Fyffe-Freil, Ria

Abstract Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (“Mass-Fix”) has replaced serum immunofixation at our institution for detection of monoclonal immunoglobulins. One advantage of Mass-Fix is the ability to differentiate pathogenic endogenous monoclonal antibodies from therapeutic monoclonal antibodies (t-mabs), which are often the first-line treatment for multiple myeloma, by reviewing the light chain signature mass. The objective of this study was to describe the distribution of t-mabs and other key characteristics of clinical serum samples analyzed by Mass-Fix in 2022. Comprehensive results for each sample were extracted retrospectively from the laboratory information system. Of 66,710 total analyzed, 30,701 (46%) samples were reported as “positive” (i.e., contains a monoclonal protein), given the tertiary nature of our institution and reference laboratory services. The positive samples were further subdivided by t-mab (detected by Mass-Fix), with a total of 7,769 (25.3%) t-mabs reported. The top five IgG kappa t-mabs reported include daratumumab (n=6,537), elotuzumab or REGN5458/5459 (n=499), isatuximab (n=348), and rituximab (n=102). Rare observations included monoclonal proteins consistent with tixagevimab/ cilgavimab, for COVID-19 infection (n=7), obinutuzumab, an anti-CD20 t-mab for multiple sclerosis (n=1) and evolocumab, an IgG lambda anti-PCSK9 inhibitor (n=6). Of the 7,769 samples, the t-mab was the only reported clone in 47.7% of cases and was found along with the original disease-associated clone in remaining cases. When the original disease clone was present, it was an IgG kappa isotype 31% of the time and could have confounded the definition of complete therapy response for patients. 69% were non-IgG kappa original clones. Mass-Fix test orders have a multiple-choice prompt to provide any current therapy to aid in the patient’s result interpretation. For those samples where a t-mab was reported, the answer to this question regarding administered therapy was often discrepant from the report: only 38.5% of daratumumab-positive samples had an affirmation of daratumumab administration. The remaining 61.5% of daratumumab-positive samples reported an assortment of therapies, including bone marrow transplant, other t-mabs, no active therapy, or the field was left blank, highlighting poor compliance. Additionally, 154/36,009 samples where the provider affirmed daratumumab administration were reported as negative (i.e., no monoclonal protein observed on Mass-Fix). Often, the send-out laboratory does not have medical record access where treatment information is detailed. In conclusion, we reported the presence of a t-mab in 11.6% of all samples tested with Mass-Fix, suggesting that t-mabs have entered the clinical practice to stay, and accurately determining their presence in the challenging environment of poor compliance to prompt questions and evolving treatment regimens is something that cannot be ignored by clinical laboratories. Mass-Fix allows detection of a t-mab in the same routine run as other testing, without need of a second immunofixation to rule out the IgG kappa finding is not a t-mab.

Abstract Background Measuring the concentration of albumin, amylase, bilirubin, cholesterol, creatinine, glucose, lactate dehydrogenase (LDH), lipase, total protein(TP), triglycerides, and urea nitrogen(UN) in body fluids(BFs) provides important information to aid in clinical decision-making. The range of expected values of these analytes in BFs may not match serum, and the distribution by fluid type is not well described. Quality control (QC) materials are designed to reflect clinically relevant concentrations in blood. Hence, the measuring ranges for assays modified for BF testing vary in suitability. Laboratorians and manufacturers would benefit from understanding the overlap in BF and serum analyte concentrations. The aim of this study was to characterize the range of BF analyte concentrations compared to serum and assess the suitability of QC materials used on these assays. Methods A retrospective analysis was performed for the following analytes in BFs with reportable ranges(including maximum dilution factor): albumin = 0.2–12.0 g/dL(×2), amylase = 3–14 000 U/L(×100), bilirubin = 0.1–72.2 mg/dL(×2), cholesterol = 4–8000 mg/dL(×10), creatinine = 0.1–92.0 mg/dL(×4), glucose = 2–3375 mg/dL(×5), LDH = 10–9000 U/L(×10), lipase = 3–300 000 U/L(×1000), TP = 0.2–36.0 g/dL(×3), triglycerides = 4–8850 mg/dL(×10), and UN = 2–300 mg/dL(×3). Chemistry tests were run on a cobas® 6000 c501 (Roche Diagnostics,Indiana). Patient analyte concentration and fluid type results reported between 9/16/2019 and 1/27/2022 at all Mayo Clinic locations were extracted from an institutional database of electronic medical record data. Serum results were included for comparison. Descriptive statistical analyses (median and range) were performed with R (version 4.2.2)/R Studio(version 2022.12.0). QC materials for BF testing were purchased from Bio-Rad (Multilevel Qual, Levels 1 and 3; Hercules, CA, USA). Target concentrations are reported. Results Conclusion BF median (range) concentrations are similar or higher for bilirubin, creatinine, glucose, lipase, and UN. Serum QC material is likely appropriate for these assays in BFs. BF median(range) concentrations are lower for albumin, cholesterol, TP, and triglycerides suggesting that serum QC material may not be well suited for BFs. The need for extended dilutions may impact BF amylase and lipase.

