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Originally published as JCO Early Release 10.1200/JCO.2005.02.1295 on May 1 2006 © 2006 American Society of Clinical Oncology. Predictors of Vinorelbine Pharmacokinetics and Pharmacodynamics in Patients With Cancer
From the Westmead Institute for Cancer Research Westmead Millennium Institute, Departments of Translational Oncology, Nuclear Medicine and Medical Oncology Sydney; Institute of Clinical Pathology and Medical Research, Westmead; Faculty of Pharmacy and Departments of Pharmacology and Medicine; Faculty of Medicine University of Sydney, Sydney; Department of Medical Oncology, Newcastle Mater Misericordiae Hospital, Waratah, Australia Address reprint requests to Howard Gurney, MD, Department of Medical Oncology, Westmead Hospital, Westmead, NSW 2145, Australia; e-mail: howardg{at}westgate.wh.usyd.edu.au
PURPOSE: Marked interindividual variation in drug disposition and toxicity pose an ongoing challenge to chemotherapy dosage individualization. The aim of this study was to evaluate pretreatment clinical features, genotype and functional indicators of drug clearance as predictors of vinorelbine clearance, and myelotoxicity that could inform dosage optimization. PATIENTS AND METHODS: Forty-one patients with cancer received a 60 mg intravenous dose of vinorelbine. Pretreatment routine body size measurements and blood tests were performed. Midazolam clearance and hepatic technetium labeled sestamibi (99mTc-MIBI) clearance were used to investigate CYP3A and ABCB1 (MDR1, P-glycoprotein) phenotype respectively and selected single nucleotide polymorphisms in CYP3A and ABCB1 were documented. A limited blood sampling strategy was employed and vinorelbine concentrations were determined by high-performance liquid chromatography. Posterior Bayesian estimates of vinorelbine clearance were obtained for each patient using population pharmacokinetic modeling. Myelotoxicity was estimated from the fractional survival of neutrophils post-treatment. RESULTS: There was 4.3-fold variation in vinorelbine clearance across the cohort. In a multivariable analysis, pretreatment estimated creatinine clearance (P < .01) and hepatic 99mTc-MIBI clearance (P = .01) were independent predictors of vinorelbine clearance. Fractional survival of neutrophils ranged from 1.3% to 100% and was significantly correlated with vinorelbine clearance (P < .01). Body-surface area was the only pretreatment predictor of fractional survival of neutrophils independent of vinorelbine clearance (P = .02). CONCLUSION: Specific indicators of drug clearance provide predictive information about vinorelbine pharmacokinetics, and body-surface area, probably reflecting normal bone marrow reserve, provides an additional pharmacodynamic indicator. Use of a fixed dose of vinorelbine with modifications guided by pretreatment measures is worthy of prospective evaluation.
Optimal dosage of cytotoxic chemotherapy achieves a balance between maximal anticancer effect and treatment related toxicity. There are substantial inter individual differences in the systemic effects of chemotherapy, attributed principally to variable drug disposition. Currently, measures of body size, including body-surface area (BSA) are commonly used to individualize chemotherapy dosage. However, these are generally poor indicators of drug pharmacokinetics1,2 and the role of more specific pretreatment indicators of drug clearance in dosage individualization is an active area of research. Principal mechanisms involved in the clearance of common chemotherapeutic agents include metabolism by the CYP3A family of cytochrome P450 enzymes and excretion into bile and/or urine by the adenosine triphosphate-binding cassette transporters such as ABCB1 (MDR1, P-glycoprotein).3,4 These clearance pathways are influenced by a range of environmental and genetic factors and many studies have demonstrated substantial inter- and/or intrapatient variation in their activity.5 Vinorelbine is a vinca alkaloid that has been used in the treatment of a wide range of cancer types. In humans, mechanisms of vinorelbine clearance are not clear but animal studies suggest biliary excretion is a major elimination route,6 and studies indicate that vinorelbine is an ABCB1 substrate,7,8 which is consistent with data showing vinorelbine clearance is reduced by coadministration of the ABCB1 inhibitor zosuquidar in cancer patients.9 In addition, metabolism principally by CYP3A isoenzymes has been shown in vitro10 and both unchanged vinorelbine and an active metabolite have been documented in urine of patients.11 Myelotoxicity, especially neutropenia, is the dose-limiting toxicity of many chemotherapeutic drugs, including vinorelbine, and a large degree of inter-patient variation in myelosuppression has been observed.12-14 This may be largely attributable to pharmacokinetic differences, however the intrinsic susceptibility of normal tissues to the toxic effects of chemotherapy may also vary. For example, Denham et al demonstrated a weak but significant correlation between age and the neutrophil nadir count independent of drug exposure,15 possibly due to a age-related fall in bone marrow cellularity.16 Therefore, pretreatment indicators of normal tissue reserve may also have a role in optimal dosage determination. We have explored the relationship between a range of pretreatment measures with the pharmacokinetics and myelotoxicity of vinorelbine in a cohort of cancer patients treated with a fixed dose of this chemotherapeutic agent. The overall aim was to determine the utility of measures for predicting clearance and toxicity of an anticancer drug.
