Evaluating the Cost-Effectiveness of NSCLC Treatments: New Insights From a Recent Review

Non-small cell lung cancer (NSCLC) is a major driver of economic strain on healthcare sysh tems worldwide due to its high treatment costs. A systematic literature review published earlier this month in the Journal of Managed Care & Specialty Pharmacy, highlights the challenges in assessing the cost-effectiveness of treatments for this disease. As therapies advance and reshape NSCLC care, accurately evaluating these treatments’ cost-effectiveness is increasingly crucial to ensure optimal resource allocation.

The review, conducted by a team of researchers at the Swedish Institute for Health Economics (IHE), analyzed 237 cost-effectiveness models for NSCLC published from 2012 to October 2023, revealing a wide range of approaches in estimating treatment costs and outcomes.

Although most models included the same three basic outcomes — progression-free survival, progressive disease and death — there was considerable variability in how they assessed treatment impact. Many models also incorporated biomarkers to guide treatment selection, adding further variability.

One key finding of the review is that many existing models fall short of adhering to established best practices for economic evaluation. This lack of adherence could lead to inaccurate cost-effectiveness estimates, potentially affecting decision-making in clinical settings. Moreover, the review emphasizes that existing models may not be well-suited for evaluating personalized treatments, which are increasingly becoming the norm in NSCLC care.

Michael Willis, Ph.D.

According to Michael Willis, Ph.D., corresponding author of the study and research director at IHE in Lund, Sweden, the increasing availability of targeted therapies presents both opportunities and challenges in cost-effectiveness modeling.

“Our principal motivation for performing this review was to prepare for an economic evaluation of a treatment-patient matching tool that is being created as part of the EU-sponsored I3LUNG project,” Willis said in an interview with Managed Healthcare Executive. “By matching patients with the treatments most likely to benefit them, and least likely to harm them [due to adverse effects], the goal is improving outcomes for each individual patient and improving overall economic efficiency for society.”

He added that these models often need to account for complex variables, such as the use of high-cost treatments and testing. Although “the recent boom in new treatments” can improve outcomes, Willis said, they also significantly increase treatment costs.

"Making high-quality, open-source models available to researchers and decision-makers can solve key challenges in economic modeling for NSCLC," Willis said. "Such models can improve transparency, reduce wastage from building redundant models, and help ensure that decisions are based on transparent, well-vetted, validated tools."

The increasing number of models published, especially in recent years, reflects the growing need for cost-effectiveness analysis as personalized treatment becomes more widespread, Willis observed. "As long as new treatments come along, more models will presumably be developed—unless, of course, important open-source models catch on and become widely used," he says.

Looking to the future, Willis sees a promising evolution of economic modeling in NSCLC treatment. However, he cautions that no single model will suffice for every application.

"Open-source models will not be sufficient for all study problems," he said. "Different models will be needed depending on the specifics of the analysis, such as those for drug-drug comparisons or diagnostic-diagnostic comparisons.”

Although the number of cost-effectiveness models for NSCLC continues to grow, there remains significant room for improvement in aligning treatment costs with outcomes. This can be achieved through better adherence to best practices and the use of validated models.

Ultimately, Willis said, “better resource allocation decisions lead to better patient outcomes.”