MARCO TEÓRICO

Introduction

As discussed earlier (seeClinical efficacy and safety issues arising from European Medicines Agency, National Institute for Health and Care Excellence and Food and Drug Administration assessments of licensed regenerative medicines), it can be anticipated that almost all of the pivotal trials of regenerative medicines submitted for assessment for marketing authorisation will utilise a surrogate or intermediate outcome (or end point). A surrogate may be either a laboratory or a physiological measure of the patients’ experience that could be used to predict or provide an early measure of therapeutic effect. This section presents an overview of surrogate outcome measures and their use in clinical research and highlights issues pertinent to the development and appraisal of regenerative medicines.

Methods

To describe the use of surrogate end points as primary outcome measures in trials of new therapeutic agents a review of the most relevant and up-to-date literature was performed. The review was not systematic but was designed more as a pragmatic rapid review to assimilate current information and opinion on the use and suitability of surrogates in therapeutic trials. The review began with a search of key guidelines on the use of surrogate end points produced by the FDA, NICE DSU (Decision Support Unit) (University of Sheffield) and European Network for Health Technology Assessment (EUnetHTA) and survey results produced by the National Institute for Health Research (NIHR) HTA programme on the cost-effective use of surrogate outcomes. Citation and reference searches followed, which produced a library of relevant peer-reviewed publications and statistical reports on evidence for the use of surrogate end points in medicine. All relevant studies identified are presented inAppendix 4(seeTable 44).

Definition and examples of surrogate outcomes

Ideally, it is expected that the relative effectiveness of drugs and treatments will be based on final clinical end points,87_{that is, an outcome that the patient, the clinician and other stakeholders hope to avoid such}

as morbidity, impaired quality of life and/or death.88_{RCTs with large sample sizes and extended follow-up}

periods are often required to capture the statistical significance of a treatment’s or an intervention’s impact on a patient-relevant outcome.87_{However, the requirements of RCTs are often impractical when}

considered alongside pressures of time for products to go to market and in particular the urgent need for new treatments for patients with chronic but life-threatening diseases. The principal rationale for the use of a surrogate outcome is a more rapid assimilation of data without the need for large and lengthy trials in patients for whom mortality rates are high or treatment options are few.89

For example, OS is considered the gold standard to measure benefit in many clinical trials as it provides a precise and statistically and clinically meaningful end point. However, mature OS data are difficult to achieve because of the length of time needed and the number of deaths required for appropriate statistical analyses. Furthermore, OS as a measure of therapeutic success becomes less useful as the course and duration of diseases such as cancer move from being acute to more chronic; longitudinal effects of chronic disease such as comorbidities and additional ongoing treatments add further limitations to OS as an outcome.90,91

As a solution, there has recently been a steady move (by regulatory bodies) away from OS as a clinical end point measure and towards more short-term surrogate measures.

A generally accepted definition of a surrogate has followed that of Temple (p. 4):92

‘a laboratory measurement or physical sign used as a substitute for a clinically meaningful endpoint that measures directly how a patient feels, functions or survives’. However, chronic disease programmes and patient-reported outcomes have meant that a broader definition is now needed to better fit the HTA perspective.93,94_{Although the term}

‘intermediate end point’is sometimes used synonymously with surrogate end point,95_{it is often used to refer}

to more patient-relevant outcomes than those typically thought of as surrogates. However, for the purposes of this report, the term‘surrogate outcome’will be used in its broadest sense.

Examples of approved drugs based on the use of validated surrogate end points include antihypertensives and blood pressure in stroke research, cholesterol-lowering agents and serum cholesterol and treatments for glaucoma and intraocular pressure;96_{CD4 count for acquired immunodeficiency syndrome (AIDS)}

or death in human immunodeficiency virus (HIV) infection;97_{and bone density for bone fracture in}

osteoporosis.89_{However, occasionally such approvals have to be revised when long-term data become}