Patient Cohort Patients in this study were included in two previous published reports.17,18 The primary inclusion criterion was histologically proven malignancy suitable for vinorelbine treatment. Other inclusion criteria have been previously described.17,18 Forty-five patients were enrolled, however four patients withdrew before administration of vinorelbine and were not included in this analysis. The study was approved by the Western Sydney Area Health Service Human Research Ethics Committee and informed consent was obtained from all patients.
Vinorelbine Administration and Assay Vinorelbine blood concentrations were measured by isocratic high-performance liquid chromatography (HPLC) with fluorescence detection using a modification of the method of Robieux et al.21 Briefly, frozen blood samples (1 mL) were thawed, mixed and extracted (diethyl ether, 5 mL) with slow mixing (45 minutes) and centrifugation (2,000 g, 5 minutes) after addition of internal standard vinblastine (20 µL, 1 µg/mL). After two extractions, organic phases were combined, evaporated (to 1 mL) under nitrogen at 40°C, and back-extracted into 75 mmol/L phosphate buffer pH 2.7 without sodium dodecyl sulfate (220 µL) with shaking (45 minutes) and centrifugation (1,500 g, 5 minutes). The aqueous layer was transferred into auto-sampler vials and injected (50 µL) into HPLC system (Shimadzu model LC-10AD pump, SIL-10A autosampler and fluorescence detector RF-535 [excitation wavelength 280 nm, emission 360 nm], controlled by Shimadzu LC10 software; Kyoto, Japan).
The HPLC mobile phase consisted of acetonitrile: phosphate buffer (40.5:59.5 v/v) and the phosphate buffer was prepared as 75 mmol/L phosphoric acid: 75 mmol/L potassium dihydrogen orthophosphate (1:5 v/v), containing 0.08g/L sodium dodecyl sulfate and adjusted to pH 2.7 with phosphoric acid. Mobile phase was pumped (0.9 mL/min) through a C18 HPLC column (Nova Pak 4 µm, 3.9 x 300 mm, Waters Australia Pty Ltd, Sydney, Australia) with a C18 Nova Pak (4 µm, 3.9 x 20 mm) guard column. Vinblastine and vinorelbine eluted at 7.4 minutes and 18.0 minutes, respectively. Extraction efficiency for vinorelbine and vinblastine was 61.7% ± 3.3% and 74.0% ± 9.9% (n = 9), respectively. The standard curve was linear over the range 5 to 100 ng/mL. Quality control blood samples of 5 ng/mL and 25 ng/mL vinorelbine were quantitated with each analytic run. Intraday assay precision (relative SD) ranged from 0.3 to 9.0% and inter-day assay precision ranged from 0.9 to 7.0%, while accuracy was within 7% at all assayed concentrations. The limit of quantitation of the assay with precision
Estimation of Vinorelbine Clearance
Hepatic Elimination of Technetium Labeled Sestamibi
Midazolam Clearance
CYP 3A5 and ABCB1 SNP analysis
Measurement of Treatment-Related Myelosuppression
Statistical Analysis Variables with P values less than .1 on univariate analysis were considered for possible inclusion in a multivariable general linear model. Backward stepwise selection was used to identify a set of independent predictors of vinorelbine clearance and fractional neutrophil survival post vinorelbine. Normal quantile-quantile plots were used to check the validity of the underlying assumption of normally distributed residuals. Data are reported as mean ± SD.
The study cohort comprised 41 patients with metastatic cancer. Other features are summarized in Table 1.
Pharmacokinetics of Vinorelbine Vinorelbine blood concentrations were measured in 34 patients (83%) and concentration-time data were best described by a three compartment pharmacokinetic model with a homoscedastic residual error. The population mean estimates (± interpatient SD) for vinorelbine clearance and the volume of distribution of the central compartment were 33.1 ± 12.4 L/h and 24.8 ± 12.6 l, respectively. The estimated interpatient variability (expressed as a coefficient of variation) in vinorelbine clearance and central compartment were 37% and 51%, respectively. The population estimates of the intercompartmental transfer rate constants were 8.05 ± 7.5 hours–1, 0.36 ± 0.21 hours–1, 0.64 ± 0.27 hours–1and 0.00026 ± 0.0016 hours–1 for k12, k21, k13, and k31, respectively. Individual posterior Bayesian estimates of vinorelbine clearance (Fig 1) showed a 4.3-fold variation across the patient cohort (range, 9.9 to 42.9 L/h).
