TY - JOUR
T1 - The indication area of a diagnostic test. Part II--the impact of test dependence, physician's decision strategy, and patient's utility
AU - Stalpers, Lukas J. A.
AU - Nelemans, Patty J.
AU - Geurts, Sandra M. E.
AU - Jansen, Erik
AU - de Boer, Peter
AU - Verbeek, André L. M.
PY - 2015
Y1 - 2015
N2 - Any diagnostic test has an indication area of prior probabilities wherein the gain in diagnostic certainty outweighs its loss. Here, we investigate whether indication area and the maximum diagnostic gain are robust measures if we assume test dependence, alternative physician's heuristics, and varying patient's utilities. Three mathematical functions for the dependence of test sensitivity (Se) and specificity (Sp) on the prior disease probability were studied. In addition, three different decision heuristics for further management were explored for the case that "no test" would be done. Finally, the valuation of test outcomes was varied. A sensitivity analysis was performed to determine the impact of the alternative assumptions on the indication area and maximum diagnostic gain. By assuming test dependence, the indication area shifts to higher priors and increases the maximum diagnostic gain. Decision strategies assuming a "threshold before treat" can inadvertently widen the indication area and increase the maximum diagnostic gain. Varying patient utilities will usually reduce the net diagnostic gain. A sensitivity analysis revealed the robustness of the model. The indication area and the maximum diagnostic gain are robust measures of test performance and are easier to interpret than the classical performance measures
AB - Any diagnostic test has an indication area of prior probabilities wherein the gain in diagnostic certainty outweighs its loss. Here, we investigate whether indication area and the maximum diagnostic gain are robust measures if we assume test dependence, alternative physician's heuristics, and varying patient's utilities. Three mathematical functions for the dependence of test sensitivity (Se) and specificity (Sp) on the prior disease probability were studied. In addition, three different decision heuristics for further management were explored for the case that "no test" would be done. Finally, the valuation of test outcomes was varied. A sensitivity analysis was performed to determine the impact of the alternative assumptions on the indication area and maximum diagnostic gain. By assuming test dependence, the indication area shifts to higher priors and increases the maximum diagnostic gain. Decision strategies assuming a "threshold before treat" can inadvertently widen the indication area and increase the maximum diagnostic gain. Varying patient utilities will usually reduce the net diagnostic gain. A sensitivity analysis revealed the robustness of the model. The indication area and the maximum diagnostic gain are robust measures of test performance and are easier to interpret than the classical performance measures
U2 - https://doi.org/10.1016/j.jclinepi.2015.05.017
DO - https://doi.org/10.1016/j.jclinepi.2015.05.017
M3 - Article
C2 - 26142115
SN - 0895-4356
VL - 68
SP - 1129
EP - 1137
JO - Journal of Clinical Epidemiology
JF - Journal of Clinical Epidemiology
IS - 10
ER -