Randomized Controlled Trials (RCTs) and Real-world Outcomes in Hematological Malignancies: Minding the Gap

A blog by Jeff Elton, PhD | CEO, ConcertAI and Lindsey Gasparini | VP, Informatics at NeoGenomics

Coincident with the 2023 American Society of Hematology meeting early December, a published article that received significant attention, recirculation, and citation in multiple channels, compared the outcomes of standard of care multiple myeloma (MM) patients with the clinical trial data that contributed to the drug’s approval, noting significantly poorer outcomes in the real-world population, where the survival benefit was sometimes years shorter.

Why? These sorts of observations are not new. For years there has been an ongoing debate that real-world population outcomes are below those of the original clinical trial populations. This is the result of multiple factors. It is important to note that it is not necessarily the result of poor study design, nor an active strategy to ‘assure’ a specific study outcome. Rather, as is the case with many scientific and business processes, there are ‘ways of working’ and conventions of practice that had, and to a degree continue, to guide decisions. Examples of these include study designs, endpoints selected for a specific disease, how those endpoints are measured, the targeted cohorts for the active treatment and control arms, etc. Perhaps most significant is the selection of settings and sites for the clinical trial itself.

Traditionally, most clinical trials are performed at academic medical centers (AMCs) where the mission of the organization is to conduct research. Theclinical staff has a significant allocation to research and these facilities have the infrastructure designed to administer both advanced standard of care therapies, and new protocols or studies. The majority of the centers tend to be located in the largest urban areas, close to major universities and large-scale business activity. While the missions of these centers has always emphasized serving their communities and not just those who have financial means,, the nature of access and economics have tended to see the patient population as broadly in better health, and of higher economic means. Given that many of these academic centers make the majority of clinical trials available, there are often capacity dilemmas. In aggregate there is a meaningful imbalance as there are more trials looking for patients than there are patients available who meet trial eligibility criteria. We note, this is not statement about the role of these centers being negative or being a source of bias – that is actually not the case at all. AMC’s are often the first point of observation and insight into new disease mechanisms or novel therapies. They AMCs are , critically important and a differential advantage of the US healthcare system given that they are the primary, and sometimes only, sites for clinical trials. The challenge is, we are beginning to see the number of studies increase substantially, with the I/E requirements becoming every more narrow, with traditional research sites no longer able to assure the successful accruals.

Over the last two years, the US FDA has encouraged sponsors to have the design of the trial, and the populations participating in the trial, more closely match the ultimate standard of care population that may have access to a new medicine should it be approved. This one simple shift is having a tremendous impact on the design of trials and broad movement to have more studies performed in a community versus academic setting.

While it may seem fairly straightforward, changing the location of trials requires more than just a simple selection of new sites. Community oncology and urology sites have a very special place in the healthcare delivery system of the US. They are in all communities, even those that are very rural and less populated. They see patients of all backgrounds and ethnicities, many with a health history that includes less care or care access, and therefore more patients have advanced stages of diabetes and cardiovascular diseases, as just two examples. They also tend to have more limited ‘economic degrees of freedom’ in that they may need two wage earners to make a living. These folks often view the schools their children attend and the after-school programs they may also participate in, as a requirement for their ability to hold a job. It would not be unusual for families to make decisions about which health problems, procdeures or new medicines merited interventions or where they would “make do.” So, when a diagnosis of cancer is arrived at, it triggers several other decisions and tradeoffs. If the concept of a clinical trial is introduced, the decision to participate may be made based on if participation would require any additional visits and how that would impact time away from work or childcare responsibilities.

These community based sites have limited resources to support research. Their primary objective is clinical care. Their reimbursement is quite different (e.g., buy-and-bill for certain therapeutics dispensed in their pharmacies) than the models applied to the leading academic research centers that recognize their roles as training centers. Therefore, any sponsor requirements, trial requirements, or administrative burden will potentially be considered to determine if it lowers their productivity, or how it may limit their ability to take on other clinical trials.

