Identification of SOD1 as the mutated protein in a significant subset of familial amyotrophic lateral sclerosis (FALS) cases has led to the generation of transgenic rodent models of autosomal dominant SOD1 FALS. Mice carrying 23 copies of the human SOD1(G93A) transgene are considered the standard model for FALS and ALS therapeutic studies. To date, there have been at least 50 publications describing therapeutic agents that extend the lifespan of this mouse. However, no therapeutic agent besides riluzole has shown corresponding clinical efficacy. We used computer modeling and statistical analysis of 5429 SOD1(G93A) mice from our efficacy studies to quantify the impact of several critical confounding biological variables that must be appreciated and should be controlled for when designing and interpreting efficacy studies. Having identified the most critical of these biological variables, we subsequently instituted parameters for optimal study design in the SOD1(G93A) mouse model. We retested several compounds reported in major animal studies (minocycline, creatine, celecoxib, sodium phenylbutyrate, ceftriaxone, WHI-P131, thalidomide, and riluzole) using this optimal study design and found no survival benefit in the SOD1(G93A) mouse for any compounds (including riluzole) administered by their previously reported routes and doses. The presence of these uncontrolled confounding variables in the screening system, and the failure of these several drugs to demonstrate efficacy in adequately designed and powered repeat studies, leads us to conclude that the majority of published effects are most likely measurements of noise in the distribution of survival means as opposed to actual drug effect. We recommend a minimum study design for this mouse model to best address and manage this inherent noise and to facilitate more significant and reproducible results among all laboratories employing the SOD1(G93A) mouse.

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Background One in five fibromyalgia sufferers use acupuncture treatment within two years of diagnosis. Objectives To examine the benefits and safety of acupuncture treatment for fibromyalgia. Search methods We searched CENTRAL, PubMed, EMBASE, CINAHL, National Research Register, HSR Project and Current Contents, as well as the Chinese databases VIP and Wangfang to January 2012 with no language restrictions. Selection criteria Randomised and quasi-randomised studies evaluating any type of invasive acupuncture for fibromyalgia diagnosed according to the American College of Rheumatology (ACR) criteria, and reporting any main outcome: pain, physical function, fatigue, sleep, total well-being, stiffness and adverse events. Data collection and analysis Two author pairs selected trials, extracted data and assessed risk of bias. Treatment effects were reported as standardised mean differences (SMD) and 95%confidence intervals (CI) for continuous outcomes using different measurement tools (pain, physical function, fatigue, sleep, total well-being and stiffness) and risk ratio (RR) and 95% CI for dichotomous outcomes (adverse events).We pooled data using the random-effects model. Main results Nine trials (395 participants) were included. All studies except one were at low risk of selection bias; five were at risk of selective reporting bias (favouring either treatment group); two were subject to attrition bias (favouring acupuncture); three were subject to performance bias (favouring acupuncture) and one to detection bias (favouring acupuncture). Three studies utilised electro-acupuncture (EA) with the remainder using manual acupuncture (MA) without electrical stimulation. All studies used ’formula acupuncture’ except for one, which used trigger points. Low quality evidence from one study (13 participants) showed EA improved symptoms with no adverse events at one month following treatment. Mean pain in the non-treatment control group was 70 points on a 100 point scale; EA reduced pain by a mean of 22 points (95% confidence interval (CI) 4 to 41), or 22% absolute improvement. Control group global well-being was 66.5 points on a 100 point scale; EA improved well-being by a mean of 15 points (95% CI 5 to 26 points). Control group stiffness was 4.8 points on a 0 to 10 point; EA reduced stiffness by a mean of 0.9 points (95% CI 0.1 to 2 points; absolute reduction 9%, 95% CI 4% to 16%). Fatigue was 4.5 points (10 point scale) without treatment; EA reduced fatigue by a mean of 1 point (95% CI 0.22 to 2 points), absolute reduction 11% (2% to 20%). There was no difference in sleep quality (MD 0.4 points, 95% CI −1 to 0.21 points, 10 point scale), and physical function was not reported. Moderate quality evidence from six studies (286 participants) indicated that acupuncture (EA or MA) was no better than sham acupuncture, except for less stiffness at one month. Subgroup analysis of two studies (104 participants) indicated benefits of EA. Mean pain was 70 points on 0 to 100 point scale with sham treatment; EA reduced pain ...

A transgenic animal model for anterior horn cell loss was established in 1994. This model is based on the insertion of a high copy number of disease-causing human Cu/Zn SOD mutations into the intact mouse genome. It serves to establish hypotheses for the pathogenesis of anterior horn cell death, but also to test potential pharmacological approaches to therapy in human ALS. Today, more than 100 -- published and unpublished -- compounds have been tested in this animal model, a large part of them being reported as successful. However, it proved to be difficult to translate these therapeutic successes in the animal model into human trials. Also, a number of disease-modifying strategies were difficult to reproduce, even by the same group. On the other hand, the step from mice to men means a huge investment for the sponsors of clinical trials and the scientific community. Therefore, establishment of standard methods for drug testing in ALS models is mandatory. In this workshop, clinical and preclinical researchers established in the field of ALS/MND met in Holland in March 2006 in order to establish guidelines for the community for drug testing in mouse models.

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