The influence of various covariates (including weight, race, smoking, gender, age, mild-to-moderate alcohol intake, and body surface area) on the population pharmacokinetic parameters of phenytoin in adult epileptic patients in South Africa was investigated. The parameters were the maximum metabolic rate (Vm) and the Michaelis-Menten (MM) constant (Km) of phenytoin. The study population comprised 332 black and colored epileptic patients (note: "black" refers to indigenous people of South Africa, who speak one of the Bantu languages as their native language; "colored" refers to people considered to be of mixed race, classified as such by the apartheid former government of South Africa). The influence of covariates on Vm and Km estimates was determined using nonlinear mixed-effects modeling (NONMEM). Parameter models describing the factors that could potentially influence Vm and Km were tested using the Michaelis-Menten parallel MM and first-order elimination models, to which 853 steady state dose-to-serum concentration pairs were fitted. The results indicated that body weight, smoking, race, and age (65 years or older), in descending order of importance, significantly influenced Vm (p < 0.05). Although a significant difference (p = 0.03) in Km was found between black and colored patients, incorporating the influence of race in Km in the final regression model did not improve the fit of the model to the data, which indicated that the variability in Km was accounted for by Vm. The scaling factors for smoking, colored patients and age (65 years or older) in Vm were 1.16, 1.10, and 0.88, respectively. These factors should be taken into account when adjusting phenytoin dose.

Breast cancer is one of the major healthcare challenges in South Africa (SA). Data published by the National Cancer Registry [1] in 2014 showed that breast cancer represented 22% of all cancers affecting women in SA, making it the most prevalent cancer affecting women in this country. Understanding the total cost of care for breast cancer is important from a health funder perspective, i.e. policymakers and hospital administration, in budget allocation and in decision-making [2] in a resource-constrained environment. Objectives To develop a method to determine the cost of breast cancer treatment with chemotherapy per episode of care and to quantify the associated costs relating to chemotherapy at Groote Schuur Hospital (GSH), a tertiary government hospital in Western Cape Province, SA. These costs included costs associated with the management of adverse events arising from chemotherapy. Methods Study design A retrospective cohort analysis was performed to determine the cost of an episode of care for treatment of breast cancer with chemotherapy. Cost estimates for an episode of care were obtained for each stage of breast cancer. The episode of care was defined as the care provided from 2 months prior to the date of commencing chemotherapy (pre-chemotherapy phase), during chemotherapy (treatment phase) and until 6 months after the date when the last cycle of chemotherapy was administered (follow-up phase). The episode of care was on average a period of 10-12 months per patient. Participants A total of 1 024 patients were extracted from the electronic database. Two hundred patients were randomly selected using a random number generator. Patients were included in the study based on the following criteria: (i) a diagnosis of breast cancer; (ii) registration date at the oncology department from 1 April 2013 to 31 March 2015; (iii) evidence of receipt of chemotherapy with two or more health encounters [3] related to breast cancer, e.g. doctor consultation in oncology ward and a mammogram; and (iv) age ≥18 years. Patients were excluded from the study based on the following criteria: (i) male; (ii) initiated on hormone therapy but not chemotherapy; (iii) enrolled in a clinical trial; and (iv) a primary diagnosis of cancer that was not breast cancer. This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

This study was conducted to assess whether the parallel Michaelis-Menten and first-order elimination (MM+FO) model fitted the data better than the Michaelis-Menten (MM) model, and to validate the MM+FO model and its parameter estimates. The models were fitted to 853 steady state dose: serum concentration pairs obtained in 332 adults with epilepsy using nonlinear mixed-effects modeling (NONMEM). The MM+FO model fitted the data better than the MM model. The validity of the pharmacokinetic models and the estimated population parameter values was tested using the naive prediction method. The estimation and validation of the pharmacokinetic parameters were undertaken in two separate patient groups (cross-validation) obtained by splitting the data set. Patients were randomly allocated to two equally matched groups (groups 1 and 2). The predictive performance was assessed using 770 paired predicted versus actual dose or measured serum concentrations. The population pharmacokinetic parameters estimated by NONMEM in group 1 were validated in group 2 and vice versa. When predicting steady state serum concentration, the MM+FO model was clearly superior to the MM model (mean bias of 0.91 and 8.13 mg/L, respectively).

A possible mechanism for fenfluramine-induced pulmonary hypertension has been investigated. Fenfluramine, like chlorphentermine, may inhibit the pulmonary uptake and/or metabolism of 5-hydroxytryptamine (5-HT). This allows more 5-HT to remain in the pulmonary circulation, where it may exert a greater vasoconstrictor action resulting in pulmonary hypertension. Chlorphentermine has been shown to inhibit the uptake and metabolism of 5-HT. The effect of fenfluramine on the pulmonary disposition of [14C]5-HT has been investigated, in comparison with chlorphentermine, using a recirculating isolated perfused rat lung system. The pulmonary disposition of [14C]5-HT was assessed by measuring the change in [14C]5-HT concentration in the perfusion medium during the experiment and at the end, and the concentration in the lung at the end of the experiment. The concentration of 5-hydroxyindoleacetic acid, a metabolite of 5-HT, was measured in perfusate and lung samples. Mean pulmonary clearance of 5-HT for the control lung and lungs challenged with either fenfluramine (2.5 microM) or chlorphentermine (25 microM) was 4.514, 1.316 and 1.007 mL min(-1), respectively (n = 5). The concentration of 5-HT found in the lungs at the end of the experiment for the control and the lungs preloaded with fenfluramine or chlorphentermine was 695.05+/-9.69, 638.65+/-10.27 and 617.3+/-14.38 ng g(-1), respectively. Fenfluramine, like chlorphentermine, inhibited the pulmonary disposition of 5-HT resulting in an elevated perfusate level of 5-HT. This is a possible contributing mechanism for fenfluramine-induced pulmonary hypertension. The effect of fenfluramine was less pronounced than chlorphentermine.

No abstract