Integrating biomarkers to predict renal and cardiovascular drug efficacy:PRE score applications from drug registration to personalized medicine

The prevalence of chronic kidney disease is increasing worldwide, and forecasts for 2030 indicate that the number of patients requiring renal replacement therapies will more than double. The increase in requirement of renal replacement therapies and the availability of only few proven effective therapies highlight the need to develop new drugs and intervention strategies. In the current drug development and registration process a single renal risk marker is selected and a drug is targeted towards that risk marker. However, there are multiple causes of renal disease that may not all be captured by a single risk marker alone, and drugs have multiple effects beyond the target risk marker (so-called off-target effects). There have been several examples of medications that show a beneficial effect on a risk marker (e.g. blood pressure), but did not improve clinically meaningful outcomes (e.g. myocardial infarction, stroke). Better prediction of drug effects on clinical outcomes may be achieved by risk scores that integrate the effect on multiple risk markers, instead of using single markers alone. In this thesis we determined whether an approach that integrates medication response in multiple risk markers (the so-called PRE score) can be implemented in drug development. We show that the PRE score does a consistently better job at predicting long-term drug effects, compared to using single risk markers alone. The PRE score could be used to provide an early assessment of a medicine’s clinical efficacy and therefore has promising implications for implementation in practice, such as in clinical drug development or regulatory decision-making

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There is discussion whether medicines can be authorized on the market based on evidence from surrogate endpoints. We assessed opinions of different stakeholders on this topic.We conducted an online questionnaire that targeted various stakeholder groups (regulatory agencies, pharmaceutical industry, academia, relevant public sector organisations) and medical specialties (cardiology or nephrology vs. other). Participants were enrolled through purposeful sampling. We inquired for conditions under which surrogate endpoints can be used, the validity of various cardio-renal biomarkers and new approaches for biomarker use.Participants agreed that surrogate endpoints can be used when the surrogate is scientifically valid (5-point Likert response format, mean score: 4.3, SD: 0.9) or when there is an unmet clinical need (mean score: 3.8, SD: 1.2). Industry participants agreed to a greater extent than regulators and academics. However, out of four proposed surrogates (blood pressure (BP), HbA1c, albuminuria, CRP) for cardiovascular outcomes or end-stage renal disease, only use of BP for cardiovascular outcomes was deemed moderately accurate (mean: 3.6, SD: 1.1). Specialists in cardiology or nephrology tended to be more positive about the use of surrogate endpoints.Stakeholders in drug development do not oppose to the use of surrogate endpoints in drug marketing authorization, but most surrogates are not considered valid. To solve this impasse, increased efforts are required to validate surrogate endpoints and to explore alternative ways to use them

Surrogate endpoints in clinical trials of chronic kidney disease progression:moving from single to multiple risk marker response scores

Purpose of review There is increased interest in developing surrogate endpoints for clinical trials of chronic kidney disease progression, as the established clinically meaningful endpoint end-stage renal disease requires large and lengthy trials to assess drug efficacy. We describe recent developments in the search for novel surrogate endpoints. Recent findings Declines in estimated glomerular filtration rate (eGFR) of 30% or 40% and albuminuria have been proposed as surrogates for end-stage renal disease. However, changes in eGFR or albuminuria may not be valid under all circumstances as drugs always have effects on multiple renal risk markers. Changes in each of these other 'off-target' risk markers can alter renal risk (either beneficially or adversely), and can thereby confound the relationship between surrogates that are based on single risk markers and renal outcome. Risk algorithms that integrate the short-term drug effects on multiple risk markers to predict drug effects on hard renal outcomes may therefore be more accurate. The validity of these risk algorithms is currently investigated. Summary Given that drugs affect multiple renal risk markers, risk scores that integrate these effects are a promising alternative to using eGFR decline or albuminuria. Proper validation is required before these risk scores can be implemented

The renal protective effect of angiotensin receptor blockers depends on intra-individual response variation in multiple risk markers

AimsAngiotensin receptor blockers (ARBs) are renoprotective and targeted to blood pressure. However, ARBs have multiple other (off-target) effects which may affect renal outcome. It is unknown whether on-target and off-target effects are congruent within individuals. If not, this variation in short term effects may have important implications for the prediction of individual long term renal outcomes. Our aim was to assess intra-individual variability in multiple parameters in response to ARBs in type 2 diabetes. MethodsChanges in systolic blood pressure (SBP), albuminuria, potassium, haemoglobin, cholesterol and uric acid after 6 months of losartan treatment were assessed in the RENAAL database. Improvement in predictive performance of renal outcomes (ESRD or doubling serum creatinine) for each individual using ARB-induced changes in all risk markers was assessed by the relative integrative discrimination index (RIDI). ResultsSBP response showed high variability (mean -5.7 mmHg, 5(th) to 95(th) percentile -36.5 to +24.0 mmHg) between individuals. Changes in off-target parameters also showed high variability between individuals. No congruency was observed between responses to losartan in multiple parameters within individuals. Using individual responses in all risk markers significantly improved renal risk prediction (RIDI 30.4%, P <0.01) compared with using only SBP changes. Results were successfully replicated in two independent trials with irbesartan, IDNT and IRMA-2. ConclusionsIn this post hoc analysis we showed that ARBs have multiple off-target effects which vary between and within individuals. Combining all ARB-induced responses beyond SBP provides a more accurate prediction of who will benefit from ARB therapy. Prospective trials are required to validate these findings

Characteristics of respondents.

<p>*Percentage compared to surveyed population.</p><p>Characteristics of respondents.</p