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We report a systematic review and meta-analysis of research using animal models of chemotherapy-induced peripheral neuropathy (CIPN). We systematically searched 5 online databases in September 2012 and updated the search in November 2015 using machine learning and text mining to reduce the screening for inclusion workload and improve accuracy. For each comparison, we calculated a standardised mean difference (SMD) effect size, and then combined effects in a random-effects meta-analysis. We assessed the impact of study design factors and reporting of measures to reduce risks of bias. We present power analyses for the most frequently reported behavioural tests; 337 publications were included. Most studies (84%) used male animals only. The most frequently reported outcome measure was evoked limb withdrawal in response to mechanical monofilaments. There was modest reporting of measures to reduce risks of bias. The number of animals required to obtain 80% power with a significance level of 0.05 varied substantially across behavioural tests. In this comprehensive summary of the use of animal models of CIPN, we have identified areas in which the value of preclinical CIPN studies might be increased. Using both sexes of animals in the modelling of CIPN, ensuring that outcome measures align with those most relevant in the clinic, and the animal’s pain contextualised ethology will likely improve external validity. Measures to reduce risk of bias should be employed to increase the internal validity of studies. Different outcome measures have different statistical power, and this can refine our approaches in the modelling of CIPN. [ABSTRACT FROM AUTHOR]

In biomedicine and many other fields, there are growing concerns around the reproducibility of research findings, with many researchers bein g unable to replicate their own or others' results. This raises important questions as to the validity and usefulness of much published research. In this review, we aim to engage researchers in the issue of research reproducibility and equip them with the necessary tools to increase the reproducibility of their research. We first high light the causes and potential impact of non-reproducible research and emphasise the benefits of working reproducibly for the researcher and broader research community. We address specific targets for improvement and steps that individual researchers can take to increase the reproducibility of their work. We next provide recommendations for improving the design and conduct of experiments, focusing on in vivo animal experiments. We describe common sources of poor internal validity of experiments and offer practical guidance for limiting these potential sources of bias at different experi mental stages, as well as discussing other important considerations during experimental design. We provide a list of key resources available to researchers to improve experimental design, conduct, and reporting. We then discuss the importance of open research practices such as study preregistration and the use of preprints and describe recommendations around data management and sharing. Our review emphasises the importance of reproducible work and aims to empower every individual researcher to contribute to the reproducibility of research in their field. [ABSTRACT FROM AUTHOR]

The reliability of experimental findings depends on the rigour of experimental design. Here we show limited reporting of measures to reduce the risk of bias in a random sample of life sciences publications, significantly lower reporting of randomisation in work published in journals of high impact, and very limited reporting of measures to reduce the risk of bias in publications from leading United Kingdom institutions. Ascertainment of differences between institutions might serve both as a measure of research quality and as a tool for institutional efforts to improve research quality. [ABSTRACT FROM AUTHOR]