The diagnostic workup for systemic mastocytosis differs from consensus recommendations: Results of a worldwide survey

Objective

Mastocytosis is a complex disorder affecting various organs. The diagnostic workup can be challenging and requires a multidisciplinary approach including the use of uncommon tests. To assess mastocytosis management around the globe, we conducted the first worldwide online survey for physicians.

Methods

A 21-item questionnaire was sent out to the members of the World Allergy Organization (WAO), the Global Allergy and Asthma European Network (GA2LEN), the Urticaria (UCARE) and Angioedema (ACARE) Centers of Reference and Excellence, the German Society of Allergology and Clinical Immunology (DGAKI), and the European Mast Cell and Basophil Research Network (EMBRN) in April-June 2021.

Results

Across 628 respondents from 79 countries 87.7% and 9.7% of physicians were allergists/clinical immunologists and/or dermatologists. Participating physicians were from all regions of the world (Europe, EU: 41.6%; North America, NA: 24.8%; Latin America, LA: 14.5%; Asia-Pacific, AP: 12.6%; and Africa/Middle East, AME: 6.5%). Only 2.2% of respondents worked at Specialized Mastocytosis Centers (SMCs) in North America or European Union. Physicians reported caring for 4 patients with mastocytosis per year, with higher numbers in European Union and Asia Pacific (5/year) compared to Latin America (2/year). Dermatologists and physicians who work at SMCs reported higher patient numbers (15/year and 80/year, respectively). Suspicion of mastocytosis in the allergology and dermatology community is commonly driven by anaphylaxis (82.9%), mastocytosis skin lesions (82.1%), or elevated tryptase levels (76.6%). Osteoporosis and gastrointestinal symptoms less often prompted suspicion of mastocytosis (21.4% and 49.9%, respectively). World Health Organisation (WHO)-diagnostic criteria and classification, regardless of the region, are only used by about 50% of physicians, with higher rates for SMCs (83.3%). Serum tryptase, bone marrow biopsy, and KIT D816V mutation analysis are included in the diagnostic workup by 90.9%, 61.5%, and 58.4% of physicians, respectively. The biggest challenges for the management of mastocytosis are the lack of more effective treatment options (51.1%), missing multidisciplinary networks (47.1%), and the lack of experience of specialists from other disciplines (39.0%).

Conclusions

The diagnostic workup for mastocytosis differs from consensus recommendations and varies between regions. This may be improved by establishing active multidisciplinary networks, increasing access to diagnostic procedures, consistently applying WHO criteria, and developing new Mastocytosis Centers of Reference and Excellence.

MPN-352 Clinicopathologic and Molecular Correlates of Organ Damage Across the Spectrum of Advanced Systemic Mastocytosis

CONTEXT

Advanced SM (AdvSM) comprises 3 subtypes: aggressive SM (ASM), SM with an associated hematologic neoplasm (SM-AHN), and mast cell leukemia (MCL). The patterns of organ damage, which have been defined by WHO, IWG, and modified IWG (mIWG) criteria, across the spectrum of AdvSM have not been well characterized.

OBJECTIVE

1) To describe the distribution of organ damage in AdvSM patients (pts) at initial presentation or at the time of trial enrollment; 2) To evaluate clinicopathologic and molecular correlates of organ damage.

DESIGN

Observational study of adults with AdvSM.

SETTING

Tertiary referral center.

PATIENTS OR OTHER PARTICIPANTS

Our cohort included 240 AdvSM pts: 66 from the Stanford MPN registry and 174 from the phase I EXPLORER and phase II PATHFINDER studies of avapritinib in AdvSM.

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

Hematologic and non-hematologic organ damage as defined by WHO, IWG, and mIWG criteria.

