Serum Protein Electrophoresis Tests Research Articles

Clinical and Laboratory Indications for Serum Protein Electrophoresis Testing in US Veterans: A Retrospective Cohort Study

Introduction: Serum Protein Electrophoresis (SPEP) is a frequently ordered diagnostic test when there is suspicion of plasma cell dyscrasia, based on clinical or laboratory abnormalities. This study describes the demographic characteristics of US Veterans who underwent SPEP testing, evaluates the distribution of clinical and laboratory abnormalities, and their influence on SPEP test ordering by Veteran Health Administration (VHA) providers. Methods: The study employed a retrospective cohort design utilizing national data from the VHA. We included Veterans aged 50-65 years who had a total protein test performed at any time. Veterans who were dually enrolled in VHA and Medicare were excluded because of the unavailability of laboratory data in Medicare. An ordered SPEP was defined by Current Procedural Terminology codes of 84165 or 83883. Multivariable logistic regression was performed to examine the association of SPEP testing with clinical and laboratory indications, including, chronic kidney disease, anemia, pathologic fractures, vertebral fracture, neuropathy, total protein level, hypercalcemia, and body mass index, as well as sociodemographic factors, including, race, sex, socioeconomic status, and geographic location. The clinical and laboratory indications were selected based on literature review and clinicians' input. For patients who received SPEP testing, data on these indications within one year before their initial SPEP test were used. For patients who did not receive SPEP testing, these indications were collected within one year of their most recent total protein test. Result: Between 1999 and 2022, 294,640 Veterans were identified, with 17,035 (5.78%) undergoing SPEP testing. Veterans who had SPEP testing were mostly male (77%), White (51%), and frequently obese (BMI>30 kg/m 2) (42%). In addition, 17% of these Veterans who had SPEP testing had neuropathy, 15% had anemia, 11% had chronic kidney disease, 4% had a total protein level > 8.5gm/dL, and 2% had hypercalcemia. Only 0.5% had pathologic fractures and 0.5% had vertebral fractures. VHA providers ordered SPEP tests more often in African American Veterans than White Veterans (OR 1.34, 95% CI 1.29-1.39), and less often in underweight (BMI < 18.5 kg/m 2) Veterans compared to normal-weight (18.5-24.9 kg/m 2) Veterans (OR 0.55, 95% CI 0.40-0.74). SPEP testing was more likely in Veterans having total protein level >8.5gm/dL (OR 3.87, 95% CI 3.47-4.32), vertebral fracture (OR 3.44, 95% CI 2.47-4.81), anemia (OR 3.26, 95% CI 3.06-3.48), hypercalcemia (OR 3.04, 95% CI 2.53-3.65), neuropathy (OR 2.55, 95% CI 2.43-2.69), pathologic fracture OR 2.38, 95% CI 2.38-1.52), and chronic kidney disease (OR 1.97, 95% CI 1.81-2.14) compared to Veterans without the respective indication. Conclusions: VHA providers were likely to order a SPEP for protein level >8.5gm/dL, vertebral fracture, anemia, hypercalcemia, neuropathy, pathologic fracture, and chronic kidney disease. Obesity and demographic factors such as African American race were also associated with SPEP testing. Further research is needed to evaluate the combined influence of these factors on SPEP testing, as well as factors that lead clinicians to order multiple SPEP tests prior to the diagnosis of plasma cell dyscrasias.

Update on the Outcome of M-Protein Screening Program of Multiple Myeloma in China: A 7-Year Cohort Study

Background: To improve the early detection rate of multiple myeloma(MM), the M-protein screening system has been performed in hospital population at Zhongshan Hospital Fudan University since 2014, with electrophoretic-based screening integrated into routine blood tests. This study updated the 7-year follow-up findings of MM patients diagnosed by screening-driven and end-organ symptom-driven pattern. Methods: The retrospective study compared the characteristics and results of two alternative diagnosis patterns by reviewing the plasma cell disease database of MM patients diagnosed between January 2014 and October 2021 at hospital. Screening-driven patients were classified as having an incidental finding of M-protein during workup of unrelated medical conditions or routine body check-up, while symptom-driven patients exhibited myeloma-related end-organ damage's symptoms. Results: Over 300 million serum protein electrophoresis tests were performed during 7 years, with 1-2 percent yielding positive results, prompting patients to seek further examination. Of 911 confirmed MM cases (concurrent amyloidosis excluded), 366 were assigned to the screening-driven group while 545 were to the symptom-driven group. In comparison to the symptom-driven group, the screening group had more IgG phenotypes (P=0.001), earlier ISS stages(P<0.001), fewer disease-related symptoms (hypercalcemia, renal insufficiency, anemia and bone lesion), lower ECOG scores (P<0.001), less extramedullary disease (P<0.001), a lower rate of bone marrow plasma cells(P<0.001), and lower level of lactate dehydrogenase(LDH)(P=0.018) at baseline. Regarding first-line therapy, it was found that while both groups had comparable exposure to proteasome inhibitor and immunomodulatory drugs as well as rates of the best efficacy, the screening group was more likely to have >2-drug regimens and ≧ 6 induction cycles than the other group. Patients detected through screening had a significantly longer median progression-free survival (PFS) time than the symptom-driven group (62.2 VS 24.9 months) with median follow-ups of 32.9 and 27.8 months, respectively. Furthermore, the screening group did not achieve the median overall survival (OS) time, which was 62.3 months in the symptom group. In multivariate cox analysis, the screening-driven diagnostic pattern remains an independent prognostic factor indicating favorable PFS and OS in MM patients after adjusting for well-acknowledge myeloma prognostic factors. Conclusion: Routine M-protein screening for MM in hospital patients results in an earlier diagnosis and better patient outcomes in China. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Positive findings in repeated serum protein electrophoresis tests after an initial negative result in patients without prior history of plasma cell disorders: a pilot retrospective database study

