Application of structured statistical analyses to identify a biomarker predictive of enhanced tralokinumab efficacy in phase III clinical trials for severe, uncontrolled asthma

Abstract

Background Tralokinumab is an anti–interleukin (IL)-13 monoclonal antibody investigated for the treatment of severe, uncontrolled asthma in two Phase III clinical trials, STRATOS 1 and 2. The STRATOS 1 biomarker analysis plan was developed to identify biomarker(s) indicative of IL-13 activation likely to predict tralokinumab efficacy and define a population in which there was an enhanced treatment effect; this defined population was then tested in STRATOS 2. Methods The biomarkers considered were blood eosinophil counts, fractional exhaled nitric oxide (FeNO), serum dipeptidyl peptidase-4, serum periostin and total serum immunoglobulin E. Tralokinumab efficacy was measured as the reduction in annualised asthma exacerbation rate (AAER) compared with placebo (primary endpoint measure of STRATOS 1 and 2). The biomarker analysis plan included negative binomial and generalised additive models, and the Subgroup Identification based on Differential Effect Search (SIDES) algorithm, supported by robustness and sensitivity checks. Effects on the key secondary endpoints of STRATOS 1 and 2, which included changes from baseline in standard measures of asthma outcomes, were also investigated. Prior to the STRATOS 1 read-out, numerous simulations of the methodology were performed with hypothetical data. Results FeNO and periostin were identified as the only biomarkers potentially predictive of treatment effect, with cut-offs chosen by the SIDES algorithm of > 32.3 ppb and > 27.4 ng/ml, respectively. The FeNO > 32.3 ppb subgroup was associated with greater AAER reductions and improvements in key secondary endpoints compared with the periostin > 27.4 ng/ml subgroup. Upon further evaluation of AAER reductions at different FeNO cut-offs, ≥37 ppb was chosen as the best cut-off for predicting tralokinumab efficacy. Discussion A rigorous statistical approach incorporating multiple methods was used to investigate the predictive properties of five potential biomarkers and to identify a participant subgroup that demonstrated an enhanced tralokinumab treatment effect. Using STRATOS 1 data, our analyses identified FeNO at a cut-off of ≥37 ppb as the best assessed biomarker for predicting enhanced treatment effect to be tested in STRATOS 2. Our findings were inconclusive, which reflects the complexity of subgroup identification in the severe asthma population. Trial registration STRATOS 1 and 2 are registered on ClinicalTrials.gov ( NCT02161757 registered on June 12, 2014, and NCT02194699 registered on July 18, 2014). Electronic supplementary material The online version of this article (10.1186/s12890-019-0889-4) contains supplementary material, which is available to authorized users.

Type 2 immunity‐driven diseases: Towards a multidisciplinary approach

“… 123 , 124 , 125 Strategies to find suitable biomarkers (blood eosinophils, FeNO, serum periostin) to select potential responders were designed but did not succeed. 126 In contrast, phase 3 clinical trials recently demonstrated a significant improvement of AD under treatment with tralokinumab with or without topical steroids compared with topical steroids alone or placebo. 127 , 128 Promising results from a phase II study considering lebrikizumab in moderate‐to‐severe AD led to the recent onset of 2 parallel phase III clinical trials (ADVOCATE 1 and 2, NCT04146363, NCT04178967).…”

Pathological Roles and Clinical Usefulness of Periostin in Type 2 Inflammation and Pulmonary Fibrosis

“…Biomarker-based precision medicine will provide significant clinical benefits in the selection of treatment responders, risk prediction, prognosis, and treatment design strategies in allergic diseases (asthma, CRS and AD) or IPF management. Asthma is a common disease that affects approximately 339 million people worldwide, up to 10% of whom are severely affected [167,168]. Patients with severe asthma have a reduced quality of life, frequent emergency room visits and hospitalisations for acute exacerbations, and consume most asthma-related healthcare resources [169].…”

“…To date, five biologics have been approved for patients with asthma, but unfortunately, not all of them are effective for all patients with severe asthma, and biomarkers are needed to identify those who are most likely to benefit from biologics. In terms of biomarkers, these include serum total IgE for anti-IgE therapy (omalizumab) and blood eosinophil counts for anti-IL-5 Rα (benralizumab), anti-IL-5 therapy (mepolizumab, reslizumab), and anti-IL-4Rα therapy (dupilumab), but they are not completely stratified [167]. The fact that the effective drugs vary from patient to patient may be attributed to the fact that in asthma, the underlying mechanism of airway inflammation that causes the disease is different in each patient, resulting in a diversity of diseases.…”

“…Thus, the use of Xolair treatment may affect the serum/plasma levels of periostin, suggesting periostin may be a possible monitoring marker. Tralokinumab, an anti-IL-13 monoclonal antibody, is being developed to treat severe uncontrolled asthma [167]. The results of the phase III clinical trial (STRATOS 1) showed that FeNO in the breath and serum periostin (SIDES algorithm: FeNO cut-off SIDES algorithm: FeNO cut-off value > 32.3 ppb: periostin cut-off value > 27.4 ng/mL) were the only biomarkers that could predict treatment response [167].…”