RESULTS

Thirty-seven pts (15%) had ASM, 165 (69%) had SM-AHN, and 38 (16%) had MCL. Pts with MCL had the highest transfusion requirement and the largest liver and spleen volumes by imaging. In multivariate analyses comparing SM-AHN to ASM/MCL, SM-AHN pts had higher absolute neutrophil and monocyte counts and presence of SRSF2, ASXL1, or RUNX1 (S/A/R) mutations. ASM/MCL pts had higher tryptase levels and bone marrow mast cell burden. Compared to midostaurin-naïve pts, those who had received midostaurin had a greater bone marrow mast cell burden (P=0.06) but less frequently met WHO liver (P<0.001) and WHO malabsorption (P<0.001) criteria. Compared to pts with KIT D816V only, pts with ≥1 S/A/R mutations had lower median hemoglobin (P=0.02) and platelet count (P=0.02) and higher direct bilirubin (P=0.02), alkaline phosphatase (P=0.03), and spleen volume (P=0.06). They exhibited more WHO-defined cytopenias (P=0.007) and were more likely to meet WHO hypersplenism criteria (P=0.03).

CONCLUSIONS

In AdvSM, patterns of organ damage reflect disease subtype, prior therapy, and mutation profile. These data can help inform enrollment of AdvSM pts into clinical trials that currently require ≥1 organ damage findings. Grant Acknowledgments: ASH HONORS Award, NIH grant P30CA124435.

Clinical efficacy comparison of avapritinib with other tyrosine kinase inhibitors in gastrointestinal stromal tumors with PDGFRA D842V mutation: a retrospective analysis of clinical trial and real-world data

Background

Avapritinib, a potent inhibitor of KIT and platelet-derived growth factor receptor A (PDGFRA) tyrosine kinases, has demonstrated unprecedented clinical activity in PDGFRA D842V-mutant gastrointestinal stromal tumors (GIST).

Methods

This retrospective analysis compared efficacy of avapritinib in patients enrolled in the NAVIGATOR phase 1 trial (NCT02508532) with the efficacy of other tyrosine kinase inhibitors (TKIs) in patients with unresectable/metastatic PDGFRA D842V-mutant GIST enrolled in a retrospective natural history study (Study 1002). The primary endpoint was overall survival (OS) from the start of reference treatment (avapritinib for NAVIGATOR patients or first-line TKI for treatment of unresectable/metastatic GIST for Study 1002 patients); the secondary endpoint was progression-free survival (PFS). Adjusted Kaplan–Meier survival curves were compared by Cox regression.

Results

Fifty-six (NAVIGATOR) and 19 (Study 1002) patients with PDGFRA D842V-mutant GIST were evaluated; of the 56 patients from NAVIGATOR, a subgroup of patients treated with either 300 mg (recommended phase 2 dose) or 400 mg (maximum tolerated dose) avapritinib starting dose (n = 38) were analyzed separately. Patient characteristics were adjusted for imbalances by propensity score between the study groups. Inverse probability of treatment weighting-adjusted Kaplan–Meier analysis of OS showed median OS was not reached for NAVIGATOR patients treated with any of the avapritinib doses tested and was 12.6 months for Study 1002 patients; OS rate at 6/48 months was 100%/63% in NAVIGATOR and 56%/17% in Study 1002 (P = 0.0001). In the 300/400 mg subgroup, adjusted OS rates at 6/36 months were 100%/73 and 68%/20% in Study 1002 (P = 0.0016). Adjusted median PFS was 29.5 months in NAVIGATOR and 3.4 months in Study 1002.

Conclusions

In this indirect, retrospective analysis, avapritinib demonstrated more durable survival outcomes compared with other TKIs in patients with unresectable/metastatic PDGFRA D842V-mutant GIST.

Trial registration

The NAVIGATOR trial was registered at ClinicalTrials.gov as per July 2015, Identifier: NCT02508532.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08013-1.

Real-world healthcare resource utilization in patients with indolent non-Hodgkin lymphoma: differences between patients treated with first-line ibrutinib or bendamustine + rituximab

Objective: This study evaluated the real-world healthcare resource utilization (HCRU) and costs in patients diagnosed with an indolent non-Hodgkin lymphoma (iNHL) and treated with either first-line ibrutinib monotherapy (IbM) therapy or bendamustine plus rituximab combination therapy (BR).Methods: Treatment-naïve iNHL patients in the IBM MarketScan Research Databases were identified based on the first prescription of either IbM or BR therapy between 02/01/2014 and 08/30/2017.Results: A greater proportion of IbM patients (n = 207) had at least one inpatient admission (IP) or emergency room visit (ER), both all-cause and iNHL-related, than BR (n = 1337) patients. In addition, the mean number of IP admissions and ER visits was significantly higher in the IbM cohort. No differences in total costs were found. Outpatients costs were higher in IbM patients and medical costs were higher in BR patients.Conclusions: These real-world findings highlight the importance of considering the healthcare resource utilization and the associated costs of iNHL patients which may be associated with their first-line therapy.

