Shomali, William

Abstract The incidence of venous thromboembolism (VTE) in patients with acute lymphoblastic leukemia (ALL) receiving asparaginase-based induction is high despite primary thromboprophylaxis. Our aim was to derive and externally validate a VTE risk prediction model in patients with ALL receiving asparaginase-based induction. We conducted a multicenter retrospective cohort study of patients (aged ≥18 years) with newly diagnosed ALL receiving asparaginase-based induction. The derivation and external validation cohorts included 306 and 94 patients, respectively. Primary outcome was VTE at any site. A cause-specific Cox proportional hazards model stratified by thromboprophylaxis and center was performed to identify VTE risk factors in the derivation cohort. A risk prediction model for VTE at 30 days was derived using variables with P value < .05 in the multivariable model and was tested in the validation cohort. VTE risk factors on multivariable analysis in the derivation cohort included D-dimer ≥1 μg fibrinogen equivalent unit per mL (hazard ratio [HR], 2.64; 95% confidence interval [CI], 1.07-6.5) and hemoglobin (HR for each 1 g/dL increment, 1.19; 95% CI, 1.06-1.34) at ALL diagnosis. A VTE risk score based on these variables distinguished between a 4% (95% CI, 0.72-12) and 20% (95% CI, 14-27) 30-day cumulative incidence of VTE in the derivation cohort, with similar findings in the validation cohort (area under the curve, 0.56). The negative predictive value for VTE at 30 days was 96% and 93% in the derivation and validation cohorts, respectively, and the positive predictive value was 20% in both. We derived and validated a model using D-dimer and hemoglobin, which stratifies VTE risk in patients with ALL receiving asparaginase-based induction.

Background: Patients with acute lymphoblastic leukemia (ALL) receiving L-asparaginase (ASP) based induction therapy have a high risk of venous thromboembolism (VTE). Studies investigating universal thromboprophylaxis strategies have yielded sub-optimal results. Risk prediction models are needed to identify high-risk patients who would be candidates for intensification of thromboprophylaxis, and lower risk patients who are unlikely to benefit. Aims: Derive and externally validate a risk prediction model for VTE in patients with ALL receiving ASP therapy. Methods: We conducted a multicenter, international, cohort study of patients with newly-diagnosed ALL receiving ASP-based induction therapy (≥18yrs). The derivation and external validation cohorts included 306 and 97 patients without VTE prior to ASP therapy, respectively. Patients on therapeutic anticoagulation at index were excluded. Patients were followed from date of first ASP dose for 100 days post ALL diagnosis or until VTE, therapeutic anticoagulation or death. Candidate predictors were documented at ALL diagnosis and included demographics, disease and treatment characteristics, VTE history, comorbidities, thromboprophylaxis, complete blood count, fibrinogen and d-dimer. D-dimer was only analyzed within the 7 derivation cohort centers who routinely tested this at ALL diagnosis with <20% missing values. Primary outcome was VTE at any site (centrally confirmed). Secondary outcomes included major bleeding by ISTH criteria. Cause-specific Cox proportional hazard regression was performed to identify VTE risk factors in the derivation cohort while treating death as a competing event. Variables with p-value <0.1 on univariable analysis were included in a multivariable model and subsequently used in the risk model if p-value <0.05. Lastly, the derived VTE risk prediction model was tested in the external validation cohort for association with time to VTE using cause-specific Cox proportional hazard model. All analyses were stratified by center and use of low molecular weight heparin prophylaxis (at any dose on the date of first ASP dose). Results: The cumulative incidence of VTE in the derivation cohort was 17% at 30 days (95% confidence interval [CI] 13% - 21%) and 22% at 90 days (95% CI 17% - 27%). The multivariable model included hyperlipidemia (hazard ratio [HR] 1.35; 95% CI 0.56 - 3.27), body mass index ≥ 25 kg/m² (HR 1.49; 95% CI 0.75 - 2.95), platelet count ≥ 25 x 10⁹/L (HR 1.42; 95% CI 0.67 - 3.00), increasing hemoglobin per 1 g/dL (HR 1.17; 95% CI 1.03 - 1.32) and d-dimer ≥ 1 µg FEU/mL (HR 2.68; 95% CI 1.08 - 6.66). Hemoglobin as a continuous variable and d-dimer ≥ 1 µg FEU/mL were included in the final model and used to create a risk score which was weighted by estimated log-HR sum of these risk factors. The lowest risk quartile (risk score below 2.1) successfully differentiated between a lower 30-day cumulative VTE incidence (4%, 95% CI 0.72% - 12%) compared with the other quartiles (20%, 95% CI 14% - 27%; HR 4.40, 95% CI 1.54 - 12.5) which were defined as high risk (score ≥2.1). The risk score's negative predictive value (NPV) for VTE at 30 days was 96% and positive predictive value (PPV) was 20%. The validation cohort (n=97 from 3 external cohorts with routine d-dimer measurement) included 16 (16.5%) patients in the low-risk group and 81 (83.5%) in the high-risk group, with a 30-day VTE incidence of 6.3% (95% CI 0% - 17%) and 21% (95% CI 12% - 30%), respectively (HR 6.22; 95% CI 0.85 - 45.8; p = 0.073)). The NPV (93.7%) and PPV (21%) were comparable to the derivation cohort. The 30-day incidence of major bleeding was 0% (95% CI NR - NR) in low-risk patients (HR 1.36; 95% CI 0.27 - 6.77) and 2.0% (95% CI 0.55% - 5.4%) in the high-risk group. Conclusion: Patients with ALL receiving ASP induction therapy have a 17% VTE risk at 30 days. We derived and externally validated a VTE risk prediction model based upon d-dimer and hemoglobin. This model successfully identifies at least 16.5% of patients with ALL who have a low VTE risk after ASP treatment. Using this model, novel prevention strategies which may be associated with cost and risk could now be tailored to patients with higher risk. Prospective studies are needed to validate the model's performance and role in VTE risk management.

