Evidence from biomarkers and surrogate endpoints

Endpoint selection and evaluation in hematology studies

Observational studies and clinical trials in hematology aim to examine treatments for blood disorders. The outcomes being studied must address the goals of the study and provide meaningful information about treatment course, disease progression, describe patients' survival experience and quality of life. Endpoints are the specific measures of these outcomes, and much consideration should be given to their selection. In this review, we describe the outcomes and endpoints frequently used in studying hematologic diseases and provide general guidelines for their statistical analysis. The main focus is on clinical outcomes which are commonly used in establishing treatment safety and efficacy. We also briefly discuss the role surrogate and composite endpoints play in hematology studies. The importance of patient reported outcomes to comprehensive assessment of the treatment effectiveness is highlighted. Provided practical considerations for choosing primary and secondary endpoints may be helpful in designing hematology clinical trials.

Biomarkers as Biomedical Bioindicators: Approaches and Techniques for the Detection, Analysis, and Validation of Novel Biomarkers of Diseases

A biomarker is any measurable biological moiety that can be assessed and measured as a potential index of either normal or abnormal pathophysiology or pharmacological responses to some treatment regimen. Every tissue in the body has a distinct biomolecular make-up, which is known as its biomarkers, which possess particular features, viz., the levels or activities (the ability of a gene or protein to carry out a particular body function) of a gene, protein, or other biomolecules. A biomarker refers to some feature that can be objectively quantified by various biochemical samples and evaluates the exposure of an organism to normal or pathological procedures or their response to some drug interventions. An in-depth and comprehensive realization of the significance of these biomarkers becomes quite important for the efficient diagnosis of diseases and for providing the appropriate directions in case of multiple drug choices being presently available, which can benefit any patient. Presently, advancements in omics technologies have opened up new possibilities to obtain novel biomarkers of different types, employing genomic strategies, epigenetics, metabolomics, transcriptomics, lipid-based analysis, protein studies, etc. Particular biomarkers for specific diseases, their prognostic capabilities, and responses to therapeutic paradigms have been applied for screening of various normal healthy, as well as diseased, tissue or serum samples, and act as appreciable tools in pharmacology and therapeutics, etc. In this review, we have summarized various biomarker types, their classification, and monitoring and detection methods and strategies. Various analytical techniques and approaches of biomarkers have also been described along with various clinically applicable biomarker sensing techniques which have been developed in the recent past. A section has also been dedicated to the latest trends in the formulation and designing of nanotechnology-based biomarker sensing and detection developments in this field.

Clinical endpoints in oncology - a primer

Clinical endpoints are essential for assessing the safety and efficacy of new cancer therapies. They are used by oncologists to help guide clinical decision making. While overall survival (OS) has frequently been regarded as the "gold standard" primary clinical endpoint, it's utility is constrained by several disadvantages. The time-consuming nature of trials using OS has led to a recent push to explore surrogate clinical endpoints and their potential to serve as primary clinical endpoints in lieu of OS. Additionally, it is becoming evident that other endpoints add valuable information about quality of life and treatment failure as their use is becoming increasingly prevalent in oncology clinical trials. Without a doubt, the use of clinical endpoints will continue to expand and evolve as new cancer therapies are developed and novel treatments, including immunotherapy, draw interest. This review explores the roles of primary and surrogate clinical endpoints as well as the benefits and drawbacks of each specific endpoint. In addition, it directly compares the unique features of each suggesting some of the specific uses each one fulfills.

The insulin-like growth factor system in multiple myeloma: diagnostic and therapeutic potential

Multiple myeloma (MM) is a highly heterogeneous plasma cell malignancy. The MM cells reside in the bone marrow (BM), where reciprocal interactions with the BM niche foster MM cell survival, proliferation, and drug resistance. As in most cancers, the insulin-like growth factor (IGF) system has been demonstrated to play a key role in the pathogenesis of MM. The IGF system consists of IGF ligands, IGF receptors, IGF binding proteins (IGFBPs), and IGFBP proteases and contributes not only to the survival, proliferation, and homing of MM cells, but also MM-associated angiogenesis and osteolysis. Furthermore, increased IGF-I receptor (IGF-IR) expression on MM cells correlates with a poor prognosis in MM patients. Despite the prominent role of the IGF system in MM, strategies targeting the IGF-IR using blocking antibodies or small molecule inhibitors have failed to translate into the clinic. However, increasing preclinical evidence indicates that IGF-I is also involved in the development of drug resistance against current standard-of-care agents against MM, including proteasome inhibitors, immunomodulatory agents, and corticoids. IGF-IR targeting has been able to overcome or revert this drug resistance in animal models, enhancing the efficacy of standard-of-care agents. This finding has generated renewed interest in the therapeutic potential of IGF-I targeting in MM. The present review provides an update of the impact of the different IGF system components in MM and discusses the diagnostic and therapeutic potentials.

