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Cancer Therapy: Clinical |
Authors' Affiliations: 1 Northern Institute for Cancer Research; 2 School of Clinical Medical Sciences (Child Health), University of Newcastle upon Tyne, Newcastle upon Tyne; 3 Department of Haematology/Oncology, Great Ormond Street Hospital, London; 4 Department of Paediatric Oncology, Manchester Children's Hospital, Manchester; 5 Paediatric Oncology Unit, St. James's Hospital, Leeds; 6 Royal Liverpool Children's Hospital, Alder Hey, Liverpool; 7 Royal Marsden Hospital, Surrey; 8 Department of Paediatrics, Addenbrooke's Hospital, Cambridge; and 9 UKCCSG, University of Leicester, Leicester, United Kingdom
Requests for reprints: Alan V. Boddy, Northern Institute for Cancer Research, Paul O'Gorman Building, Medical School, Framlington Place, University of Newcastle upon Tyne, Newcastle upon Tyne NE2 4HH, United Kingdom. Phone: 44-191-246-4412; Fax: 44-191-246-4301; E-mail: alan.boddy{at}ncl.ac.uk.
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Abstract |
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Experimental Design: Dactinomycin was administered to 31 patients by bolus i.v. infusion, at doses of 0.70 to 1.50 mg/m2. Plasma concentrations were determined by liquid chromatography-mass spectrometry up to 24 hours after drug administration and National Cancer Institute Common Toxicity Criteria was assessed.
Results: Pharmacokinetic data analysis suggested that a three-compartment model most accurately reflected dactinomycin pharmacokinetics. However, there was insufficient data available to fully characterize this model. A median peak plasma concentration (Cmax) of 25.1 ng/mL (range, 3.2-99.2 ng/mL) was observed at 15 minutes after administration. The median exposure (AUC0-6), determined in 16 patients with sampling to 6 hours, was 2.67 mg/L.min (range, 1.12-4.90 mg/L.min). After adjusting for body size, AUC0-6 and Cmax were positively related to dose (P = 0.03 and P = 0.04, respectively). Patients who experienced any level of Common Toxicity Criteria grade had a 1.46-fold higher AUC0-6, 95% confidence interval (1.02-2.09). AUC0-6 was higher in patients <40 kg, possibly indicating a greater toxicity risk.
Conclusions: Data presented suggest that dosing of dactinomycin based on surface area is not optimal, either in younger patients in whom the risk of toxicity is greater, or in older patients where doses are capped.
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Dosage regimens for the treatment of patients with Wilms tumor in the U.K. have been revised on more than one occasion due to concerns regarding potential underdosing or a possible link between toxicity from venoocclusive disease of the liver and dactinomycin dosing. Similar amendments to dosing were required during a Children's Oncology Group study for the treatment of rhabdomyosarcoma (5). Venoocclusive disease, a severe hepatic toxicity with a reported incidence of 2% to 13.5% across different clinical studies (6–8), is the main drawback to the clinical use of dactinomycin. However, despite the many changes to the dosing of dactinomycin, optimum dosage regimens for the treatment of infants and young children remain unclear. As dactinomycin is metabolized in the liver, with both the liver and kidneys involved in drug excretion, development of renal and hepatic function in young children may be an important factor in influencing its clinical pharmacology. This could potentially lead to significant variations in drug pharmacokinetics between infants and older children.
As the dose intensity of dactinomycin treatment has been clearly defined as a significant risk factor for the development of hepatotoxicity in Wilms tumor, it would seem logical to carry out pharmacokinetic studies in these patients. This would allow potential correlations to be investigated between the extent of interpatient variation in exposure to dactinomycin and clinical response and toxicity. However, to date, there is a paucity of information regarding the clinical pharmacology of dactinomycin, with no pharmacokinetic studies having been carried out in pediatric patients, and a very limited number of studies in adults. Indeed, the only publications in this area are those focusing on the analytical methods developed, with data from one or two patients to show a clinical application (9–12). No dactinomycin pharmacokinetic study has been published using these methods, possibly due to concerns over a lack of specificity for the parent drug, or due to the labor-intensive nature of the methods, making the analysis of large numbers of clinical samples unrealistic.
We have recently developed a liquid chromatography-mass spectrometry assay which allows the quantification of dactinomycin concentrations in plasma obtained from patients receiving dactinomycin in the clinic (13). In the current study, we have used this assay to investigate the pharmacokinetics of dactinomycin in a pediatric patient population, including patients receiving treatment for several different types of malignancy.
