Clinical trial designs incorporating predictive biomarkers

Abstract

Development of oncologic therapies has traditionally been performed in a sequence of clinical trials intended to assess safety (phase I), preliminary efficacy (phase II), and improvement over the standard of care (phase III) in homogeneous (in terms of tumor type and disease stage) patient populations. As cancer has become increasingly understood on the molecular level, newer “targeted” drugs that inhibit specific cancer cell growth and survival mechanisms have increased the need for new clinical trial designs, wherein pertinent questions on the relationship between patient biomarkers and response to treatment can be answered. Herein, we review the clinical trial design literature from initial to more recently proposed designs for targeted agents or those treatments hypothesized to have enhanced effectiveness within patient subgroups (e.g., those with a certain biomarker value or who harbor a certain genetic tumor mutation). We also describe a number of real clinical trials where biomarker-based designs have been utilized, including a discussion of their respective advantages and challenges. As cancers become further categorized and/or reclassified according to individual patient and tumor features, we anticipate a continued need for novel trial designs to keep pace with the changing frontier of clinical cancer research.

Prospective Biomarker Study in Advanced RAS Wild-Type Colorectal Cancer: POSIBA Trial (GEMCAD 10-02)

“…We believe that our approach has several strengths compared with enriched randomized designs . First, we do not preassume that the proposed biomarkers really are drivers for targeted agent prediction and therefore allow for better evaluation of multiple biomarkers.…”

Statistical controversies in clinical research: basket trials, umbrella trials, and other master protocols: a review and examples

“…Specifically, when molecularly targeted treatments are studied in early phase trials, it must be decided whether to allow all eligible patients with a given disease to enroll, whether to restrict enrollment to those patients hypothesized to experience the greatest benefit from targeted therapy, or whether to do some combination of the two through mid-trial adaptive measures [32,33]. In the case of a standard 'all-comers' design, the targeted agent may only benefit a selected group of patients and thus a strong subgroup effect may instead appear as a weak overall effect, though randomization of markerpositive and marker-negative patients to targeted versus nontargeted treatment can play an important role of validating the treatment-by-marker interaction hypothesis.…”

Two‐stage enrichment clinical trial design with adjustment for misclassification in predictive biomarkers

“…To control the type I error rate and to estimate the power, we need to calculate the correlation matrix of (Z (1) ,…”

“…Generally speaking, marker‐based trial designs can be broadly classified as retrospective/prospective or sequential/nonsequential. Recently, Renfro et al gave a review and provided many references and several examples. Shih and Lin considered hypotheses and relative efficiency of stratified designs and precision medicine designs and showed that the stratified design is much more efficient than the so‐called marker‐based strategy designs.…”