Cytokines: monitors of disease severity for the clinic

BACKGROUND

Cytokines communicate between the cells of the immune system and its targets to maintain homeostasis after injury or pathogenic events. They are involved in almost any pathological situation imaginable.

OBJECTIVE

To verify the importance of cytokines as biomarkers in current preclinical (aetiopathogenic, development of new therapies) and clinical studies (diagnosis, disease severity, prognosis and response to therapy).

METHOD/RESULTS

A Medline search with the query 'cytokine' AND 'biomarker' AND a variable for a variety of biomedical fields, followed by deeper-level searches, demonstrated the immense popularity of cytokines as biomarkers in almost any biomedical field.

CONCLUSION

As cytokines are not disease-specific they do not serve as single diagnostic biomarkers. The strength of the cytokines resides in monitoring disease severity, prognosis and response to treatment.

Biomarkers in Alzheimer's disease drug development

Developing new therapies for Alzheimer's disease (AD) is critically important to avoid the impending public health disaster imposed by this common disorder. Means must be found to prevent, delay the onset, or slow the progression of AD. These goals will be achieved by identifying disease-modifying therapies and testing them in clinical trials. Biomarkers play an increasingly important role in AD drug development. In preclinical testing, they assist in decisions to develop an agent. Biomarkers in phase I provide insights into toxic responses and drug metabolism and in Phase II proof-of-concept trials they facilitate go/no-go decisions and dose finding. Biomarkers can play a role in identifying presymptomatic patients or specific patient subgroups. They can provide evidence of target engagement before clinical changes can be expected. Brain imaging can serve as a primary outcome in Phase II trials and as a key secondary outcome in Phase III trials. Magnetic resonance imaging is currently best positioned for use in large multicenter clinical trials. Cerebrospinal fluid (CSF) measures of amyloid beta protein (Aβ), tau protein, and hyperphosphorylated tau (p-tau) protein are sensitive and specific to the diagnosis of AD and may serve as inclusion criteria and possibly as outcomes in clinical trials targeting relevant pathways. Plasma measures of Aβ are of limited diagnostic value but may provide important information as a measure of treatment response. A wide variety of measures of detectable products of cellular processes are being developed as possible biomarkers accessible in the cerebrospinal fluid and plasma or serum. Surrogate markers that can function as outcomes in pivotal trials and reliably predict clinical outcomes are needed to facilitate primary prevention trials of asymptomatic persons where clinical measures may be of limited value. Fit-for-purpose biomarkers are increasingly available to guide AD drug development decisions.

NMR-based metabolomic analysis of cerebrospinal fluid and serum in neurological diseases--a diagnostic tool?

We sought to evaluate the diagnostic accuracy of metabolomic biomarker profiles in neurological conditions (idiopathic intracranial hypertension (IIH), multiple sclerosis (MS) and cerebrovascular disease (CVD) compared to controls with either no neurological disease or mixed neurological diseases). Spectra of CSF (n = 87) and serum (n = 72) were acquired using (1)H NMR spectroscopy. Multivariate pattern recognition analysis was used to identify disease-specific metabolite biomarker profiles. The metabolite profiles were then used to predict the diagnosis of a second cohort of patients (n = 25). CSF metabolite profiles were able to predict diagnosis with a sensitivity and specificity of 80% for both IIH and MS. The CVD serum metabolite profile was 75% sensitive and specific. On analysing the second patient cohort, the established metabolite biomarker profiles generated from the first cohort showed moderate ability to segregate patients with IIH and MS (sensitivity:specificity of 63:75% and 67:75%, respectively). These findings suggest that NMR spectroscopic metabolic profiling of CSF and serum can identify differences between IIH, MS, CVD and mixed neurological diseases. Metabolomics may, therefore, have the potential to be developed into a clinically useful diagnostic tool. The identification of disease-unique metabolites may also impart information on disease pathology.

Challenges to demonstrating disease-modifying effects in Alzheimer's disease clinical trials

Progress in understanding the molecular biology of Alzheimer's disease (AD) has provided a number of plausible therapeutic targets for disease-modifying interventions. To advance these agents toward eventual US Food and Drug Administration (FDA) approval and incorporation into clinical practice by physicians and acceptance by patients and caregivers it is necessary to reach consensus on the meaning of disease modification and on what information is needed to provide a compelling factual basis for distinguishing disease modification from symptomatic treatment effects. Disease modification requires that the intervention have an impact of underlying pathology and pathophysiology of AD; disease course modification, illness modification or disability sparing are alternate terminologies that could be applied to symptomatic agents that do not affect the underlying neurobiology of AD. A variety of trial designs have been proposed to provide information supporting disease modification including change from baseline designs, survival type designs, staggered start designs, and staggered withdrawal designs. Each of these has shortcomings, and by themselves trial designs are not likely to provide sufficient information to conclusively prove that disease modification has occurred. Incorporation of a biomarker into clinical trials will support the claim for disease modification. Such a surrogate marker ideally should respond to the intervention, predict the clinical response to the intervention, and be compellingly related to the neurobiology of AD in the pathway affected by the intervention. A third axis of information supportive of disease modification is derived from observation of the effect of treatment in animal models of AD. The triad of a clinical outcome consistent with disease modification, support from a surrogate marker incorporated into the clinical trial, and basic science information indicating the effect of the therapy on a model of AD would combine to make a convincing case for disease modification.