Abstract Background Hemolysis is a pre-analytic issue that challenges clinical laboratories. When a specimen with significant hemolysis is obtained in our laboratory, tests where the hemolysis threshold is exceeded are not reported and blood is recollected. Unfortunately, in a subset of patients, the recollected specimen is also hemolyzed (termed “recurrent hemolysis”). In these cases, the second recollection utilizes special collection and handling protocols (i.e., hand-carried to lab, plasma collection, etc.) to mitigate preventable causes of hemolysis. Lipemia is also a known contributor to specimen hemolysis. Mayo Clinic Rochester experienced an increased rate of hemolysis as well as recurrent hemolysis during the height of the COVID-19 pandemic (January 2022). The objective of this study was to investigate the increased rate of recurrent hemolysis and compare to a rate prior to the COVID-19 pandemic (January 2019). Methods Retrospective data analysis was performed for January 2019 (negative control) and January 2022. The number of Mayo Clinic Rochester hospital admissions, admitting diagnosis, medications administered, and number of test collections performed were obtained using reporting functionality in our Electronic Health Record (EHR), Epic. The Laboratory Information System, SoftLab, was utilized to obtain recollection rates due to hemolysis. Data were normalized to total patient admissions for the specified period to account for inter-year variability. R/R Studio was utilized to analyze and visualize the data. Pearson’s Chi-squared test for independence was performed on categorical variables (significance defined as P < 0.05). Results A 28% decrease in hospital admissions (n = 3958:Jan-22 vs n = 5517:Jan-19) and a 23% decrease in total specimens collected on hospitalized patients (n = 40 557:Jan-22 vs n = 52 373:Jan-19) was observed between Jan-19 to Jan-22. However, the laboratory observed a 6% increase in hemolyzed specimens (n = 256:Jan-22 vs n = 241:Jan-19). Recurrent hemolysis occurred in 24% (n = 62/256) of Jan-22 and 17% (n = 43/241) of Jan-19 hemolyzed specimens and required special handling protocols. COVID positive patients comprised 48% (n = 30/62) of those requiring special handling protocols in Jan-22. Further examination revealed 34% (n = 21/62) of Jan-22 and 12% (n = 5/43) of Jan-19 cases of recurrent hemolysis were due to lipemia (P < 0.01). Chart review highlighted a potential source of lipemia from the administration of propofol, a lipophilic sedative emulsion. Of those COVID positive cases with recurrent hemolysis due to lipemia (n = 15/30), 93% (n = 14/15) were receiving propofol at the time of collection (P < 0.001). Conclusion We observed increased rates of specimen hemolysis during the COVID-19 pandemic. While most hemolysis resolves upon specimen recollection, patients with recurrently hemolyzed specimens often require special specimen collection and handling protocols to mitigate hemolysis. Approximately half of the recurrent hemolysis cases in Jan 2022 were COVID-19 positive patients. Lipemia-induced hemolysis was also more frequent in this patient population presumably due to the administration of propofol, a lipophilic emulsion sedative commonly used for COVID positive patients requiring sedation and ICU-level care. It is critical to understand the variety of factors which may contribute to recurrent hemolysis, as intervening with specialized collection and handling protocols to reduce observed pre-analytical hemolysis is required to provide accurate and timely laboratory results.

