A flexible threshold biomarker trial design for treatment intensification and de-intensification

In Oncology, prognostic biomarkers are commonly used to tailor treatment intensity to a patient's risk of disease progression. Several recent Phase III trials embed two studies within one protocol, comparing standard versus de-intensified therapy in good-prognosis patients and intensified versus standard therapy in poor-prognosis patients, using a single fixed biomarker threshold to classify patients into good and poor prognosis. Such designs are clinically intuitive but rely on a prespecified cut-point for which there can be substantial uncertainty as to the optimal value.

We propose a flexible threshold, biomarker-based design in which patients with intermediate biomarker values are randomized to three arms (control, de-intensified, intensified), while those at the extremes are randomized between control and de-intensified therapy (low biomarker) or intensified (high biomarker). The design jointly tests non-inferiority of de-intensified therapy in lower-risk patients and superiority of intensified therapy in higher-risk patients, while estimating the optimal biomarker thresholds. Family-wise Type I error is controlled through a two-stage bootstrap testing procedure.

In simulation settings where the alternative non-inferiority and superiority hypotheses hold over broad overlapping biomarker regions, the proposed flexible threshold biomarker design has greater power than a fixed threshold design while maintaining appropriate Type I error control. When the optimal decision rule matches the prespecified fixed cutoff, the two designs perform similarly. This reflects a bias-variance trade-off, in which fixed threshold designs perform well when the cutoff is correctly specified, whereas the flexible threshold biomarker design is more robust when the optimal threshold is uncertain or misspecified.

The proposed flexible threshold biomarker design offers a robust and efficient framework for trials seeking to tailor treatment intensity using a prognostic biomarker. The approach is broadly applicable to other diseases in which both escalation and de-escalation of therapy are of clinical interest and there is clinical equipoise among the three treatment options for patients with intermediate biomarker values.