Misleading hyperprolactinaemia in pregnancy

Cross-reactivity in assays for prolactin and optimum screening policy for macroprolactinaemia

OBJECTIVES

Macroprolactin cross-reacts in immunoassays for prolactin causing apparent hyperprolactinaemia (macroprolactinaemia) and consequent misdiagnosis and mismanagement of patients.

METHODS

We determined the prevalence of macroprolactinaemia using prolactin immunoassays with reported "high" (Tosoh) or "low" cross-reactivity (Roche) with macroprolactin. We additionally modelled the effects of increasing the screening threshold on workload and sensitivity in the detection of macroprolactinaemia.

RESULTS

A review of routine requests for prolactin received in a 12 month period identified 670 sera with hyperprolactinaemia (Tosoh assay). Treatment with polyethylene glycol (PEG) precipitation demonstrated normal levels of monomeric prolactin in 165 sera (24.6%) indicating macroprolactinaemia. In the macroprolactinaemic cohort, total prolactin levels were lower with the Roche assay (473 ± 132 mU/L; mean ± SD) compared to the Tosoh assay (683 ± 217 mU/L), p < 0.005. The prevalence of macroprolactinaemia was also lower with the Roche assay (6.2%). The number of samples that required screening for macroprolactinaemia fell by 14% when Roche gender specific total prolactin reference limits were applied. Use of a higher screening threshold (700 mU/L) reduced the screening workload considerably (Roche by 45%, Tosoh by 37%) however, the sensitivity of detection of macroprolactinaemia decreased markedly (Roche 90%, Tosoh 59%).

CONCLUSIONS

Macroprolactin interferes in both Tosoh and Roche prolactin immunoassays. Use of an assay with a relatively low cross reactivity with macroprolactin, e.g. Roche, will lead to a modest reduction in the screening workload. Increasing the screening threshold above the upper limit of the assay reference interval will also reduce the screening workload but leads to disproportionate increases in the number of cases of macroprolactinaemia which are missed.

Evaluation of autoantibodies and immunoglobulin G subclasses in women with suspected macroprolactinemia

BACKGROUND

Macroprolactin mostly composed of an immunoglobulin G (IgG) and a monomeric prolactin (PRL) represents the major circulating PRL form in the patients with macroprolactinemia that are usually asymptomatic and may not require treatment. In this study, we aimed to evaluate the prevalence of antithyroid and antinuclear antibodies, as well as the IgG subclass distributions in the patients suspected for macroprolactinemia.

METHODS

From January to July in 2018, totally 317 patients with elevated PRL were subjected to the polyethylene glycol (PEG) precipitation assay. The patients with recovery rates of ≤60% were subjected for IgG subclass determination and autoantibody testing including thyroid peroxidase antibody (aTPO), antithyroglobulin antibody (aTG), and antinuclear antibodies (ANA).

RESULTS

The higher the post-PEG PRL recovery rates, the less typical hyperprolactinemia symptoms and the higher prevalence of autoantibodies were observed. The IgG1 and IgG3 were the predominant subclasses in the PRL-IgG complexes according to the immunoprecipitation experiments.

CONCLUSION

The patients with post-PEG PRL recovery rates of <40% and 40%-60% were likely to represent two distinct populations of different clinical presentations. The prevalence of autoantibodies and IgG subclasses distribution suggested their pathogenic significance in the development of macroprolactinemia.

The epidemiology, diagnosis and treatment of Prolactinomas: The old and the new

Prevalence and incidence of prolactinomas are approximately 50 per 100,000 and 3-5 new cases/100,000/year. The pathophysiological mechanism of hyperprolactinemia-induced gonadotropic failure involves kisspeptin neurons. Prolactinomas in males are larger, more invasive and less sensitive to dopamine agonists (DAs). Macroprolactin, responsible for pseudohyperprolactinemia is a frequent pitfall of prolactin assay. DAs still represent the primary therapy for most prolactinomas, but neurosurgery has regained interest, due to progress in surgical techniques and a high success rate in microprolactinoma, as well as to some underestimated side effects of long-term DA treatment, such as impulse control disorders or impaired quality of life. Recent data show that the suspected effects of DAs on cardiac valves in patients with prolactinomas are reassuring. Finally, temozolomide has emerged as a valuable treatment for rare cases of aggressive and malignant prolactinomas that do not respond to all other conventional treatments.

Reference ranges for serum total and monomeric prolactin for the current generation Abbott Architect assay

BACKGROUND

Exclusion of macroprolactinaemia, a well-recognised interference, as the cause of hyperprolactinaemia is essential to avoid potential misdiagnosis and mismanagement of patients. We have derived gender-specific serum total and post-polyethylene glycol (PEG) precipitation monomeric reference ranges for the recently re-standardised Abbott Architect prolactin assay.

