Predictive biomarker validation in practice: lessons from real trials

Prognosis research strategy (PROGRESS) 4: stratified medicine research

In patients with a particular disease or health condition, stratified medicine seeks to identify those who will have the most clinical benefit or least harm from a specific treatment. In this article, the fourth in the PROGRESS series, the authors discuss why prognosis research should form a cornerstone of stratified medicine, especially in regard to the identification of factors that predict individual treatment response

Molecular imaging for personalized cancer care

Molecular imaging is rapidly gaining recognition as a tool with the capacity to improve every facet of cancer care. Molecular imaging in oncology can be defined as in vivo characterization and measurement of the key biomolecules and molecularly based events that are fundamental to the malignant state. This article outlines the basic principles of molecular imaging as applied in oncology with both established and emerging techniques. It provides examples of the advantages that current molecular imaging techniques offer for improving clinical cancer care as well as drug development. It also discusses the importance of molecular imaging for the emerging field of theranostics and offers a vision of how molecular imaging may one day be integrated with other diagnostic techniques to dramatically increase the efficiency and effectiveness of cancer care.

Clinical trial designs for testing biomarker-based personalized therapies

BACKGROUND

Advances in molecular therapeutics in the past decade have opened up new possibilities for treating cancer patients with personalized therapies, using biomarkers to determine which treatments are most likely to benefit them, but there are difficulties and unresolved issues in the development and validation of biomarker-based personalized therapies. We develop a new clinical trial design to address some of these issues. The goal is to capture the strengths of the frequentist and Bayesian approaches to address this problem in the recent literature and to circumvent their limitations.

METHODS

We use generalized likelihood ratio tests of the intersection null and enriched strategy null hypotheses to derive a novel clinical trial design for the problem of advancing promising biomarker-guided strategies toward eventual validation. We also investigate the usefulness of adaptive randomization (AR) and futility stopping proposed in the recent literature.

RESULTS

Simulation studies demonstrate the advantages of testing both the narrowly focused enriched strategy null hypothesis related to validating a proposed strategy and the intersection null hypothesis that can accommodate to a potentially successful strategy. AR and early termination of ineffective treatments offer increased probability of receiving the preferred treatment and better response rates for patients in the trial, at the expense of more complicated inference under small-to-moderate total sample sizes and some reduction in power.

LIMITATIONS

The binary response used in the development phase may not be a reliable indicator of treatment benefit on long-term clinical outcomes. In the proposed design, the biomarker-guided strategy (BGS) is not compared to 'standard of care', such as physician's choice that may be informed by patient characteristics. Therefore, a positive result does not imply superiority of the BGS to 'standard of care'. The proposed design and tests are valid asymptotically. Simulations are used to examine small-to-moderate sample properties.

CONCLUSION

Innovative clinical trial designs are needed to address the difficulties and issues in the development and validation of biomarker-based personalized therapies. The article shows the advantages of using likelihood inference and interim analysis to meet the challenges in the sample size needed and in the constantly evolving biomarker landscape and genomic and proteomic technologies.

Predictive biomarkers in colorectal cancer: usage, validation, and design in clinical trials

As cancer treatment development has shifted its attention to targeted therapies, it is becoming increasingly important to provide tools for selecting the right treatment for an individual patient to achieve optimal clinical benefit. Biomarkers, identified and studied in the process of understanding the nature of the disease at the molecular pathogenesis level, have been increasingly recognized as a critical aspect in more accurate diagnosis, prognosis assessment, and therapeutic targeting. Predictive biomarkers, which can aid treatment decisions, require extensive data for validation. In this article, we discuss the definition, clinical usages, and more extensively the clinical trial designs for the validation of predictive biomarkers. Predictive biomarker validation methods can be broadly grouped into retrospective and prospective designs. Retrospective validation utilizes data from previously conducted prospective randomized controlled trials. Prospective designs include enrichment designs, treatment-by-marker interaction designs, marker-based strategy designs, and adaptive designs. We discuss each design with examples and provide comparisons of the advantages and disadvantages among the different designs. We conclude that the combination of scientific, clinical, statistical, ethical, and practical considerations provides guidance for the choice of the clinical trial design for validation of each proposed predictive biomarker.