Positive findings in repeated serum protein electrophoresis tests after an initial negative result in patients without prior history of plasma cell disorders: a pilot retrospective database study

Diagnostic yield of repeated serum protein electrophoresis tests after an initial negative result: A pilot retrospective database study

Background: Serum protein electrophoresis is a laboratory test that detects monoclonal immunoglobulin. It is used to screen for plasma cell disorders. There is currently limited evidence concerning the diagnostic performance of repeat serum protein electrophoresis following an initial negative result. In this pilot retrospective observational study, we described the utility of repeat serum protein electrophoresis testing for new diagnoses of plasma cell disorders at a large tertiary health network.

Surveillance of Monoclonal Gammopathy of Undetermined Significance: A Proposed Change

Background:Monoclonal gammopathy of undetermined significance (MGUS) is a diagnosis that is often incidentally made after a serum protein electrophoresis (SPEP) is ordered as part of the evaluation for multiple nonspecific symptoms and is often ordered by non-hematologists. Currently, there is a lack of guidance regarding the extent of evaluation and follow-up required for these patients.Objective:Determine whether the risk stratification of the abnormal SPEP predicted progression to multiple myeloma (MM) or other lymphoplasmacytic malignancies (LPM) and could act as a guideline for appropriate follow-up in attempts to provide evidence-based, higher value care.Design:A retrospective review was performed of patients referred to the county hematology clinic for an abnormal SPEP from 2012 to 2019. The SPEP results were then risk-stratified and individual patient charts were reviewed to determine the symptomatology present at the time it was ordered, as well as the clinical course of the patients over time.Main Measures:Patients were stratified into low, low-intermediate, high-intermediate, and high risk groups for progression to MM based on the Mayo Clinic criteria. Additional information was also analyzed including the number of SPEP tests per patient, the indication stated for ordering the SPEP, and the presence of symptoms that are associated with MM at the time the SPEP was ordered, including anemia, renal failure, hypercalcemia, and bone lesions (commonly known as “CRAB symptoms”).Results:We abstracted data from 436 patients referred to the hematology clinic associated with a large county hospital system for an abnormal SPEP. The most common documented reasons for SPEP testing were increased creatinine (35%), protein gap (12%), and decreased hemoglobin (11%). Of these patients, 24 (5.5%) developed MM, 19 of whom were stratified into the high-intermediate risk group. More than a thousand SPEP results were obtained in the low and low-intermediate risk groups with only 5 patients diagnosed with MM. In the high-intermediate and low-intermediate risk groups, between 2-3 SPEP tests were performed prior to making the diagnosis of MM. In the low risk group, 6 SPEP tests were performed prior to reaching the MM diagnosis. Among the 5 patients in the low and low-intermediate risk groups who developed MM, all 5 had one or more of the CRAB symptoms at the time of the initial SPEP.Conclusion:Of the patients with MGUS who progressed to MM, approximately 80% were in the high-intermediate risk group. Of the remaining patients who progressed to MM from the lower risk groups, all had one or more of the previously mentioned CRAB symptoms, a higher percentage compared to the low and low-intermediate risk groups overall. In the absence of symptomatic disease, there is insufficient evidence to support serial SPEP testing in the lower risk patients. The use of evidence-based risk stratification may minimize unnecessary testing and hematology referrals while resulting in significant cost-savings and higher value care. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Designing an Expert System for the Diagnosis of Multiple Myeloma by Using Rough Set Theory