METHODS

Prolactin was measured in serum samples obtained from males (n=49) and females (n=52) using the current Abbott Architect immunoassay pre- and post-PEG precipitation. Gender-specific reference ranges were derived for total and monomeric (post-PEG) prolactin. Routine patients' samples (n=175) with a serum total prolactin >700 mIU/L were screened for macroprolactinaemia to assess classification compared with our previous post-PEG precipitation percentage recovery-based approach.

RESULTS

Reference ranges for serum total prolactin were 58-419 mIU/L (male) and 63-561 mIU/L (female). Male and female monomeric prolactin reference ranges were 32-309 mIU/L and 39-422 mIU/L, respectively. Mean (SD) post-PEG percentage recovery of the IS 84/500 prolactin standard was 80 (2.3)%. Of 175 patients' samples screened for macroprolactinaemia, 149 had monomeric prolactin concentrations (median monomeric prolactin=1035 mIU/L; median recovery=83%) above the gender-specific reference range. Monomeric prolactin concentrations (median monomeric prolactin=162 mIU/L; median recovery=20%) in the remaining 26 were within the reference ranges. One patient classified as macroprolactin positive and another classified as macroprolactin negative would not have been identified as such using the previous recovery-based approach.

CONCLUSIONS

The use of post-PEG monomeric reference ranges not only identifies hyperprolactinaemia due solely to macroprolactinaemia but has the added advantage of identifying patients who have simultaneous true monomeric hyperprolactinaemia and elevated concentrations of macroprolactin.

Determination of prolactin: the macroprolactin problem

Serum prolactin is frequently measured when investigating patients with reproductive disorders and elevated concentrations are found in up to 17% of such cases. Clinical laboratories rely predominantly on automated analysers to quantify prolactin levels using sandwich immunometric methodologies. Though generally robust and reliable, such immunoassays are susceptible to interference from a high molecular mass prolactin/IgG autoantibody complex termed macroprolactin. While macroprolactin remains reactive to varying degrees in all prolactin immunoassays, it exhibits little if any biological activity in vivo and consequently its presence is considered clinically irrelevant. Macroprolactinaemia, defined as hyperprolactinaemia due to excess macroprolactin with normal concentrations of bioactive monomeric prolactin, may lead to misdiagnosis and mismanagement of hyperprolactinemic patients if not recognised. Current best practice recommends that all sera with elevated total prolactin concentrations are sub-fractionated using polyethylene glycol precipitation to provide a more meaningful clinical measurement of the bioactive monomeric prolactin content. Manufacturers of prolactin assays should strive to minimise interference from macroprolactin in their assays. Clinical laboratories should introduce screening procedures to exclude macroprolactinaemia in all patients identified as having hyperprolactinaemia. Clinicians should be aware of this potential diagnostic pit fall and insist on PEG screening of all hyperprolactinaemic sera.

Serum Total Prolactin and Monomeric Prolactin Reference Intervals Determined by Precipitation with Polyethylene Glycol: Evaluation and Validation on Common ImmunoAssay Platforms

Background: Macroprolactin is an important source of immunoassay interference that commonly leads to misdiagnosis and mismanagement of hyperprolactinemic patients. We used the predominant immunoassay platforms for prolactin to assay serum samples treated with polyethylene glycol (PEG) and establish and validate reference intervals for total and monomeric prolactin.

Methods: We used the Architect (Abbott), ADVIA Centaur and Immulite (Siemens Diagnostics), Access (Beckman Coulter), Elecsys (Roche Diagnostics), and AIA (Tosoh) analyzers with samples from healthy males (n = 53) and females (n = 93) to derive parametric reference intervals for total and post-PEG monomeric prolactin. Concentrations of immunoreactive prolactin isoforms in serum samples from healthy individuals were established by gel filtration chromatography (GFC). We then used samples from 22 individuals whose hyperprolactinemia was entirely attributable to macroprolactin and 32 patients with true hyperprolactinemia to compare patient classifications and prolactin concentrations measured by GFC with the newly derived post-PEG reference intervals.

Results: Parametric reference intervals for post-PEG prolactin in male and female serum samples, respectively, were (in mIU/L): 61–196, 66–278 (Centaur); 63–245, 75–381 (Elecsys); 70–301, 92–469 (Access); 72–229, 79–347 (Architect); 73–247, 83–383 (AIA); and 78–263, 85–394 (Immulite). Concordance between GFC and immunoassay-specific post-PEG reference intervals was observed in 311 of 324 cases and for 31 of 32 patients with true hyperprolactinemia and 17 of 22 patients with macroprolactinemia. Results leading to misclassification occurred in a few analyzers for 5 macroprolactinemia patient samples with relatively minor increases in post-PEG prolactin (mean 61 mIU/L).

