The number of antidepressants available to patients is dizzying, which can make it difficult to determine which prescription will be the best fit鈥攊t鈥檚 not uncommon for patients to try several drugs before finding one that works for them. To compound this issue, treatments don鈥檛 act immediately, often taking one to three weeks to take effect, leaving vulnerable patients at-risk.
Dr. Erica Moodie and a group of researchers at 捆绑SM社区 hope to determine which anti-depressants might work best for certain types of patients based on factors like their age and BMI (body mass index). The project, which involves several researchers from 捆绑SM社区 and the US consortium , is funded by an Innovative Ideas grant from 捆绑SM社区鈥檚 Healthy Brains, Healthy Lives.
The approach taken by Dr. Moodie and her team differs from other studies in a key way: 鈥淢ost of the studies that are done try to find the best treatment on average,鈥� Dr. Moodie explains. 鈥淭hat鈥檚 fine overall, but individual patients aren鈥檛 average patients, so they may do better on one treatment versus another. Not only that, but patients change over time. Depression can be a relapsing and remitting disease鈥攖here may be other life events that cause the need for more or less treatment at any given time. We鈥檙e looking to come up with more specific guidelines for how to choose among the many, many drugs available to patients.鈥�
It鈥檚 especially important to get the treatment right the first time because, as co-investigator Dr. Christel Renoux points out, missing the mark can have significant consequences. 鈥淲e know that, in the early treatment period, the patient may be at increased risk of anxiety, agitation and suicide. You want to get it right on the first try so, when it starts to work, it works well.鈥�
To develop these guidelines, the team is analyzing data from electronic medical records of patients from the United Kingdom鈥檚 Clinical Practice Research Datalink (CPRD). These data include complete medical information from around 13 million patients, followed by roughly 700 general practitioners and, of these, the team has identified over 200,000 individual patients who fit their criteria. 鈥淚t鈥檚 data from real-world, clinical practice and not over-selected populations,鈥� Dr. Renoux explains. 鈥淲e have all their medical information over time鈥攍ifestyle, smoking history, alcohol use, prescriptions issued by the GP, hospital referrals and hospitalization data. As long as they stay within one of the practices that we have access to, we have their entire medical follow-up by their GP.鈥�
Having access to long-term data for each patient allows the researchers to study the effectiveness of different antidepressant treatments on different patients over time. Dr. Moodie鈥檚 PhD student, Janie Coulombe, is responsible for analyzing thousands of medical records through a brand-new statistical method developed by 捆绑SM社区 graduate student Dr. Gabrielle Simoneau. Using this method, the team was able to analyze their cohort of patients to see if there is a link between any of their characteristics and the effectiveness of prescribed antidepressants. The approach of focusing on data-driven research (rather than traditional, hypothesis-based research) is becoming more and more common, and for good reason. As Coulombe explains, the team aims to expand their findings by gathering more information from other datasets to make sure their rules are reproducible and broadly applicable. 鈥淭his project is a little bit exploratory. We鈥檙e mostly hoping to find signals of variables that can help in tailoring antidepressant therapy to patients, and we鈥檙e also assessing to what extent these variables can help in improving treatment outcomes.鈥�
The team will soon be embarking on parallel work on another dataset from the U.S. (MHRN), which, as Dr. Moodie describes, differs from the CPRD dataset in several ways. 鈥淭he U.S. data are more fine-grained in many ways than the CPRD data鈥攚e have more symptoms and more patient-level covariates. But, since those data are from the U.S., it represents a more select, high-income population because the U.S. doesn鈥檛 have a public health-care system like Canada or the U.K. Between these two prongs of data and the analyses that we鈥檙e doing now, we have a population that鈥檚 pretty representative of the general population in clinical care. Also, I always see Canada as being somewhere in the middle of the U.S. and the U.K., so my hope is, if those two populations aren鈥檛 too different, then it鈥檚 probably not too different from the experiences that we would see here.鈥�
Since gaining access to the CPRD data, the team has made considerable headway and are close to sharing guidelines on how to choose a treatment among some of the most common antidepressants. While the project鈥檚 conclusion is set for March 2020, Dr. Moodie explained that ideas and methods gained from this work could potentially be applied to other projects of a similar nature. 鈥淲e could easily do a similar sort of project by taking what we鈥檝e learned to look at other classes of drugs or other forms of mental illness. I think we have a really nice framework for how to do this within the CPRD鈥攊t鈥檚 really been an excellent springboard for expanding these types of methods and questions within the CPRD.鈥�
