Reply to Commentary by Cummings (2022): Surrogate endpoints extend beyond biomarkers.
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ABSTRACT:
SUBMITTER: Manyara AM
PROVIDER: S-EPMC9323349 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
Publications
Reply to Commentary by Cummings (2022): Surrogate endpoints extend beyond biomarkers.
Manyara Anthony Muchai AM Ciani Oriana O Taylor Rod S RS
Alzheimer's & dementia (New York, N. Y.) 20220726 1
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Project description:Kidney disease and its related comorbidities impose a large public health burden. Despite this, the number of clinical trials in nephrology lags behind many other fields. An important factor contributing to the relatively slow pace of nephrology trials is that existing clinical endpoints have significant limitations. "Hard" endpoints for chronic kidney disease, such as progression to end-stage renal disease, may not be reached for decades. Traditional biomarkers, such as serum creatinine in acute kidney injury, may lack sensitivity and predictive value. Finding new biomarkers to serve as surrogate endpoints is therefore an important priority in kidney disease research and may help to accelerate nephrology clinical trials. In this paper, I first review key concepts related to the selection of clinical trial endpoints and discuss statistical and regulatory considerations related to the evaluation of biomarkers as surrogate endpoints. This is followed by a discussion of the challenges and opportunities in developing novel biomarkers and surrogate endpoints in three major areas of nephrology research: acute kidney injury, chronic kidney disease, and autosomal dominant polycystic kidney disease.
| S-EPMC4646734 | biostudies-other
Project description:Recently a new definition of surrogate endpoint, the "principal surrogate," was proposed based on causal associations between treatment effects on the biomarker and on the clinical endpoint. Despite its appealing interpretation, limited research has been conducted to evaluate principal surrogates, and existing methods focus on risk models that consider a single biomarker. How to compare principal surrogate value of biomarkers or general risk models that consider multiple biomarkers remains an open research question. We propose to characterize a marker or risk model's principal surrogate value based on the distribution of risk difference between interventions. In addition, we propose a novel summary measure (the standardized total gain) that can be used to compare markers and to assess the incremental value of a new marker. We develop a semiparametric estimated-likelihood method to estimate the joint surrogate value of multiple biomarkers. This method accommodates two-phase sampling of biomarkers and is more widely applicable than existing nonparametric methods by incorporating continuous baseline covariates to predict the biomarker(s), and is more robust than existing parametric methods by leaving the error distribution of markers unspecified. The methodology is illustrated using a simulated example set and a real data set in the context of HIV vaccine trials.
| S-EPMC3163011 | biostudies-literature
Project description: Not available
| S-EPMC9323348 | biostudies-literature
Project description:Cell therapy for heart disease began clinically more than a decade ago. Since then, numerous trials have been performed, but the studies have been underpowered, focusing primarily on low-risk patients with a recent myocardial infarction. Many data have accumulated on surrogate endpoints such as ejection fraction, but few clinical conclusions can be drawn from such studies. We argue here that the time is right for targeting larger and/or higher-risk populations for whom there is some expectation of being able to influence mortality or rehospitalization.
| S-EPMC3902289 | biostudies-literature
Project description:Cardiac magnetic resonance offers multiple facets in the diagnosis, risk stratification, and management of patients with myocardial diseases. Particularly, its feature to precisely monitor disease activity lends itself to quantify response to novel therapeutics. This review critically appraises the value of cardiac magnetic resonance imaging biomarkers as surrogate endpoints for prospective clinical trials. The primary focus is to comprehensively outline the value of established cardiac magnetic resonance parameters in myocardial diseases. These include heart failure, cardiac amyloidosis, iron overload cardiomyopathy, hypertrophic cardiomyopathy, cardio-oncology, and inflammatory cardiomyopathies like myocarditis and sarcoidosis.