Conclusions: Our validated normative reference data for sera pretreated with PEG and analyzed on the most commonly used immunoassay platforms should facilitate the more widespread introduction of macroprolactin screening by clinical laboratories.

Technology insight: measuring prolactin in clinical samples

Measurement of prolactin is one of the most commonly undertaken hormonal investigations in evaluating patients with reproductive disorders. Hyperprolactinemia is found in up to 17% of such cases. Diagnostic evaluation of hyperprolactinemia is difficult but is facilitated by a logical approach where a thorough patient history is obtained, secondary causes of hyperprolactinemia are excluded, and the limitations of current prolactin assays are appreciated. Once hyperprolactinemia has been confirmed, attempts to establish the underlying cause can start. Given current workloads, laboratories rely on automated platforms to measure prolactin, most of which employ two-site immunoassay sandwich methods. Although generally robust and reliable, such immunoassays are susceptible to interference, and good collaboration between clinicians and the laboratory helps to minimize problems. A major challenge facing laboratories is correct differentiation of patients with true hyperprolactinemia from those with macroprolactinemia. Macroprolactin is a high-molecular-mass, biologically inactive form of prolactin that is detected to varying degrees by all prolactin immunoassays. Conservative estimates suggest that the presence of macroprolactin leads to misdiagnosis in as many as 10% of all reported instances of biochemical hyperprolactinemia. In the absence of specific testing, macroprolactin represents a diagnostic pitfall that results in the misdiagnosis and mismanagement of large numbers of patients.

Specificity and Clinical Utility of Methods for the Detection of Macroprolactin

Background: Increased serum concentrations of macroprolactin are a relatively common cause of misdiagnosis and mismanagement of hyperprolactinemic patients.

Methods: We studied sera from a cohort of 42 patients whose biochemical hyperprolactinemia was explained entirely by macroprolactin. Using 5 pretreatments, polyethylene glycol (PEG), protein A (PA), protein G (PG), anti-human IgG (anti-hIgG), and ultrafiltration (UF), to deplete macroprolactin from sera before immunoassay, we compared residual prolactin concentrations with monomer concentrations obtained by gel-filtration chromatography (GFC). A monomeric prolactin standard was used to assess recovery and specificity of the pretreatment procedures.

Results: Residual prolactin concentrations in all pretreated sera differed significantly (P &lt;0.001) from monomeric concentrations obtained after GFC. PEG underestimated (mean, 75%), whereas PA, PG, anti-hIgG, and UF overestimated (means, 178%, 151%, 178%, and 112%, respectively) the amount of monomer present. Of the 5 methods examined, PEG correlated best with GFC (r = 0.80) followed by PG (r = 0.78), PA (r = 0.72), anti-hIgG (r = 0.70), and UF (r = 0.61). After UF or pretreatment with anti-hIgG or PEG, recovery of monomeric prolactin standard was low: 60%, 85%, and 77% respectively. In contrast, pretreatment with PA or PG gave almost quantitative recovery.

Conclusions: None of the methods examined yielded results identical to the GFC method. PEG pretreatment yielded results that correlated best and is recommended as the first-choice alternative to GFC.

Macroprolactinemia: the consequences of a laboratory pitfall

The objective of this study was to assess the prevalence of macroprolactin, a macromolecule with reduced bioactivity, in hyperprolactinemic patients. Prolactin was measured before and after precipitation of macroprolactin by polyethylene glycol in 306 patients. Only patients with prolactin values >700 mIU/L (n = 270) entered the study. In 23% of the patients, macroprolactinemia was found. In women, the occurrence of macroprolactinemia increased with advancing age (< 30 yr: 16%; 30-45 yr: 28%; > 45 yr: 42%; p < 0.05). A priori clinical signs of hyperprolactinemia (morphological abnormalities in pituitary imaging, galactorrhea infertility) occurred significantly less frequently in macroprolactinemia than in true hyperprolactinemia. In eight females macroprolactinemia and true hyperprolactinemia appeared simultaneously. To avoid diagnostic and therapeutic pitfalls, the screening for macroprolactinemia of all patients with prolactin levels of > 700 mIU/ L is recommended.

Frequent misdiagnosis and mismanagement of hyperprolactinemic patients before the introduction of macroprolactin screening: application of a new strict laboratory definition of macroprolactinemia

BACKGROUND

Macroprolactin (big big prolactin) has reduced bioactivity and is measured by immunoassays for prolactin when it accumulates in the plasma of some individuals. We applied normative data for serum prolactin after treatment of sera to remove macroprolactin to elucidate the contribution of macroprolactin to misleading diagnoses, inappropriate investigations, and unnecessary treatment.

