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Abstract While undisputedly important, and part of any systematic review (SR) by definition, evaluation of the risk of bias within the included studies is one of the most time-consuming parts of performing an SR. In this paper, we describe a case study comprising an extensive analysis of risk of bias (RoB) and reporting quality (RQ) assessment from a previously published review (CRD42021236047). It included both animal and human studies, and the included studies compared baseline diseased subjects with controls, assessed the effects of investigational treatments, or both. We compared RoB and RQ between the different types of included primary studies. We also assessed the “informative value” of each of the separate elements for meta-researchers, based on the notion that variation in reporting may be more interesting for the meta-researcher than consistently high/low or reported/non-reported scores. In general, reporting of experimental details was low. This resulted in frequent unclear risk-of-bias scores. We observed this both for animal and for human studies and both for disease-control comparisons and investigations of experimental treatments. Plots and explorative chi-square tests showed that reporting was slightly better for human studies of investigational treatments than for the other study types. With the evidence reported as is, risk-of-bias assessments for systematic reviews have low informative value other than repeatedly showing that reporting of experimental details needs to improve in all kinds of in vivo research. Particularly for reviews that do not directly inform treatment decisions, it could be efficient to perform a thorough but partial assessment of the quality of the included studies, either of a random subset of the included publications or of a subset of relatively informative elements, comprising, e.g. ethics evaluation, conflicts of interest statements, study limitations, baseline characteristics, and the unit of analysis. This publication suggests several potential procedures.

Abstract The nasal potential difference test (nPD) is an electrophysiological measurement which is altered in patients and animal models with cystic fibrosis (CF). Because protocols and outcomes vary substantially between laboratories, there are concerns over its validity and precision. We performed a systematic literature review (SR) of the nPD to answer the following review questions: A. Is the nasal potential difference similarly affected in CF patients and animal models?”, and B. “Is the nPD in human patients and animal models of CF similarly affected by various changes in the experimental set-up?”. The review protocol was preregistered on PROSPERO (CRD42021236047). We searched PubMed and Embase with comprehensive search strings. Two independent reviewers screened all references for inclusion and extracted all data. Included were studies about CF which described in vivo nPD measurements in separate CF and control groups. Risk of bias was assessed, and three meta-analyses were performed. We included 130 references describing nPD values for CF and control subjects, which confirmed substantial variation in the experimental design and nPD outcome between groups. The meta-analyses showed a clear difference in baseline nPD values between CF and control subjects, both in animals and in humans. However, baseline nPD values were, on average, lower in animal than in human studies. Reporting of experimental details was poor for both animal and human studies, and urgently needs to improve to ensure reproducibility of experiments within and between species.

Abstract Background Drug development is currently hampered by high attrition rates; many developed treatments fail during clinical testing. Part of the attrition may be due to low animal-to-human translational success rates; so-called “translational failure”. As far as we know, no systematic overview of published translational success rates exists. Systematic scoping review The following research question was examined: “What is the observed range of the animal-to-human translational success (and failure) rates within the currently available empirical evidence?”. We searched PubMed and Embase on 16 October 2017. We included reviews and all other types of “umbrella”-studies of meta-data quantitatively comparing the translational results of studies including at least two species with one being human. We supplemented our database searches with additional strategies. All abstracts and full-text papers were screened by two independent reviewers. Our scoping review comprises 121 references, with various units of measurement: compound or intervention (k = 104), study/experiment (k = 10), and symptom or event (k = 7). Diagnostic statistics corresponded with binary and continuous definitions of successful translation. Binary definitions comprise percentages below twofold error, percentages accurately predicted, and predictive values. Quantitative definitions comprise correlation/regression (r2) and meta-analyses (percentage overlap of 95% confidence intervals). Translational success rates ranged from 0 to 100%. Conclusion The wide range of translational success rates observed in our study might indicate that translational success is unpredictable; i.e. it might be unclear upfront if the results of primary animal studies will contribute to translational knowledge. However, the risk of bias of the included studies was high, and much of the included evidence is old, while newer models have become available. Therefore, the reliability of the cumulative evidence from current papers on this topic is insufficient. Further in-depth “umbrella”-studies of translational success rates are still warranted. These are needed to evaluate the probabilistic evidence for predictivity of animal studies for the human situation more reliably, and to determine which factors affect this process.