Recent clinical trials with omapatrilat: new developments.

Omapatrilat belongs to the vasopeptidase inhibitors, ie, drugs that possess the ability to inhibit simultaneously the membrane-bound zinc metalloproteases, angiotensin-converting enzyme (ACE), and the neutral endopeptidase EC 3.4.24.11 (NEP). Omapatrilat was targeted to treat patients with hypertension and congestive heart failure. The preclinical and early clinical studies conducted with omapatrilat were very promising. Indeed, omapatrilat appeared to be a very potent antihypertensive agent with very favorable effects on cardiac function in heart failure patients. In contrast to these early studies, the large clinical trials were more disappointing. The results of the OCTAVE trial confirmed the antihypertensive efficacy of omapatrilat, but at the price of an angioedema rate more than threefold higher than that of an ACE inhibitor in the overall population (2.17% vs 0.68%), and close to fourfold higher in the black population. In OVERTURE, a large randomized control trial in heart failure, angioedema was also more common with omapatrilat, but the incidence was much lower (0.8% with omapatrilat vs 0.5% with enalapril). However, omapatrilat was not convincingly superior to the ACE inhibitor. Because angioedema is probably a class side effect of vasopeptidase inhibitors, the higher incidence of this potentially life-threatening complication with omapatrilat has likely stopped the development of this new class of agents. The future of vasopeptidase inhibitors will depend on the ability to improve the risk/benefit ratio either by developing agents that produce less angioedema, or by defining more precisely a high-risk population that could take advantage of dual ACE/NEP inhibition.

4th annual conference on Clinical Trials in Alzheimer's Disease: Highlights

��In a sign that researchers are grappling with therapy development, the 4th annual conference on Clinical Trials in Alzheimer's Disease was filled beyond its venue's capacity, drawing 522 researchers from around the globe. Held 3-5 November 2011 in San Diego, CTAD is the brainchild of Paul Aisen, Jacques Touchon, Bruno Vellas, and Michael Weiner. The conference posted no ringing trial successes. Instead, scientists worked on methodological aspects they hope will improve future trials' chances. They discussed Bayesian models, simulated placebos, and biomarker data standards. They presented alternative outcome measures to the ADAS-cog, ranging widely from composite scales that are sensitive early on to continuous measures that encompass a patients' day-to-day variability. They focused on EEG, and on a collective effort to develop patient-reported outcomes. Highlights include:Whence and Where To: History and Future of AD Therapy Trials��Webinar: Evolution of AD Trials��Nutrient Formulation Appears to Grease Memory Function��Door Slams on RAGE��Clinical Trials: Making "Protocols From Hell" Less Burdensome��EEG: Coming in From the Margins of Alzheimer's Research?��EEG: Old Method to Lend New Help in AD Drug Development?������

Options for clinical trials of pre and post-natal treatments for congenital toxoplasmosis

Clinical trials comparing different drug regimens and strategies for the treatment of congenital toxoplasmosis and its clinical manifestations in the liveborn child in different clinical settings should aim at formally evaluating the net benefit of existing treatments and at developing new therapeutic options. Currently, there is no ideal drug for congenital toxoplasmosis; future research should focus on the screening of new active drugs and on their pre-clinical and early clinical development, with a focus on pharmacokinetic/dynamic studies and teratogenicity. For the prenatal treatment of congenital toxoplasmosis, a trial comparing spiramycine to pyrimethamine-sulphadiazine and placebo would allow a formal estimation of the effect of both drugs in infected pregnant women. In newborn children, the net benefit of pyrimethamine-sulphadiazine should also be formally assessed. These trials will be implemented in settings where prenatal screening for Toxoplasma gondii is currently implemented. Trials should be carefully designed to allow for translation to other settings and modelling tools like cost-effectiveness analysis should be used to provide clinicians and founders with the best available evidence to establish recommendations.

Genus-specific kinetoplast-DNA PCR and parasite culture for the diagnosis of localised cutaneous leishmaniasis: applications for clinical trials under field conditions in Brazil

The positivities of two methods for the diagnosis of localised cutaneous leishmaniasis (CL) were estimated in 280 patients enrolled in a clinical trial. The trial was conducted in an endemic area of Leishmania (Viannia) braziliensis and trial participants were patients with skin ulcers and positive leishmanin skin tests. Patients underwent aspirative skin punctures of the ulcerated lesions and lymph nodes for in vitro cultures, which were processed under field conditions at the local health centre. Skin lesion biopsies were tested at a reference laboratory using kinetoplastid DNA (kDNA)-PCR to detect DNA. The median time required to obtain a positive culture from the skin samples was seven days and the contamination rate of the samples was 1.8%. The positivities of the cultures from skin lesions, kDNA-PCR and the combination of the two methods were 78.2% (95% CI: 73-82.6%), 89.3% (95% CI: 85.1-92.4%) and 97.1% (95% CI: 94.5-98.5%). We conclude that parasite culture is a feasible method for the detection of Leishmania in field conditions and that the combination of culture and PCR has a potential role for the diagnosis of CL in candidates for clinical trials.

Compositional ideas in the bayesian analysis of categorical data with application to dose finding clinical trials

Compositional random vectors are fundamental tools in the Bayesian analysis of categorical data.Many of the issues that are discussed with reference to the statistical analysis of compositionaldata have a natural counterpart in the construction of a Bayesian statistical model for categoricaldata.This note builds on the idea of cross-fertilization of the two areas recommended by Aitchison (1986)in his seminal book on compositional data. Particular emphasis is put on the problem of whatparameterization to use

The prognostic value of health-related quality-of-life data in predicting survival in glioblastoma cancer patients: results from an international randomised phase III EORTC Brain Tumour and Radiation Oncology Groups, and NCIC Clinical Trials Group study.

