Порівняння методів

	Прагматичне вкладене дослідження випадок-контроль	Вкладене дослідження «випадок-контроль»
Галузь	Епідеміологія	Епідеміологія
Родина	Process / pipeline	Process / pipeline
Рік появи	1977 (nested case-control); pragmatic variant emerged in real-world evidence research from 1990s onwards	1973–1977
Автор методу	Duncan Thomas (nested case-control); pragmatic design concept from Schwartz & Lellouch (1967)	Nathan Mantel (1973); D. C. Thomas (1977 formalization)
Тип	Observational epidemiological study design	Hybrid observational study design
Основоположне джерело	Thomas, D. C. (1977). Addendum to: Methods of cohort analysis: Appraisal by application to asbestos mining. Journal of the Royal Statistical Society, Series A, 140(4), 469–491.	Thomas, D. C. (1977). Addendum to: Methods of cohort analysis: Appraisal by application to asbestos mining. Journal of the Royal Statistical Society, Series A, 140(4), 469–491.
Інші назви	real-world nested case-control, pragmatic NCC, nested case-control in routine data, real-world evidence nested case-control	NCC study, nested CC design, case-control within cohort, density sampling case-control
Пов'язані	5	6
Підсумок	A pragmatic nested case-control study embeds a case-control analysis within a pre-existing real-world cohort — typically drawn from electronic health records, administrative claims, or disease registries — to examine associations between exposures and outcomes under routine clinical conditions. Controls are sampled from the risk set (those still at risk at the time each case occurs), preserving temporal sequence while dramatically reducing data-collection costs compared with a full cohort analysis.	A nested case-control study is an efficient observational design embedded within a defined cohort. For each participant who develops the outcome of interest (a case), a small number of matched controls are sampled from those still at risk at the same point in time. This density-sampling strategy yields odds ratios that approximate incidence-rate ratios from the full cohort at a fraction of the data-collection cost — making it the preferred alternative when measuring exposures for all cohort members would be prohibitively expensive or technically demanding.