The Challenge of Relapsed/Refractory Multiple Myeloma (RRMM) and a Role for Real-World Evidence (RWE)

Survival of myeloma patients has improved due to the development and approval of new treatments. However, there remains an incomplete understanding of how heavily pretreated patients with relapsed/refractory multiple myeloma (RRMM) are treated in routine clinical practice and the effectiveness of those treatments, given the limited number of regulatory approved treatments in this setting. Clinical practice differs greatly beyond 3rd line treatment and there is a lack of knowledge of how this impacts patient outcomes.

Approval and reimbursement of new treatments for RRMM in patients who are refractory to an IMiD and PI and have received (as part of their previous treatment) a PI, an IMiD, and an anti-CD38 antibody, are increasingly sought, based on single-arm phase two efficacy data from regulatory designed studies. However, the availability of real-world data in this setting is limited. What is more, there are several other confounding factors in RRMM to which the availability of real-world evidence could be part of the solution. 

Multiple prior lines of treatment including exposure to 3 main classes of drugs

Multiple available combinations of proteasome inhibitors, immunomodulators (IMIDs), and monoclonal antibodies are shifting the relapsed/refractory multiple myeloma (RRMM) treatment landscape. An increase in single-arm phase II studies approved by the FDA and the EMA and a lack of head-to-head trials of triplet treatment combinations present a huge challenge to health technology assessment and payer bodies as well as clinicians and patients.

The combination treatment cost-effectiveness challenge

When these triplet treatment combinations contain more than one on patent treatment, the cost of adding an additional treatment to an already expensive backbone treatment is likely to result in significant cost-effectiveness challenges, even if in extreme cases, the new add-on treatment was given away at zero price. 

Potential for diminishing returns 

Myeloma is a relapsing and remitting cancer and its genetic evolution over time means that its clone becomes increasingly high-risk, aggressive, and resistant to treatment. This means that treatment outcomes i.e., progression-free and overall survival, will normally dimmish with each subsequent line of treatment. However, with the introduction of CAR-T treatment and other cell and gene treatments in the pipeline, this may change in the future for some patients.

Disease symptoms treatment impact on quality of life

The symptoms and complications of myeloma are not insignificant and accumulate over time in what is already an older and elderly and frail population predominantly. This, coupled with the potential side-effects of treatment, means that quality of life concerns may be prohibitive even when an effective treatment is available. As a consequence, not only must the treatment be effective in a hard-to-treat population, but it must also have a decent side-effect profile. This is not easy to achieve.

Regulatory v HTA and payer evidence needs and market power

The same evidence often results in different decisions by different decision-makers. Whereas the FDA is looking for evidence that a treatment works and is safe, an HTA body needs to know how well it works and what it cost compared to the current standard of care, and consequentially what is its value. Market forces also dictate that a regulatory trial will be designed to answer FDA questions and reflect the needs of a US market. 

RWE and RRMM

Any data source needs to be critically appraised prior to use, and the same applies to RWD. When establishing an RWE cohort of RRMM patients to investigate the current standard of care, validatory steps must be taken to ensure that the dataset is representative of the patient population:

  •  Multiple centres must be included to avoid single-centre bias.
  •  Key metrics need to be cross-checked versus the current gold standard – typically baseline patient and clinical demographics reported in population-based cancer registries or large-scale peer-reviewed epidemiological studies while considering the subtleties of the incident and prevalent measurements.
  • The median follow-up period of the RWE cohort should align with the median OS (overall survival) of MM patients to ensure the cohort is not biased.
  •  Completeness of data: frequency of health contact events, range of test results reported, and prescription patterns amongst a feasibility subset must be appraised by clinical experts to elucidate whether the data is providing an accurate patient journey.
  • Challenges to using RWE that can be overlooked involve accurate reporting of survival metrics: mortality data can be a challenge as most RWE datasets are not designed to capture this and linkage to additional sources may be required. 

Understanding the RWE data source, its nuances, and the ability to identify and account for any biases is critical. Taking all these factors, and more, into consideration when establishing an RRMM RWE dataset ensures that the ensuing picture of the standard of care treatment pathways for RRMM patients are accurate and provide reliable data on outcomes.

To find out more about our work in Multiple Myeloma, email info@realworld.health