Background: One of the most interesting and important topics in the field of information systems and knowledge management is the concept of eliciting rules and collecting the knowledge of human experts in various subjects to be used in expert systems. Many scientists have used decision support systems to support businesses or organizational decision-making activities, including clinical decision support systems for medical diagnosis. Objective: In this study, a rough set based expert system is designed for the diagnosis of one type of blood cancer called multiple myeloma. In order to improve the validity of generated models, three condition attributes that define the shape of “Total protein”, “Beta2%” and “Gamma%” are added to the models to improve the decision attribute value domain. Method: In this study, 1100 serum protein electrophoresis tests are investigated and based on these test results, 15 condition attributes are defined. Four different rule models are obtained through extracting rules from reducts. Janson and Genetic Algorithm with "Full" and "ORR" approaches have been used to generate reducts. Results: The GA/ORR of the information system with 87% accuracy is used as an inference engine of an expert system and a unique user interface is designed to automatically analyze test results based on these generated models. Gamma% is detected as a core attribute of the information system. Conclusion: Based on the results of generating reducts, the Gamma% attribute is detected as a core of the information system. This means that information, which is resulted from this conditional attribute, has the greatest impact on the diagnosis of multiple myeloma. The GA/ORR model with 87% accuracy is selected as the inference engine of the expert system and finally, a unique user interface is created to help specialists diagnose multiple myeloma.

Post-MGUS Diagnosis Serum M-Protein Velocity and the Risk of Progression of MGUS to Multiple Myeloma

Introduction: Multiple myeloma (MM) is a common hematologic malignancy that is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS). The biology of this myelomagenesis has been studied; yet little is known about clinical predictors of progression of MGUS to MM. Studies have shown that higher serum M-protein concentrations at MGUS diagnosis are associated with MM, and M-protein concentrations change over time. We aimed to study whether the rate of rise in serum M-protein concentration between MGUS diagnosis and MM diagnosis - M-protein velocity - can predict the progression of MGUS to MM.Methods: Data from the U.S. Veterans Health Administration database were used. A cohort of patients diagnosed with MGUS between October 1, 1999 and December 31, 2009 were identified using the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code 273.1 and followed through August 6, 2013. MM diagnosis among these patients were identified by ICD-9-CM code 203.0 and the International Classification of Diseases for Oncology codes 9731/3, 9732/3, and 9734/3. Patient chart review was performed to verify MGUS and MM diagnoses and obtain data on M-protein concentration at MGUS diagnosis and immunoglobulin (Ig) subtype. We excluded patients with a diagnosis of human immunodeficiency virus; non-Ig G or non-Ig A patients; or patients with only one measurement of M-protein concentration between MGUS diagnosis and 6 months before MM diagnosis. MGUS patients who had progressed to MM were matched (in a 1:4 ratio) to those who had not developed MM based on age at MGUS diagnosis. To define M-protein velocity, we used all M-protein concentration values measured between MGUS diagnosis and 6 months before MM diagnosis. A 6-month M-protein velocity was computed as the rate of rise in M-protein per 6 months, and a patient can have ≥1 velocities between MGUS diagnosis and 6 months before MM diagnosis. To analyze the time between MGUS diagnosis and MM diagnosis, we used multivariable Cox model with the following covariates: sex, race, body mass index, comorbidities, and M-protein concentration at MGUS diagnosis; immunoglobulin G; and time-varying 6-month M-protein velocities.Results: A total of 900 MGUS patients were included in the analysis. Among them, 146 MGUS patients progressed to MM. As shown in Figure 1, an M-protein velocity of 1 g/dL increase per 6 months was associated with a significantly higher risk of progression to MM (hazard ratio, HR: 6.34; p<0.0001). An increasing level of M-protein concentration at MGUS diagnosis also increased the risk of the progression (HR: 3.23; p<0.0001 per 1 g/dL increase). Immunoglobulin G subtype was negatively associated with the risk of progression of MGUS to MM (HR: 0.40; p<0.0001).Conclusion: MGUS patients with M-protein concentrations increasing more than 1 g/dL per 6 months after MGUS diagnosis may be associated with a higher risk of progression to multiple myeloma. Close monitoring of serum M-protein concentration through serum protein electrophoresis tests after a diagnosis of MGUS is needed for early detection and timely treatment of this incurable malignancy. [Display omitted] DisclosuresSanfilippo:Bristol Meyers Squibb: Speakers Bureau. Carson:Seattle Genetics: Honoraria.