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Patients and Methods |
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Blood sampling and analysis. Blood samples for measurement of dactinomycin concentration were obtained from a central line prior to administration and at 15 and 30 minutes, and 1, 2, 4, 6, and 24 hours post-administration. Actual sampling times were recorded for all patients studied and were as follows (median value and range given): 15 minutes, 17 (15-25); 30 minutes, 32 (26-50); 60 minutes, 60 (57-68); 120 minutes, 122 (112-132); 240 minutes, 241 (215-297); 360 minutes, 360 (330-385); 1,440 minutes, 1,440 (1,295-1,531). All eight samples were obtained in a total of seven children, with between two and seven samples obtained from the remaining patients; most frequently with the omission of the 24 hours post-administration sample. The actual number of samples obtained at each of the specified time points are given in Table 2. Samples were obtained from 17 patients with double lumen central venous catheters, 9 patients with single lumen lines, and 5 patients with Port-a-Cath access. All lines were flushed thoroughly following administration of dactinomycin and prior to the withdrawal of samples for pharmacokinetic analysis and separate drug infusion and sampling sites were used whenever possible. Blood samples (2 mL) were collected in heparinized tubes and centrifuged at 1,200 x g for 10 minutes at 4°C. Plasma was separated and frozen at –20°C prior to analysis using a validated liquid chromatography-mass spectrometry assay, with a limit of quantitation of 1.0 ng/mL (13).
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) were estimated, again using the logarithmic trapezoidal rule. Extrapolation to infinity was done using an estimate of the terminal phase half-life obtained from the slope of the concentration versus time curve using the 6- and 24-hour samples. Clearance was estimated as dose divided by AUC0-. Two- and three-compartment models were fitted to data from the patients with 24-hour samples. During estimation, observations were weighted according to the inverse of the squared expected plasma concentrations. The Akaike Information Criterion was used to assess goodness of fit.
The development of a population model for dactinomycin was undertaken using the first-order conditional estimation method with 
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interaction implemented as part of the NONMEM version V level 1.1 software (14). This was carried out using data from all patients studied. The nonlinear nature of the loge plasma concentration versus time curve suggested that a two-compartment model or a higher order model would be appropriate. Parameter estimates for the two-compartment model were obtained using ADVAN3 with the TRANS4 reparameterization, whereas ADVAN5 was used for the three-compartment model. A composite error model was used to describe the intrasubject variation.
Statistical analysis. The primary pharmacokinetic end points for the study were peak dactinomycin plasma concentration (concentration at 15 minutes) and AUC0-6. Linear regression was used to determine the relationship between log10 peak concentration and log10 AUC0-6 and dose of dactinomycin, patient weight and body surface area. Differences in mean log10 peak concentration and log10 AUC0-6 between patient groups were assessed using the t test (two groups) or one-way ANOVA (more than two groups). Adjustment for weight and/or dose was made using ANCOVA. The following variables were considered: sex, tumor type, line type, concurrent chemotherapy, CTC grade 1 or higher treatment-related toxicity for infection, fever, aspartate transaminase, alanine transaminase, platelets. Also considered were grade 1 or higher, grade 2 or higher, and grade 3 or higher for any of the abovementioned toxicities. Statistical analysis was done using MINITAB release 13.1.
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Results |
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TopAbstractPatients and MethodsResultsDiscussionReferences |
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Pharmacokinetics. A total of 144 plasma concentrations were obtained from 31 patients as shown in Fig. 2. Summary statistics on plasma concentrations of dactinomycin at each of the sampling times are presented in Table 2. Although the majority of the early samples were available for analysis, only 16 valid samples were obtained at 6 hours, further reduced to 7 samples after 24 hours. Failure to obtain full sampling for all patients was due to the outpatient nature of the treatment. Sampling was not limited by considerations of patient safety or due to toxicity. The median plasma concentration of dactinomycin at 15 minutes (peak concentration, Cmax) was 25.1 ng/mL (range, 3.2-99.2 ng/mL), with a median concentration of 2.4 ng/mL (range, 1.4-3.4 ng/mL) at 24 hours. No relationship was observed between the type of central venous access used for blood sampling and dactinomycin plasma pharmacokinetic parameters.
