Model input parameters
To predict costs and health outcome as effects of DI, both the direct and indirect effects of the imaging test itself on health outcome and costs should be considered as model input parameters (Fig. 1).

Direct effects
Direct effects are those that apply for all patients undergoing the diagnostic test regardless of the outcome of the test. Direct effects of imaging modalities on health vary, depending on the modality used, from negligible in, e.g. ultrasound, to considerable in invasive techniques like catheter angiography. The “considerable” effects are mainly a consequence of the risk of complications inherent to these invasive techniques. The use of contrast agents in diagnostic imaging carries the risk of adverse reactions and nephrotoxicity [26–29]. The effects of these sequelae on health status depend on the chemical properties of the contrast agent used and the way it is administered (oral, intravenous, intra-arterial, intrathecal). Radiation exposure from diagnostic tests using X-Rays has a small but not negligible effect on health status especially in models addressing a large patient population. The risk of inducing cell mutations is present in all diagnostic modalities using X-Rays and increases with radiation dose and exposure times. Data on these risks are provided in the Biological Effects of Ionizing Radiation (BEIR) reports [30]. Besides these stochastic effects of radiation exposure deterministic effects, or tissue reactions, can occur at high dosage or long exposure times. These effects occur above a certain threshold and should, therefore, only be considered if there is a possibility that this threshold will be reached. Direct psychological health effects of imaging should be considered in CEA of DI if relevant, for example if imaging is very burdensome [31, 32]. These effects consist of potential short-term psychological effects of the imaging test itself.
Direct costs of diagnostic testing include depreciation of the hardware, cost of personnel and materials (e.g., contrast agents). To be considered in the determination of these direct costs are influencing factors like imaging time and mode of utilization of the equipment (24/7 versus office hours) since both define the patient throughput for the imaging equipment. The latter form of direct costs rise especially when using expensive hardware and long examinations, such as MRI and PET. Besides the aforementioned types, additional costs caused by the above described adverse events and complications need to be included based on their prevalence. These costs comprise additional hospitalization and treatment costs. Ultimately societal costs of radiation-induced malignancies can be transferred to additional costs of those tests for which this is applicable. Ideally real costs are used in a CEA, and tariffs or reimbursement fees are used only if they accurately represent the real costs.

Indirect effects
Indirect effects of a diagnostic test depend on the consequences of the test result. Both health status and costs related to this health status are characteristics of the patient and diagnostic tests do not directly change these parameters. Diagnostic tests guide the management of patients. Assuming optimal circumstantial factors, a “perfect” diagnostic test will theoretically result in the optimal management. One may assume that the optimal management leads to the best health status (though not necessarily to lowest costs). “Imperfect” diagnostic tests will in some cases lead to suboptimal management. The effect of diagnostic tests on outcome parameters lies, therefore, only in the imperfectness of the test, usually presented as sensitivity and specificity, or positive and negative predictive values. Indirect psychological effects are gaining more attention and consist of the positive or negative psychological effects of the diagnostic information of the test result on a patient’s view on his or her health [32–34].
Outcome parameters for health status are generally represented as quality-adjusted life years (QALYs), although other outcome parameters might be used for specific study objectives (e.g., life-years saved). QALYs are derived from the general life expectancy estimates of the target population and disutilities (i.e., reduction in quality of life) related to the disease of interest, the treatment, and the diagnostic test. The use of QALYs allows for the relative importance of false positive or negative results of a diagnostic test (reflected in sensitivity and specificity) to be weighed. Costs are calculated from the allocated treatment, medication, hospitalization, etc. Furthermore, costs can be transferred from known societal costs of specific health conditions that might apply. Table 1 provides a schematic overview of model input parameters for the example of different follow-up imaging strategies in curatively treated NSCLC [6].
Table 1 Schematic example of model input parameters
Model Parameter Mean SE/SD/range Distribution Source
Probabilities p
 p Progressive Disease 0.85 fixed *
Diagnostics
PET-CT
 p imaging test true positive (Sensitivity) * * beta *
 p imaging test true negative (Specificity) * * beta *
CT
 p imaging test true positive (Sensitivity) * * beta *
 p imaging test true negative (Specificity) * * beta *
X-Ray
 p imaging test true positive (Sensitivity) * * beta *
 p imaging test true negative (Specificity) * * beta *
Costs c (€)
Diagnostics
 c PET-CT whole body 1.364 € fixed [35],*
 c CT chest 204 € fixed [35],*
 c X-Ray chest 39 € fixed [35],*
Treatment
 c * * * * *
Utilities (u)
 u No disease 0.68 0.1 beta [1],*
 u Progression, detected * * beta [1],*
 u Progression, undetected * * beta [1],*
 u Dead 0.00 * fixed [1],*