Thresholds for medical decision making are the probabilities of disease at which clinicians choose to initiate testing or therapy. A descriptive analysis of clinicians\u27 decision making can derive their test and test-treatment thresholds and has the potential to explain variations in test utilization. A previously described method summarizes thresholds for a group of clinicians by determining the range of probability which includes the maximum number of clinicians\u27 individual thresholds. However, there is no statistical procedure to compare the summary measure of thresholds that is derived from the distribution of clinicians\u27 thresholds. We describe two alternative methods of developing a summary measure of the thresholds for a grou...
Background Clinical prediction models are useful in estimating a patient's risk of having a certain ...
Multivariable regression models are widely used in medical literature for the purpose of diagnosis o...
Objective: Network meta-analyses have extensively been used to compare the effectiveness of multip...
Diagnosis and treatment is a complex interaction of subjective information and impressions, objectiv...
Our objective was to determine the test and treatment thresholds for common acute primary care condi...
When a decision table is used to find a maximum expected utility testing strategy, it is based on a ...
Many continuous medical tests often rely on a threshold for diagnosis. There are two sequential test...
<p>Cartoon illustrating two distinct, unrelated, values that are both called “threshold”. The statis...
<p>x = diseased; 1-x = not diseased; Tc = Treatment cost; Tmort = mortality caused by the treatment;...
1. benefit 30%, harm = 5%, threshold = 17% (- - -), 2. benefit 40%, harm = 5%, threshold = 12.5% (--...
Diagnostic tests are often evaluated by comparison of the areas under receiver op-erating charactens...
International audienceBackground: Estimating the optimal threshold (and especially the confidence in...
Objectives: To evaluate how the rank probabilities obtained from network meta -analysis (NMA) change...
Most of the methodological literature on evaluating an additional marker for risk prediction involve...
We consider medical decision-making under diagnostic and therapeutic uncertainty and analyze how amb...
Background Clinical prediction models are useful in estimating a patient's risk of having a certain ...
Multivariable regression models are widely used in medical literature for the purpose of diagnosis o...
Objective: Network meta-analyses have extensively been used to compare the effectiveness of multip...
Diagnosis and treatment is a complex interaction of subjective information and impressions, objectiv...
Our objective was to determine the test and treatment thresholds for common acute primary care condi...
When a decision table is used to find a maximum expected utility testing strategy, it is based on a ...
Many continuous medical tests often rely on a threshold for diagnosis. There are two sequential test...
<p>Cartoon illustrating two distinct, unrelated, values that are both called “threshold”. The statis...
<p>x = diseased; 1-x = not diseased; Tc = Treatment cost; Tmort = mortality caused by the treatment;...
1. benefit 30%, harm = 5%, threshold = 17% (- - -), 2. benefit 40%, harm = 5%, threshold = 12.5% (--...
Diagnostic tests are often evaluated by comparison of the areas under receiver op-erating charactens...
International audienceBackground: Estimating the optimal threshold (and especially the confidence in...
Objectives: To evaluate how the rank probabilities obtained from network meta -analysis (NMA) change...
Most of the methodological literature on evaluating an additional marker for risk prediction involve...
We consider medical decision-making under diagnostic and therapeutic uncertainty and analyze how amb...
Background Clinical prediction models are useful in estimating a patient's risk of having a certain ...
Multivariable regression models are widely used in medical literature for the purpose of diagnosis o...
Objective: Network meta-analyses have extensively been used to compare the effectiveness of multip...