Altogether this means that clinical trial design, trial diversity objectives, and sites selected need to be well thought out and designed with a set of common and interdependent objectives. Only then can we advance towards the goals of having trial designs that provide the highest confidence in the benefit and safety of a new therapeutic for the ultimate standard-of-care population that may receive it.

All clinical research is hard, in that it requires dedicated effort of sponsors and sites over years, to identify eligible patients, gain their consent to participate, support them over the life of the study so they remain in the trial, and to document and quality-review all data in assurance of the highest veracity statistical analyses in the ultimate submission to regulatory bodies.

So, while all research is hard, hematological malignancy studies are even harder. There are over 200,000 newly diagnosed patients per year with some form of hematological malignancy and approximately 2 million patients living with these cancers. Patient treatment options at first diagnosis or at first relapse are highly variable and complex. The duration of response, thankfully, has gotten progressively longer, with the implication that waiting for a relapse or refractory status in a patient is less certain and requires longer-term surveillance. When you add these factors together, you are evaluating very narrow sub-cohorts based on past treatment and drug exposures for very narrow trial designs. Essentially finding the needle in one haystack, to then place that patient into a narrow location in a new haystack. Today, 10% of all newly diagnosed cancers are hematological malignancies, a greater proportion of patients who remain alive and under active care are living with hematological malignancies, and an even greater number of new trials are being initiated for these diseases.

ConcertAI has been working on these new objectives for the last two to three years. With the largest research dataset for oncology and hematology in the world, we generate datasets specific to research insights to guide first-in-human trials, inform Ph2b/3 trial designs based on early phase results, generate supporting documentation on standard of care outcomes as part of a submission package, and develop external control arms where sponsors and regulators deem that a suitable alternative to a classic RCT design. We have developed solutions for designing registrational trials that look at all aspects of the current standard of care, across settings, and that provide a special focus on achieving study and disease relevant diversity. We are putting the most advanced clinical AI, Natural Language Processing models, and generative AI behind the firewall of research sites to do patient matching that is an order-of-magnitude faster than humans alone with comparable accuracy. We are creating clinical trial technologies that require no data entry by the site research teams and that provide a higher quality data package to sponsors.

Our recently announced partnership with NeoGenomics is directed at the importance and complexity of hematological malignancies real world studies and clinical trials. We now have the deepest, broadest, biomarker rich, and longest duration of observation data sets in hematology. These now include hundreds of biomarkers and the ability to bring together hematological pathology digital sources for AI model development and enabled insights. Few solutions can inform trial design, form the basis for early regulatory interactions, support regulatory registries, and support post-approval RWE studies at scale. A version of our trial design and site optimization solution will be deployed for hematology, enabling the biomarker depth and narrow cohort requirements of contemporary hematology trials designs. We are also dedicated to enhancing and building community research capacity and capabilities as we jointly integrate clinical trial technology solutions at the cloud and site level.

Studies citing major gaps in RCT and RWE outcomes are important. They stand as a data-informed reminder of the work in front of us. There is a movement across the industry to change where and how trials are done. We see it in the new community care centers scaling or initiating their trial programs and in the sponsors working diligently to engage sites they’ve never worked with in the past and to do so with new contracting and technology solutions in assurance of a minimum of burden. These new collaborative approaches between the biopharma innovators and the community care providers stand to accelerate needed medicines, improve the generalizability of trial data to the ultimate standard of care population, and assure greater treatment options for the greatest number of patients.

Sometimes achieving a new outcome is not about incremental improvements, but full reconsideration of legacy operational models and how the system works. That is what is now underway and what we are committed to, in partnership with research sites, research networks, sponsors, patient advocacy organizations, medical societies, and the patients themselves.

The content in the blogs herein relate to the opinions and views expressed by the individual blog author(s) and contributors and are not necessarily the viewpoints held by NeoGenomics Inc., or any of its affiliates or entities.

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