Abstract Cholestatic liver diseases, such as primary sclerosing cholangitis and primary biliary cirrhosis, can lead to serum accumulation of lipoprotein X (LpX). LpX is a multilamellar particle high in cholesterol but lacking structural apolipoproteins A1 or B. The absence of ApoB results in no negative feedback on cholesterol biosynthesis and prevents LpX clearance from the liver. While clinical signs and symptoms typically precede laboratory findings, it is possible that in medically complex patients the identification of LpX could be the first observation of cholestatic liver disease. Traditional laboratory methods are insufficient to identify LpX as it is of similar density to low-density lipoprotein (LDL). LpX contains a high concentration of cholesterol which is erroneously reported as LDL-C by routine clinical methods. As LpX is a rare complication of liver disease, clinicians may presume the elevation is a coincidental familial hypercholesterolemia rather than a sequela of liver disease. Currently, lipoprotein gel electrophoresis is the only laboratory method to identify LpX. In this method only performed in specialty lipid laboratories, LpX is readily identified by its unique reverse electrophoretic mobility relative to other lipoproteins. The objective of this study was to characterize lipid panels from LpX-positive samples and develop a suitable mechanism to identify LpX-containing samples with good clinical validity. From 21,377 clinical electrophoresis results reported between Nov 2011 to Nov 2021, LpX was identified in 157 serum samples. Overall, patients with LpX were younger (median 44y vs. 55y, p<0.0001) with significantly higher total cholesterol (812mg/dL vs 190mg/dL, p<0.0001) and lower high density lipoprotein-cholesterol (HDL-C; 3mg/dL vs 45mg/dL, p<0.0001). Data were randomly split (70/30) into training (n=14,964) and testing (n=6,413) cohorts. Receiver operator characteristic curve analysis identified optimal thresholds of 22.5 mg/dL HDL-C (AUC = 0.94) and 378.5 mg/dL total cholesterol (AUC = 0.91), as well as a nonHDL-C/HDL-C ratio of 9.2 (AUC = 0.995). Applying these cutoffs to the testing cohort achieved a sensitivity/specificity of 98%/81% for HDL-C, 96%/87% for total cholesterol, and 98%/94% for nonHDL-C/HDL-C ratio. A multivariate model combining these three parameters showed a sensitivity/specificity of 97%/85%, respectively. In conclusion, low HDL-C, elevated total cholesterol and a ratio of nonHDL-C/HDL-C >9.2 are associated with the presence of LpX. The ratio of nonHDL-C/HDL-C is the most sensitive and specific predictor of LpX. If confirmed in other cohorts, laboratories could include a reporting comment on lipid panels with a nonHDL-C/HDL-C ratio >9.2 cautioning a high suspicion for the presence of LpX and recommending confirmatory testing. It may also be prudent to caution that LDL-C results may not be accurate. In conclusion, identifying patients with high suspicion of LpX based on abnormal lipid panel results may aide in clinical diagnosis, even when an assay to detect LpX is not readily available.

Background: There is limited long-term follow-up of patients undergoing parathyroidectomy. Recurrence is described as 4% to 10%. This study evaluated persistence and recurrence of hypercalcemia in primary hyperparathyroidism after parathyroidectomy. Methods: Single-institution retrospective (1965–2010) population-based cohort from Olmsted County (MN) of patients undergoing surgery for primary hyperparathyroidism. Patients’ demographic data, preoperative and postoperative laboratory values, clinical characteristics, surgical treatment, and follow-up were noted. Results: A total of 345 patients were identified, 75.7% female, and median age 58.4 years [interquartile range (IQR): 17.6]. In all, 68% of patients were asymptomatic and the most common symptoms were musculoskeletal complaints (28.4%) and nephrolithiasis (25.6%). Preoperative median serum calcium was 11 mg/dL (IQR: 10.8–11.4 mg/dL), and median parathyroid hormone was 90 pg/mL (IQR: 61–169 pg/dL). Bilateral cervical exploration was performed in 38% and single gland resection in 79% of cases. Median postoperative serum calcium was 9.2 mg/dL (IQR: 5.5–11.3). Nine percent of patients presented persistence of hypercalcemia, and recurrence was found in 14% of patients. Highest postoperative median serum calcium was 10 mg/dL (IQR: 6–12.4), and median number of postoperative calcium measurements was 10 (IQR: 0–102). Postoperative hypercalcemia was identified in 37% of patient. Fifty-three percent were attributed to secondary causes, most commonly medications, 22%. Three percent of patients required treatment for postoperative hypercalcemia. Median time to recurrence and death were 12.2 and 16.7 years, respectively. Conclusion: Recurrent hypercalcemia after successful parathyroidectomy is higher than previously reported. Most cases are transient and often associated to other factors with only the minority requiring treatment. Long-term follow-up of serum calcium should be considered in patients after successful parathyroidectomy.