The estimated vinorelbine clearance of a patient receiving dexamethasone 8 mg daily (a known CYP3A inducer) was 38.7 L/h and two patients receiving the CYP3A inhibitor verapamil (240 mg daily) were 22.9 L/h and 35.6 L/h. These estimates of vinorelbine clearance (within 1 SD of population mean estimate) suggest these medications did not significantly impact on vinorelbine clearance compared with other patients.
Association Between Pretreatment Phenotype, Genotype, and Vinorelbine Clearance
A significant correlation was found between vinorelbine clearance and estimated creatinine clearance (r = 0.34; P = .05; Fig 2A). There was a trend towards correlation between vinorelbine and hepatic 99mTc-MIBI clearance (r = 0.32; P = .07; Fig 2B). BSA did not correlate with vinorelbine clearance (r = 0.17; P = .33; Fig 2C).
There was no association between vinorelbine clearance and CYP3A5*1/*3 genotype or the ABCB1 SNPs tested for. We have previously shown these ABCB1 SNPs to be in linkage disequilibrium,18 with two three-locus haplotypes likely to account for the majority of the chromosomes (exon 12-21-26 C-G-C, and T-T-T, 32% and 48%, respectively in this cohort). ABCB1 haplotype frequencies were not significantly associated with vinorelbine clearance (data not shown). In a multivariable analysis including covariates listed in Table 2 with P < .1 as possible predictors of vinorelbine clearance (ie, sex, estimated creatinine clearance, and hepatic 99mTc-MIBI clearance), estimated creatinine clearance (P = .002), and hepatic 99mTc-MIBI clearance (P = .01) were the only independent predictors identified (Table 3). These two factors in combination accounted for 36% of interpatient variability in vinorelbine clearance. Partial correlation between vinorelbine clearance and creatinine clearance when adjusted for hepatic 99mTc-MIBI clearance was 0.53. Conversely, partial correlation between vinorelbine clearance and hepatic 99mTc-MIBI clearance was 0.44 when adjusted for creatinine clearance. The Q-Q residual plot identified two outlying residuals associated with two patients with very low vinorelbine clearance, one of whom had relatively low hepatic 99mTc-MIBI clearance (9.3 mL/min) and the other with low creatinine clearance (24.8 mL/min). Creatinine clearance and hepatic 99mTc-MIBI clearance remained as independent predictors when these two patients were excluded in the multivariable analysis (data not shown). The resulting residuals showed no evidence of departure from normality.
Vinorelbine Myelotoxicity After 60-mg Fixed Dose of Vinorelbine One patient with metastatic prostate cancer died suddenly while neutropenic 14 days after vinorelbine administration. Otherwise, the fixed dose of vinorelbine was well tolerated and there were no other episodes of grade 3 or grade 4 nonhematologic toxicity. Post-treatment neutrophil counts were available for 39 of the 41 patients (95%) with a mean ± SD of 4.5 ± 1.9 counts per patient between 7.3 ± 2.7 days and 17.8 ± 3.4 days post-treatment. Of the 34 patients with available estimates of vinorelbine clearance, nadir neutrophil count was available for all patients and fractional survival of neutrophils for 33 of 34 patients (97%). Nadir neutrophil count of 2.0 ± 1.2 x109/L (range, 0.1 to 5.5 x109/L) was reached after 11 ± 3 days (n = 39). There was considerable variation in fractional survival of neutrophils between individual patients with mean ± SD of 37.7% ± 22.7% (range, 1.3% to 100.0%).
Association Between Vinorelbine Clearance, Pretreatment Phenotype, and Myelosuppression
The association between various pretreatment phenotypic measures and post-treatment fractional survival of neutrophils is summarized in Table 2. Fractional survival of neutrophils correlated significantly with sex (P = .02), BSA (Spearman's rho; r = 0.48; P  .01; Fig 3B), height (r = 0.41; P = .01), and estimated creatinine clearance (r = 0.39; P = .02). In a multivariable analysis, sex, BSA, height, estimated creatinine clearance, hepatic 99mTc-MIBI clearance, and vinorelbine clearance (ie, covariates with P < .1) were considered as possible predictors. BSA and vinorelbine clearance were the only independent predictors of fractional survival of neutrophils post-treatment using backward stepwise selection (Table 3). The Q-Q residual plot showed no evidence of departure from normality.
