Probabilistic Bayesian reasoning can help identifying potentially wrong immunoassays results in clinical practice: even when they appear ‘not-unreasonable’

A Black Swan in clinical laboratory practice: the analytical error due to interferences in immunoassay methods

It is well known that the results of immunoassay methods can be affected by specific or non-specific interferences, ranging from 0.4% to 4.0%. The presence of interference may greatly compromise the accuracy of immunoassay analyses causing an error in the measurement, producing false-positive or false-negative results. From a clinical point of view, these analytical errors may have serious implications for patient care because they can cause misdiagnosis or inappropriate treatment. Unfortunately, it is a very difficult task to identify the irregular analytical errors related to immunoassay methods because they are not detectable by normal laboratory quality control procedures, are reproducible within the test system, may be clinically plausible and are relatively rare. The first line of defense against erroneous results is to use in laboratory practice only immunoassay systems with the highest level of robustness against interference. The second line of defense is always taking into account the possibility of interference in immunoassay results. A correct approach should be addressed on identification of samples at high risk of interference. The attainment of this goal requires a critical review of the test result in relation to patient's clinical conditions and literature data, taking into account the analytical characteristics of the immunoassay system. The experts in immunoassay systems should make every effort to find some specific and reliable quality indicators for irregular analytical errors in order to better detect and monitor erroneous immunoassay results due to specific or non-specific interferences.

The insulin autoimmune syndrome (IAS) as a cause of hypoglycaemia: an update on the pathophysiology, biochemical investigations and diagnosis

Insulin autoimmune syndrome (IAS) is considered to be very rare in Caucasians. Understanding its pathophysiology is paramount in (a) appreciating its potential impact on analyses of pancreatic hormones and (b) explaining its highly variable clinical manifestations in non-diabetic, non-acutely ill patients with indeterminate hypoglycaemia. The underlying aetiology of IAS is the presence of variable affinity/avidity endogenous insulin antibodies in significant amounts. The two types of insulin antibodies namely antibodies which bind insulin and/or proinsulin(s) and receptor antibodies (insulin mimetic) will be discussed. Their biochemical and immunological roles in causing hypoglycaemia will be highlighted. Clinical manifestations of IAS can vary from mild and transient to spontaneous, severe and protracted hypoglycaemia necessitating in extreme cases plasmapheresis for glycaemic control. Antibodies of IAS can interfere in pancreatic immunoassay tests causing erroneous and potentially misleading results. Thorough testing for endogenous insulin antibodies must be considered in the investigations of non-diabetic, non-acutely ill patients with indeterminate and/or unexplained hypoglycaemia.

Serum sample containing endogenous antibodies interfering with multiple hormone immunoassays. Laboratory strategies to detect interference

OBJECTIVES

Endogenous antibodies (EA) may interfere with immunoassays, causing erroneous results for hormone analyses. As (in most cases) this interference arises from the assay format and most immunoassays, even from different manufacturers, are constructed in a similar way, it is possible for a single type of EA to interfere with different immunoassays. Here we describe the case of a patient whose serum sample contains EA that interfere several hormones tests. We also discuss the strategies deployed to detect interference.

SUBJECTS AND METHODS

Over a period of four years, a 30-year-old man was subjected to a plethora of laboratory and imaging diagnostic procedures as a consequence of elevated hormone results, mainly of pituitary origin, which did not correlate with the overall clinical picture.

RESULTS

Once analytical interference was suspected, the best laboratory approaches to investigate it were sample reanalysis on an alternative platform and sample incubation with antibody blocking tubes. Construction of an in-house 'nonsense' sandwich assay was also a valuable strategy to confirm interference. In contrast, serial sample dilutions were of no value in our case, while polyethylene glycol (PEG) precipitation gave inconclusive results, probably due to the use of inappropriate PEG concentrations for several of the tests assayed.

CONCLUSIONS

Clinicians and laboratorians must be aware of the drawbacks of immunometric assays, and alert to the possibility of EA interference when results do not fit the clinical pattern.

Negative interference by rheumatoid factor of plasma B-type natriuretic peptide in chemiluminescent microparticle immunoassays

Background

The chemiluminescent microparticle immunoassay (CMIA) is widely used for the quantitative determination of B-type natriuretic peptide (BNP) in human ethylenediaminetetraacetic acid plasma. Rheumatoid factor (RF) is usually thought to result in a positive interference in immunoassays, but it is not clear whether its presence in plasma can lead to interferences in the CMIA of BNP.

Methods

The estimation of BNP recovery was carried out by diluting high-concentration BNP samples with RF-positive or RF-negative plasma at a ratio of 1∶9. The diluted samples were then tested using the ARCHITECT i2000 System and ARCHITECT BNP Reagent Kits and the recovery was then calculated.

Results

When the RF level ranged from 48 to 1420 IU/mL, the average recovery of BNP was 79.29% and 91.61% in the RF-positive and RF-negative plasma samples, respectively, and was thus significantly lower in the group of RF-positive plasma samples than in the group of RF-negative plasma samples. At a dilution of 1∶16, the measured BNP level increased by >36% in six of the seven RF-positive plasma samples. The recovery of BNP increased significantly in the RF-positive plasma samples after pretreatment with IgG-sensitive latex particles. In addition, The BNP recovery was not significantly related to the plasma RF at concentrations ranging from 48 to 2720 IU/mL.

Conclusions

Measurement of BNP by CMIA is susceptible to interference from RF leading to predominantly (but not exclusively) lower results. Pretreatment of samples with blocking reagents is advisable prior to the initiation of denying patient's necessary treatment.