available. The drug gefitinib was approved in the USA in 2003 for patients with non-small-cell lung cancer based on tumour response rate, a surrogate end point. When, in 2005, the results from later studies showed no significant benefit in terms of survival, the FDA withdrew approval for its use in new patients. Therefore, although surrogate end points offer the potential of real benefit–in providing patients with faster access to treatments and saving triallists time and resources_–they may also have important drawbacks. Most notably (as the gefitinib example demonstrates), there may be uncertainty about the relationship between surrogate and real clinical end points and this may result in treatment efficacies being overestimated. A meta-epidemiological study that compared 84 trials that used surrogate outcomes with 101 trials that used patient-relevant outcomes showed that trials reporting surrogate end points had larger treatment effects: on average, trials using surrogate outcomes reported treatment effects that were 28–48% higher than those of trials using final patient-relevant outcomes and this result was consistent across sensitivity and secondary analyses.98_{The study characteristics of trials using surrogate outcomes and}

those of trials using patient-relevant outcomes were well balanced except for median sample size (371 vs. 741) and single-centre status (23% vs. 9%). Their risks of bias did not differ. This finding illustrates the importance of surrogate end points being appropriately validated and of quantifying the level of certainty of association of treatment effect between the surrogate and patient-relevant final outcomes.98

Validation

Surrogate outcomes can be unreliable without sufficient validation; for example, two major antiarrhythmic drugs, encanaide and flecanaide, reduced arrhythmia but caused a more than threefold increase in overall

mortality99_{and cardiac inotropes improved short-term cardiac haemodynamic function but can increase}

mortality.100_{Such examples may fuel uncertainty about the validity of surrogates. The results of a questionnaire}

study of 74 stakeholders in the drug development of cardio-renal disease indicated that, although the use of surrogates is not opposed, most are not considered valid.101_{Out of the four surrogate outcomes suggested as}

an end point for trials–blood pressure, glycated haemoglobin (HbA1c), albuminuria or C-reactive protein (CRP)–

only use of blood pressure was considered moderately accurate. Questionnaire responders from industry valued the accuracy of surrogates consistently higher than academic and regulatory responders.

General principles of validation

For a surrogate to be a reliable outcome measure it is generally accepted that the measure must be on the ‘causal pathway’from the intervention to the clinical outcome.89_{The possible reasons for treatment or trial}

failure associated with surrogate end points have been discussed by Fleming and DeMets102_{and more}

recently by Taylor and Elston:89

l the surrogate is not on the causal pathway of the disease process

l of several causal pathways of disease, the intervention affects only the pathway mediated by the surrogate

l the surrogate is not on the pathway of the intervention’s effect or is insensitive to its effect

l the intervention has mechanisms of action independent of the disease process (and so its effect will not be captured by a surrogate outcome).

A number of guidelines have been proposed for assessing the validity of surrogate end points87,89,100,102_and

further work has also been published on scoring schemas for the value of surrogates.103

As a result of a review, Elston and Taylor88_{recommended that, before a surrogate outcome is accepted, a}

systematic review of the evidence for the validation of the surrogate/final outcome relationship should be conducted. Furthermore, the evidence on surrogate validation should be presented according to an explicit hierarchy, such as:

l level 1_–evidence demonstrating that treatment effects on the surrogate correspond to effects on the patient-related outcome (from clinical trials)

l level 2_–evidence demonstrating a consistent association between surrogate outcome and final patient-related outcome (from epidemiological/observational studies)

l level 3–evidence of biological plausibility of the relationship between surrogate and final patient- related outcome (from pathophysiologic studies and/or understanding of the disease process). Methods for the statistical validation of surrogates as outcome measures have also developed.99,104,105

Validation of specific surrogate outcomes

Surrogate outcomes in oncology

A recently published systematic review of trial-level meta-analyses of randomised trials quantifying the association between surrogate and final outcomes in cancer included 36 studies.106_{The review found that}

all validation studies used only a subset of the available trials and that the evidence supporting the use of surrogate outcomes in cancer trials is limited. The results are summarised inTable 3.

The results of the review indicate that little research effort has been invested in validating tumour response as a surrogate for clinical outcomes; the available evidence suggests that better tumour-level surrogate outcomes are required. The clinical outcome surrogates (intermediate outcomes) for OS, particularly PFS, have been better studied and appear to perform better. However, the range of results for PFS indicates that the validation of a surrogate in one disease and setting cannot be assumed to hold for other diseases and settings.

