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Accommodating covariates in roc analysis

In relation to this, the receiver operating characteristic (ROC) curve is a tool that simply describes the range of trade-offs achieved by a diagnostic test.

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There is a possibility that the diagnostic test gives a positive result for a non-diseased individual or a negative result for a diseased individual.ROC (receiver operating characteristic) curve analysis is well established for assessing how well a marker is capable of discriminating between individuals who experience disease onset and individuals who do not.The classical (standard) approach of ROC curve analysis considers event (disease) status and marker value for an individual as fixed over time, however in practice, both the disease status and marker value change over time.illustrate the cases and controls that contribute to the three definitions of sensitivity and specificity (C/D and I/D with the baseline marker, and I/S with both the baseline and longitudinal markers), with closed circles indicate individuals who had an event, open circles indicate individuals who had censored event-times.a Illustration for cases and controls of C/D, I/D and I/S (baseline) definitions.C/D: A, B and E are cases and C, D and F are controls; I/D: Only A is the case and C, D and F are controls; I/S: Only A is the case and D and F are controls.

b Illustration for cases and controls of I/S (longitudinal) definitions.

In the standard ROC curve analysis, the individual’s disease status is defined once a marker value is measured and it is assumed to be fixed for the whole study period.

The study period is usually take a long follow-up and during this, the individual without disease earlier may have the disease.

Information and signalling of future disease identification may be given by a single continuous measurement marker or a score.

A single measurement could be any clinical measure such as cell percentage in the synthesis phase to detect breast cancer [] used the prognostic score of four covariates (age, platelet count, prothrombin time, and serum alpha-fetoprotein level) to predict compensated cirrhosis patients’ survival and also used a score of three baseline characteristics (age, white blood cell and performance status) to predict event-free survival (EFS) in acute leukaemia patients.

Only A is the case and D and F are the controls It is more appropriate to apply the C/D definitions when there is a specific time of interest that is used to discriminate between individuals experiencing the event and those event-free prior to the specific time.