| S-EPMC11032206 | biostudies-literature
Project description:SummaryFrangakis and Rubin (2002, Biometrics 58, 21-29) proposed a new definition of a surrogate endpoint (a "principal" surrogate) based on causal effects. We introduce an estimand for evaluating a principal surrogate, the causal effect predictiveness (CEP) surface, which quantifies how well causal treatment effects on the biomarker predict causal treatment effects on the clinical endpoint. Although the CEP surface is not identifiable due to missing potential outcomes, it can be identified by incorporating a baseline covariate(s) that predicts the biomarker. Given case-cohort sampling of such a baseline predictor and the biomarker in a large blinded randomized clinical trial, we develop an estimated likelihood method for estimating the CEP surface. This estimation assesses the "surrogate value" of the biomarker for reliably predicting clinical treatment effects for the same or similar setting as the trial. A CEP surface plot provides a way to compare the surrogate value of multiple biomarkers. The approach is illustrated by the problem of assessing an immune response to a vaccine as a surrogate endpoint for infection.
| S-EPMC2726718 | biostudies-literature
Project description: Not available
| S-EPMC8530261 | biostudies-literature
Project description:In kidney transplant recipients, late graft failure is often multifactorial. In addition, primary endpoints in kidney transplantation studies seek to demonstrate the short-term efficacy and safety of clinical interventions. Although such endpoints might demonstrate short-term improvement in specific aspects of graft function or incidence of rejection, such findings do not automatically translate into meaningful long-term graft survival benefits. Combining many factors into a well-validated model is therefore more likely to predict long-term outcome and better reflect the complexity of late graft failure than using single endpoints. If conditional marketing authorization could be considered for therapies that aim to improve long-term outcomes following kidney transplantation, then the surrogate endpoint for graft failure in clinical trial settings needs clearer definition. This Consensus Report considers the potential benefits and drawbacks of several candidate surrogate endpoints (including estimated glomerular filtration rate, proteinuria, histological lesions, and donor-specific anti-human leukocyte antigen antibodies) and composite scoring systems. The content was created from information prepared by a working group within the European Society for Organ Transplantation (ESOT). The group submitted a Broad Scientific Advice request to the European Medicines Agency (EMA), June 2020: the request focused on clinical trial design and endpoints in kidney transplantation. Following discussion and refinement, the EMA made final recommendations to ESOT in December 2020 regarding the potential to use surrogate endpoints in clinical studies that aim to improving late graft failure.
| S-EPMC9163814 | biostudies-literature
Project description:BackgroundAlternative endpoints to overall survival (OS) are frequently used to assess treatment efficacy in randomized controlled trials (RCT). Their properties in terms of surrogate outcomes for OS need to be assessed. We evaluated the surrogate properties of progression-free survival (PFS), time-to-progression (TTP) and time-to-treatment failure (TTF) in advanced soft tissue sarcomas (STS).ResultsA total of 21 trials originally met the selection criteria and 14 RCTs (N = 2846) were included in the analysis. Individual-level associations were moderate (highest for 12-month PFS: Spearman's rho = 0.66; 95% CI [0.63; 0.68]). Trial-level associations were ranked as low for the three endpoints as per the IQWiG criterion.Materials and methodsWe performed a meta-analysis using individual-patient data (IPD). Phase II/III RCTs evaluating therapies for adults with advanced STS were eligible. We estimated the individual- and the trial-level associations between then candidate surrogates and OS. Statistical methods included weighted linear regression and the two-stage model introduced by Buyse and Burzykowski. The strength of the trial-level association was ranked according to the German Institute for Quality and Efficiency in Health Care (IQWiG) guidelines.ConclusionsOur results do not support strong surrogate properties of PFS, TTP and TTF for OS in advanced STS.
| S-EPMC6195375 | biostudies-literature
Project description:Recent advances in cardiovascular magnetic resonance (CMR) now allow the accurate and reproducible measurement of many aspects of cardiac and vascular structure and function, with prognostic data emerging for several key imaging biomarkers. These biomarkers are increasingly used in the evaluation of new drugs, devices and lifestyle modifications for the prevention and treatment of cardiovascular disease. This review outlines a conceptual framework for the application of imaging biomarkers to clinical trials, highlights several important CMR techniques which are in use in randomised studies, and reviews certain aspects of trial design, conduct and interpretation in relation to the use of CMR.
| S-EPMC3142342 | biostudies-other