The last entry noted that the NACB (National Academy of Clinical Biochemistry) guidelines for glucose meters (subscription may be required) ignored my Letter (1) and our review article on glucose meter standards (2).
But the guidelines did mention a simulation study, which I have previously critiqued. So let me expand on this critique. The simulation study provided some contour plots relating bias and imprecision to total error (or insulin dosage error rates). Now the beauty of contour plots is that they let one visualize things very nicely. The requirements for a contour plot are two variables that describe a third variable (the response) which is what these authors had. But if there are more than two variables – which is the case – then the contour plots (limited to two variables) are bogus.
I mention in my critique that the authors of the simulation study neglected to account for random interferences. This is not just to account for large errors. For example, hemoglobin is well known to cause a small interference in glucose meters, which although small adds to the overall variability.
I add here that the authors also neglected to account for pre- and post-analytical errors. Now you might ask are such errors relevant if someone is just interested in the meter accuracy. Well, observed errors can be an interaction between pre- and post-analytical errors and meter design. And pre- and post-analytical errors that are independent of the meter are still important in assessing insulin dosage errors, which was the purpose of the simulation. The point is that neglecting error sources renders the simulation to be meaningless.
- Krouwer JS. Wrong thinking about glucose standards. Clin Chem, 2010;56:874-875.
- Krouwer JS and Cembrowski GS. A review of standards and statistics used to describe blood glucose monitor performance. Journal of Diabetes Science and Technology, 2010;4:75-83.