Line of therapy and patient preferences regarding lung cancer treatment: a discrete-choice experiment

A growing literature on patient preferences informs decisions in research, regulatory science, and value assessment, but few studies have explored how preferences vary across patients with differing treatment experience. We sought to quantify patient preferences for the benefits and risks of lung cancer treatment and test how preferences differed by line of therapy (LOT).

Preferences were elicited using a discrete choice experiment (DCE) following rigorous patient and stakeholder engagement. The DCE spanned five attributes (each with three levels): progression-free survival (PFS), short-term side effects, long-term side effects, risk of developing late-onset side effects, and mode of administration (MOA) - each defined across 3 relevant levels. A D-efficient design was used to generate 3 survey blocks of 9 paired-profile choice tasks each and respondents were asked which profile they preferred and then if they preferred to have no treatment (opt-out). A mixed logit model, controlling for opt-out, was used to estimate preferences. Preferences and trade-offs between PFS and other attributes were compared across two groups: those receiving ≤1 LOT and those receiving ≥2 LOT.

Of the 466 participants, 42% received ≤1 LOT and 58% received ≥2 LOT. Stated preferences differed between the groups overall (p<.001) and specifically for 18 months of PFS (p<.001), moderate short-term side effects (p<.001), no long-term side effects (p=.03), and 30% chance of late-onset side effects (p=.02). Those receiving differing amounts of LOT were willing to trade different amounts of PFS to change from moderate to mild short-term side effects (p<.001), moderate to no (p<.001) and mild to no (p<.001) long-term side effects. There were also differing amounts of tradeoff acceptable between the groups for a 10% decrease in risk of late-onset side effects (p=.016), a decrease in MOA from infusion every 3 weeks to pills taken daily at any time (p=.005) and from pills taken daily without food to pills taken daily at any time (p<.001).

We demonstrate differences in preferences based on experience with LOT, suggesting that patient treatment experience may have an impact on their preferences. As patient preference data become an important component of treatment decision making, preference differences should be considered when recommending therapies at different stages in the treatment journey. Understanding patient preferences regarding treatment decisions is essential to informing shared decision-making and ensuring treatment plans are consistent with patients' goals.