Progression-free survival or time to progression

The suitability of PFS or TTP as an appropriate surrogate measure in advanced or metastatic cancer research has been reviewed.94_{The review identified 19 papers covering eight different tumour types. Data}

sets included the relationship between the measures within aggregated trial data and the effect on individuals within IPD. The studies employed a variety of different data sets and statistical techniques, but the lack of standardisation across the studies made it very difficult for the review to identify any consistent relationship between the surrogate and the overall outcome measure.

In a recent review of current statistical approaches to surrogate end point validation based on meta- analysis in various advanced-tumour settings,107_{the suitability of PFS and TTP was assessed using three}

validation frameworks: Elston and Taylor’s framework, the German Institute of Quality and Efficiency in Health Care’s (IQWiG) framework and the Biomarker Surrogacy Evaluation Schema (BSES3). The findings suggested that the strength of the association between the two surrogates and OS was generally low. The level of evidence (observation level vs. treatment level) available varied considerably by cancer type and evaluation tools and was not always consistent, even within one specific cancer type. This study emphasises the challenges of surrogate end point validation and the importance of building consensus on the development of evaluation frameworks.

A recently published study analysed the degree of difference in treatment effects between surrogate end points and OS in RCTs of pharmacological therapies in advanced colorectal cancer.108_{Univariate and}

multivariate random-effects meta-analyses were used to estimate pooled summary treatment effects. The ratio of hazard ratios (HRs) to odds ratios (ORs) and differences in medians were used to quantify the degree of difference in treatment effects between the surrogate end points and OS. The study found a larger treatment effect for the surrogates than for OS. The authors suggested that previous surrogacy relationships observed between PFS/TTP and OS in selected settings may not apply across other classes or lines of therapy.108

Minimal residual disease

Minimal residual disease (MRD) is a surrogate outcome that has been accepted by a regulatory agency, the FDA. With current intensive treatments, many acute leukaemia patients will enter morphological complete remission (CR). This is typically defined as patients having<5% blasts (abnormal, immature cells) in the

bone marrow. If no further therapy is given after entering CR, most patients will relapse, demonstrating that microscopy-based evaluations are incapable of detecting all tumour cells. However, diagnostic techniques can now quantify and monitor MRD, which is invisible to the trained eye, in patients in CR. The ability to quantitatively measure the amount of MRD at various times after achieving CR can guide subsequent treatment.109_{Studies have shown that MRD before stem cell transplantation is a strong} TABLE 3 Summary of the results from a systematic review of trial-level meta-analyses of randomised trials quantifying the association between surrogate and final outcomes in cancer

Surrogate and clinical outcome

Number of studies

Range of correlation coefficients

Level of correlation (low, medium or high) Pathological complete response for event-free survival 2 0.17–0.28 Low

Pathological complete response for OS 2 0.30–0.49 Low

Response rate for OS 11 0.32–0.68 Low to medium

Locoregional control for OS 2 0.52–0.84 Medium to high

Event-free survival for OS 3 0.79–0.86 High

Disease-free survival for OS 7 0.62–0.98 High

PFS for OS 30 0.29–0.99 Low to high

independent predictor of subsequent relapse in children with high-risk or very high-risk acute lymphocytic (lymphoblastic) leukaemia (ALL).110,111

Threshold levels for MRD may vary depending on the population being considered. For children receiving first-line chemotherapy for ALL, leukaemia cell concentrations of 0.01% (1 in 10,000) have been described as optimal for identifying higher-risk patients for potential intervention.112_{For children with ALL who have}

had a previous relapse, the best MRD threshold for predicting disease-free survival (DFS) at 10 years has been reported as 0.001%.113_{The FDA has concluded that the evidence base to indicate that early MRD}

status is the strongest predictor of long-term event-free survival (EFS) in ALL is unequivocal.114_{It added}

that the magnitude of the importance of its critical role in risk stratification for treatment decisions has furthered the consideration of its potential as a surrogate end point for clinical trials of investigational therapeutic interventions. However, results from the UKALL R3 trial, which compared different

chemotherapy treatments for children in first relapse, showed that the longer-term outcome of having MRD-negative status in patients who have already had one relapse may well vary according tohowthe status was achieved.115_{There is, therefore, some uncertainty in how MRD negativity correlates to long-term}

outcomes in relapsed populations.