Detecting Cases of Monoclonal Gammopathy of Undetermined Significance in Electronic Health Data

Introduction: Multiple myeloma (MM) is known to be preceded by the largely asymptomatic and incidentally diagnosed condition monoclonal gammopathy of undetermined significance (MGUS). Retrospective studies estimate that 3% of all US adults aged ≥50 years have this premalignant condition, and that MGUS patients have a lifelong risk of progression to MM of about 1% per year. This persistent uncertainty results in heightened anxiety and clinical surveillance, and the associated financial burden. Recent population-based studies of MGUS have identified cases through testing stored blood specimens, an expensive and inefficient process that hinders initiation of large-scale studies of MGUS etiology and outcome. Thus, to facilitate population-based MGUS research, we are developing an algorithm to efficiently and accurately identify patients diagnosed with MGUS in longitudinally-collected automated healthcare claims and electronic health record (EHR) data. Our aim is to achieve maximum positive predictive value (PPV) with an algorithm that can be applied to large electronic health datasets to accurately identify MGUS cases for longitudinal studies of MGUS etiology, natural history, and health service utilization, minimizing the need for individual chart review.Methods: Men and women aged ≥50 years who sought care at a large, community-based healthcare provider group in central Massachusetts at least once between 2007 and 2015 and were enrolled for ≥12 months were eligible for this analysis. Patients diagnosed with MM prior to, or ≤3 months after the first MGUS diagnosis (ICD-9 code 273.1) were excluded. The MGUS case-finding algorithm was constructed using the Virtual Data Warehouse (VDW) at the Meyers Primary Care Institute. The VDW, which has been adopted by healthcare systems participating in the NCI-funded Cancer Research Network, is a distributed, standardized resource comprised of clinical and administrative data, and populated with linked demographic, administrative, outpatient laboratory, and healthcare utilization data.The first step of the algorithm identified all eligible patients with ≥2 MGUS diagnosis codes entered on different dates within a 12 month period. Next, we selected those patients who, within 90 days of MGUS diagnosis, had: A) ≥1 code for a serum protein electrophoresis test (CPT code 84155 or 84156); B) a serum or urine immunofixation test (CPT 86334 or 86335); and C) an office visit with an oncologist. Relevant protein electrophoresis test results, which typically appear as text in the EHR, were not extractable from available data, and thus patients met the algorithm criteria if the corresponding CPT code was present in their EHR. A targeted manual chart review, conducted by three nurse abstractors and adjudicated by two clinicians, validated the algorithm and constituted the gold standard for subsequent calculations of PPV.Results: The algorithm identified 833 subjects with ≥2 MGUS diagnosis codes in their EHR within a 12 month period; 429 (52%) patients met all four algorithm criteria. Records for 250 of the latter patients (58%) were selected for review. Potential MGUS cases meeting all four algorithm criteria were 85% white, 51% female, had a median of 10 MGUS diagnosis codes in their EHR, and a mean age of 74 years at diagnosis. In the underlying patient population, immunofixation was routinely ordered for patients with abnormal protein electrophoresis test results; thus, 98% of patients who had a protein electrophoresis test also had an immunofixation test, reducing the discriminatory capacity of this algorithm step. Review of the first 2% of charts suggests a preliminary PPV of 75% or greater for the four-step algorithm; chart review is ongoing.Conclusions: Early results from this single-site study suggest that MGUS cases can be identified with reasonable accuracy in electronic health data through a four-step algorithm. However, in light of the frequent use of immunofixation noted above, the incorporation of specific lab test results may be required to improve the PPV. Following completion of ongoing chart review, the algorithm will be applied to a second Cancer Research Network healthcare system with a shared data structure for further refinement, and to evaluate its performance in an independent population. DisclosuresNo relevant conflicts of interest to declare.

Designing a medical rule model system by using rough–grey modeling

PurposeIn this study, a hybrid rough and grey set-based rule model is designed for diagnosis of one type of blood cancer called multiple myeloma (MM). The grey clustering method is used to combine the same condition attributes and to improve the validity of the final model.Design/methodology/approachSome tools of the rough set theory (RST) and grey incidence analysis (GIA) are used in this research to analyze the serum protein electrophoresis (SPE) test results. An RST-based rule model is extracted based on the laboratory SPE test results of patients. Also, one decision attribute and 15 condition attributes are used to extract the rules. About four rule models are constructed due to the different algorithms of data complement, discretization, reduction and rule generation. In the following phases, the condition attributes are clustered into seven clusters by using a grey clustering method, the value set of the decision attribute is decreased by using manual discretizing and the number of observations is increased in order to improve the accuracy of the model. Cross-validation is used for evaluation of the model results and finally, the best model is chosen with 5,216 rules and 98% accuracy.FindingsIn this paper, a new rule model with high accuracy is extracted based on the combination of the grey clustering method and RST modeling for diagnosis of the MM disease. Also, four primary rule models and four improved rule models have been extracted from different decision tables in order to define the result of SPE test of patients. The maximum average accuracy of improved models is equal to 95% and related to the gamma globulins percentage attribute/object-related reducts (GA/ORR) model.Research limitations/implicationsThe total number of observations for rule extraction is 115 and the results can be improved by further samples. To make the designed expert system handy in the laboratory, new computer software is under construction to import data automatically from the electrophoresis machine into the resultant rule model system.Originality/valueThe main originality of this paper is to use the RST and GST together to design and create a hybrid rule model to diagnose MM. Although many studies have been carried out on designing expert systems in medicine and cancer diagnosis, no studies have been found in designing systems to diagnose MM. On the other hand, using the grey clustering method for combining the condition attributes is a novel solution for improving the accuracy of the rule model.

