLC patients. The T790M and L858R or exon 19 deletion were found in the ctDNA of 49 and 56% patients, respectively. The median (range) concentration in these samples were 7.3 (5.1-3688.7), 11.7 (5.1-12,393.3) and 27.9 (5.9-2896.7) copies/mL, respectively. Using local polynomial regression, the number of copies of EGFR mutations per mL increased several months prior to progression on standard response evaluation. CONCLUSION: This change was more pronounced for the driver mutations than for the resistance mutations. In conclusion, quantification of EGFR mutations in plasma ctDNA was predictive of treatment outcomes in NSCLC patients. In particular, an increase in driver mutation copy number could predict disease progression.

Contains fulltext : 235476.pdf (Publisher’s version ) (Closed access), BACKGROUND: Based on reassuring short-term foetal and maternal safety data, there is an increasing trend to administer chemotherapy during the second and third trimesters of pregnancy. The pharmacokinetics (PK) of drugs might change as a result of several physiological changes that occur during pregnancy, potentially affecting the efficacy and safety of chemotherapy. OBJECTIVE: With this analysis, we aimed to quantitatively describe the changes in the PK of docetaxel, paclitaxel, doxorubicin and epirubicin in pregnant women compared with non-pregnant women. METHODS: PK data from 9, 20, 22 and 16 pregnant cancer patients from the International Network of Cancer, Infertility and Pregnancy (INCIP) were available for docetaxel, paclitaxel, doxorubicin and epirubicin, respectively. These samples were combined with available PK data from non-pregnant patients. Empirical non-linear mixed-effects models were developed, evaluating fixed pregnancy effects and gestational age as covariates. RESULTS: Overall, 82, 189, 271, and 227 plasma samples were collected from pregnant patients treated with docetaxel, paclitaxel, doxorubicin and epirubicin, respectively. The plasma PK data were adequately described by the respective models for all cytotoxic drugs. Typical increases in central and peripheral volumes of distribution of pregnant women were identified for docetaxel, paclitaxel, doxorubicin and epirubicin. Additionally, docetaxel, doxorubicin and paclitaxel clearance were increased in pregnant patients, resulting in lower exposure in pregnant women compared with non-pregnant patients. CONCLUSION: Given the interpatient variability, the identified pregnancy-induced changes in PK do not directly warrant dose adjustments for the studied drugs. Nevertheless, these results underscore the need to investigate the efficacy of chemotherapy, when administered during pregnancy.

In recent years new targeted small molecule kinase inhibitors have become available for pediatric patients with cancer. Relationships between drug exposure and treatment response have been established for several of these drugs in adults. Following these exposure–response relationships, pharmacokinetic (PK) target minimum plasma rug concentration at the end of a dosing interval (Cmin) values to guide therapeutic drug monitoring (TDM) in adults have been proposed. Despite the fact that variability in PK may be even larger in pediatric patients, TDM is only sparsely applied in pediatric oncology. Based on knowledge of the PK, mechanism of