Safety of tapentadol compared with other opioids in chronic pain treatment: network meta-analysis of randomized controlled and withdrawal trials.

OBJECTIVE: To assess the relative safety of oral tapentadol PR and other opioid analgesics for moderate or severe chronic pain in adults, we conducted a systematic review and network meta-analysis (NMA). METHODS: A systematic review was conducted to identify randomized controlled trials (RCTs) and randomized withdrawal trials of tapentadol with other WHO stage II and III opioid analgesics in patients with moderate or severe chronic pain. Searches were conducted in MEDLINE, EMBASE, PubMed, Cochrane databases and trial registries. Feasibility assessment evaluated the trials' suitability for NMA. Outcomes assessed were overall AEs, overall serious adverse events, constipation, nausea, dizziness, somnolence, headache, and discontinuation due to AEs. Randomized withdrawal trials were analyzed separately to other RCTs. RESULTS: Searches conducted in April 2019 identified 16,604 records. Following screening and feasibility assessment, 29 RCTs and 19 randomized withdrawal trials were identified and included in the NMA. Consistent with existing research, evidence from RCTs suggested that tapentadol is associated with relatively lower odds of adverse events occurring than most active comparators. The withdrawal trial data were less clear, with higher uncertainty around the results, and results that appear to contradict the RCT evidence. There are a number of trial design factors that may be affecting these results. CONCLUSIONS: RCT evidence suggests that tapentadol can be a useful treatment option for patients suffering from chronic pain and in need of an opioid analgesic. Opioids should be prescribed by a qualified physician only after other analgesics have been considered, taking side effects and misuse risk into account.

Issues in association mapping with high-density SNP data and diverse family structures.

Genetic association studies have the potential to identify causative genetic variants with small effects in complex diseases, but it is not at all clear which study designs best balance power with sample size, especially when taking into account the difficulty of obtaining a sample of the necessary structure. The 14 contributions from the Genetic Analysis Workshop 15 group 3 used data sets with rheumatoid arthritis as primary phenotype from problem 2 (real data) and Problem 3 (simulated data) to investigate design and analysis problems that arise in candidate-gene, candidate-region, and genome-wide association studies. We identified three major themes that were addressed by multiple groups: (1) comparing family-based and case-control study designs with each other and with hybrid designs incorporating both related and unrelated individuals; (2) exploring and comparing techniques of combining information from multiple, correlated single-nucleotide polymorphisms; and (3) comparing analyses that select the model(s) of best fit with the ultimate aim of detecting the joint effects of several unlinked single-nucleotide polymorphisms. These contributions achieved some success in improving upon existing methods. For example, tests using related cases and unrelated controls can achieve higher power than the tests using unrelated cases and unrelated controls. Aside from these successes, the group 3 contributions highlight some interesting areas for future research.