Real-World Evidence in Oncology

At Innova Solutions, we help bridge this gap between research and real life. Our AI-powered RWD/E approach brings together deep domain expertise, advanced data engineering, and flexible engagement models to unlock high-quality, regulatory-grade evidence—faster and more efficiently.

This blog explores why it’s time to move beyond trials alone—and how as technology partners, we are helping life sciences organizations turn complex cancer data into meaningful, real-world impact.

Trials Alone Can’t Represent the Diverse Reality of Treatment

Randomized controlled trials (RCTs) evaluate the efficacy and toxicity of novel treatments against standard-of-care comparators and are considered the “gold standard” for determining whether there is a cause-and-effect relationship between treatment and outcome. Before their adoption in clinical practice, RCTs were considered the highest level of evidence for defining the efficacy of treatments. However, RCTs often face challenges regarding their external validity. The generalizability of their results can be affected by various factors, such as differences in patient populations, variations in care between the clinical trial environment and real-world practices, and trial durations.

• Limited Patient Population Representation
  A Cohort of patients participating in a clinical trial may not be representative of the broader patient population, as only around 7.1% of patients are enrolled in RCTs [Source: Commission on Cancer, American College of Surgeons].Older patients aged 65 years and above are consistently under-represented in clinical trials, even though cancer is more commonly diagnosed in older people. There is also an under-representation of patients from racial and ethnic minorities, those with socioeconomic disadvantages, and patients with complex health problems; therefore, RCTs may lack information about treatment tolerability and efficacy in patients with multiple co-morbidities and poor performance status.
• Variations in Care Provisioning
  Patient care provided in clinical trials does not necessarily represent routine clinical practice. Clinical trial participants are monitored more closely than patients in routine practice, which may influence outcomes. There is evidence that clinical trial participants benefit from the ‘trial effect’ or ‘protocol/Hawthorne effect’, which states that the clinical trial participation may have a positive effect on outcomes due to more intensive care. This is reinforced by the fact that patients referred for clinical trial participation at specialist centers have better survival outcomes than those who are not.
• Extended Trial Timelines
  According to a pharmaceutical industry report based on 4100 oncology trials, the average duration of phase III oncology trials was approximately 5 years. Data on key clinical outcomes, such as overall survival, can take many years to mature. This often leads to the use of surrogate endpoints that can be available in shorter time frames, such as response rate and progression-free survival. Recent analyses show that approval for two-thirds of oncology drugs by the United States Food and Drug Administration (FDA) was based on surrogate outcomes. However, many RCTs use surrogate endpoints that are not adequately validated measures of patient benefit. Furthermore, RCTs have limited patient numbers and follow-up durations.

The Value of Real-World Evidence in Patient Care

Real-world evidence (RWE) fills in the gaps. It collects extensive data outside the controlled environment of clinical trials, including information from electronic health records, cancer registries, and patient surveys. By analyzing this data, researchers can uncover how treatments perform in real-world healthcare settings. In oncology, RWE is rapidly gaining significance because it addresses critical clinical and policy questions that RCTs cannot fully resolve, providing a more holistic understanding of patient outcomes over time.

The cancer medicine development life cycle is an iterative process, and it is critical to identify the areas where evidence is needed to drive high-quality care and optimize outcomes for cancer warriors.

How evidence-based insights enhance personalized patient care:

The diverse nature of real-world data opens a wide range of potential applications in cancer research. Here’s how:

• Addressing Evidence Gaps in Underrepresented Populations
  Traditionally, clinical trials have underrepresented specific patient groups, such as older adults. This leads to a lack of evidence to guide their care. Real-world data provides opportunities to study the magnitude of these evidence gaps, identify contributing factors, and gain insights into effective management and outcomes for these patients.
• Understanding Treatment Use and Outcomes in Real-World Settings
  Real-World Evidence is critical in reducing the efficacy-effectiveness gap because it captures treatment performance beyond the RCT environment. While RCTs demonstrate what is possible under controlled conditions, they often overlook how real patients, who differ in age, comorbidities, and care environments, respond to treatment. RWE allows us to understand, explore, and describe how these variations affect outcomes—such as survival and toxicity—and helps clinicians to deepen their understanding of the difference between “what happens in RCTs” (efficacy) and “what happens in the real world” (effectiveness), bringing evidence closer to real-world oncology practice.
• Advancing Research in Rare Cancers
  It is challenging to generate evidence to guide the care of patients with rare cancers due to difficulty in accruing sufficient participants and statistical power to detect differences in outcomes. Observational studies using real-world data are increasingly being recognized as a means to advance research into rare cancers by improving the understanding of their natural history, evaluating clinical practice, establishing standards of care, and generating hypotheses for testing in clinical trials.
• Evaluating Rare and Long-Term Toxicities
  RCTs are often limited in their ability to provide information on rare and late-onset treatment toxicities. In contrast, real-world data studies often include larger patient populations that have been observed over longer periods, enabling the detection and analysis of these less common and delayed adverse events.
• Improving Health Economic Evaluations
  Health economic evaluation is used to model the anticipated costs associated with the adoption of new cancer medicines and is often used by health technology assessment bodies to determine funding of and access to treatments. However, these predictive models and estimates are often based on assumptions that may not accurately reflect the true costs of health interventions in the real world. Real-world data can enable the estimation of actual health care use and costs to support health economic evaluation.

Conclusion

RWE provides a unique opportunity to understand how treatments practically perform in a variety of patient populations and everyday clinical conditions. While RWE offers useful information on effectiveness, sustainability, long-term outcomes, and health economics, it does not replace the methodological rigor of randomized controlled trials. RWE and RCTs are complementary; together, they provide a better and more useful approach for decision-making, regulatory policy, and individualized patient care in oncology.

From integrating fragmented data to delivering regulatory-grade insights, our RWD/E ecosystem is designed to turn evidence into action—faster. At Innova Solutions, we empower life sciences teams to navigate this journey with confidence.