After a fixed dose of vinorelbine, there was considerable interpatient variation in the vinorelbine clearance estimates and treatment-related myelosuppression. These two end points were correlated such that individuals with rapid clearance showed the least myelosuppressive effects. In a comparison with a range of pretreatment phenotypic indicators and genotype, vinorelbine clearance was independently associated with estimated creatinine and hepatic 99mTc-MIBI clearance. The only pretreatment factor that remained as a predictor of fractional survival of neutrophils, independent of clearance, was the body size measurement BSA. In this study, a limited sampling strategy was employed and vinorelbine clearance was estimated using mixed effects modeling. This validated approach has been successfully implemented in previous investigations.19,24 This approach voids the need to collect numerous samples from patients, increasing the scope for conducting rigorous pharmacokinetic investigations in patients with advanced cancer. The vinorelbine clearance and associated interpatient variability estimates determined in this study were in close agreement with previous population pharmacokinetic studies19,20,24 supporting the veracity of present data. The relationship between estimated creatinine clearance and vinorelbine clearance observed has previously been reported,27 and is consistent with a known, albeit minor, contribution of renal elimination to vinorelbine clearance.11 A possible confounder in this relationship is age, as this included in the Cockcroft and Gault formula, used to estimate creatinine clearance.28 However, we found no significant association between age and vinorelbine clearance indicating that the association with estimated creatinine clearance was not entirely determined by age. In a multivariable analysis, an independent association between hepatic 99mTc-MIBI clearance and vinorelbine clearance suggested that interpatient variation in ABCB1 activity has a significant impact on vinorelbine pharmacokinetics. Conversely, midazolam clearance, an established probe of CYP3A activity, failed to correlate with vinorelbine clearance. CYP3A metabolism may play a minor role in vinorelbine clearance as the active decetyl metabolite was found in minimal quantities in serum following intravenous infusion.11 Absence of detectable effects of CYP3A inducers or inhibitors in three patients, in combination with evidence from an animal study showing no impact of the CYP3A inducer rifampicin on vinorelbine clearance,29 further supports this conclusion. We have previously reported that specific SNPs in CYP3A5 and ABCB1 are associated with elimination phenotype mediated by these proteins in cancer patients.17,18 However, these associations were relatively weak, reflecting the impact of other factors on activity of these pathways. Given the likely contribution of multiple elimination mechanisms to vinorelbine clearance, the failure of a relationship with CYP3A5 and ABCB1 genotype is not surprising irrespective of the demonstrated association with a phenotypic marker of ABCB1 activity. In keeping with the correlation between vinorelbine clearance and degree of myelosuppresion, the same pretreatment clearance indicators were associated with both end points. However, unlike vinorelbine clearance, myelosuppression correlated with height and BSA, and BSA was the only pretreatment indicator of myelosuppression independent of vinorelbine clearance in a multivariable analysis. BSA has repeatedly been shown to be a poor indicator of drug clearance phenotype,1,2 and it is likely that the relationship between BSA and myelosuppression reflects an influence that is unrelated to drug disposition. A possible explanation for a relationship between BSA and degree of myelosuppression is that BSA reflects the patient's bone marrow reserve. Consistent with this hypothesis, it has previously been shown that the quantity of bone marrow required for rescue following a lethal dose of total-body irradiation was closely correlated with body weight in an animal study.30 Furthermore, we have previously reported a weak but significant relationship between the degree of neutropenia postepirubicin treatment and height.31 Minimizing both under- and overdosing remains the practical aim of chemotherapy dose calculation. In this study of 41 patients with advanced cancer, use of a fixed dose of vinorelbine was relatively safe but variation in clearance was greater than four-fold across the cohort. Notwithstanding the statistical correlation between certain pretreatment phenotypic features and vinorelbine clearance and myelotoxicity, none of the features examined were sufficiently strong indicators to provide a basis for precise dose calculation. Clearly, relying on any individual parameter to individualize dose will still result in the substantial variation in drug effect seen with current BSA based dosing methods. A reasonable practical alternative may be to use a fixed dose of vinorelbine with adjustments guided by indicators of drug clearance and normal tissue reserve, especially for patients whose results are in the outer range. In this regard, this exploratory study suggests that creatinine and hepatic 99mTc-MIBI clearance may usefully predict individual vinorelbine pharmacokinetics and that BSA may predict bone marrow reserve. Although these results need to be confirmed in a larger cohort, it is ironic that BSA appears to be the best parameter to fulfill this latter role because currently BSA is commonly used to normalize vinorelbine dose. However, it is important to recognize the specific information conveyed by BSA in this context and its independence from clearance phenotype.
The authors indicate no potential conflicts of interest.
We thank Karen Byth, PhD, for assistance with statistic analysis.
Supported by a postgraduate medical scholarship from the National Health and Medical Research Council of Australia (M.W.) and S.A. and M.G. acknowledge support from Staff Specialists Trust Fund, Newcastle Mater Misericordiae Hospital. M.W. and R.L.B. contributed equally to this article and share the first author designation. The authors of this manuscript confirm that it contains original work. Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.
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Copyright © 2006 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
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ABSTRACT
INTRODUCTION