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Two- and three-compartment models were fitted to the data from patients with 24-hour samples. For two of the seven patients, it was not possible to fit the three-compartment model despite using numerous different starting values for the parameter estimates. Figure 3 shows the fitted curves for a representative patient. Although the three-compartment model seems to fit well, the two-compartment model underestimates plasma concentrations at around 2 hours and overestimates at 6 hours. This pattern of under- and overestimation was seen in the remaining patients. The Akaike Information Criterion for the three-compartment model was lower than that of the two-compartment model for each of the patients reflecting the improved fit of the three-compartment model. Differences in Akaike Information Criterion ranged from 5.8 to 25.4 with a median difference of 18.6.
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The median AUC0-6 was 2.67 mg/L.min (range, 1.12-4.90 mg/L.min) in the 16 patients with valid 6-hour samples. Cmax and AUC0-6 were statistically significantly related to patient weight and body surface area (P < 0.01 for each). An increase in body weight of 10 kg resulted in an estimated 1.32-fold decrease in Cmax, 95% confidence interval (1.19, 1.47) and a 1.19-fold decrease in AUC0-6, 95% confidence interval (1.09-1.31). After adjusting for patient weight (or body surface area), using linear regression, Cmax was found to be positively related to dose (P = 0.03) and after adjusting for body surface area, AUC0-6 was found to be positively related to dose (P = 0.04). Figure 4 shows the relationship between dose of dactinomycin administered and the peak concentration, Cmax (A) and dactinomycin systemic exposure as defined by AUC0-6 (B).
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Tumor type. There was significant variation in Cmax with tumor type (P < 0.01, ANOVA). Body weight was again a confounding factor as patients with Ewing sarcoma tended to be older and consequently larger, whereas those with Wilms tumor tended to be younger and smaller. Again after adjusting for weight and dose, Cmax and tumor type were no longer significantly related (P = 0.701).
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Discussion |
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TopAbstractPatients and MethodsResultsDiscussionReferences |
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Thirty-one children and young adolescents, receiving dactinomycin chemotherapy as part of their standard clinical treatment, were studied over a period of 22 months in seven U.K. centers. Patients were being treated for a wide range of malignancies including Wilms tumor, Ewing sarcoma, and soft tissue sarcoma. Samples for pharmacokinetic analysis were obtained at defined time points up to 24 hours following drug administration. The complete data set obtained from all patient samples was used to investigate the fitting of various pharmacokinetic models. The characterization of a meaningful population pharmacokinetic model was not possible due to the small number of patients for whom a full set of pharmacokinetic samples was available; only 7 of the 31 patients having plasma samples available beyond the 6-hour time point. However, it was evident that a two-compartment population model was not appropriate for these data. Individual models fitted to the patients with complete data suggest that a three-compartment model most accurately reflects the pharmacokinetics of dactinomycin in children. A modification in the sampling schedule with the addition of later time points up to 72 hours, as well as an earlier time point at 5 minutes after administration, would have been beneficial. However, predicting the optimal sampling times prior to the opening of the study was difficult due to the lack of published data. The practical issue of obtaining samples up to 48 or 72 hours, which would be required to accurately characterize the clearance of dactinomycin, is likely to present problems with access to patients who are not being treated as study center inpatients. This type of problem is a common consideration in the planning of clinical pharmacology studies in pediatric oncology but may be of particular concern with the long half-life of dactinomycin and the patient group being studied. Population pharmacokinetic approaches will therefore play an important role in the planning of future studies.
A wide range of dactinomycin plasma concentrations were observed in the 31 patients studied, with a Cmax range of 3.2-99.2 ng/mL. These concentrations are equivalent to those shown to inhibit RNA synthesis in tumor cell lines (15). Noncompartmental pharmacokinetic analysis was carried out on data from seven patients where a full set of samples were taken at regular time intervals up to 24 hours following dactinomycin administration. Estimated clearance of dactinomycin varied from 68 to 203 mL/min/m2, with the terminal phase half-life (t1/2) ranging from 14 to 43 hours, suggesting extensive extravascular distribution. Although it is encouraging that these parameters exhibited a similar range of variation across the seven patients with data to 24 hours, these parameter values should be interpreted with caution. As plasma concentrations of dactinomycin were only measured up to 24 hours, a substantial degree of data extrapolation was required to obtain parameter estimates. Further studies incorporating more intensive and prolonged sampling times are needed for definitive determination of dactinomycin pharmacokinetic parameters.
