Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value.

BACKGROUND: Demonstrating safety and efficacy of new medical treatments requires clinical trials but clinical trials are costly and may not provide value proportionate to their costs. As most health systems have limited resources, it is therefore important to identify the trials with the highest value. Tools exist to assess elements of a clinical trial such as statistical validity but are not wholistic in their valuation of a clinical trial. This study aims to develop a measure of clinical trials value and provide an online tool for clinical trial prioritisation. METHODS: A search of the academic and grey literature and stakeholder consultation was undertaken to identify a set of criteria to aid clinical trial valuation using multi-criteria decision analysis. Swing weighting and ranking exercises were used to calculate appropriate weights of each of the included criteria and to estimate the partial-value function for each underlying metric. The set of criteria and their respective weights were applied to the results of six different clinical trials to calculate their value. RESULTS: Seven criteria were identified: 'unmet need', 'size of target population', 'eligible participants can access the trial', 'patient outcomes', 'total trial cost', 'academic impact' and 'use of trial results'. The survey had 80 complete sets of responses (51% response rate). A trial designed to address an 'Unmet Need' was most commonly ranked as the most important with a weight of 24.4%, followed by trials demonstrating improved 'Patient Outcomes' with a weight of 21.2%. The value calculated for each trial allowed for their clear delineation and thus a final value ranking for each of the six trials. CONCLUSION: We confirmed that the use of the decision tool for valuing clinical trials is feasible and that the results are face valid based on the evaluation of six trials. A proof-of-concept applying this tool to a larger set of trials with an external validation is currently underway.

Assessing neuro-oncology clinical trial impact and value: Testing a novel multi-criteria decision analysis app.

BACKGROUND: Many clinical trials are conducted globally, creating challenges in deciding which trial outcomes deserve a clinician's focus and where to direct limited resources. Determining the 'value' of a clinical trial relative to others could be useful in this context. The aim of this study was to test a novel web-based application using multi-criteria decision analysis (MCDA) to rank clinical trial value. METHODS: The MCDA tool combines seven metrics: unmet need; target population size; access; outcomes; cost; academic impact and use of results. Clinical trials were ranked according to their calculated 'value' - meaning the importance or worth of a trial. We determined face validity of the app using a set of ten published Phase 3 neuro-oncology clinical trials. A survey of neuro-oncology clinicians asked them to rank the same ten clinical trials, and to rank the seven metrics in terms of importance. RESULTS: The two highest app-ranked trials were in concordance with that of the survey respondents, and consistent with the two studies that have had the most impact on routine clinical practice in neuro-oncology. Of the seven metrics, surveyed clinicians considered patient outcomes and unmet need to be the most important when determining clinical trial value. CONCLUSIONS: The metrics app was able to rank and produce a numerical 'value' for existing phase 3 neuro-oncology clinical trials. In the future, a related app to prospectively rank future trials at the startup stage could be developed to help centers determine which should be prioritized to be conducted at their site.

Decreased expression of mGluR5 within the dorsolateral prefrontal cortex in autism and increased microglial number in mGluR5 knockout mice: Pathophysiological and neurobehavioral implications.

Metabotropic glutamate receptor 5 (mGluR5) and microglial abnormalities have been implicated in autism spectrum disorder (ASD). However, controversy exists as to whether the receptor is down or upregulated in functioning in ASD. In addition, whilst activation of mGluR5 has been shown to attenuate microglial activation, its role in maintaining microglial homeostasis during development has not been investigated. We utilised published microarray data from the dorsolateral prefrontal cortex (DLPFC) of control (n=30) and ASD (n=27) individuals to carry out regression analysis to assess gene expression of mGluR5 downstream signalling elements. We then conducted a post-mortem brain stereological investigation of the DLPFC, to estimate the proportion of mGluR5-positive neurons and glia. Finally, we carried out stereological investigation into numbers of microglia in mGluR5 knockout mice, relative to wildtype littermates, together with assessment of changes in microglial somal size, as an indicator of activation status. We found that gene expression of mGluR5 was significantly decreased in ASD versus controls (p=0.018) as well as downstream elements SHANK3 (p=0.005) and PLCB1 (p=0.009) but that the pro-inflammatory marker NOS2 was increased (p=0.047). Intensity of staining of mGluR5-positive neurons was also significantly decreased in ASD versus controls (p=0.016). Microglial density was significantly increased in mGluR5 knockout animals versus wildtype controls (p=0.011). Our findings provide evidence for decreased expression of mGluR5 and its signalling components representing a key pathophysiological hallmark in ASD with implications for the regulation of microglial number and activation during development. This is important in the context of microglia being considered to play key roles in synaptic pruning during development, with preservation of appropriate connectivity relevant for normal brain functioning.

Biomarker investigations related to pathophysiological pathways in schizophrenia and psychosis.

Post-mortem brain investigations of schizophrenia have generated swathes of data in the last few decades implicating candidate genes and protein. However, the relation of these findings to peripheral biomarker indicators and symptomatology remain to be elucidated. While biomarkers for disease do not have to be involved with underlying pathophysiology and may be largely indicative of diagnosis or prognosis, the ideal may be a biomarker that is involved in underlying disease processes and which is therefore more likely to change with progression of the illness as well as potentially being more responsive to treatment. One of the main difficulties in conducting biomarker investigations for major psychiatric disorders is the relative inconsistency in clinical diagnoses between disorders such as bipolar and schizophrenia. This has led some researchers to investigate biomarkers associated with core symptoms of these disorders, such as psychosis. The aim of this review is to evaluate the contribution of post-mortem brain investigations to elucidating the pathophysiology pathways involved in schizophrenia and psychosis, with an emphasis on major neurotransmitter systems that have been implicated. This data will then be compared to functional neuroimaging findings as well as findings from blood based gene expression investigations in schizophrenia in order to highlight the relative overlap in pathological processes between these different modalities used to elucidate pathogenesis of schizophrenia. In addition we will cover some recent and exciting findings demonstrating microRNA (miRNA) dysregulation in both the blood and the brain in patients with schizophrenia. These changes are pertinent to the topic due to their known role in post-transcriptional modification of gene expression with the potential to contribute or underlie gene expression changes observed in schizophrenia. Finally, we will discuss how post-mortem studies may aid future biomarker investigations.