Egbert van der Meulen, PhD, Senior Director of Biostatistics, Global Biometrics, Ferring Pharmaceuticals

With CDISC standards being implemented fully at Ferring Pharmaceuticals, the use of SAS and JMP Clinical is a natural next step for central statistical monitoring and beyond. We have built a SAS and JMP Clinical template for central statistical monitoring that is easy to adapt to the specific trial at hand. Its main focus is on poor, if not fraudulent, site performance using statistical inference, as well as overall trial performance (e.g., in terms of recruitment quality as opposed to recruitment speed and hitting the right target population). Site performance is assessed from various angles by looking at primary, key secondary and key safety endpoints, as these are most important. Site performance is also assessed by looking at visit dates, data entry times and digit preferences, as these may be most sensitive to data anomalies. The idea is to look for unnatural small variations, unnatural high or low incidences and unanticipated correlation structures. A demonstration of the template will be given.

Published on ‎03-24-2025 08:43 AM by Community Manager Community Manager | Updated on ‎03-27-2025 09:00 AM

Egbert van der Meulen, PhD, Senior Director of Biostatistics, Global Biometrics, Ferring Pharmaceuticals

With CDISC standards being implemented fully at Ferring Pharmaceuticals, the use of SAS and JMP Clinical is a natural next step for central statistical monitoring and beyond. We have built a SAS and JMP Clinical template for central statistical monitoring that is easy to adapt to the specific trial at hand. Its main focus is on poor, if not fraudulent, site performance using statistical inference, as well as overall trial performance (e.g., in terms of recruitment quality as opposed to recruitment speed and hitting the right target population). Site performance is assessed from various angles by looking at primary, key secondary and key safety endpoints, as these are most important. Site performance is also assessed by looking at visit dates, data entry times and digit preferences, as these may be most sensitive to data anomalies. The idea is to look for unnatural small variations, unnatural high or low incidences and unanticipated correlation structures. A demonstration of the template will be given.



Start:
Mon, Mar 14, 2016 05:00 AM EDT
End:
Thu, Mar 17, 2016 01:00 PM EDT
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