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Study Objective. To evaluate the extent of agreement between plasma gentamicin concentrations determined from samples collected by using implantable subcutaneous central venous catheters (ports) with the push-pull method and those collected by finger lancet punctures in children with febrile neutropenia. Design. Prospective, randomized study. Setting. University-affiliated, tertiary care hospital. Patients. Sixty-two children with cancer who had single- or double-lumen ports and who received gentamicin for treatment of febrile neutropenia between February 2008 and October 2009. Intervention. One blood sample was collected from the port by using the push-pull method at the same time one blood sample was collected by finger lancet puncture for determination of plasma gentamicin concentrations. Measurements and Main Results. Forty-four pairs of samples were available for assessment of agreement, and 43 were available for pharmacokinetic analysis. Agreement between plasma gentamicin concentrations determined from blood samples from ports and finger lancet punctures was assessed by the intraclass correlation coefficient (ICC), Bland-Altman analysis, and comparison of simulated dosage adjustments. Changes in port patency were monitored for 1 week after port sampling. Differences in simulated dosage adjustments calculated by using either the port or finger lancet puncture samples that differed by greater than 20% were considered clinically significant. Agreement between the 44 finger lancet puncture and port sample pairs was excellent (ICC 0.991, 95% confidence interval 0.984–0.995). Port plasma gentamicin concentrations were 4.7% lower than those concentrations determined in blood from finger lancet punctures. The observed limits of agreement ranged from −20.5% to 11%. Differences in dosage adjustments calculated by using port and finger lancet puncture plasma gentamicin concentrations were not clinically significant in 38 (88%) of 43 cases. No changes in port patency were observed in the week after port sampling. Conclusion. The push-pull method of blood sampling is a reliable and safe option for determining plasma gentamicin concentrations in children with ports.

Background Dactinomycin (AMD) and vincristine (VCR) have been used for the treatment of childhood cancer over the past 40 years but evidence-based dosing guidance is lacking.

Actinomycin-D is an antineoplastic agent that inhibits RNA synthesis by binding to guanine residues and inhibiting DNA-dependent RNA polymerase. Although actinomycin-D has been used to treat rhabdomyosarcoma and Wilms tumor for more than 40 years, the dose/exposure relationship is not well characterized. The objective of this study was to develop an initial population pharmacokinetic model to describe actinomycin-D disposition in children and young adults from which a prospective study could be designed. A total of 165 actinomycin-D plasma concentration measurements from 33 patients, aged 1.6 to 20.3 years, were used for the analysis. The data were analyzed using nonlinear mixed-effects modeling with the NONMEM software system. Age, weight, and gender were examined as covariates for the ability to explain interindividual variability in actinomycin-D pharmacokinetics. The final model was qualified via predictive check and non-parametric bootstrap procedures. A 3-compartment model with first-order elimination was chosen as the structural model. Allometric expressions incorporating weight were used to describe the effects of body size on actinomycin-D pharmacokinetics. Age and gender had no discernible effects on actinomycin-D pharmacokinetics in the population studied. The predictive check showed that the developed model was able to simulate data in close agreement with the actual study observations. The availability of an initial population pharmacokinetic model to describe actinomycin-D pharmacokinetics will facilitate the development of a large-scale clinical trial to study the actinomycin-D dose/exposure relationship in pediatric patients with rhabdomyosarcoma and Wilms tumor. The covariate analysis described by the current data set suggests that indices of body size captured via allometric expressions improve the partition of variation in actinomycin-D pharmacokinetics from this pilot data set. Relationships between pharmacokinetics and toxicity will be examined in future prospective studies in which children less than 1 year old will be enrolled. Refereed/Peer-reviewed

Tumour suppressor genes are a group of genes whose loss contributes to malignancy. The original hypothesis surrounding tumour suppressor genes defined a ‘two-hit’ requirement for mutagenesis; however, it is now known that deletion, silencing or downregulation of one or more genes may lead to cancer formation. There is a growing list of putative tumour suppressor genes, and recently several new candidates were added. Research into apoptosis, or programmed cell death, continues to expand. As pathways for which tumour suppressor genes are responsible become clearer, so do potential therapeutics to capitalise on these targets. A summary of the mechanisms by which tumour suppressor genes may act, the mutations which lead to tumourigenesis, and the clinical implications of these phenomena are presented. Key Concepts: Tumour suppressor genes prevent mutagenesis. Perturbation of tumour suppressor gene function may lead to cancer formation. The first tumour suppressor gene identified was the Rb gene, and mutations in the gene lead to the childhood cancer known as retinoblastoma. Although many tumour suppressor genes require two mutations to cause a loss-of-function, in some cases, downregulation of a single tumour suppressor gene may lead to cancer. The p53 gene is involved in a complex pathway of cell death and cell arrest, and mutations in p53 or other genes in the pathway can lead to the development of cancer. There are several other modulators of tumour formation, including telomeres, adhesion molecules and microRNA, that may function like tumour suppressor genes. Identification of tumour suppressor genes has lead to the development of anticancer therapeutic agents targeted to specific pathways that take advantage of this knowledge. Keywords: oncogene; cancer; tumour; tumour suppressor; p53; apoptosis