Identifying and reducing potentially wrong immunoassay results even when plausible and "not-unreasonable"

The primary role of the clinical laboratory is to report accurate results for diagnosis of disease and management of illnesses. This goal has, to a large extent been achieved for routine biochemical tests, but not for immunoassays which remained susceptible to interference from endogenous immunoglobulin antibodies, causing false, and clinically misleading results. Clinicians regard all abnormal results including false ones as "pathological" necessitating further investigations, or concluding iniquitous diagnosis. Even more seriously, "false-negative" results may wrongly exclude pathology, thus denying patients' necessary treatment. Analytical error rate in immunoassays is relatively high, ranging from 0.4% to 4.0%. Because analytical interference from endogenous antibodies is confined to individuals' sera, it can be inconspicuous, pernicious, sporadic, and insidious because it cannot be detected by internal or external quality assessment procedures. An approach based on Bayesian reasoning can enhance the robustness of clinical validation in highlighting potentially erroneous immunoassay results. When this rational clinical/statistical approach is followed by analytical affirmative follow-up tests, it can help identifying inaccurate and clinically misleading immunoassay data even when they appear plausible and "not-unreasonable." This chapter is largely based on peer reviewed articles associated with and related to this approach. The first section underlines (without mathematical equations) the dominance and misuse of conventional statistics and the underuse of Bayesian paradigm and shows that laboratorians are intuitively (albeit unwittingly) practicing Bayesians. Secondly, because interference from endogenous antibodies is method's dependent (with numerous formats and different reagents), it is almost impossible to accurately assess its incidence in all differently formulated immunoassays and for each analytes/biomarkers. However, reiterating the basic concepts underpinning interference from endogenous antibodies can highlight why interference will remain analytically pernicious, sporadic, and an inveterate problem. The following section discuses various stratagems to reduce this source of inaccuracy in current immunoassay results including the role of Bayesian reasoning. Finally, the role of three commonly used follow-up affirmative tests and their interpretation in confirming analytical interference is discussed.

Negative interference in serum HBsAg ELISA from rheumatoid factors

Background

RF(Rheumatoid factor) is usually thought to cause positive interference in immunoassay. Recently, our study showed that high-concentration RFs caused negative interference as well as positive interference in serum HBsAg(Hepatitis B surface antigen) ELISA(Enzyme-linked immunosorbent assay), but it is unclear that RF causing negative interference is an anomaly produced by a certain ELISA kit or a common property of most of HBsAg ELISA kits.

Methods

Serum models were made by blending HBsAg-positive sera and high- or moderate-concentration RFs sera at the ratio of 1: 9, then one-step and two-step ELISA were adopted to determine HBsAg in serum models.

Results

No matter what kind of kit used, one-step ELISA showed that HBsAg S/CO( sample/cut off) values in serum models were significantly lower than original values. Bivariate correlations tests showed decline rates of HBsAg S/CO Values were not associated to serum RF concentrations ranging from 288 to 3560 IU/mL. HBsAg converted to be negative in 69.80% serum models with original-value ranging from 1.00 to 10.00, and in 2.68% serum models with higher original-value. RF causing decline of HBsAg S/CO value provided by one-step ELISA was more obvious than that provided by two-step ELISA.

Conclusions

It is concluded that susceptibility of all HBsAg ELISA assays to interference from RF, leading to predominantly lower and in some cases "false-negative" results, and moreover, the lower the original HBsAg S/CO Value, the higher the false-negative rate.

Belief is only half the truth--or why screening for heterophilic antibody interference in certain assays makes double sense

BACKGROUND

Interference in immunoassays may cause both false-negative and false-positive results. It may be detected using a number of affirmative tests such as reanalysis of certain samples using different assay platforms with known bias, after the addition of blocker antibodies, or assessment of linearity and parallelism following serial doubling dilutions. One should look for interference where it is likely and has high medical impact. Probabilistic Bayesian reasoning is a statistical tool to identify samples where interference is most likely. But when looking for interference where it is likely, do we find it where it has the largest population health consequences?

METHODS

We used information theory to quantify the effect of assay interference by calculating the Shannon information content (using logarithms with base 2). We then obtained lower bounds of the population health consequences of a particular test and combined these expressions to get lower bounds of the population health consequences of interference.

RESULTS AND CONCLUSION

We suggest that assays having a low frequency of true positives should be the primary target of retesting because: (i) assays with a low frequency of true positives exhibit a high likelihood of interference and (ii) the population health consequences of false-positive results are generally higher for assays with a low frequency of true positives. Finally, we give a worked example having a realistic frequency of interference and test costs. In some immunoassays (e.g., tumour markers), adding a blocker to all tests can be a more cost-efficient mean than retesting positive samples.

Heterophilic antibody interference in commercial immunoassays; a screening study using paired native and pre-blocked sera

Heterophilic antibodies are still an important source of interference in immunoassays. We have conducted a screening study for interference in a panel of commercially available assays using two sera known to contain high titer Fc-reactive heterophilic antibodies.

The sera were distributed to laboratories participating in the Nordic External Quality Assessment cooperation (EQANord). Duplicate samples pre-blocked with aggregated murine monoclonal MAK33 were also supplied. Discrepancies (>50%) between the results for native and blocked samples were used to classify the tested assays as susceptible to interference. A total of 170 different assay kits covering 91 analytes were tested.

We found that 21 assays, covering 19 different analytes, were susceptible to interference from the heterophilic antibodies in the two sera. Many of these are clinically and commercially important assays. Some of the false results were grossly elevated and could have been detrimental to patient care in a clinical setting.

Heterophilic antibodies with Fc-reactivity remain a threat. A more widespread use of antibody fragments and aggregated immunoglobulin could potentially improve the heterophilic antibody resistance of assays intended for clinical use.