Defining and labeling disease-modifying treatments for Alzheimer's disease

Alzheimer's disease (AD) might be treated with symptomatic, neuroprotective, or neurorestorative therapies. Neuroprotective and neurorestorative interventions are disease-modifying therapies. Disease modification can be defined as treatments or interventions that affect the underlying pathophysiology of the disease and have a beneficial outcome on the course of AD. In a clinical trial the criteria for affecting the underlying cause of the disease can be supported by demonstrating an effect on a biomarker such as medial temporal atrophy on magnetic resonance imaging (MRI) or diminished tau or phospho-tau levels in cerebrospinal fluid. The claim for a beneficial effect on the clinical course of AD is supported by a drug-placebo difference on the primary clinical outcomes of the clinical trial. A statistically significant correlation between the biomarker outcome and the clinical trial outcome would support the claim that these are based on the same underlying mechanism. Delayed start or staggered withdrawal designs might in themselves support a disease-modifying claim but are difficult to implement. A combination of clinical outcomes and biomarker measures is a more likely pathway to a disease-modifying claim. Labeling of disease-modifying agents might refer to slowing of disease progression, delay in reaching predefined disease milestones, or reduction in progression of a biomarker such as cerebral atrophy or ventricular enlargement on MRI. Prevention claims will depend heavily on biomarker outcomes.

The validity of biomarkers as surrogate endpoints in Alzheimer's disease by means of the Quantitative Surrogate Validation Level of Evidence Scheme (QSVLES)

OBJECTIVE

To evaluate the validity of biomarkers that are currently being proposed as potential surrogate endpoints in AD clinical trials with the aid of the "Quantitative Surrogate Validation Level of Evidence Schema" (QSVLES) proposed by Lassere et.al. (1).

PROCEDURE

A Pubmed literature search was conducted to identify AD biomarkers with SEP potential, and the QSVLES was applied to determine the extent of the SEP validity.

RESULTS

MRI, PET and MRS measures attained a total validity score of 4, NAA/Cre a total score of 5, and cerebral blood flow (SPECT), Abeta , Tau and APP a total score of 2. None of these biomarkers could fall into the rank of Levels 1 or 2, reserved for SEPs, according to the QSVLES criteria. This was mainly attributed to the lack of sufficient evidence that was derived from high ranking studies (RCT, prospective observational studies).

CONCLUSION

Though residing on SEPs as sole determinants of the benefit/risk ratio of AD medications seems to be pretty far, there could be certain cases where the use of SEPs may be beneficial, making efficient therapies available faster when there is a major public health interest involved. However, the potential risks of relying on invalid SEPs should not be underestimated and therefore the research on SEP validation and the development of specific validation guidance should be encouraged. The QSVLES, though not devoid of criticism, may be proposed as a starting point.

Thalamic metabolism and symptom onset in preclinical Huntington's disease

The neural basis for the transition from preclinical to symptomatic Huntington's disease (HD) is unknown. We used serial positron emission tomography (PET) imaging in preclinical HD gene carriers (p-HD) to assess the metabolic changes that occur during this period. Twelve p-HD subjects were followed longitudinally with [11C]-raclopride and [18F]-fluorodeoxyglucose PET imaging, with scans at baseline, 18 and 44 months. Progressive declines in striatal D2-receptor binding were correlated with concurrent changes in regional metabolism and in the activity of an HD-related metabolic network. We found that striatal D2 binding declined over time (P < 0.005). The activity of a reproducible HD-related metabolic covariance pattern increased between baseline and 18 months (P < 0.003) but declined at 44 months (P < 0.04). These network changes coincided with progressive declines in striatal and thalamic metabolic activity (P < 0.01). Striatal metabolism was abnormally low at all time points (P < 0.005). By contrast, thalamic metabolism was elevated at baseline (P < 0.01), but fell to subnormal levels in the p-HD subjects who developed symptoms. These findings were confirmed with an MRI-based atrophy correction for each individual PET scan. Increases in network expression and thalamic glucose metabolism may be compensatory for early neuronal losses in p-HD. Declines in these measures may herald the onset of symptoms in gene carriers.

