Itinai.com biomedical laboratory close up still scene close u e4996bf4 1113 41b3 8fdd 0d1e6c918068 3
Itinai.com biomedical laboratory close up still scene close u e4996bf4 1113 41b3 8fdd 0d1e6c918068 3

Addressing treatment switching in the ALTA-1L trial with g-methods: exploring the impact of model specification

Addressing Treatment Switching in the ALTA-1L Trial

Background

Treatment switching in clinical trials can complicate understanding the true effects of treatments. Standard analyses may not show the real impact when patients switch treatments. For instance, the ALTA-1L trial suggested that brigatinib might lead to better overall survival compared to crizotinib if no switching occurred. A special analysis showed a Hazard Ratio (HR) of 0.50 after accounting for switching, compared to an initial HR of 0.81.

Methods

We visualized the treatment switching scenario using a directed acyclic graph. We re-evaluated the ALTA-1L trial data with advanced statistical methods to compare two treatment strategies: always using brigatinib versus always using crizotinib. Various sensitivity analyses were conducted to ensure robustness in our findings.

Results

Using our analysis methods, we found that the cumulative HRs ranged from 0.38 to 0.73 and Risk Ratios (RRs) ranged from 0.52 to 0.79. The parametric g-formula showed cHRs between 0.61 and 0.72 and RRs between 0.71 and 0.79.

Conclusion

Our findings suggest that the initial estimate may have underestimated the benefit of brigatinib by 10-45 percentage points with IPCW and 10-20 percentage points with the parametric g-formula. This highlights the need for thorough sensitivity analyses, as results can vary significantly.

Trial Registration

Clinicaltrials.gov Identifier: NCT02737501

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