Identification of biomarkers for risk stratification of cardiovascular events using genetic algorithm with recursive local floating search

Conventional biomarker discovery focuses mostly on the identification of single markers and thus often has limited success in disease diagnosis and prognosis. This study proposes a method to identify an optimized protein biomarker panel based on MS studies for predicting the risk of major adverse cardiac events (MACE) in patients. Since the simplicity and concision requirement for the development of immunoassays can only tolerate the complexity of the prediction model with a very few selected discriminative biomarkers, established optimization methods, such as conventional genetic algorithm (GA), thus fails in the high-dimensional space. In this paper, we present a novel variant of GA that embeds the recursive local floating enhancement technique to discover a panel of protein biomarkers with far better prognostic value for prediction of MACE than existing methods, including the one approved recently by FDA (Food and Drug Administration). The new pragmatic method applies the constraints of MACE relevance and biomarker redundancy to shrink the local searching space in order to avoid heavy computation penalty resulted from the local floating optimization. The proposed method is compared with standard GA and other variable selection approaches based on the MACE prediction experiments. Two powerful classification techniques, partial least squares logistic regression (PLS-LR) and support vector machine classifier (SVMC), are deployed as the MACE predictors owing to their ability in dealing with small scale and binary response data. New preprocessing algorithms, such as low-level signal processing, duplicated spectra elimination, and outliner patient's samples removal, are also included in the proposed method. The experimental results show that an optimized panel of seven selected biomarkers can provide more than 77.1% MACE prediction accuracy using SVMC. The experimental results empirically demonstrate that the new GA algorithm with local floating enhancement (GA-LFE) can achieve the better MACE prediction performance comparing with the existing techniques. The method has been applied to SELDI/MALDI MS datasets to discover an optimized panel of protein biomarkers to distinguish disease from control.

Computational prediction models for early detection of risk of cardiovascular events using mass spectrometry data

Early prediction of the risk of cardiovascular events in patients with chest pain is critical in order to provide appropriate medical care for those with positive diagnosis. This paper introduces a computational methodology for predicting such events in the context of robust computerized classification using mass spectrometry data of blood samples collected from patients in emergency departments. We applied the computational theories of statistical and geostatistical linear prediction models to extract effective features of the mass spectra and a simple decision logic to classify disease and control samples for the purpose of early detection. While the statistical and geostatistical techniques provide better results than those obtained from some other methods, the geostatistical approach yields superior results in terms of sensitivity and specificity in various designs of the data set for validation, training, and testing. The proposed computational strategies are very promising for predicting major adverse cardiac events within six months.

Logical Analysis of Data (LAD) model for the early diagnosis of acute ischemic stroke

Background

Strokes are a leading cause of morbidity and the first cause of adult disability in the United States. Currently, no biomarkers are being used clinically to diagnose acute ischemic stroke. A diagnostic test using a blood sample from a patient would potentially be beneficial in treating the disease.

Results

A classification approach is described for differentiating between proteomic samples of stroke patients and controls, and a second novel predictive model is developed for predicting the severity of stroke as measured by the National Institutes of Health Stroke Scale (NIHSS). The models were constructed by applying the Logical Analysis of Data (LAD) methodology to the mass peak profiles of 48 stroke patients and 32 controls. The classification model was shown to have an accuracy of 75% when tested on an independent validation set of 35 stroke patients and 25 controls, while the predictive model exhibited superior performance when compared to alternative algorithms. In spite of their high accuracy, both models are extremely simple and were developed using a common set consisting of only 3 peaks.

