Chemotherapy-induced peripheral neuropathy (CIPN) is a disabling pain condition resulting from chemotherapy for cancer. Severe acute CIPN may require chemotherapy dose reduction or cessation. There is no effective CIPN prevention strategy; treatment of established chronic CIPN is limited, and the prevalence of CIPN is not known. Here we used a systematic review to identify studies reporting the prevalence of CIPN. We searched Embase, Medline, CAB Abstracts, CINAHL, PubMed central, Cochrane Library, and Web of Knowledge for relevant references and used random-effects meta-regression to estimate overall prevalence. We assessed study quality using the CONSORT and STROBE guidelines, and we report findings according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidance. We provide a qualitative summary of factors reported to alter the risk of CIPN. We included 31 studies with data from 4179 patients in our analysis. CIPN prevalence was 68.1% (57.7-78.4) when measured in the first month after chemotherapy, 60.0% (36.4-81.6) at 3months and 30.0% (6.4-53.5) at 6months or more. Different chemotherapy drugs were associated with differences in CIPN prevalence, and there was some evidence of publication bias. Genetic risk factors were reported in 4 studies. Clinical risk factors, identified in 4 of 31 studies, included neuropathy at baseline, smoking, abnormal creatinine clearance, and specific sensory changes during chemotherapy. Although CIPN prevalence decreases with time, at 6months 30% of patients continue to suffer from CIPN. Routine CIPN surveillance during post-chemotherapy follow-up is needed. A number of genetic and clinical risk factors were identified that require further study.

Meta-analyses of data from human studies are invaluable resources in the life sciences and the methods to conduct these are well documented. Similarly there are a number of benefits in conducting meta-analyses on data from animal studies; they can be used to inform clinical trial design, or to try and explain discrepancies between preclinical and clinical trial results. However there are inherit differences between animal and human studies and so applying the same techniques for the meta-analysis of preclinical data is not straightforward. For example preclinical studies are frequently small and there is often substantial heterogeneity between studies. This may have an impact on both the method of calculating an effect size and the method of pooling data. Here we describe a practical guide for the meta-analysis of data from animal studies including methods used to explore sources of heterogeneity.

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.

The use of systematic review and meta-analysis of preclinical studies has become more common, including those of studies describing the modeling of cerebrovascular diseases. Empirical evidence suggests that too many preclinical experiments lack methodological rigor, and this leads to inflated treatment effects. The aim of this review is to describe the concepts of systematic review and meta-analysis and consider how these tools may be used to provide empirical evidence to spur the field to improve the rigor of the conduct and reporting of preclinical research akin to their use in improving the conduct and reporting of randomized controlled trials in clinical research. As with other research domains, systematic reviews are subject to bias. Therefore, we have also suggested guidance for their conduct, reporting, and critical appraisal.

Pain can significantly decrease the quality of life of patients with advanced cancer. Current treatment strategies often provide inadequate analgesia and unacceptable side effects. Animal models of bone cancer pain are used in the development of novel pharmacological approaches. Here we conducted a systematic review and meta-analysis of publications describing in vivo modelling of bone cancer pain in which behavioural, general health, macroscopic, histological, biochemical, or electrophysiological outcomes were reported and compared to appropriate controls. In all, 150 publications met our inclusion criteria, describing 38 different models of bone cancer pain. Reported methodological quality was low; only 31% of publications reported blinded assessment of outcome, and 11% reported random allocation to group. No publication reported a sample size calculation. Studies that reported measures to reduce bias reported smaller differences in behavioural outcomes between tumour-bearing and control animals, and studies that presented a statement regarding a conflict of interest reported larger differences in behavioural outcomes. Larger differences in behavioural outcomes were reported in female animals, when cancer cells were injected into either the tibia or femur, and when MatLyLu prostate or Lewis Lung cancer cells were used. Mechanical-evoked pain behaviours were most commonly reported; however, the largest difference was observed in spontaneous pain behaviours. In the spinal cord astrocyte activation and increased levels of Substance P receptor internalisation, c-Fos, dynorphin, tumor necrosis factor-α and interleukin-1β have been reported in bone cancer pain models, suggesting several potential therapeutic targets. However, the translational impact of animal models on clinical pain research could be enhanced by improving methodological quality.

Improved reporting standards, and adoption of experimental protocols that emphasize control of experimental bias, are likely to improve understanding and confidence in pain biology.

Rationale: Cardiac stem cells (CSC) therapy has been clinically introduced for cardiac repair after myocardial infarction (MI). To date, there has been no systematic overview and meta-analysis of studies using CSC therapy for MI.Objective: Here, we used meta-analysis to establish the overall effect of CSCs in preclinical studies and assessed translational differences between and within large and small animals in the CSC therapy field. In addition, we explored the effect of CSC type and other clinically relevant parameters on functional outcome to better predict and design future (pre)clinical studies using CSCs for MI. Methods and Results:A systematic search was performed, yielding 80 studies. We determined the overall effect of CSC therapy on left ventricular ejection fraction and performed meta-regression to investigate clinically relevant parameters. We also assessed the quality of included studies and possible bias. The overall effect observed in CSC-treated animals was 10.7% (95% confidence interval 9.4-12.1; P<0.001) improvement in ejection fraction compared with placebo controls. Interestingly, CSC therapy had a greater effect in small animals compared with large animals (P<0.001). Meta-regression indicated that cell type was a significant predictor for ejection fraction improvement in small animals. Minor publication bias was observed in small animal studies. Conclusions:

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.