Current issues for health technology assessment and cost-effectiveness models

Regulatory bodies find it acceptable for trials to be shorter, to have fewer participants and to use surrogate outcomes when populations are rare and there is a high unmet clinical need. However, a commitment to ongoing research is mandatory to receive longer-term approval; if research is not continued or if it is continued but efforts to validate the surrogate fail, the approval will be withdrawn.96_{From a regulatory}

and HTA perspective, the absence of data on clinical end points might be acceptable when a clinical end point is difficult or impossible to study. The EUnetHTA summarised its findings into eight recommendations for end points used in the relative effectiveness assessment (REA) of pharmaceuticals:87

1. Efficacy assessments of pharmaceuticals should be based whenever possible on final patient-relevant clinical end points (e.g. morbidity, overall mortality).

2. Biomarkers and intermediate end points will be considered as surrogate end points if they can reliably substitute for a clinical end point and predict its clinical benefit.

3. Surrogate end points should be adequately validated and this must have been demonstrated based on biological plausibility and empirical evidence.

4. Validation of a surrogate is normally undertaken in a specific population and for a specific drug intervention. Demonstration of surrogate validation both within and across drug classes should be thoroughly justified.

5. The availability of a sufficiently large safety database is particularly important and evidence on safety outcomes should always be reported.

6. The absence of data on clinical end points might be acceptable when a clinical end point is difficult or impossible to study (very rare or delayed) or the target population is too small to obtain meaningful results on relevant clinical end points even after very long follow-up (very slowly progressive and/or rare diseases). However, these exceptions need to be carefully argued and agreed in advance.

7. Reassessment requirements for further data should be clearly defined when an assessment has been previously made based on surrogate end points.

8. Further methodological research on the use of surrogate outcomes is needed to inform future REA approaches for the handling of surrogates.

Similarly, Elston and Taylor88_{recommended that a HTA or cost-effectiveness model based on a surrogate}

outcome should be undertaken only when it is not possible to base the assessment of clinical effectiveness and cost-effectiveness on final patient-related outcomes [i.e. mortality, important clinical events and health-related quality of life (HRQoL)]. In such cases, a systematic review of the evidence for the validation of the surrogate/final outcome relationship should be performed and the evidence on surrogate validation should be presented according to an explicit hierarchy.

Given the difficulty in validating surrogate outcomes, which conflicts with the need to use such outcomes in clinical research, Ciani and Taylor93_{commented on the requirement to recognise the need for pragmatic}

high-level evidence, preferably from meta-analyses and regression modelling using both surrogate and final outcomes for HTA. This is demonstrated by a study conducted to illustrate the potential to reduce uncertainty around the clinical outcome by estimating it from a multivariate meta-analysis.116_Bayesian

multivariate meta-analysis was used to synthesise data on correlated outcomes in rheumatoid arthritis. Estimates from the Health Assessment Questionnaire (HAQ) were mapped onto the HRQoL measure, the EuroQol-5 Dimensions (EQ-5D) questionnaire, and the effect was compared with mapping the HAQ obtained from the univariate approach. The results showed that use of multivariate meta-analysis can lead to reduced uncertainty around the effectiveness parameter. By allowing all of the relevant data to be incorporated in estimating clinical effectiveness outcomes, including data from surrogate outcomes, multivariate meta-analysis can improve the estimation of health utilities through mapping methods. In their review of HTA and cost-effectiveness models, Taylor and Elston89_{found that only one of the four}

reports undertook a systematic review to specifically seek the evidence base for the association between surrogate and final outcomes. Furthermore, this was the only report to provide level 1 surrogate–final outcome validation evidence (i.e. RCT data) showing a strong association between the change in surrogate outcome (biopsy-confirmed acute rejection) and the change in final outcome (graft survival) at an

individual patient level. The outcome of the review was to make recommendations for the evaluation of surrogate end points in a HTA (these are listedin Appendix 4,Table 44).

Taylor and Elston_’s89_{HTA publication has been key to providing insight into the use of surrogates within}

the HTA and cost-effectiveness models framework and presents the range of approaches. This includes HR calculation, transition probabilities within a model of natural history and predictive risk equations, used by researchers to quantify the relationship between surrogate and clinical end points.88

In addition to calls for the validation of commonly used surrogate outcomes, there is a need for novel,