Phase 3 trials in oncology are pivotal for advancing therapeutic strategies, but complexities in trial designs, particularly crossover methodologies, can significantly impact outcomes. According to Yufei Liu, MD, PhD, assistant professor of radiation oncology at City of Hope, patient transitions between treatment arms can skew results and affect clinical decision-making.
Crossover Designs and Data Interpretation
Liu emphasized the need for meticulous data interpretation when crossover designs are used. "In using the technique of the fragility of the phase 3 clinical trials that I assessed, we essentially are directly addressing that question by crossing patients over from one arm of a clinical trial to another arm, and using that approach, we can see that it can significantly affect the results of clinical trials," Liu noted. She added that sometimes only a few crossover patients can dramatically alter a trial's significance. Liu suggests assessing outcomes of patients who crossed over and comparing results with and without crossovers to ensure consistent conclusions.
Challenges in Selecting Primary Endpoints
Overall survival remains the gold standard for phase 3 trials, but challenges arise when sample sizes are insufficient or overall survival data takes too long to mature. Surrogate endpoints like progression-free survival are often used, but Liu cautions that these can be misleading. "There is certainly some danger to using these end points, because, in a way, the more end points that we use, the more chances that we can find an end point that just happens to be more statistically significant," she explained. Liu advocates for conversations with practitioners to determine which outcomes truly serve as surrogates for overall survival.
Impact of Surrogate Endpoints on Trial Fragility
Progression-free survival can make trials appear less fragile compared to overall survival, potentially masking the fragility of the latter. Liu noted, "Sometimes these surrogate end points can mask the fragility of trials. It is almost like you are choosing whichever end point gives you the most significant P value. In terms of your most important end point, which is their survival, it is sometimes that can be masked in these circumstances."
Role of Subgroup Analyses
Subgroup analyses can provide interesting insights but are often underpowered, making results fragile. "Whenever we do subgroup analyses, these are essentially unplanned, so we certainly do not have enough power to detect differences," Liu stated. While these analyses can generate hypotheses, Liu cautions against drawing firm conclusions due to the lack of statistical power.
Balancing Trial Results with Real-World Evidence
Oncologists should integrate phase 3 trial results with existing data and clinical significance. Liu advises, "Whenever we see the results of phase 3 trials, whether they end up being positive or negative, we also have to think about the clinical significance of what we are testing as well."
Approaching Fragile, Statistically Significant Results
Liu suggests that the fragility of a clinical trial offers a different perspective compared to relying solely on statistical values. "I think the fragility of a clinical trial allows us to assess clinical trials in a different way...If we see a fragile, statistically significant result, it suggests that we may want to design another trial—potentially a larger one with a bigger sample size—to ensure that what we're seeing is not just a statistical fluke," Liu explained. She also noted that assessing fragility by flipping the most extreme patients can address concerns about outliers.
Importance of Long-Term Follow-Up Studies
Long-term follow-up studies are crucial for validating phase 3 trial results, especially when assessing overall survival. "I think there is certainly no substitute for having a long-term follow-up and giving the time to see how patients do," Liu emphasized. Despite the desire for quick answers, following up at 5 and 10 years can reveal whether early-stage results persist.
Strategies for Increasing Trial Robustness
Increasing sample size is paramount for robust clinical trials. Liu acknowledged the challenges in enrolling sufficient patients, especially for rare cancers or trials addressing difficult questions. She also highlighted the importance of carefully tracking and analyzing crossover patients, as well as using appropriate statistical tools. "Sometimes, the statistical tools we use aren't necessarily the best for analyzing the data," Liu noted, emphasizing the need for a robust statistical team.
Fragility as a Tool, Not a Substitute
Liu clarified that fragility analysis is a supplementary tool, not a replacement for P-values. "I think the biggest thing is that this fragility tool is not a substitute for the P value...However, this is another tool we can use in our toolbox," she stated. Fragility analysis can help visualize trial results and guide decisions on whether to add more patients or extend the trial.