This is one of the few studies that have explored the value of baseline symptoms and health-related quality of life (HRQOL) in predicting survival in brain cancer patients. Baseline HRQOL scores (from the EORTC QLQ-C30 and the Brain Cancer Module (BN 20)) were examined in 490 newly diagnosed glioblastoma cancer patients for the relationship with overall survival by using Cox proportional hazards regression models. Refined techniques as the bootstrap re-sampling procedure and the computation of C-indexes and R(2)-coefficients were used to try and validate the model. Classical analysis controlled for major clinical prognostic factors selected cognitive functioning (P=0.0001), global health status (P=0.0055) and social functioning (P<0.0001) as statistically significant prognostic factors of survival. However, several issues question the validity of these findings. C-indexes and R(2)-coefficients, which are measures of the predictive ability of the models, did not exhibit major improvements when adding selected or all HRQOL scores to clinical factors. While classical techniques lead to positive results, more refined analyses suggest that baseline HRQOL scores add relatively little to clinical factors to predict survival. These results may have implications for future use of HRQOL as a prognostic factor in cancer patients.

Liver safety assessment: required data elements and best practices for data collection and standardization in clinical trials.

A workshop was convened to discuss best practices for the assessment of drug-induced liver injury (DILI) in clinical trials. In a breakout session, workshop attendees discussed necessary data elements and standards for the accurate measurement of DILI risk associated with new therapeutic agents in clinical trials. There was agreement that in order to achieve this goal the systematic acquisition of protocol-specified clinical measures and lab specimens from all study subjects is crucial. In addition, standard DILI terms that address the diverse clinical and pathologic signatures of DILI were considered essential. There was a strong consensus that clinical and lab analyses necessary for the evaluation of cases of acute liver injury should be consistent with the US Food and Drug Administration (FDA) guidance on pre-marketing risk assessment of DILI in clinical trials issued in 2009. A recommendation that liver injury case review and management be guided by clinicians with hepatologic expertise was made. Of note, there was agreement that emerging DILI signals should prompt the systematic collection of candidate pharmacogenomic, proteomic and/or metabonomic biomarkers from all study subjects. The use of emerging standardized clinical terminology, CRFs and graphic tools for data review to enable harmonization across clinical trials was strongly encouraged. Many of the recommendations made in the breakout session are in alignment with those made in the other parallel sessions on methodology to assess clinical liver safety data, causality assessment for suspected DILI, and liver safety assessment in special populations (hepatitis B, C, and oncology trials). Nonetheless, a few outstanding issues remain for future consideration.

A mixed approach for proving non-inferiority in clinical trials with binary endpoints

When a new treatment is compared to an established one in a randomized clinical trial, it is standard practice to statistically test for non-inferiority rather than for superiority. When the endpoint is binary, one usually compares two treatments using either an odds-ratio or a difference of proportions. In this paper, we propose a mixed approach which uses both concepts. One first defines the non-inferiority margin using an odds-ratio and one ultimately proves non-inferiority statistically using a difference of proportions. The mixed approach is shown to be more powerful than the conventional odds-ratio approach when the efficacy of the established treatment is known (with good precision) and high (e.g. with more than 56% of success). The gain of power achieved may lead in turn to a substantial reduction in the sample size needed to prove non-inferiority. The mixed approach can be generalized to ordinal endpoints.

Defining responses to therapy and study outcomes in clinical trials of invasive fungal diseases: Mycoses Study Group and European Organization for Research and Treatment of Cancer consensus criteria.

Invasive fungal diseases (IFDs) have become major causes of morbidity and mortality among highly immunocompromised patients. Authoritative consensus criteria to diagnose IFD have been useful in establishing eligibility criteria for antifungal trials. There is an important need for generation of consensus definitions of outcomes of IFD that will form a standard for evaluating treatment success and failure in clinical trials. Therefore, an expert international panel consisting of the Mycoses Study Group and the European Organization for Research and Treatment of Cancer was convened to propose guidelines for assessing treatment responses in clinical trials of IFDs and for defining study outcomes. Major fungal diseases that are discussed include invasive disease due to Candida species, Aspergillus species and other molds, Cryptococcus neoformans, Histoplasma capsulatum, and Coccidioides immitis. We also discuss potential pitfalls in assessing outcome, such as conflicting clinical, radiological, and/or mycological data and gaps in knowledge.

New validated prognostic models and prognostic calculators in patients with low-grade gliomas diagnosed by central pathology review: a pooled analysis of EORTC/RTOG/NCCTG phase III clinical trials.

Background In a previous study, the European Organisation for Research and Treatment of Cancer (EORTC) reported a scoring system to predict survival of patients with low-grade gliomas (LGGs). A major issue in the diagnosis of brain tumors is the lack of agreement among pathologists. New models in patients with LGGs diagnosed by central pathology review are needed. Methods Data from 339 EORTC patients with LGGs diagnosed by central pathology review were used to develop new prognostic models for progression-free survival (PFS) and overall survival (OS). Data from 450 patients with centrally diagnosed LGGs recruited into 2 large studies conducted by North American cooperative groups were used to validate the models. Results Both PFS and OS were negatively influenced by the presence of baseline neurological deficits, a shorter time since first symptoms (<30 wk), an astrocytic tumor type, and tumors larger than 5 cm in diameter. Early irradiation improved PFS but not OS. Three risk groups have been identified (low, intermediate, and high) and validated. Conclusions We have developed new prognostic models in a more homogeneous LGG population diagnosed by central pathology review. This population better fits with modern practice, where patients are enrolled in clinical trials based on central or panel pathology review. We could validate the models in a large, external, and independent dataset. The models can divide LGG patients into 3 risk groups and provide reliable individual survival predictions. Inclusion of other clinical and molecular factors might still improve models' predictions.