Prospective review of SPEP orders confirms need for testing algorithm.

e19326 Background: Serum protein electrophoresis (SPEP) identifies monoclonal proteins associated with plasma cell disorders including multiple myeloma. There are no large prospective studies looking at clinical ordering patterns of SPEPs. This study will determine the percent of monoclonal proteins detected by SPEP testing and factors that are or are not associated with identifying monoclonal proteins. We predict that SPEP testing is commonly ordered and not thoroughly evaluated prompting a need for an algorithm to ensure appropriate use and follow up testing. Methods: In our academic center, we captured data on all SPEP tests ordered from March 17 to June 16, 2019. We chart reviewed each associated patient to collect the following: patient age and sex, SPEP result, hemoglobin, serum albumin, total serum protein, serum calcium, serum creatinine, presence of proteinuria, serum free light chains, immunoglobulins (IgG, IgA, IgM), serum immunofixation, urine protein electrophoresis, urine immunofixation, bone marrow biopsy report, imaging results (bone survey, PET, MRI) and echocardiograms. We ascertained the reason for ordering the SPEP, inpatient or outpatient status of the patient and the ordering department. Results: There were 929 SPEPs ordered. 410 (44%) ordered on “new” patients with no previously identified M-spike. Of the 410 “new” SPEP orders, 57 (14%) detected a M-spike. 8 (2%) led to a diagnosis requiring treatment: 7 new cases of myeloma and 1 case of AL amyloidosis. 108 (26%) of the 410 “new” SPEP orders were ordered in the inpatient setting with 20 “new” M-spikes identified. Only 4 of the 108 inpatient SPEP orders identified a diagnosis requiring treatment—4 cases of myeloma. These patients had SPEPs ordered due to pathologic fractures related to lytic lesions and acute renal failure with other associated CRAB features. Neurologic findings were the most common reason for ordering “new” SPEPs, 106 (26%) of the 410 with only 7 with M-spike—all low risk MGUS. Only 2 of 26 patients were found to have low risk MGUS when SPEP was ordered as part of a rheumatologic work up. All 6 patients with SPEP ordered for dermatologic reasons were negative for M-spike. 23 (40%) of the 57 “new” M-spikes had no follow up testing to determine the clinical significance. Conclusions: This prospective review on the use of SPEP orders in an academic medical center documents the need to provide an algorithm to aide effective use of testing to decrease inpatient ordering and provide guidance on appropriate follow up testing. We found a very low yield with SPEP testing for neurologic, rheumatologic and dermatologic reasons.

A thin-film interferometry-based label-free immunoassay for the detection of daratumumab interference in serum protein electrophoresis

BackgroundDaratumumab (DARA) is a fully human anti-CD38 IgG1-κ monoclonal antibody drug used in the treatment of multiple myeloma (MM). While serum protein electrophoresis (SPEP) is an important assay for diagnosis and monitoring of patients with MM, DARA can appear in the γ-region as a single band and interfere with the interpretation of SPEP results. An approach to detect the interference is measuring the quantity of DARA in serum samples and assessing its impact on SPEP results. Immunoassays based on label-free technologies, i.e. label-free immunoassays (LFIA’s), can achieve real-time immunometric measurement without attaching a reporter molecule (enzyme, fluorophore, etc.) to the immunocomplex. The recorded time course of the immunocomplex formation allows for quantitation on initial binding rate, which facilitates rapid measurement within a few minutes. Based on the thin-film interferometry (TFI) technology, a rapid LFIA was established for the quantitation of DARA in serum samples. MethodsThe TFI-based LFIA for DARA was validated for imprecision (CV), accuracy, limit of quantitation (LOQ), and analytical measurement range (AMR). Interference to the LFIA was evaluated using a group of protein samples, as well as hemolytic, lipemic, and icteric clinical samples. ResultsThe precision of the TFI-based LFIA’s for DARA ranged from 6.5% to 10.7% (within-run CV), and 7.4% to 11.6% (between-run CV), with a bias of −2.1% to 10.1%. The LOQ was 10 μg/ml (n = 4, CV 9.8%), with an AMR ranging from the LOQ to 1000 μg/ml. The LFIA was used to measure 37 patient samples submitted for SPEP testing. The LFIA results were 100% consistent with the history of DARA use as documented in the medical record. ConclusionsThe TFI-based LFIA was successful at accurately identifying DARA in serum samples and can be used to identify DARA interference in SPEP testing. This work demonstrates the applicability of label-free technologies, particularly the TFI technology, to clinical diagnostic needs. Given the simplicity and the speed of the testing process, the TFI technology provides a unique testing approach for the measurement of proteins in clinical samples.

