STATISTICS Outliers should not be deleted merely


because they increase a limit. Investigate transcription errors, instrument flags, contamination and other identifiable causes – as always. A genuine sporadic high blank is directly relevant to false detection. Similarly, values reported as zero or “below range” are observations shaped by the instrument’s reporting algorithm, not proof that the underlying analytical signal is zero.


Worked example The following simulated example illustrates the decisions. It is not patient data or validation of a commercial assay. A laboratory evaluates a generic biomarker reported in arbitrary units. Sixty blank measurements across several runs have a right bounded distribution. The empirical 95th percentile is used rather than forcing a Gaussian model. In this example, the LoB is 0.16 units (blue dashed line, Fig 1). Eighty measurements of a low pool with target concentration 0.32 units exceed the LoB in 97.5% of replicates, supporting an illustrative LoD close to 0.32 units. For quantitation, five low


concentrations are studied across routine conditions. Before testing, the laboratory requires CV at or below 20% and absolute bias at or below 10%. The first level meeting both criteria is 0.60 units. The LoQ is therefore 0.60 units, not 0.32 units. Results between the LoD and LoQ can provide evidence that analyte is present, but their numerical magnitude does not meet the laboratory’s predefined quantitative requirement (Table 3). Interpolation between tested


concentrations may be reasonable when a suitable performance model has been prespecified and fits the data – but should be done carefully. It should not imply more resolution than the experiment supports. Reporting an LoQ of 0.573 units from sparse levels would imply meaningless precision. A defensible claim is usually rounded to a concentration


Result region At or below LoB Above LoB but below LoD Target


0.40 0.60 0.80 1.20 2.00


CV


26.0% 18.0% 13.0% 9.0% 6.0%


Table 3. Further data from the worked example. supported by the design and calibration.


From analytical limits to reporting rules


The analytical study should lead to an explicit reporting policy. Below the LoB, a numerical result generally should not be interpreted as evidence that analyte is present. Between the LoB and LoD, occasional true low samples will exceed the blank threshold, but detection is not achieved with the target probability. Between the LoD and LoQ, detection can be reliable while numerical performance remains inadequate. At or above the LoQ, quantitative reporting is supported within the other validated boundaries of the method (Table 4). These are analytical categories, not


universal report phrases. The correct wording depends on the measurand and clinical pathway. For some assays, presence below the LoQ is clinically useful. For others, reporting “detected” can cause harm if specificity or contamination controls are inadequate. A diagnostic cut-off should not be replaced by the LoD, and the LoD should not be moved to match a desired clinical cut-off. Instead, establish whether the procedure has suitable capability around the decision concentration. A claimed limit must describe the


complete measurement procedure under stated conditions, not merely the instrument’s ability to register a signal. Sample preparation, extraction, dilution,


Defensible analytical statement


Indistinguishable from blank at the selected false positive probability


More signal than most blanks, but detection probability is below the selected target


At or above LoD but below LoQ Analyte is detected with the stated probability, but the number fails quantitative criteria


At or above LoQ


The result meets the predefined low end quantitative criteria


Table 4. Examples of analytical categories, not universal report phrases. 20 WWW.PATHOLOGYINPRACTICE.COM October 2026


calibration, matrix and software rules can all affect low end performance. Changing any of these may require re-evaluation. The number of decimal places in a claim should reflect study resolution and routine reporting, not the precision of statistical software.


Common misconceptions LoB is zero: Even an analyte-free sample can generate a non-zero apparent result. The LoB characterises that response. It is not assumed to be zero.


LoD is the lowest calibrator: A calibrator level is a design choice. Detection capability depends on blank and low sample distributions and the selected error probabilities.


LoQ is always 10 standard deviations or a 20% CV: Such conventions may be used in defined contexts, but they are not universal quantitative requirements. LoQ must be tied to prespecified acceptable performance.


LoD proves a low result is accurate: LoD addresses detection probability. Accuracy, precision and fitness for quantitative use require separate evidence.


A lower LoD always means a beter assay: A lower limit is advantageous only when reliable low-end information maters and other performance is adequate. Broad superiority claims require evidence beyond detection capability and are outside the scope of this article.


Possible laboratory reporting approach


Report “not detected” or “<LoD” according to the validated policy. Do not report zero unless zero is the defined measurand value


Avoid a confident detected/not detected claim based on a single result. Use a validated grey zone or repeat rule if clinically justified


Report “detected, <LoQ” or a qualified result if the clinical service needs this distinction


Report numerically, subject to the validated measuring interval, units, rounding and other method limitations


Bias


15.0% 8.0% 4.0% 2.0% 1.0%


Quantative criteria met


No Yes Yes Yes Yes


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