Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Utafiti wa Meta-analytic wa Awamu ya IV× | Utafiti wa Cohort× | |
|---|---|---|
| Nyanja | Epidemiolojia | Epidemiolojia |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1990s–2000s (formalised as regulatory requirement context grew) | Mid-20th century (formal epidemiological design codified ~1950s) |
| Mwanzilishi≠ | Developed through the convergence of meta-analytic methods (Glass, 1976; Hedges & Olkin, 1985) and post-marketing pharmacoepidemiology frameworks | Doll & Hill (British Doctors Study, 1951); Snow (cholera, 1854) |
| Aina≠ | Evidence synthesis applied to post-marketing observational and trial data | Observational longitudinal study design |
| Chanzo asilia≠ | Sutton, A. J., Abrams, K. R., Jones, D. R., Sheldon, T. A., & Song, F. (2000). Methods for Meta-Analysis in Medical Research. Wiley. ISBN: 978-0471490661 | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| Majina mbadala | Phase IV meta-analysis, post-marketing meta-analysis, pharmacoepidemiologic meta-analysis, post-approval systematic review and meta-analysis | longitudinal study, follow-up study, panel study, incidence study |
| Zinazohusiana≠ | 3 | 6 |
| Muhtasari≠ | A meta-analytic Phase IV study pools and quantitatively synthesises data from multiple Phase IV (post-marketing) sources — including observational cohorts, registries, spontaneous adverse-event databases, and post-approval randomised trials — to produce a single, more precise estimate of a drug or device's real-world effectiveness, safety, or utilisation pattern. By applying meta-analytic weighting to heterogeneous post-marketing evidence, it bridges the gap between tightly controlled pre-approval trials and the complexity of routine clinical practice. | A cohort study assembles a group of individuals who share a common starting point — typically freedom from the outcome of interest — and follows them over time to observe who develops the outcome. By comparing incidence rates between exposed and unexposed subgroups, researchers can estimate relative risk and absolute risk differences. Cohort studies are the gold-standard observational design for measuring disease incidence and establishing temporal relationships between exposure and outcome. |
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