Approximating International Myeloma Working Group Uniform Response Criteria to Derive Response for Multiple Myeloma (MM) Patients Using Data from Electronic Health Records (EHR)

Approximating International Myeloma Working Group Uniform Response Criteria to Derive Response for Multiple Myeloma (MM) Patients Using Data from Electronic Health Records (EHR)

Artificial Neural Network (ANN) and regression model for predicting the Albumin to Globulin (A/G) ratio in a serum protein electrophoresis test

Multiple myeloma affects the several parts of bodies such as the spine, skull, pelvis and ribs. The cause of multiple myeloma is not known properly. The poor prognoses is associated with most cancers creates a sense of urgency for the brains behind healthcare Artificial Intelligence (AI) research. AI is able to detect cancer and other diseases earlier than possible through standard diagnostic methods, which could be lifesaving for future patients. The main objective of the research paper is to predict the Albumin to Globulin (A/G) ratio obtained by the electrophoresis test by developing regression model and Artificial Neural Network (ANN) model. The results obtained showed that the Mean Square Error (MSE) obtained by ANN model is less than the MSE obtained by the regression model.

Artificial Neural Network (ANN) and Regression Model for Predicting the Albumin to Globulin (A/G) Ratio in a Serum Protein Electrophoresis Test

Multiple myeloma affects the several parts of bodies such as the spine, skull, pelvis and ribs. The cause of multiple myeloma is not known properly. The poor prognoses is associated with most cancers creates a sense of urgency for the brains behind healthcare Artificial Intelligence (AI) research. AI is able to detect cancer and other diseases earlier than possible through standard diagnostic methods, which could be lifesaving for future patients. The main objective of the research paper is to predict the Albumin to Globulin (A/G) ratio obtained by the electrophoresis test by developing regression model and Artificial Neural Network (ANN) model. The results obtained showed that the Mean Square Error (MSE) obtained by ANN model is less than the MSE obtained by the regression model.

The Real-World Frequency of 24-Hour Urine Protein Electrophoresis (UPEP), Serum Free Light Chain (SFLC), and Serum Protein Electrophoresis (SPEP) Testing in Patients with Multiple Myeloma (MM)

IntroductionUp to 20% of MM patients present with light-chain-only multiple myeloma (LCMM), which is not detectable using serum protein electrophoresis testing. 24-hour urinalysis may be the guideline-endorsed method for monitoring LCMM, but impracticalities can limit its use. We sought to assess how patients with MM and LCMM were followed for progression in the community setting by specimen type using real-world data, analyzing the frequency of testing for patients with MM (based on SPEP) or LCMM (based on UPEP or SFLC).MethodsThis retrospective cohort study used information from the Flatiron Health database, which is derived from electronic health record data; Institutional Review Board approval with a waiver of informed consent was obtained. The cohort included 4591 patients followed for MM and LCMM from 01/01/2011 to 06/30/2018 at community oncology clinics across the United States. The cohort was limited to patients with a confirmed diagnosis of MM on or after 01/01/2011, who received at least one line of therapy and did not receive a stem cell transplant. Patients whose start of MM treatment (captured through chart review) was > 30 days before the start of structured activity in the database were excluded as this may indicate missing therapy data. The specimen type was the test used to follow patients for progression throughout their disease course. Tests were eligible to define the specimen type if they occurred ≤ 90 days before or any time after an initial MM diagnosis. If a patient had multiple test types within this timeframe, the specimen type was determined using a hierarchy (at least one detectable SPEP [≥ 1 g/dL] > at least one detectable 24-hour UPEP [≥ 200 mg] > SFLC [any numeric value]), consistent with International Myeloma Working Group (IMWG) criteria. A LCMM diagnosis was assumed when a detectable M spike (≥1 g/dL) via SPEP could not be found 90 days before or any time after the initial MM diagnosis date, but a detectable lab value was found within that timeframe via 24-hour UPEP (≥ 200mg) or a SFLC (any numeric value).ResultsAmong all patients in the cohort with MM (N=4591), 27.7% (N=1272) received a UPEP test, 58.1% (N=2666) received a SFLC test, and 79.2% (N=3635) received a SPEP test at baseline, defined as occurring within 90 days on either side of the MM diagnosis date. Patients with a UPEP specimen type had less frequent testing than patients with a SPEP or SFLC specimen type. For patients with a UPEP specimen type (N=229), the median of the median time between two tests was 95 days, compared to 42 days for patients with a SFLC specimen type (N=1274) and 35 days for patients with a SPEP specimen type (N=2536). 32.7% (N=1503) of the cohort had LCMM; of those patients, 84.8% were followed by SFLC while only 15.2% were followed by UPEP.Conclusions24-hour urine tests for UPEP are not used often in routine clinical practice despite IMWG guidelines: the guidelines may not reflect a realistic standard of care in the real-world setting. While performing UPEP in addition to SFLC regularly may be the ideal practice for monitoring LCMM, impracticalities such as issues with collection technique and proper storage of urine samples may be hindering its regular use in the real world. The SFLC test may present a more realistic alternative for evaluation of disease status in patients with LCMM, and its ease of use could facilitate more frequent serial testing. This in turn could improve the measurement of progression at more regular intervals, potentially reducing patient exposure to therapies that are no longer effective. To our knowledge, this is the first study to investigate the differences in utilization of UPEP, SFLC, and SPEP testing conducted to follow MM and LCMM progression in the real world. [Display omitted] DisclosuresFoster:Flatiron Health: Employment. Lipitz:Flatiron Health: Employment. Torres:Flatiron Health: Employment. Carson:Roche: Consultancy; Flatiron Health: Employment; Washington University in St. Louis: Employment.

