Literature DB >> 7845919

Nested case-control studies.

V L Ernster1.   

Abstract

The nested case-control study design (or the case-control in a cohort study) is described here and compared with other designs, including the classic case-control and cohort studies and the case-cohort study. In the nested case-control study, cases of a disease that occur in a defined cohort are identified and, for each, a specified number of matched controls is selected from among those in the cohort who have not developed the disease by the time of disease occurrence in the case. For many research questions, the nested case-control design potentially offers impressive reductions in costs and efforts of data collection and analysis compared with the full cohort approach, with relatively minor loss in statistical efficiency. The nested case-control design is particularly advantageous for studies of biologic precursors of disease. To advance its prevention research agenda, NIH might be encouraged to maintain a registry of new and existing cohorts, with an inventory of data collected for each; to foster the development of specimen banks; and to serve as a clearinghouse for information about optimal storage conditions for various types of specimens.

Mesh:

Year:  1994        PMID: 7845919     DOI: 10.1006/pmed.1994.1093

Source DB:  PubMed          Journal:  Prev Med        ISSN: 0091-7435            Impact factor:   4.018


  66 in total

1.  The impact of delayed source control and antimicrobial therapy in 196 patients with cholecystitis-associated septic shock: a cohort analysis

Authors:  Constantine J. Karvellas; Victor Dong; Juan G. Abraldes; Erica L.W. Lester; Anand Kumar
Journal:  Can J Surg       Date:  2019-06-01       Impact factor: 2.089

2.  A Bayesian semiparametric approach for incorporating longitudinal information on exposure history for inference in case-control studies.

Authors:  Dhiman Bhadra; Michael J Daniels; Sungduk Kim; Malay Ghosh; Bhramar Mukherjee
Journal:  Biometrics       Date:  2012-02-07       Impact factor: 2.571

3.  Screening for aortic injury with chest radiography and clinical factors.

Authors:  Jared R Kirkham; C Craig Blackmore
Journal:  Emerg Radiol       Date:  2007-07-06

Review 4.  Case-control studies in pharmacoeconomic research: an overview.

Authors:  J Jaime Caro; Krista F Huybrechts
Journal:  Pharmacoeconomics       Date:  2009       Impact factor: 4.981

5.  Early urinary biomarkers of acute kidney injury in preterm infants.

Authors:  Mina Hanna; Patrick D Brophy; Peter J Giannone; Mandar S Joshi; John A Bauer; Satish RamachandraRao
Journal:  Pediatr Res       Date:  2016-04-07       Impact factor: 3.756

6.  A targeted maximum likelihood estimator for two-stage designs.

Authors:  Sherri Rose; Mark J van der Laan
Journal:  Int J Biostat       Date:  2011-03-11       Impact factor: 0.968

7.  Navigating the road ahead: addressing challenges for use of metabolomics in epidemiology studies.

Authors:  Majda Haznadar; Padma Maruvada; Eliza Mette; John Milner; Steven C Moore; Holly L Nicastro; Joshua N Sampson; L Joseph Su; Mukesh Verma; Krista A Zanetti
Journal:  Metabolomics       Date:  2014-04-01       Impact factor: 4.290

8.  Host condition and individual risk of cowpox virus infection in natural animal populations: cause or effect?

Authors:  P M Beldomenico; S Telfer; L Lukomski; S Gebert; M Bennett; M Begon
Journal:  Epidemiol Infect       Date:  2009-01-15       Impact factor: 2.451

9.  Utility of tissue microarrays for profiling prognostic biomarkers in clinically localized prostate cancer: the expression of BCL-2, E-cadherin, Ki-67 and p53 as predictors of biochemical failure after radical prostatectomy with nested control for clinical and pathological risk factors.

Authors:  Joseph Nariculam; Alex Freeman; Simon Bott; Phillipa Munson; Noriko Cable; Nicola Brookman-Amissah; Magali Williamson; Roger S Kirby; John Masters; Mark Feneley
Journal:  Asian J Androl       Date:  2008-12-01       Impact factor: 3.285

Review 10.  The yin and yang of vitamin D receptor (VDR) signaling in neoplastic progression: operational networks and tissue-specific growth control.

Authors:  F C Campbell; Haibo Xu; M El-Tanani; P Crowe; V Bingham
Journal:  Biochem Pharmacol       Date:  2009-09-06       Impact factor: 5.858

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