Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Estudio de Fase IV ajustado por riesgo× | Emparejamiento por Puntuación de Propensión× | |
|---|---|---|
| Campo≠ | Epidemiología | Estadística para la investigación |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1990s–2000s (formalized with ICH E2E and EMA PASS guidelines) | 1983 |
| Autor original≠ | Regulatory and pharmacoepidemiology community (ICH, EMA, FDA frameworks) | Paul Rosenbaum and Donald Rubin |
| Tipo≠ | Observational / quasi-experimental clinical study design | Method |
| Fuente seminal≠ | Strom, B. L. (Ed.). (2005). Pharmacoepidemiology (4th ed.). John Wiley & Sons. ISBN: 978-0470863107 | Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. DOI ↗ |
| Alias≠ | risk-adjusted post-marketing surveillance study, adjusted Phase IV trial, risk-stratified post-authorization study, PASS with risk adjustment | PSM, propensity score weighting, covariate balance |
| Relacionados | 3 | 3 |
| Resumen≠ | A risk-adjusted Phase IV study is an observational or semi-experimental post-marketing study conducted after a drug or device has received regulatory approval. It uses statistical risk-adjustment techniques — such as propensity score matching, inverse probability weighting, or multivariable regression — to control for confounding by indication and baseline patient differences, thereby producing more credible safety, effectiveness, and utilization estimates than unadjusted real-world analyses. | Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias. |
| ScholarGateConjunto de datos ↗ |
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