Can harmonisation of outcomes bridge the translation gap for pre-clinical research? A systematic review of outcomes measured in mouse models of type 2 diabetes

Clinical trials are undertaken to evaluate the effectiveness and safety of treatments in defined populations, and use pre-defined outcome measures. However, there is often marked variability between trials in the outcomes measured and reported which contributes to research waste through the inability to compare findings and synthesise evidence from multiple trials [1]. These issues can be addressed through the use of a core outcome set (COS), defined as “the minimum [set of outcomes] that should be measured and reported in all clinical trials of a specific condition” [2]. Indeed, in the case of rheumatoid arthritis, a core outcome set has increased the consistency of outcome reporting, and use of the COS has increased over time [3]. There are currently 337 COSs spanning 31 disease areas that have been developed for clinical research or practice or both [4]. However, despite the uptake of COSs in clinical trials, little is known about their relationship to the outcomes measured at other stages of the research pathway.

In pre-clinical research there is a recognised issue in the ability of animal models to predict effectiveness in humans, with large variability in translational success rates [5‐7]. Pre-clinical systematic reviews have been proposed as a way to improve understanding of pre-clinical effectiveness and how this can inform clinical trials [8‐10]. Yet, as in clinical trials, the ability to systematically review the literature is impacted by issues of methodological rigour and further compounded by heterogeneity in the outcomes measured and reported [1, 11]. Initiatives to improve the reporting of methodological details, for instance, the Animal Research: Reporting In Vivo Experiments (ARRIVE) guidelines [12], do not consider the choice of study outcome(s), that may impact not only on the ability to systematically compare and contrast the study results but also on the translatability of pre-clinical research to later phase trials. While the STAIR criteria for preclinical stroke research does address this issue, their requirements are rather broad [13]. We sought to explore the issue of outcome heterogeneity in pre-clinical research and the potential application of a COS using type 2 diabetes research as a case study. Type 2 diabetes is a global health concern; it has been estimated that 700 million people aged 20–79 will be affected by diabetes by 2045, the majority of these cases being type 2 diabetes [14‐16]. There are a number of established animal models for the study of type 2 diabetes [17, 18] with mouse models offering several advantages, including ease of induction of type 2 diabetes, a relatively short breeding span, and availability of physiological and invasive testing [19]. Mice are widely used in endocrine and metabolic research and, if all research areas are taken into account, represent the most widely used animal model in pre-clinical research [20]. We aimed to systematically review outcomes measured in pre-clinical research for type 2 diabetes using a mouse model, and to compare these to outcomes measured in clinical trials of glucose lowering interventions in type 2 diabetes [21]. Finally we examine the extent of the applicability of an existing COS [22] for type 2 diabetes in pre-clinical research.

Addressing methodological issues in pre-clinical research will help researchers take one step closer to achieving successful translation of safe and effective treatments [12, 27, 28]. However, the issue of outcome heterogeneity in pre-clinical studies, demonstrated here for type 2 diabetes, has been overlooked, impacting on the ability to synthesise evidence, contributing to research waste and widening the translational gap.

Initiatives to harmonise outcomes have focused on later phase effectiveness trials [2, 24] yet there is potential to apply COS across the research pathway. In the case of type 2 diabetes, over 70% of the existing COS was measured, to some extent, in publications using pre-clinical mouse models. Discordance was observed for outcomes relating to long term complications but these too were infrequently measured in clinical trials with “gangrene and amputation of the leg, foot or toe”, and “cerebrovascular disease” not measured at all and “deterioration of vision” and “myocardial infarction” each measured in a single clinical trial [21]. There were also limits of the pre-clinical search strategy which excluded studies that used specific mouse models of a long term diabetes complication. Mice display a different rate of development/aging to humans that cannot easily be converted between species [29, 30]; consequently, disease progression and time to the onset of long term complications may not be feasible to assess unless a specific animal model, pre-disposed to the development of such conditions, is used.

Whilst mouse models are the most frequently used pre-clinical animal model, there are limitations in the physiological assessments that can be undertaken. A review of large animal and non-human primate models may identify further overlap of outcomes with those assessed in phase 3/4 clinical trials due to the ability to perform particular physiological assessments in these larger animals.

Death is reported in clinical trials, either as a specific outcome or in the collection of serious adverse events, and is routinely recorded in clinical practice but in the pre-clinical setting it is widely accepted that “death as an endpoint to a procedure should be avoided as far as possible and replaced by earlier, humane endpoints” [31]. Instead, alternative surrogate outcomes for death may be more appropriate and alleviate terminal distress in mice whilst also capturing the core outcome [32, 33.]

In the present study we have applied surrogate markers of quality of life including “food and water intake”, measured in 39% of studies. Yet in these studies the reason for measurement was not specified and, in the case of some diabetes treatments, may indicate assessment of a side effect of treatment (weight gain) or polydipsia (a symptom of elevated blood glucose). Animal welfare encompasses an animal’s overall quality of life, taking into consideration its physical and psychological health along with the suitability of living conditions that give the animal opportunity to exhibit natural behaviours. Assessment of welfare is a critical component of research involving animals but this may go unreported in study publications. This under-reporting is further compounded by multiple methods of assessment and clarity is needed on how quality of life should be measured [34].

A COS has the potential to reduce the risk of outcome reporting bias, an issue that has been highlighted in both pre-clinical and clinical research [35, 36]. For a COS to contribute to reducing the risk of reporting bias there is an expectation that it is used in its entirety or that clear justification is made for why some outcomes have not been measured. It is important to recognise that it may not be practical, or indeed ethical, to measure the full set of core outcomes in every pre-clinical study and instead data on the core outcomes may be collected by the triangulation of data from multiple pre-clinical studies. Using glycaemic control as an example in the present study it is clear that not only are there different ways to define the outcome but, in the case of HbA1c, multiple methods of measurement. For pre-clinical studies to apply the COS there needs to be clear reporting on which of the outcomes will be measured, including reasons why outcomes are not assessed, together with consensus on “how” each of the core outcome should be measured and further work is warranted in this area.

The COS developed for type 2 diabetes shows a large overlap with outcomes already measured and reported in pre-clinical research using a mouse model of type 2 diabetes. Application of the COS, using agreed methods, in both pre-clinical research and clinical trials will mean that the same outcomes are measured and reported as a minimum, across the research pathway, facilitating evidence synthesis that has the potential to identify the most promising treatments.