Clinical trial design in the age of molecular profiling

The accelerating science of molecular profiling has necessitated a rapid evolution in clinical trial design. Traditional clinical research begins with Phase I studies to characterize dose-limiting toxicities and defines maximally tolerated doses of drugs in small numbers of patients. Traditional Phase II studies test these drugs at the doses discovered during Phase I drug development in small numbers of patients evaluating efficacy and safety. Phase III studies test new therapies to demonstrate improved activity or improved tolerability compared with a standard of care regimen or a placebo. The rapid advances in the understanding of signal transduction, and the identification of new potential diagnostic and therapeutic targets, now require the design and implementation of molecular clinical trials that are very different than traditional Phase I, II, or III trials. The main differentiating factor is the use of a molecular end point to stratify a subset of patients to receive a specific treatment regimen. This chapter focuses on the issues surrounding (a) the definition of clinical end points and the assessment of tumor response; (b) clinical trial design models to define the targeted pathway; and (c) the need for appropriate biomarkers to monitor the response.

Design of clinical trials for biomarker research in oncology

The developmental pathway from discovery to clinical practice for biomarkers and biomarker-directed therapies is complex. While several issues need careful consideration, two critical issues that surround the validation of biomarkers are the choice of clinical trial design (which is based on the strength of the preliminary evidence and marker prevalence) and the biomarker assay related issues surrounding the marker assessment methods such as the reliability and reproducibility of the assay. This review focuses on trial designs for marker validation, both in the setting of early phase trials for initial validation, as well as in the context of larger definitive trials. Designs for biomarker validation are broadly classified as retrospective (i.e., using data from previously well-conducted, randomized, controlled trials) or prospective (enrichment, allcomers or adaptive). We believe that the systematic evaluation and implementation of these design strategies are essential to accelerate the clinical validation of biomarker-guided therapy, thereby taking us a step closer to the goal of personalized medicine.

Innovative Clinical Trial Designs: Toward a 21st-Century Health Care System

Whereas the 20th-century health care system sometimes seemed to be inhospitable to and unmoved by experimental research, its inefficiency and unaffordability have led to reforms that foreshadow a new health care system. We point out certain opportunities and transformational needs for innovations in study design offered by the 21st-century health care system, and describe some innovative clinical trial designs and novel design methods to address these needs and challenges.

Gene expression profiling for guiding adjuvant chemotherapy decisions in women with early breast cancer: an evidence-based and economic analysis

In February 2010, the Medical Advisory Secretariat (MAS) began work on evidence-based reviews of published literature surrounding three pharmacogenomic tests. This project came about when Cancer Care Ontario (CCO) asked MAS to provide evidence-based analyses on the effectiveness and cost-effectiveness of three oncology pharmacogenomic tests currently in use in Ontario.Evidence-based analyses have been prepared for each of these technologies. These have been completed in conjunction with internal and external stakeholders, including a Provincial Expert Panel on Pharmacogenomics (PEPP). Within the PEPP, subgroup committees were developed for each disease area. For each technology, an economic analysis was also completed by the Toronto Health Economics and Technology Assessment Collaborative (THETA) and is summarized within the reports.THE FOLLOWING REPORTS CAN BE PUBLICLY ACCESSED AT THE MAS WEBSITE AT: www.health.gov.on.ca/mas or at www.health.gov.on.ca/english/providers/program/mas/mas_about.htmlGENE EXPRESSION PROFILING FOR GUIDING ADJUVANT CHEMOTHERAPY DECISIONS IN WOMEN WITH EARLY BREAST CANCER: An Evidence-Based and Economic AnalysisEpidermal Growth Factor Receptor Mutation (EGFR) Testing for Prediction of Response to EGFR-Targeting Tyrosine Kinase Inhibitor (TKI) Drugs in Patients with Advanced Non-Small-Cell Lung Cancer: An Evidence-Based and Ecopnomic AnalysisK-RAS testing in Treatment Decisions for Advanced Colorectal Cancer: an Evidence-Based and Economic Analysis

OBJECTIVE

To review and synthesize the available evidence regarding the laboratory performance, prognostic value, and predictive value of Oncotype-DX for the target population.

