Nested Case Control Study Design Definition

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Recent applications of NCC include studies showing the effects of serum lipids and lipoproteins on breast cancer risk [6], urine semaphorin-3A on renal damage in hypertensive patients [7], DNA methylation markers on type-2 diabetes [8], and plasma cytokines and the risk of HIV type one [9].

In addition to being cost effective, NCC with a smaller sample size tends to be less computationally demanding than the analysis of the full cohort study.

For a NCC with matching, Cornfield [12], Mantel and Haenszel [13], Breslow [2], Rubin [14], Rothman and Greenland [15] have pointed out that the match algorithm, the match factors, and their association with the outcome and the exposure play a critical role in validity and efficiency.

In addition, caution is needed to avoid overmatching, since this could introduce bias and inefficiency into the estimators.

Matching cases to controls according to baseline measurements of one or several confounding variables is done to control for the the effect from confounding variables.

A counter-matched study, in contrast, is when we matces cases to controls who have a different baseline risk factor exposure level.

NCC is cost effective and can be done with or without matching in the selection of a subset of the controls.

NCC analysis with good matching procedure yields estimates that are as efficient and unbiased as estimates from the full cohort study [2].

Study participants are patients aged over 70 years who underwent scheduled major non-cardiac surgery.

The primary outcome was postoperative delirium from in-hospital interviews and medical record review.

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