Safety meta data analysis

Meta Analysis of Safety Pharmacology Data Predicting Compound Promiscuity 13.2.1... 

Cholesterol Treatment Trialists (CTT) Collaborators (2005) Efficacy and safety of cholesterol-lowering treatment prospective meta-analysis of data from 90 056 participants in 14 randomised trials of statins. Lancet 366 1267-1278... 

There are now common practices in the analysis of safety data, though they are not necessarily the best. These are discussed in the remainder of this chapter, which seeks to review statistical methods on a use-by-use basis and to provide a foundation for the selection of alternatives in specific situations. Some of the newer available methodologies (meta-analysis and Bayesian approaches) should be kept in mind, however. 

Gunnell, D., Saperia, J., Ashby, D. 2005, Selective serotonin reuptake inhibitors (SSRIs) and suicide in adults meta-analysis of dmg company data from placebo controlled, randomised controlled trials submitted to the MHRA s safety review, Br.Med.f, vol. 330, no. 7488, p. 385. 

The efficacy and safety data of cilostazol in placebo-controlled clinical trials have been repeatedly subjected to meta-analysis, with the same conclusion (1,2). Cilostazol is well tolerated headache, bowel complaints, and palpitation are the most common but mild adverse effects. 

Leflunomide has anti-inflammatory, immunosuppressive, and virustatic effects. Its efficacy has been demonstrated in patients with rheumatoid arthritis and psoriatic arthritis and other conditions in randomized, double-blind, placebo-controlled trials and other studies (8-32), and it was approved for treatment of adult rheumatoid arthritis in August 1998 (Table 1) (33). In three large phase III trials (US301, n = 482 MN301, n = 358 MN302, n = 999), leflunomide was as effective and well tolerated as methotrexate and sulfasalazine and superior to placebo (34). These data were confirmed by a meta-analysis (35,36). Leflunomide is therefore indicated for patients with rheumatoid arthritis who have failed first-line disease modifying anti-rheumatic drug therapy on the basis of efficacy, safety, and costs (36). It is effective as monotherapy and in combination with methotrexate or infliximab (6). 

Baigent C, Blackwell L, Emberson J, Holland LE, Reith C, Bhala N, Peto R, Barnes EH, Keech A, Simes J, Collins R (2010) Efficacy and safety of more intensive lowering of LDL cholesterol a meta-analysis of data from 170,000 participants in 26 randomised trials. Lancet 376 1670-1681... 

Berlin JA, Crowe BJ, Whalen E, Xia HA, Koro CE, Kuebler J. 2013. Meta-analysis of clinical trial safety data in a drug development program Answers to frequently asked questions. Clinical Trials 10(1) 20-31. 

The AE double dot plot is a type of graph designed to compare safety data between an experimental treatment and its control group with a quantitative risk measurement (Eigure 11.3). It has also been used in meta-analysis in randomized controlled trials and observational studies. In AE reporting, double dot plots are often used to present the frequency of key AEs along with quantitative risk measurements. Having both types of information side-by-side helps reviewers to identify elevated AEs. 

Meta-analysis is a statistical technique that compares the effectiveness or safety of two treatments by incorporating the findings from several independent studies (DerSimonian and Laird, 1986). Network meta-analysis (NMA), also sometimes referred to as multiple (or mixed) treatment comparisons (MTCs), is the extension of the traditional meta-analysis of two treatments to simultaneous incorporation of multiple treatments, where in most cases none of the studies compared all the treatments at one time. The goal of NMA is to address the comparative effectiveness or safety of interventions while accoimting for all sources of data (Hoaglin et al., 2011 Jansen et al., 2011). 

Regulatory Issues in Meta-Analysis of Safety Data ... 

Shorf of prospectively collecting fhe safety outcome, the outcome can be retrospectively obtained and adjudicated with a well-defined procedure. This approach was faken in fhe antidepressant meta-analysis example in this chapter. This approach requires detailed extensive patient-level data. It is also helpful to have fhe individual sfudy protocol to understand the information collected in fhe frials. Wifh fhis version of a retrospective outcome ascertainment, attention should be given to potential differential outcome ascertainment between the treatment arms. If the outcome was not actively solicited, there may be differences in reporting between the arms because of unrelated side effecfs of fhe freafmenf. For example, if a drug has more side effecfs, fhe patienf may be more likely to have encounters with the study investigators and report the safety outcome. 

There are important statistical considerations in meta-analyses for the evaluation of safety. In particular, statistical methods must be valid in the presence of sparse data. As discussed previously, safety outcomes may be infrequent. Some trials may not have any relevant events. We refer to these trials as zero-event trials. The statistical methods should provide estimates with good bias properties and with valid standard errors and confidence intervals in the presence of low event coimts and zero-event trials. In any meta-analysis, the overall estimator and associated standard errors and confidence intervals should be stratified by the trials. Simple pooling of data across the trials can result in misleading results because of Simspon s paradox. With stratification, the randomize comparisons within trials are maintained. 

---