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How registries and observational studies can generate evidence to augment results from oncology trials

When we talk about all of the recent success in the oncology sector, successful clinical trials usually get most of the headlines. And rightfully so. This research has been carefully crafted to test the safety, efficacy, and performance of ground breaking drugs, bringing life changing solutions to millions of cancer patients around the world.

But clinical trials aren’t the only place where oncology research is taking place. Just as important are the oncology patient registries and non-interventional studies designed to complement trials by gathering real world data about patients outside of the trial environment.

Trial vs registry

Clinical trials are designed to test drugs on a very specific population of patients who tend to meet strict inclusion/exclusion criteria, which often includes requirements that they not suffer from co-morbidities or take medications for other diseases. These criteria are important because they create an environment where researchers can collect accurate data about treatment and outcomes, without fear that other medications or conditions will cloud their results.

But because of these criteria, participants in oncology clinical trials tend to be much “healthier” than the broader population of cancer patients treated in the real world — those who may have multiple conditions, such as hypertension, diabetes, pulmonary disease or other health issues and may be taking other medications. The clinical trial data may not explore how the new treatment may interacts with other medications and may use intermediate endpoints – that is where registries and non-interventional studies come in.

In non-interventional (or observational) studies, researchers track patient’s use of prescribed treatments in real world conditions, without interfering in any of their treatment decisions. Participating patients take the drugs prescribed by their doctors, and are in no-way influenced by the observational study. This environment offers a wealth of valuable data for researchers to explore things like drug utilization, potential off-label use, and potential side effects that may not have been picked up during the trials, and understand how the new treatment works in different subgroups of patients. Additionally, in some countries the effect of the new therapy on quality of life may be explored.

Patient registries use observational methods to gather real world information about patients with a specific cancer diagnosis or treatment and registries can be used as a vehicle to answer multiple research questions.

Along with creating a venue to recruit new patients for future clinical trials, patient registries give researchers a valuable real world environment to study treatment experiences, patient outcomes, and in some cases overall quality of life as it relates to their disease.

Patient registries and non-observational studies can also be used to monitor outcomes and study best practices in care or treatment, either for a specific duration or over a long period of time. This is important as many new oncology treatments are targeted at specific biomarkers that may allow patients to live longer, and researchers need to know whether the treatment patients received for their cancer will have any long term implications. This data is often sought by regulators, who are increasingly interested in real world research as part of post-approval pharmacovigilance as well as payers to support coverage decisions. Physicians and patients are also interested to learn what the best treatment is for specific patients. Data can also be used to develop hypotheses and answer key research questions to support current and future studies. For example, if a drug extends a patient’s lifespan but they spend that extra time bedridden, is it worth it?

Plan early and keep it simple

But building and maintaining oncology registries and observational studies isn’t easy, especially when there is growing competition among competing research groups for patients to enroll in these registries. To be successful, you need to start planning for these studies earlier on in the product life cycle, and ideally before the end of the phase III studies. This will give you the best chance of building a useful study to generate valid evidence to support multiple stakeholder needs. It will also upfront thinking to plan the best strategy for identifying where to target recruitment efforts for the target population given the crowded marketplace for treatments of many of our cancers.

Once clinics and patients have agreed to take part, the most important thing you can do is to keep things simple and aligned with routine clinical practice. It can be very tempting to want to want to collect endless data about patients’ lives and their medical history, but if there is too much information to be collected it’s more likely they will drop out.  Health care providers are busy, and we must not forget that the patients have cancer, which means if something is too burdensome and taking too much of their time, they will quickly give up on a voluntary observational study.

To avoid overwhelming your clinics and study participants, identify what data you absolutely need to meet your research objectives, then stick to it. Limit questionnaires to fifteen minutes, use technology to streamline the collection process and to reduce data entry errors, and – most importantly- make sure every question adds value.

You also want to be sure you understand exactly where key pieces of data will come from based on the patient care pathway. In many cases, oncology patients get their treatments from infusion centers, which means that details about the new treatment may not be available in regular pharmacy databases. Your study design needs to account for all of these variables if you want the study to be accurate and accepted by physicians and regulators.

Despite the challenges, registries and real world studies are vital and valuable part of oncology research. All stakeholders today are interested in this real world data, and the sooner you start planning and implementing these complementary studies the more comprehensive and valuable that data will be.