Model evaluation is an important issue in population analyses. We aimed to perform a systematic review of all population pharmacokinetic and/or pharmacodynamic analyses published between 2002 and 2004 to survey the current methods used to evaluate models and to assess whether those models were adequately evaluated. We selected 324 articles in MEDLINE using defined key words and built a data abstraction form composed of a checklist of items to extract the relevant information from these articles with respect to model evaluation. In the data abstraction form, evaluation methods were divided into three subsections: basic internal methods (goodness-of-fit [GOF] plots, uncertainty in parameter estimates and model sensitivity), advanced internal methods (data splitting, resampling techniques and Monte Carlo simulations) and external model evaluation. Basic internal evaluation was the most frequently described method in the reports: 65% of the models involved GOF evaluation. Standard errors or confidence intervals were reported for 50% of fixed effects but only for 22% of random effects. Advanced internal methods were used in approximately 25% of models: data splitting was more often used than bootstrap and cross-validation; simulations were used in 6% of models to evaluate models by a visual predictive check or by a posterior predictive check. External evaluation was performed in only 7% of models. Using the subjective synthesis of model evaluation for each article, we judged the models to be adequately evaluated in 28% of pharmacokinetic models and 26% of pharmacodynamic models. Basic internal evaluation was preferred to more advanced methods, probably because the former is performed easily with most software. We also noticed that when the aim of modelling was predictive, advanced internal methods or more stringent methods were more often used.

The elderly comprise the majority of patients with cancer and are the recipients of the greatest amount of chemotherapy. Unfortunately, there is a lack of data to make evidence-based decisions with regard to chemotherapy. This is due to the minimal participation of older patients in clinical trials and that trials have not systematically evaluated chemotherapy. This article reviews the available information with regard to chemotherapy and aging provided by a task force of the International Society of Geriatric Oncology (SIOG). Due to the lack of prospective data, the conclusions and recommendations made are a consensus of the participants. Extrapolation of data from younger to older patients is necessary, particularly to those patients older than 80 years, for which data is almost entirely lacking. The classes of drugs reviewed include alkylators, antimetabolites, anthracyclines, taxanes, camptothecins, and epipodophyllotoxins. Clinical trials need to incorporate an analysis of chemotherapy in terms of the pharmacokinetic and pharmacodynamic effects of aging. In addition, data already accumulated need to be reanalyzed by age to aid in the management of the older cancer patient.

Purpose: Paclitaxel and carboplatin are frequently used in advanced ovarian cancer following cytoreductive surgery. Threshold models have been used to predict paclitaxel pharmacokineticpharmacodynamics, whereas the time above paclitaxel plasma concentration of 0.05 to 0.2 Amol/L (t C > 0.05-0.2 ) predicts neutropenia.The objective of this study was to build a population pharmacokinetic-pharmacodynamic model of paclitaxel/carboplatin in ovarian cancer patients. Experimental Design: One hundred thirty-nine ovarian cancer patients received paclitaxel (175 mg/m 2 ) over 3 h followed by carboplatin area under the concentration-time curve 5 mg/mL*min over 30 min. Plasma concentration-time data were measured, and data were processed using nonlinear mixed-effect modeling. Semiphysiologic models with linear or sigmoidal maximum response and threshold models were adapted to the data. Results: One hundred five patients had complete pharmacokinetic and toxicity data. In 34 patients with measurable disease, objective response rate was 76%. Neutrophil and thrombocyte counts were adequately described by an inhibitory linear response model. Paclitaxel t C > 0.05 was significantly higher in patients with a complete (91.8 h) or partial (76.3 h) response compared with patients with progressive disease (31.5 h; P = 0.02 and 0.05, respectively).Patients with paclitaxel t C > 0.05 > 61.4 h (mean value) had a longer time to disease progression compared with patients with paclitaxel t C > 0.05 < 61.4 h (89.0 versus 61.9 weeks; P = 0.05).Paclitaxel t C > 0.05 was a good predictor for severe neutropenia (P = 0.01), whereas carboplatin exposure (C max and area under the concentration-time curve) was the best predictor for thrombocytopenia (P < 10 -4 ). Conclusions: In this group of patients, paclitaxel t C > 0.05 is a good predictive marker for severe neutropenia and clinical outcome, whereas carboplatin exposure is a good predictive marker for thrombocytopenia.