Conceptual and methodological issues in the design of clinical trials of antipsychotics for the treatment of schizophrenia

Schizophrenia is one of the most severe and disabling psychiatric disorders. Antipsychotic drugs offer considerable benefits in controlling symptoms and preventing relapse. The strategy for the present review of clinical trials was to ask 'What are the features of schizophrenia and the existing treatments of the illness that have implications for future clinical trials'? Six key facts were identified.First, schizophrenia is genetically 'complex'. Trials may benefit from designs including genetically related illnesses, by focussing on cross-cutting aspects of the phenotype such as psychosis or cognitive dysfunction, and by collecting information on possible moderators and mediators of treatment response.Second, schizophrenia affects multiple neurotransmitter systems. Multiple signalling pathways may need to be considered, with different time courses of response. Outcome measures from clinical trials could be collected at more frequent intervals, particularly in the early phase of response.Third, the clinical features used to define the illness are a mix of symptoms and social-occupational dysfunction, yet treatment response is often defined only by changes in symptoms. Multiple measures of functioning need to be collected at baseline and at the endpoint of trials. Consensus definitions for response, remission, relapse, recovery and recurrence need to be developed.Fourth, schizophrenia is often highly disabling. Linking treatment response in clinical trials to measures of quality-adjusted life-years will allow comparison with other medical illnesses using common metrics.Fifth, the general health and care of individuals with schizophrenia is often poor. 'Complex' interventions, which include, but are not limited to, antipsychotic medications, need to be designed and tested for the problems facing these patients.Finally, large gaps exist between clinical trials, practice guidelines and patterns of practice. Trials need to be designed to investigate widely used approaches such as antipsychotic polypharmacy, where actual practice diverges from evidence-based guidelines.

Measuring disease modification in Alzheimer's disease

We appear to be on the brink of a new epoch of treatment for Alzheimer's disease. Compelling evidence suggests that Aβ42 secretion is the triggering event in the pathogenesis of Alzheimer's disease, and that tau aggregation may be an important secondary event linked to neurodegeneration. Prophylactic administration of anti-amyloid agents designed to prevent Aβ accumulation in persons with subclinical disease is likely to be more effective than therapeutic interventions in established Alzheimer's disease. Drug development programs in Alzheimer's disease focus primarily on agents with anti-amyloid disease-modifying properties, and many different pharmacologic approaches to reducing amyloid pathology and tauopathy are being studied. Classes of therapeutic modalities currently in advanced-stage clinical trial testing include forms of immunotherapy (active β -amyloid immunoconjugate and human intravenous immunoglobulin), a γ-secretase inhibitor, the selective Aβ42-lowering agent R-flurbiprofen, and the anti-aggregation agent tramiprosate. Non-traditional dementia therapies such as the HMG-CoA reductase inhibitors (statins), valproate, and lithium are now being assessed for clinical benefit as anti-amyloid disease-modifying treatments. Positive findings of efficacy and safety from clinical studies are necessary but not sufficient to demonstrate that a drug has disease-modifying properties. Definitive proof of disease-modification requires evidence from validated animal models of Alzheimer's disease; rigorously controlled clinical trials showing a significantly improved, stabilized, or slowed rate of decline in cognitive and global function compared to placebo; and prospectively obtained evidence from surrogate biomarkers that the treatment resulted in measurable biological changes associated with the underlying disease process.

Biomarkers in chronic adult hydrocephalus

Awareness of the importance of chronic adult hydrocephalus has been raised again with the recent emergence of epidemiological studies. It is estimated that between 5 and 10% of patients suffering from dementia might, in fact, have chronic hydrocephalus. Although, surgical diversion of the cerebrospinal fluid (CSF) represents the only known procedure able to treat the symptoms of this condition, the selection of surgical patients has always been problematic. In the last 40 years, we have become wiser in using appropriate diagnostic tests for the selection of these patients; however, the area of biological markers has so far been overlooked in this condition, in contrast to that for other neurodegenerative disorders and dementias. Biomarkers are biological substances that may be used to indicate either the onset or the presence, and the progression of a clinical condition, being closely linked to its pathophysiology. In such a setting they might assist in the more appropriate selection of patients for shunt surgery. In this article, we have reviewed research carried out in the last 25 years regarding the identification of serum and CSF biomarkers for chronic hydrocephalus, discussed the potential for each one, and finally discussed the limitations for use, as well as future directions and possibilities in this field. It is concluded that tumour-necrosis factor, tau protein, lactate, sulfatide and neurofilament triple protein are the most promising CSF markers for chronic hydrocephalus. At present however, none of these meet the criteria required to justify a change clinical practice. In the future, collaborative multi-centre projects will be needed to obtain more substantial data that overcome the problems that arise from small individual and uncoordinated studies.