Scientific Concept of the National Cohort (status ... - Nationale Kohorte

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A.1 Introduction and overview
Internal boards authorized by the general assembly and the board of directors, as
the working group scientific management or the use and access committee will be
responsible for particular aspects of the scientific management (details are provided
in Part B).
A.1.6 Justification of sample size requirements
Whenever an epidemiologic study has one single outcome and one single risk factor, the
sample size necessary to establish a statistically stable association between the two is usually
based on statistical power considerations, involving subsequent sample size calculations
for detectable effect size, given type I, II errors, and making reasonable assumptions
on the incidence of the outcome and the distribution of the risk factor. Even in such highly
simplified context, other, not trivial aspects usually have to be considered, including the
relevance of the detectable effect size and various underlying assumptions with respect to
adequacy of statistical models 30-32 .
For a project of the size and breadth of scope of the National Cohort, developing a notion of
the necessary study size becomes a much more complex exercise. Clearly, considering the
large number of possible disease outcomes and the great variety of risk factors and related
study hypotheses with respect to these outcomes, the problem cannot be defined simply
and thus does not lead to a single and straightforward solution. In addition, financial costs
must also be taken into consideration, for example, with respect to the embedded study
levels with intensified phenotyping.
In Sect. A.6 of this application, issues related to selecting appropriate forms of statistical
modeling are being discussed, and detailed statistical power estimations are presented.
The arguments and estimates laid out in that section indicate that N=200,000 for level 1,
N=40,000 for level 2, and N=40,000 for the MRI program, and N=8,000 for the combined
measurements of level 2 and imaging (as justified in Sect. A.3.4) are reasonable sample
sizes for the National Cohort. Here, we illustrate this in only simplified form by highlighting
the sensitivity of the study in different incidence scenarios. This simplicity results from
the simple model we consider here, namely, that of a quantitative trait that is divided into
quartiles, where the measure of sensitivity is expressed as the RR that may be detected by
contrasting the 4th versus the 1st quartile of the trait for a significance level of 5%, power of
80%, two-sided test, given a certain number of events in the full cohort (Level 1).
Table 1.4 gives an impression of how the detectable RR’s are interrelated with the number
in the different subcohorts of the National Cohort.
Table 1.4: Minimum detectable odds ratio (statistical power 0.80, significance level 0.05) for comparison
of top to bottom quartiles of a quantitative trait, in full cohort setting.
Expected number of cases at level 1
Study level (number of subjects) 100 500 1,000 2,500 3,500 5,000 10,000
Level 1 (N=200,000) 2.1 1.4 1.3 1.17 1.14 1.11 1.08
Level 2 or imaging (N=40,000) 3.6 1.9 1.7 1.5 1.3 1.3 1.17
Level 2 plus imaging (N=8000) 9.5 3.6 2.7 1.9 1.7 1.6 1.4
A.1