GBM AGILE glossary
Read our glossary of terms for definitions on some of the key aspects of GBM AGILE.
An adaptive trial is a type of clinical trial. Unlike traditional clinical trials, the adaptive design of the trial allows for modifications to be made in response to data collected at more frequent time points throughout the trial. The goal of adaptive design is to allow outcomes to be assed more quickly than traditional trials.
Beyesian statistical methods are being used increasingly in clinical research because the Bayesian approach is ideally suited to adapting to information that accrues during a trial, potentially allowing for smaller, more informative trials and for patients to receive better treatment. Accumulating results can be assessed at any time, including continually, with the possibility of modifying the design of the trial, for example, by slowing (or stopping) or expanding accrual, imbalancing randomization to favour better-performing therapies, dropping or adding treatment arms, and changing the trial population to focus on patient subsets that are responding better to the experimental therapies. Bayesian analyses use available patient-outcome information, including biomarkers that accumulating data indicate might be related to clinical outcome. They also allow for the use of historical information and for synthesizing results of relevant trials.
Biomarkers are biological signals found in tissue, blood and bodily fluids that, in the case of cancer, can tell you about the characteristics of a tumour. In the same way a pregnancy test can detect changes in your body, testing for cancer biomarkers can tell you a lot about the changes that have happened to make the cell cancerous and can be used to predict the effectiveness of certain treatments.
Combination therapies use multiple agents or drugs together to treat a condition.
A clinical trial is a scientific study that, in a structured and standardised way, tests the health outcomes of a new intervention (i.e. drug, medical device, exercise etc.). Clinical trials test these new interventions on people who either have a certain condition or healthy volunteers (depending on the type of trial). Interventions must provide adequate data before they can be tested in a clinical trial. Clinical trials move through ‘phases’ that are used to determine the safety and effectiveness of the new intervention. Each phase will have their own protocol and endpoints. Each phase of a trial may take several years to complete. Only at the completion of the phase will the success of the intervention be evaluated.
A protocol is the written description of a clinical study. It includes the study's objectives, design, and methods. It may also include relevant scientific background and statistical information.
A trial endpoint is a way of measuring the success of a clinical trial. Common endpoints in cancer trials include ‘overall survival’ and ‘progression-free survival’. Overall survival measures the length of time a person survives from either the date of diagnosis or treatment. Progression-free survival measures the time it takes for the disease to get worse (for example for a brain tumour to re-grow) from when it was last treated. These time measurements are compared to historical data to determine whether people on the trial had better outcomes than they did historically. Statistical analysis is then used to determine if these results are statistically significant.
The term ‘statistically significant’ refers to the likelihood that a result or relationship is caused by something other than random chance.
GBM stands for glioblastoma, glioblastoma multiforme, or grade 4 astrocytoma. Glioblastoma is - a highly aggressive form of brain cancer. Glioblastomas form from the supportive star-shaped cells in the brain called astrocytes, however the tumours commonly contain other types of cells as well. Glioblastomas grow rapidly and invasively through the brain and establish a network of blood vessels. Another feature of glioblastoma tumours is the necrotic (dead) cells that may also be seen, especially toward the centre of the tumour. Glioblastomas are generally found in the cerebral hemispheres of the brain but can be found anywhere in the brain or spinal cord.
A learning system (in this context), describes the design of the GBM AGILE trial system. The learning system design can be thought of a feedback loop that takes patient data at frequent pre-determined points in time and feeds the information back into the trial to directly inform the treatment of the next patients who enters the trial system. This is in contrast to a traditional trial set-up that only analyses the data once the trial is complete. The information learned from the patient data will also be used to inform basic science in the lab, which will lead to discoveries that can inform what is tested in the system.
Rather than each individual trial having its own protocol written for testing a single therapy, a master protocol aims to streamline the drug development process by creating a ‘master protocol’ under which multiple pharmaceutical companies can test their drugs to speed up discovery.
The development of therapies tailored to an individual tumour’s genetic profile, rather than a blanket, ‘one size fits all’ approach.
Drug repurposing takes a treatment that is known or approved for one condition and tests to see if it is effective against a different kind of condition. Repurposing saves a lot of time and cost as these agents have already passed a significant amount of safety tests and characterisation. A famous example of drug repurposing is Viagra. Viagra was originally approved as an anti-hypertensive but has been repurposed for erectile dysfunction and pulmonary arterial hypertension.
For more terms about clinical trials please visit clinicaltrials.gov.