These data indicate that some of the variability in dactinomycin clearance results from factors other than body size, as indicated by the observed variation in clearance normalized to surface area, thus suggesting that surface area–based dosing is not optimal. Both peak drug concentration and drug exposure (AUC0-6) were inversely related to patient weight. Thus, the exposure to dactinomycin in larger or older patients is lower than in younger patients. Based on the current dosing guidelines for dactinomycin, the data presented here indicate that the practice of capping the dose of dactinomycin at 2 mg in larger patients may result in underdosing.
No clear impact of concomitant chemotherapy on the pharmacokinetics of dactinomycin was observed in the current study. Although patients receiving ifosfamide tended to have lower Cmax values, this relationship was influenced by the fact that these tended to be the older patients studied. The effect of ifosfamide was not statistically significant after adjusting for body weight. Vincristine was coadministered in 28 of the 31 patients studied and it was therefore not possible to discern any interaction between these two drugs. No relationship was observed between line type and dactinomycin pharmacokinetics in this study, despite sampling from single lumen cannulas. However, it may be prudent to further investigate the potential for specimen contamination with infused drug in single lumen lines prior to the initiation of a larger clinical study.
Treatment with dactinomycin was associated with limited adverse effects, with 29% of patients experiencing no observable toxicity and 42% reporting CTC grade 1 or 2 toxicities only. The most common toxicities reported were elevated concentrations of alanine transaminase and thrombocytopenia. No significant correlations were observed between individual toxicities and pharmacokinetic parameters after allowing for differences in patient weight and dose. However, a relationship was observed between dactinomycin exposure (AUC0-6) and incidence of any CTC grade toxicity, in the 16 patients for whom a 6-hour sample was available. Although further data is required to confirm these observations, these preliminary results suggest that the higher plasma concentrations of dactinomycin achieved in younger patients may result in greater risk of toxicity.
Although many agents currently used for the treatment of children with cancer have been with us for many years, there remain considerable gaps in our knowledge relating to the optimal clinical use of these drugs. This is particularly relevant to the dosing of infant patients, where modifications to dosing regimens are often based on empirical evidence and may vary considerably across protocols for different tumor types. Of relevance to the use of dactinomycin in pediatric patients is the recent publication of results from the Children's Oncology Group, concerning the treatment of children with rhabdomyosarcoma (5). For patients treated with vincristine, dactinomycin, and cyclophosphamide, the risk of chemotherapy-induced hepatopathy was 4% in children aged 3 years and older, as compared with 15% in children under 36 months of age. These results clearly indicate that dose modifications are required for younger children receiving this particular drug regimen and support previous publications concerning the vulnerability of infants being treated with dactinomycin for the treatment of Wilms tumor (16, 17). A meaningful comparison of data from infants versus older children in the dactinomycin pharmacokinetic study presented here was unfortunately not possible as in the patient population studied only one patient was under 2 years of age, with only one additional patient under the age of 3 years.
There is a potential benefit in using pharmacologic data to guide dose modifications in the relevant patient population. The current study provides preliminary pharmacokinetic data for dactinomycin in children. Although the extent of characterization of the pharmacokinetics of the drug was restricted by the number of patients for whom samples were obtained over the defined 24-hour sampling schedule, these data provide the first insight into dactinomycin pharmacokinetics in a clinical study and serve as a guide to conducting future studies in this area. Extended sampling times will be imperative in order for pharmacokinetic parameters to be estimated more precisely in future studies. This is likely to present considerable practical challenges as previously discussed. However, providing that these problems can be overcome, studies may be designed to provide a scientific rationale for the variable dosing of this drug in infants, as well as addressing issues such as the impact of dose capping in older children. The fact that many pediatric tumors now have excellent prognoses should not be a deterrent to further improvements in chemotherapy, including the avoidance of life-threatening toxicities such as venoocclusive disease.
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Footnotes |
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The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Note: This work was presented in part at the 95th Annual AACR meeting, March 27 to 31, Orlando, FL.
Received 12/13/04; revised 5/16/05; accepted 5/27/05.
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TopAbstractPatients and MethodsResultsDiscussionReferences |
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, actual dactinomycin plasma concentrations determined at specific time points. The Akaike Information Criterion was 20.0 (two-compartment) and –2.1 (three-compartment) reflecting the improved fit of the three-compartment model.
, values from individual patients.
, patients with observable toxicity (CTC grades 1-4) following dactinomycin treatment; 
, patients experiencing no toxicity.