Model-Based Network Meta-Analysis: A Framework for Evidence Synthesis of Clinical Trial Data.

Model-based meta-analysis (MBMA) is increasingly used in drug development to inform decision-making and future trial designs, through the use of complex dose and/or time course models. Network meta-analysis (NMA) is increasingly being used by reimbursement agencies to estimate a set of coherent relative treatment effects for multiple treatments that respect the randomization within the trials. However, NMAs typically either consider different doses completely independently or lump them together, with few examples of models for dose. We propose a framework, model-based network meta-analysis (MBNMA), that combines both approaches, that respects randomization, and allows estimation and prediction for multiple agents and a range of doses, using plausible physiological dose-response models. We illustrate our approach with an example comparing the efficacies of triptans for migraine relief. This uses a binary endpoint, although we note that the model can be easily modified for other outcome types.

The Many Flavors of Model-Based Meta-Analysis: Part I-Introduction and Landmark Data.

Meta-analysis is an increasingly important aspect of drug development as companies look to benchmark their own compounds with the competition. There is scope to carry out a wide range of analyses addressing key research questions from preclinical through to postregistration. This set of tutorials will take the reader through key model-based meta-analysis (MBMA) methods with this first installment providing a general introduction before concentrating on classical and Bayesian methods for landmark data.

Integrated pharmacometrics and systems pharmacology model-based analyses to guide GnRH receptor modulator development for management of endometriosis.

Endometriosis is a gynecological condition resulting from proliferation of endometrial-like tissue outside the endometrial cavity. Estrogen suppression therapies, mediated through gonadotropin-releasing hormone (GnRH) modulation, decrease endometriotic implants and diminish associated pain albeit at the expense of bone mineral density (BMD) loss. Our goal was to provide model-based guidance for GnRH-modulating clinical programs intended for endometriosis management. This included developing an estrogen suppression target expected to provide symptomatic relief with minimal BMD loss and to evaluate end points and study durations supportive of efficient development decisions. An existing multiscale model of calcium and bone was adapted to include systematic estrogen pharmacologic effects to describe estrogen concentration-related effects on BMD. A logistic regression fit to patient-level data from three clinical GnRH agonist (nafarelin) studies described the relationship of estrogen with endometrial-related pain. Targeting estradiol between 20 and 40 pg/ml was predicted to provide efficacious endometrial pain response while minimizing BMD effects.CPT: Pharmacometrics & Systems Pharmacology (2012) 1, e11; doi:10.1038/psp.2012.10; advance online publication 17 October 2012.

Technical report: A low cost technique for vessel sizing in angioplasty.

Vessel measurement in angiography is important for balloon and stent sizing. The most accurate techniques involve calibrating the angiographic image with a catheter with radioopaque markers, but these are expensive. A new method of vessel sizing for angioplasty and stenting is described: the guidewire is moved within the vessel through a set distance, and this movement is shown by digital subtraction. Testing with phantoms shows this to be simple, accurate and reproducible.

Phenelzine toxicity responsive to dantrolene.

We describe a 44-year-old man with signs of phenelzine sulfate (a monoamine oxidase inhibitor) toxicity, including coma, hyperpyrexia, hypotension, tachycardia, generalized muscular rigidity, and hyperreflexia. He recovered after IV treatment with dantrolene. Dantrolene appears to be an effective treatment for phenelzine toxicity manifested by a hypermetabolic state.