What if real-world data (RWD) sources can increase the speed of getting therapies to market? Instead of waiting five years for a clinical trial to be designed, enrolled, and completed … what if we could do it in 1/5 of the time? 

That journey is underway. 

Many organizations—academia, public and private companies, health policy groups and the FDA—are working to establish best practices for generating and evaluating RWD. In fact, Friends of Cancer Research (FOCR) brought together six organizations with oncology-focused healthcare data. The goal was to conduct an initial pilot study project in order to agree on and execute a common protocol using diverse RWD. They also wanted to explore how real-world end points could rapidly address clinically relevant questions about treatment effectiveness. 

The resulting paper, An Exploratory Analysis of Real-World End Points for Assessing Outcomes Among Immunotherapy-Treated Patients With Advanced Non–Small-Cell Lung Cancer (aNSCLC),” recently published in JCO® Clinical Cancer Informatics, outlines how the project extracted and used RWD to examine real-world end points from many different healthcare organizations. They also assessed how these related to end points in clinical trials for immunotherapy-treated aNSCLC. 

Researchers used non-identified patient data from sources such as administrative claims and electronic health records (EHRs) to assess real-world end points. They found the end points were generally consistent with each other, as well as with outcomes observed in randomized clinical trials (RCTs). As a result, researchers said they believe this “substantiates the potential validity of real-world data to support regulatory and payer decision making.”  

“RWE will be an important tool for continued learning about treatment outcomes over time, which benefits future patients.”

(FD: Inteliquet—formerly known as TransMed—contributed deidentified data on 9,118 NSCLC patients, of which 3,478 had aNSCLC, and of which 477 had been treated with PD1 inhibitors in the real-world setting. This data source contribution, taken from diversified oncology EHRs, is similar in size to that of other organizations participating in the study. More on this later.)  

Since the findings were generally consistent with each other and with outcomes observed in RCTs, the case can be made that using such aggregated RWD and real-world evidence (RWE) can benefit a number of groups. 

  • For Life Science/Sponsors/Pharma:  
    There is an opportunity to potentially shorten the time involved in bringing new therapies to patients, as well as streamline trial design. It also shows the value of using RWE to measure and quantify the comparative benefits and risks of various medical products. 
     
  • For CROs: 
    They are in a better position to work with Sponsors to develop new therapies by sharing and using their own data. This allows them to be a more strategic partner and collaborator. 
     
  • For Providers:  
    RWE will be an important tool for continued learning about treatment outcomes over time, which benefits future patients. 
     
  • For Patients: 
    It will provide access to safer therapies more quickly. It also can provide important information on smaller and specific patient populations often excluded from clinical trials. 

RWD and RWE over RCTs? 

Currently RCTs are the best way to test new treatments and show efficacy and safety of experimental drugs. But they are time-consuming and challenging to design and conduct. Sometimes, results may not correlate to patients treated in the real-world settings. While RCTs are the best method to demonstrate effects between treatments and outcomes, the researchers concede that RCTs “are often slow to accrue and expensive or are difficult to conduct because of practical or ethical reasons. Moreover, their results may not generalize to patients who are treated in the real-world setting.” 

RWE can play a role in helping advance therapies and treatments, as well as continuing the process of learning about treatments following RCTs.  

Inteliquet: A Melting Pot of Data. More Representative 

Data Inteliquet contributed is representative of the patient diversity from many types of oncology practices across the U.S. Not only does this eliminate biases, it provides a more complete representation of data due to the broad spectrum of sites and patients. Larger data sets can be restrictive when they only focus on one section of the country, one type of care setting, or only insurance claims. 

Inteliquet’s software is EHR-agnostic; it can extract and ingest data from any source. This includes many systems, including EHRs, practice management systems, laboratory information systems, and tumor registries. It also includes many diagnostic reporting, including pathology, radiology, and molecular results, among others. Along with being representative, another benefit of EHR data is the ability to observe the entire patient journey with real results, which can bring a new level of clarity to the clinical trial process. 

This is the first step on a long journey, and we will continue participating in such endeavors under the auspices of FOCR and other groups looking for ways to improve the cancer research process. 

You can read the full paper here

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© Copyright 2020 Inteliquet, Inc. All rights reserved.