Light Chain Escape in Multiple Myeloma

Light Chain Escape in Multiple Myeloma

Monoclonal Antibodies in Multiple Myeloma: A New Wave of the Future.

In 2015, 2 monoclonal antibodies were approved for the treatment of relapsed or refractory multiple myeloma (RRMM), elotuzumab and daratumumab. Elotuzumab is a monoclonal IgG-κ antibody directed against SLAMF7 (signaling lymphocytic activation molecule F7), a cell surface receptor involved in natural killer cell activation. Daratumumab is a monoclonal IgG-κ antibody that binds to CD38, a transmembrane protein found on the surface of myeloma cells and responsible for cellular adhesion and ectoenzymatic activity. Both elotuzumab and daratumumab act through recruitment of the immune system to enhance cellular cytotoxicity directed against myeloma cells. Elotuzumab requires lenalidomide and dexamethasone combined to enhance progression-free survival in patients with RRMM, and daratumumab has both single-agent and combination activity with either lenalidomide or the proteasome inhibitor bortezomib in RRMM. The adverse effect profile of both agents mainly consists of allergic-type infusion reactions. Other considerations for monoclonal antibody use in the treatment of MM include the potential for interference in serum protein electrophoresis testing and cross-reactivity of daratumumab with CD38 present on red blood cells. In the present report, we discussed the clinical development of daratumumab and elotuzumab and newer immunologic approaches to the treatment of MM.

Electrophoresis test prevalence, requesting patterns, yield and related bone marrow biopsy findings at a South African tertiary hospital: A 5-year retrospective audit

Studies of electrophoresis testing (serum protein electrophoresis (SPE), urine protein electrophoresis (UPE), immunofixation electrophoresis (IFE)) in a South African (SA) pathology laboratory setting are limited. To evaluate the prevalence, testing pattern and yield of electrophoresis tests performed over a 5-year period in a tertiary academic laboratory and to relate these findings to bone marrow biopsy findings in a few selected cases. This was a retrospective audit of all SPE, UPE and IFE tests performed on new and follow-up adult patients (aged ≥18 years) from 2010 to 2015, using data from the Tygerberg Academic Hospital (Cape Town, SA) National Health Laboratory Service hospital information system database. A subgroup analysis of all patients with negative serum (SIFE) and/or urine immunofixation (UIFE) tests who had concurrent bone marrow biopsies close to the time of IFE testing was also performed. A total of 5 086 SPE tests were performed (44.3% were follow-up tests, and of these patients 13.8% had SIFE tests); 1 299 UPE tests were performed (23.3% were follow-up tests, and of these patients 33.6% had UIFE tests). The mean ages of patients who had SIFE and UIFE tests were 59 years (standard deviation (SD) 14.2) and 60 years (SD 15), respectively. The female-to-male ratio was 1.1:1 for both SIFE and UIFE. The negative test yields for SIFE and UIFE were 31.3% and 52.1%, respectively. Bone marrow biopsy findings for patients with negative SIFE tests identified 8 out of the 20 biopsies (40.0%) as positive for myeloma. This audit provides baseline data on the prevalence of test requests, their source and the yield of electrophoresis testing in our laboratory. An increasing trend in SIFE and UIFE was evident.

Viral co-infections and paraproteins in HIV: effect on development of hematological malignancies.

