I agree with Erin that examples for clinicians would be the best way to present this. I provide an highly illustrative example here of bands (late immature neutrophil) the most common white blood cell as a biomarker for severe infection.
An understanding of the pathophysiology of the relational time series of bandemia and the white blood cell count or absolute neutrophil count is pivotal to understanding the AUC of these biomarkers and the information loss from dichotomization of them.
This is a beautiful example because the white blood cell count or absolute neutrophil count often rises first and then falls as infection worsens because the WBC is a depletable biomarker since the flux of cells exiting the vascular system to the site of infection may exceed bone marrow release. The bands, having an immature and less flexible nucleus, cannot exit between the endothelial cells as easily so their numbers and their percentage of total neutrophils in the blood rise.
Here you see how dichotomization can render the wrong result because the threshold falls on the rise side of the WBC and then is lost on the more severe fall side of the WBC (see graph). Meanwhile the bands often progressively rise making the bands the only elevated marker late in the infection.
A lack of understanding of the AUC resulted in abandonment of the measurement of bands in many hospitals around the turn of the century due to misinterpretation of the comparison of the AUCs of the absolute neutrophil count (ANC) and the bands which showed a greater AUC for the absolute neutrophil count so they thought they did not need bands.
Here you see the incorrect view that one can discover the “best biomarker” using only the instant value and generating comparison AUCs. Based on this thinking workers concluded that ANC or WBC was superior to AND could replace bands. Many centers abandoned bands based on this false interpretation of the AUC.
But the ANC is high early and the band count is high late so this was a misunderstanding and o
lack of consideration of time series information by the AUC which does not include the time domain. In other words these AUCs were dependent on the severity of infection at the time of measurement.
The ill-advised abandonment of bands as a biomarker in many hospitals has been a major loss of bedside information because it is an excellent and almost free marker for mortality. In contrast, the proprietary replacement, procalcitonin (PCT), is a poor marker for mortality. The sensitivity of bandemia is low but their presence in high numbers a vary useful marker, particularly in adults.
So showing the examples, especially this one where the information of an important and
Inexpensive and non proprietary biomarker was lost to many hospitals due to discrimination and failure to consider the time course, would go a long way for clinicians who may become lost in more complex analysis.
Some human predating bacteria like group A streptococcus and N. meningococcus generate a massive ANC and band response and then severe ANC depletion. The WBC (or ANC) threshold may not be breached if they arrive late to the hospital because the value has fallen back through the threshold as the infection worsens.
Here a lack of informed consideration of the band count and a lack of consideration of the time series relationships can result in diagnostic delay and death.
This is an excellent reference which discusses the pathophysiology of bandemia.
At Univ of Missouri, where this article is from, I recall a young recruit from Fort Leonard Wood. The boy hailed from Hawaii to serve his country and died from meningococcal infection. Such a harsh climate and an environment enclosed with the other recruits.
This is the desolate back country of western Missouri the land of the bush whackers the allies of Jessie James of the civil war. This young man, who could have stayed and enjoyed the warm North Shore, gave his life for his country like so many young Missouri boys who hurried to defend Hawaii in WWII.
These recruits need us to spend the time to have a deep understanding of these time series relationships. They deserve more than simplistic dichotomy based thinking.
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Note: Places like U of Mo., being juxtaposed the army base which trains recruits, is the perfect place to see enough of the cases to provide the lessons physcians and statisticians need to learn. Stopping the funding for this fundamental work must be prevented.