Are nested case-control studies biased
This means that a sampling strategy that uses the whole population as its source must allow for the fact that people who develop the disease of interest can be selected as controls.
Are nested case-control studies biased
The bases for this claim include a theoretical and an "empirical evaluation" argument. For example, the negative predictive value of the D-dimer test was 0. As with cohort studies, case-control studies can be prospective or retrospective. It is important to note that, unlike cohort studies, case-control studies do not follow subjects through time. Conclusion Our findings support the view that the nested case-control study is a valid and efficient design for diagnostic studies. This source population can be a group or cohort of subjects that is followed over time or not. Under these conditions, one limits patient burden and saves time and money as the index test is performed in only a sample of the control subjects. Alternatively, none of the cases might have already occurred, and new cases will be enrolled prospectively. A major flaw inherent to case-control studies, described as early as [ 13 ], is the difficulty to ensure that cases and controls are a representative sample of the same source population. The rationale, strengths and limitations of a nested case-control approach in epidemiology studies have widely been discussed in the literature [ 8 — 11 ], but not so much in the context of diagnostic accuracy research [ 6 ]. Subsequently, all patients were referred to undergo D-dimer testing.
The general practitioner systematically documented information on patient history and physical examination. Patient history included information such as age, gender, history of malignancy, and recent surgery. A nested case-control study in diagnostic research includes the full population or cohort of patients suspected of the target disease.
This phenomenon is known as the rare-disease assumption. We applied four different and frequently used case-control ratios, i. Hence, the nested case-control design is particularly advantageous when the prevalence of the target condition in the cohort of patients suspected of the target disease is rare, when the index test results are costly or difficult to collect and for re-analysing stored images or specimen.
For example, for each case:control ratio, the positive predictive value of the D-dimer test was 0.
Prospective case control study
Controls were randomly sampled from the subjects without DVT. Furthermore, the nested case-control design is of particular value when stored data serum, images etc. However, precision of the diagnostic accuracy measures will be hampered by increased variability when too little control patients are included. Not the entire population is studied, what would be a full cohort study or census approach, but rather a random sample from the source population [ 12 ]. Usually all patients with the target disease are included, but this could as well be a sample of the cases. In essence, a case-control strategy was used, but it was conducted within the context of a prospective cohort study. This suspicion was primarily defined by the presence of a painful and swollen or red leg that existed no longer than 30 days. Rothman states that one should look upon all case-control studies as being "nested" within a cohort. The OR for the calf difference test was 1. The latter was specifically chosen as it allowed for the estimation and thus comparison of the area under the ROC curve ROC area. Efficiency of the NCC model[ edit ] Commonly 1—4 controls are selected for each case. We therefore aim to show advantages of the nested case-control design for addressing diagnostic accuracy questions and discuss its pros and cons in relation to a conventional case-control design and to the full cross sectional cohort design in this domain. In all samples, we included always all cases with DVT.
Measures of diagnostic accuracy included sensitivity and specificity, positive and negative predictive values and the odds ratio OR for the D-dimer test, and the OR and the ROC area for the calf difference test. Diagnostic accuracy parameters derived from a full cross-sectional cohort of patients suspected of DVT were similar to the estimates derived from various nested case-control samples averaged over simulations.
The main difference between a case-control and a nested case-control study is that in the former the cases and controls are sampled from a source population with unknown size, whereas the latter is 'nested' in an existing predefined source population with known sample size.
Physical examination included swelling of the affected limb and difference in circumference of the calves calculated as the circumference in centimetres of affected limb minus circumference of unaffected limb, further referred to as calf difference test.
We calculated diagnostic accuracy estimates for two tests that are used to detect DVT in clinical practice.
With a case-control sampling strategy one simply takes a sample of the population in order to obtain an estimate of the exposure distribution within the population that gave rise to the cases. Figure 2 Estimates of diagnostic accuracy of the D-dimer test and calf difference test for the nested case-control samples with case-control ratios ranging from to
Nested case control matching
The 'true' disease status is obtained for all these patients with the reference standard. The cohort characteristic by which the study subjects cohort members are selected is 'the suspicion of the target disease', defined by the presence of particular symptoms or signs [ 2 ]. Hence, there is no referral or partial verification bias. We therefore aim to show advantages of the nested case-control design for addressing diagnostic accuracy questions and discuss its pros and cons in relation to a conventional case-control design and to the full cross sectional cohort design in this domain. We applied four different and frequently used case-control ratios, i. This means that a sampling strategy that uses the whole population as its source must allow for the fact that people who develop the disease of interest can be selected as controls. Accordingly, a cross-sectional study can either be a cross-sectional case-control study or a cross-sectional cohort study. The median estimate of the samples was considered as the point estimate. We discussed and showed that a case-control study nested within a well defined cohort of subjects suspected of a particular target disease with known sample size can yield valid estimates of diagnostic accuracy of an index test, including the absolute probabilities of disease presence or absence. Because it is based on the underlying cohort structure, the empirical evaluation can provide an assessment that is tailored to the specific characteristics of the study under consideration. For example, for each case:control ratio, the positive predictive value of the D-dimer test was 0. Appraisal of such conventional case-control design in diagnostic accuracy research has been limited due to its problems related to the incorrect sampling of cases and controls [ 3 — 7 ].
based on 117 review