CLINICAL NEED

CONDITION AND TARGET POPULATION The target population of this review is women with newly diagnosed early stage (stage I-IIIa) invasive breast cancer that is estrogen-receptor (ER) positive and/or progesterone-receptor (PR) positive. Much of this review, however, is relevant for women with early stage (I and II) invasive breast cancer that is specifically ER positive, lymph node (LN) negative and human epidermal growth factor receptor 2 (HER-2/neu) negative. This refined population represents an estimated incident population of 3,315 new breast cancers in Ontario (according to 2007 data). Currently it is estimated that only 15% of these women will develop a distant metastasis at 10 years; however, a far great proportion currently receive adjuvant chemotherapy, suggesting that more women are being treated with chemotherapy than can benefit. There is therefore a need to develop better prognostic and predictive tools to improve the selection of women that may benefit from adjuvant chemotherapy. TECHNOLOGY OF CONCERN: The Oncotype-DX Breast Cancer Assay (Genomic Health, Redwood City, CA) quantifies gene expression for 21 genes in breast cancer tissue by performing reverse transcription polymerase chain reaction (RT-PCR) on formalin-fixed paraffin-embedded (FFPE) tumour blocks that are obtained during initial surgery (lumpectomy, mastectomy, or core biopsy) of women with early breast cancer that is newly diagnosed. The panel of 21 genes include genes associated with tumour proliferation and invasion, as well as other genes related to HER-2/neu expression, ER expression, and progesterone receptor (PR) expression.

RESEARCH QUESTIONS

What is the laboratory performance of Oncotype-DX?How reliable is Oncotype-DX (i.e., how repeatable and reproducible is Oncotype-DX)?How often does Oncotype-DX fail to give a useable result?What is the prognostic value of Oncotype-DX?Is Oncotype-DX recurrence score associated with the risk of distant recurrence or death due to any cause in women with early breast cancer receiving tamoxifen?What is the predictive value of Oncotype-DX?Does Oncoytpe-DX recurrence score predict significant benefit in terms of improvements in 10-year distant recurrence or death due to any cause for women receiving tamoxifen plus chemotherapy in comparison to women receiving tamoxifen alone?How does Oncotype-DX compare to other known predictors of risk such as Adjuvant! Online?How does Oncotype-DX impact patient quality of life and clinical/patient decision-making?

SEARCH STRATEGY

A literature search was performed on March 19(th), 2010 using OVID MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, EMBASE, the Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Cochrane Library, and the International Agency for Health Technology Assessment (INAHTA) for studies published from January 1(st), 2006 to March 19(th), 2010. A starting search date of January 1(st), 2006 was because a comprehensive systematic review of Oncotype-DX was identified in preliminary literature searching. This systematic review, by Marchionni et al. (2008), included literature up to January 1(st), 2007. All studies identified in the review by Marchionni et al. as well as those identified in updated literature searching were used to form the evidentiary base of this review. The quality of the overall body of evidence was identified as high, moderate, low or very low according to GRADE methodology.

INCLUSION CRITERIA

Any observational trial, controlled clinical trial, randomized controlled trial (RCT), meta-analysis or systematic review that reported on the laboratory performance, prognostic value and/or predictive value of Oncotype-DX testing, or other outcome relevant to the Key Questions, specific to the target population was included.

