The sumatriptan/naratriptan aggregated patient (SNAP) database: aggregation, validation and application.

Abstract

Pooled data from multiple clinical trials can provide information for medical decision-making that typically cannot be derived from a single clinical trial. By increasing the sample size beyond that achievable in a single clinical trial, pooling individual-patient data from multiple trials provides additional statistical power to detect possible effects of study medication, confers the ability to detect rare outcomes, and facilitates evaluation of effects among subsets of patients. Data from pharmaceutical company-sponsored clinical trials lend themselves to data-pooling, meta-analysis, and data mining initiatives. Pharmaceutical company-sponsored clinical trials are arguably among the most rigorously designed and conducted of studies involving human subjects as a result of multidisciplinary collaboration involving clinical, academic and/or governmental investigators as well as the input and review of medical institutional bodies and regulatory authorities. This paper describes the aggregation, validation and initial analysis of data from the sumatriptan/naratriptan aggregate patient (SNAP) database, which to date comprises pooled individual-patient data from 128 clinical trials conducted from 1987 to 1998 with the migraine medications sumatriptan and naratriptan. With an extremely large sample size (>28000 migraineurs, >140000 treated migraine attacks), the SNAP database allows exploration of questions about migraine and the efficacy and safety of migraine medications that cannot be answered in single clinical trials enrolling smaller numbers of patients. Besides providing the adequate sample size to address specific questions, the SNAP database allows for subgroup analyses that are not possible in individual trial analyses due to small sample size. The SNAP database exemplifies how the wealth of data from pharmaceutical company-sponsored clinical trials can be re-used to continue to provide benefit.