The role of viral co-infections and paraproteins in the development of hematological malignancies (HMs) in HIV remains unclear. Using our large database of HIV+ patients, we investigated whether co-infection and paraproteinemia increase the risk of HM. Data on demographics, hepatitis B (HBV) and hepatitis C virus (HCV) co-infections, paraproteinemia, HIV characteristics, and biopsy proven malignant hematological disorders for HIV+ patients were collected over a 10-year period in a large urban hospital setting. We identified 10,293 HIV+ patients who were followed for a median duration of 53 months. Of the 10,293 patients with HIV, 229 (2.2 %) were diagnosed with a HM. Over 85% of patients in both groups were tested; no significant difference in the prevalence of chronic HBV or HCV was noted between the HM positive (n = 229) and HM negative (n = 9992) patients. The serum protein electrophoresis test was performed for 1371 of the 10,221 patients. HM positive patients, compared to HM negative, were more likely to be tested for paraproteins (OR 3.3, 95% CI 2.5-4.4) and more likely to have a discrete paraprotein band (OR 3.3, 95% CI 1.2-8.9). Discrete paraproteins exclusively correlated with the development of plasma cell malignancies. Faint or oligoclonal protein bands were seen in high grade B cell lymphomas but did not show a significant correlation with HM development. Chronic hepatitis B or C infections did not correlate with the development of HM in HIV; however, viral influence on host gene transformation may have been impacted by anti-viral therapy limiting the duration of high viremic states.

Abstract 5594: Progression of paraproteinemia in HIV-positive versus HIV-negative patients

Abstract BACKGROUND: Paraproteinemias occur in 1 to 3% of people over the age of 50 and progress to hematological malignancies (HM) at the rate of about 1% per year. In HIV+ patients a higher incidence of paraproteinemia has been reported however the rate of progression to HM remains unclear. We studied a large database comparing HIV+ and HIV- patients with paraproteinemia for incidence of HM. METHODS: Patients tested for HIV who also had a serum protein electrophoresis test (SPEP) performed between January 1st 2001 and December 31st 2011 were identified using a medical database at a large tertiary care center. SPEP+ patients were stratified into distinct (D-SPEP) or faint/multiple/oligoclonal (F-SPEP) bands by an independent laboratory technician. Demographics, coinfections and biopsy data were reviewed. RESULTS: 181,851 patients underwent a HIV test and 10,293 were HIV+. Significantly greater number of HIV+ patients (1381 of 10,293) compared to HIV- (6512 of 171,588) were tested for paraprotein (13.4% vs 3.8%, p&amp;lt;0.0001). Of those tested, the prevalence of SPEP positivity was higher in HIV+ (266 of 1381) versus HIV- (537 of 6512) (19.3% vs 8.2%, p&amp;lt;0.0001). HIV+ SPEP+ patients were more likely to have F-SPEP and light chain paraproteins compared to their HIV- counterparts. HIV+SPEP+ patients were significantly more likely to be tested and more likely to be positive for hepatitis B and C co infections. HIV- SPEP+ patients were more likely to have a D-SPEP and IgA and IgM subtype paraproteins than HIV+ patients. HIV- patients also had a higher incidence of HM which persisted when adjusted for year of SPEP and duration of follow up (p&amp;lt;0.0001). CONCLUSIONS: While a higher prevalence of paraproteinemia was noted in the HIV+, HM incidence was lower in the HIV+ compared to HIV-, suggesting that nonmalignant virus-dependent proliferation may lead to paraproteinemia in some HIV+ cases. Identification of HIV+SPEP+ cases with higher risk of HM will be clinically relevant. Table 1.Comparison of HIV+SPEP+ and HIV- SPEP+ patientsCharacteristicHIV+ SPEP+ (n = 266)HIV- SPEP+ (n = 537)p value(Chi square/ Fishers exact/ t-test)Age at SPEP test (yrs)50 (SE: 0.54)59 (SE: 0.55)&amp;lt;0.0001*F-SPEP (n,%)234 (88%)342 (63.7%)&amp;lt;0.0001D-SPEP (n,%)32 (12%)195 (36.3%)&amp;lt;0.0001*IgG (n,%)209 (78.6%)372 (73.5%)0.136IgM (n,%)4 (1.5%)42 (8.3%)&amp;lt;0.0001*IgA (n,%)3 (1.1%)40 (7.9%)&amp;lt;0.0001*Light chain (n,%)24 (9%)23 (4.5%)0.013Hepatitis C positive by serology/ viral load of those tested113/246 (45.9%)78/412 (18.9%)&amp;lt;0.0001HBsAg/ Hepatitis B viral load positive of those tested22/241 (9.1%)4/254 (2.6%)0.012Follow up after SPEP test (months)23360.003HM (n,%)17 (6.5%)83 (16.1%)&amp;lt;0.0002HM+ of F-SPEP+12/234 (5.1%)34/342 (9.9%)0.042HM+ of D-SPEP+5/32 (15.6%)49/195 (25%)0.369 Citation Format: Erin Jou, Oleg Gligich, Alvita CY Chan, Diwakar Mohan, Uriel R. Felsen, Sabarish Ayyappan, Henny H. Billett, Edwin P. Hui, Anthony TC Chan, Radha Raghupathy. Progression of paraproteinemia in HIV-positive versus HIV-negative patients. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5594. doi:10.1158/1538-7445.AM2015-5594