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| Adaptiv Kasusserie× | Studie af adaptiv diagnostisk nøjagtighed× | |
|---|---|---|
| Fagområde | Epidemiologi | Epidemiologi |
| Familie | Process / pipeline | Process / pipeline |
| Oprindelsesår≠ | Late 20th–early 21st century | 2000s–2010s (adaptive designs codified for diagnostics ~2010s) |
| Ophavsperson≠ | Evolved from classical case series methodology combined with adaptive design principles (Chow & Chang, 2008; FDA adaptive design guidance) | Adaptation of STARD framework (Bossuyt et al.) combined with adaptive design principles (Jennison & Turnbull; FDA guidance) |
| Type≠ | Observational study with adaptive monitoring | Adaptive observational/experimental study design |
| Oprindelig kilde≠ | Chow, S.-C., & Chang, M. (2008). Adaptive Design Methods in Clinical Trials. Chapman & Hall/CRC. ISBN: 978-1584887775 | Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L., ... & Cohen, J. F. (2015). STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ, 351, h5527. DOI ↗ |
| Aliasser≠ | adaptive case-series design, sequential adaptive case series, adaptive observational case series | adaptive DTA study, adaptive diagnostic test evaluation, adaptive test accuracy trial, adaptive STARD study |
| Relaterede≠ | 5 | 6 |
| Resumé≠ | An adaptive case series is an observational study design that documents a consecutive group of patients with a shared condition or exposure while incorporating pre-specified rules for modifying data collection, monitoring, or stopping criteria as accumulating evidence warrants. It combines the descriptive richness of traditional case series with the prospective flexibility of adaptive design principles, enabling structured mid-course adjustments without compromising the integrity of the recorded clinical observations. | An adaptive diagnostic accuracy study evaluates how well an index test distinguishes between patients with and without a target condition, while incorporating pre-specified interim analyses that allow modifications — such as sample size re-estimation, threshold adjustment, or subgroup enrichment — based on accumulating data. This design improves efficiency and ethical conduct compared to fixed-sample diagnostic studies, particularly when prior prevalence or test performance data are uncertain. |
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