Metronomic chemotherapy is usually associated with better tolerance than conventional chemotherapy, and encouraging response rates have been reported in various settings. However, clinical development of metronomic chemotherapy has been hampered by a number of limitations, including the vagueness of its definition and the resulting empiricism in protocol design. In this study, we developed a pharmacokinetic/pharmacodynamic mathematical model that identifies the most effective administration schedule for gemcitabine monotherapy. This model is based upon four biological assumptions regarding the mechanisms of action of metronomic chemotherapy, resulting in a set of 6 minimally parameterized differential equations. Simulations identified daily 0.5-1 mg/kg gemcitabine as an optimal protocol to maximize antitumor efficacy. Both metronomic protocols (0.5 and 1 mg/kg/day for 28 days) were evaluated in chemoresistant neuroblastoma-bearing mice and compared with the standard MTD protocol (100 mg/kg once a week for 4 weeks). Systemic exposure to gemcitabine was 14 times lower in the metronomic groups compared with the standard group. Despite this, metronomic gemcitabine significantly inhibited tumor angiogenesis and reduced tumor perfusion and inflammation, while standard gemcitabine did not. Furthermore, metronomic gemcitabine yielded a 40%-50% decrease in tumor mass at the end of treatment as compared with control mice ( = 0.002; ANOVA on ranks with Dunn test), while standard gemcitabine failed to significantly reduce tumor growth. Stable disease was maintained in the metronomic groups for up to 2 months after treatment completion (67%-72% reduction in tumor growth at study conclusion, < 0.001; ANOVA on ranks with Dunn test). Collectively, our results confirmed the superiority of metronomic protocols in chemoresistant tumors .
Aims: Chemotherapy-induced neutropenia has been associated with an increase in overall survival in non-small cell lung cancer patients. Therefore, neutrophil counts could be an interesting biomarker for drug efficacy as well as linked directly to toxicity. For drugs where neutropenia is dose limiting, neutrophil counts might be used for monitoring drug effect and for dosing optimisation. Methods: The relationship between drug effect on the first cycle neutrophil counts and patient survival was explored in a Phase III clinical trial where patients with nonsmall cell lung cancer were treated with docetaxel. Once the association has been established, dosing optimisation was performed for patients with severe toxicities (neutropenia) without compromising drug efficacy (overall survival). Results: After taking into account baseline prognostic factors, such as Eastern Cooperative Oncology Group performance status, smoking status, liver metastasis, tumour burden, neutrophil counts and albumin levels, a model-predicted drug effect on the first cycle neutrophil counts was strongly associated with patient survival (P = .005). Utilising this relationship in a dose optimisation algorithm, 194 out of 366 patients would have benefited from a dose reduction after the first cycle of docetaxel. The simulated 1-year survival probabilities associated with the original dose and the individualised dose were not different. Conclusion: The strong relationship between drug effect on the first cycle neutrophil counts and patient survival suggests that this variable could be used to individualise dosing, possibly without needing pharmacokinetic samples. The algorithm highlights that doses could be reduced in case of severe haematological toxicities without compromising drug efficacy. K E Y W O R D S chemotherapy-induced neutropenia, docetaxel, neutrophil counts, non-small cell lung cancer, precision dosing The authors confirm that the PI for this paper is Aurélie Lombard. This is a retrospective data analysis and there were no interventions performed or substances administered to patients.
Purpose During oncology clinical trials, tumour size (TS) measurements are commonly used to monitor disease progression and to assess drug efficacy. We explored inter-operator variability within a subset of a phase III clinical trial conducted from August 1995 to February 1997 and its impact on drug effect evaluation using a tumour growth inhibition model. Methods One hundred twenty lesions were measured twice at each time point; once at the hospital and once at the centralised centre. A visual analysis was performed to identify trends within the profiles over time. Linear regression and relative error ratios were used to explore the inter-operator variability of raw TS measurements and model-based estimates. Results While correlation between patient-level estimates of drug effect was poor (r 2 = 0.28), variability between the studylevel estimates was much less affected (9%). Conclusions The global evaluation of drug effect using modelling approaches might not be affected by inter-operator variability. However, the exploration of covariates for drug effect and the characterisation of an exposure-tumour shrinkage relationship seems limited by the high measurement variability that translates to a poor correlation of individual drug effect estimates. This might be addressed by the use of more precise computer-aided measurement methods.
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