Conclusion

We have successfully identified 3 biomarkers that can detect ischemic stroke with an accuracy of 75%. The performance of the classification model on the validation set and on cross-validation does not deteriorate significantly when compared to that on the training set, indicating the robustness of the model. As in the case of the LAD classification model, the results of the predictive model validate the function constructed on our support-set for approximating the severity scores of stroke patients. The correlation and root mean absolute error of the LAD predictive model are consistently superior to those of the other algorithms used (Support vector machines, C4.5 decision trees, Logistic regression and Multilayer perceptron).

Autoimmunity to GABAA-receptor-associated protein in stiff-person syndrome

Stiff-person syndrome (SPS) is an autoimmune neurological disorder characterized by autoantibodies to glutamic acid decarboxylase (GAD), the enzyme responsible for the synthesis of inhibitory neurotransmitter GABA. To search for biomarkers that distinguish SPS from other neurological disorders (OND), we used surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry to obtain proteomic profile of sera from 25 GAD-positive SPS patients and 25 controls. A significant decrease was found in the level of a protein corresponding to GABA(A)-receptor-associated protein (GABARAP), which is responsible for the stability and surface expression of the GABA(A)-receptor. Up to 70% of the SPS sera examined, compared with 10% of the controls, immunoprecipitated GABARAP protein. Antibodies raised against GABARAP immunostained neuronal cell bodies as well as axonal and dendritic processes, as visualized by confocal microscopy. In vitro experiments demonstrated that the IgG from GABARAP antibody-positive patients, but not control IgG, significantly inhibited the surface expression of GABA(A)-receptor. We conclude that GABARAP is a new autoantigen in SPS. Because the patients' IgG inhibits the expression of GABA(A)-receptors, the circulating antibodies could impair GABAergic pathways and play a role in the clinical symptomatology of SPS patients.

Quantitative RT-PCR measurement of cytochromes p450 1A1, 1B1, and 2B7, microsomal epoxide hydrolase, and NADPH oxidoreductase expression in lung cells of smokers and nonsmokers

Bronchial epithelial cells (BEC) are the progenitors of bronchogenic carcinomas and are exposed to polycyclic aromatic hydrocarbon (PAH) procarcinogens through inhalation of combustion products. PAH are converted to carcinogenic molecules through a combination of monoxygenation by cytochrome p450 (CYP) enzymes in the presence of NADPH oxidoreductase (OR) and hydrolysis by microsomal epoxide hydrolase (mEH). In artificial systems, the relative expression of these genes determines whether carcinogenic or noncarcinogenic species are generated during metabolism. This relationship was explored in humans by using quantitative competitive reverse transcriptase polymerase chain reaction amplification to determine the range of expression of CYP1A1, CYP1B1, mEH, and NADPH OR in BEC recovered from 10 nonsmokers and 9 smokers. CYP2B7 expression was evaluated because, although little is known of its substrate specificity, it is expressed at high levels in human lung tissue. CYP1A1 and CYP1B1 were expressed in BEC at significantly different levels (P < 0.05) in the 9 smokers at 1.4 +/- 2.3 x 10(4) and 2.4 +/- 3.2 x 10(3) molecules/10(6) beta-actin molecules (mean +/- STD), respectively, but each was measurable in only one of the 10 nonsmokers. There was significant inter-individual variation (P < 0.05) in both CYP1A1 and CYP1B1 expression among the subjects for whom sufficient data were obtained. The inducibility of human BEC CYP1A1 gene by PAH exposure was confirmed in vitro by incubating cultured immortalized human BEC with beta-naphthoflavone and observing a > 6-fold induction of CYP1A1 after 24 h. In contrast to BEC, alveolar macrophages expressed CYP1A1 at low (30-70 molecules/10(6) beta-actin molecules) to unmeasurable levels in both smokers and nonsmokers. There was no significant difference in expression of mEH, CYP2B7, or NADPH OR in smokers compared with nonsmokers. The inter-individual variation in absolute and relative expression of PAH metabolism enzymes in BEC reported here supports the hypothesis that inter-individual variation in ability to activate/inactivate inhaled PAH carcinogens accounts for at least some of the inter-individual variation in risk for bronchogenic carcinoma.