EXCLUSION CRITERIA

Studies that did not report original data or original data analysis,Studies published in a language other than English,Studies reported only in abstract or as poster presentations (such publications were not sought nor included in this review since the MAS does not generally consider evidence that is not subject to peer review nor does the MAS consider evidence that lacks detailed description of methodology).

OUTCOMES OF INTEREST

Outcomes of interest varied depending on the Key Question. For the Key Questions of prognostic and predictive value (Key Questions #2 and #3), the prospectively defined primary outcome was risk of 10-year distant recurrence. The prospectively defined secondary outcome was 10-year death due to any cause (i.e., overall survival). All additional outcomes such as risk of locoregional recurrence or disease-free survival (DFS) were not prospectively determined for this review but were reported as presented in included trials; these outcomes are referenced as tertiary outcomes in this review. Outcomes for other Key Questions (i.e., Key Questions #1, #4 and #5) were not prospectively defined due to the variability in endpoints relevant for these questions.

SUMMARY OF FINDINGS

A total of 26 studies were included. Of these 26 studies, only five studies were relevant to the primary questions of this review (Key Questions #2 and #3). The following conclusions were drawn from the entire body of evidence: There is a lack of external validation to support the reliability of Oncotype-DX; however, the current available evidence derived from internal industry validation studies suggests that Oncotype-DX is reliable (i.e., Oncotype-DX is repeatable and reproducible).Current available evidence suggests a moderate failure rate of Oncotype-DX testing; however, the failure rate observed across clinical trials included in this review is likely inflated; the current Ontario experience suggests an acceptably lower rate of test failure.In women with newly diagnosed early breast cancer (stage I-II) that is estrogen-receptor positive and/or progesterone-receptor positive and lymph-node negative:There is low quality evidence that Oncotype-DX has prognostic value in women who are being treated with adjuvant tamoxifen or anastrozole (the latter for postmenopausal women only),There is very low quality evidence that Oncotype-DX can predict which women will benefit from adjuvant CMF/MF chemotherapy in women being treated with adjuvant tamoxifen.In postmenopausal women with newly diagnosed early breast cancer that is estrogen-receptor positive and/or progesterone-receptor positive and lymph-node positive:There is low quality evidence that Oncotype-DX has limited prognostic value in women who are being treated with adjuvant tamoxifen or anastrozole,There is very low quality evidence that Oncotype-DX has limited predictive value for predicting which women will benefit from adjuvant CAF chemotherapy in women who are being treated with adjuvant tamoxifen.There are methodological and statistical limitations that affect both the generalizability of the current available evidence, as well as the magnitude and statistical strength of the observed effect sizes; in particular:Of the major predictive trials, Oncotype-DX scores were only produced for a small subset of women (<40% of the original randomized population) potentially disabling the effects of treatment randomization and opening the possibility of selection bias;Data is not specific to HER-2/neu-negative women;There were limitations with multivariate statistical analyses.Additional trials of observational design may provide further validation of the prognostic and predictive value of Oncotype-DX; however, it is unlikely that prospective or randomized data will become available in the near future due to ethical, time and resource considerations.There is currently insufficient evidence investigating how Oncoytpe-DX compares to other known prognostic estimators of risk, such as Adjuvant! Online, and there is insufficient evidence investigating how Oncotype-DX would impact clinician/patient decision-making in a setting generalizable to Ontario.

The emerging role of insulin-like growth factor 1 receptor (IGF1r) in gastrointestinal stromal tumors (GISTs)

Recent years have seen a growing interest in insulin-like growth factor 1 receptor (IGF1R) in medical oncology. Interesting data have been reported also on IGF1r in gastrointestinal stromal tumors (GISTs) especially in children and in young adult patients whose disease does not harbour mutations on KIT and PDGFRA and are poorly responsive to conventional therapies. However, it is too early to reach conclusions on IGF1R as a novel therapeutic target in GIST because the receptor's biological role is still to be defined and the clinical significance in patients needs to be studied in larger studies. We update and comment the current literature on IGF1R in GISTs and discuss the future perspectives in this promising field.