METHODS

We reviewed records of women attending a tertiary referral center who had prolactin >1000 mIU/L. Application of a reference interval to polyethylene glycol (PEG)-treated hyperprolactinemic sera identified 21 patients in whom hyperprolactinemia was accounted for entirely by the presence of macroprolactin. Presenting clinical features, diagnoses, and treatment were compared in these patients and 42 age-matched true hyperprolactinemic patients.

RESULTS

Prolactin concentrations in sera of 110 healthy individuals ranged from 78 to 564 mIU/L. The range of values for the sera after PEG treatment was 70-403 mIU/L. For macroprolactinemic samples, PEG treatment decreased mean (SD) prolactin from 1524 (202) mIU/L to 202 (27) mIU/L but decreased it only from 2096 (233) mIU/L to 1705 (190) mIU/L in true hyperprolactinemic patients (P <0.01 between groups). Oligomenorrhea or amenorrhea and galactorrhea were the most common clinical features in both groups, although they occurred more frequently in true hyperprolactinemic patients (P <0.05). Serum estradiol and luteinizing hormone concentrations were significantly higher in participants with macroprolactinemia than in those with true hyperprolactinemia (P <0.05). Among participants with retrospectively identified macroprolactinemia, pituitary imaging was performed in 93% and treatment with dopamine agonist was prescribed in 87%.

CONCLUSIONS

Macroprolactin is a significant cause of misdiagnosis, unnecessary investigation, and inappropriate treatment. The use of an appropriate reference interval for the PEG immunoprecipitation procedure may be of particular importance in those patients who have an excess of both macroprolactin and monomeric prolactin.

Gross variability in the detection of prolactin in sera containing big big prolactin (macroprolactin) by commercial immunoassays

A high molecular mass form of prolactin (PRL), macroprolactin, accumulates in the sera of some subjects. Although macroprolactin exhibits limited bioactivity in vivo, it retains immunoreactivity. We examined the frequency of macroprolactinemia in clinical practice and the ability of immunoassay systems to distinguish between macroprolactin and monomeric PRL. Of 300 hyperprolactinemic sera identified, 71 normalized following treatment of sera with polyethylene glycol, indicating that 24% of hyperprolactinemia could be accounted for by macroprolactin. Ten of these macroprolactinemic sera were circulated to 18 clinical laboratories. Two sets of PRL measurements of the 10 untreated sera were obtained from each of the nine most commonly used immunoassay systems. Across the nine assay systems, differences in the PRL estimates ranged from 2.3- to 7.8-fold. Elecsys users reported the highest PRL levels. Somewhat lower values were reported for DELFIA systems followed by Immuno-1, AxSYM, and Architect assays. The Immulite 2000 assay generated PRL levels equivalent to approximately 50% of those reported by the high-reading methods. The lowest PRL levels were reported by Access, ACS:180, and Centaur systems. To avoid confusion caused by the frequent presence of macroprolactin accounting for hyperprolactinemia, secondary screening for the presence of macroprolactin is recommended.

Reactivity of macroprolactin in common automated immunoassays

OBJECTIVES

To evaluate a simple assay for macroprolactin for use with the Bayer Immuno 1 analyzer, and to compare the reactivity of macroprolactin in commonly used automated prolactin assays.

METHODS

Macroprolactin in serum was precipitated in a buffer containing 13.3% polyethylene glycol (PEG) 8000, redissolved, and assayed on the Bayer Immuno 1 for PRL. Presence of macroprolactin was confirmed in some sera by FPLC using a Pharmacia Superose 12 column, followed by prolactin assay of the fractions on the Immuno 1. Sera with and without macroprolactin were then also assayed on the Abbott AxSYM, Bayer Centaur, Beckman Access, and Roche Elecsys.

RESULTS

The PEG precipitation assay is simple and reproducible (CVs < 15%), and we established a normal range of < 20% precipitation of total PRL by PEG. The assay correlates well with the amount of macroprolactin separated by FPLC as a peak with a MW of approximately 180 kDa. Macroprolactin showed the following cross-reactivities in commonly used PRL assays: Roche Elecsys > Bayer Immuno 1 > Abbott AxSYM > Bayer Centaur > Beckman Access, with the Centaur showing more variability than other assays.

CONCLUSION

Macroprolactin can be easily quantitated using the Immuno 1 PRL assay after PEG precipitation. It cross-reacts to different degrees with common prolactin assays, and is a major source of variability between them.