Chronic myeloid leukemia (CML) is defined by the presence of Philadelphia chromosome resulting from a reciprocal translocation between chromosomes 9 and 22 [t9;22] that gives rise to a BCR::ABL1 fusion gene. CML occurs in 3 different phases (chronic, accelerated, and blast phase) and is usually diagnosed in the chronic phase in developed countries. Tyrosine kinase inhibitor (TKI) therapy is a highly effective treatment option for patients with chronic phase–CML. The primary goal of TKI therapy in patients with chronic phase–CML is to prevent disease progression to accelerated phase–CML or blast phase–CML. Discontinuation of TKI therapy with careful monitoring is feasible in selected patients. This manuscript discusses the recommendations outlined in the NCCN Guidelines for the diagnosis and management of patients with chronic phase–CML.

Background. Some patients who present with clinical features consistent with idiopathic hypereosinophilic syndrome (HES; absolute eosinophil count (AEC) ≥1.5 x 10 9/L with related end organ damage) are ultimately diagnosed with a myeloid neoplasm. Although FIP1L1::PDGFRA is the most common molecular abnormality in this setting, many other fusion genes, point mutations and cytogenetic abnormalities have been implicated in driving primary (neoplastic) eosinophilia. Given the poor prognosis of these disorders in the absence of treatment and the availability of targeted therapies for many of the driver mutations, it is becoming increasingly important to rapidly identify the underlying genetic alteration. In this regard, the expense and variable sensitivity of molecular diagnostic tests remains problematic. Although clinical features have been reported to distinguish between PDGFRA-associated myeloid neoplasms and D816V KIT-positive systemic mastocytosis with hypereosinophilia, little is known about the clinical phenotypes of other subsets of patients. This multicenter retrospective study aimed to assemble a large cohort of patients with HES secondary to a myeloid neoplasm to explore the utility of clinical and laboratory features in predicting the underlying molecular abnormality. Methods. Retrospective, de-identified data from 16 centers were collected via an online Research Electronic Data Capture repository. Patients and associated data were obtained from in-house research databases and/or electronic medical record searches at each site. Clinical and laboratory data were entered in accordance with local Institutional Review Boards. Inclusion criteria were peripheral blood hypereosinophilia (AEC >1.5 x 10 9/L) on at least two occasions and one of the following: ≥1 confirmed genetic abnormality recurrently associated with primary myeloid neoplasms, other evidence of clonal eosinophilia, or increased blasts (≥2% in the blood or >5% but <20% in the marrow). Patients with acute myeloid leukemia were excluded. Results. A total of 277 patients followed between 1990 and 2022 were included in the analysis. Median length of follow up was 31 months (range <1-356), and 217/277 (78%) were alive at last follow up. The most common genetic abnormality was FIP1L1::PDGFRA (n=131) followed by D816V KIT mutations (n=39) and alterations involving JAK2 (n=22) (Figure 1). Five patients had genetic abnormalities involving two distinct genes recurrently associated with eosinophilic myeloid neoplasms. The overall median age at diagnosis was 55 years (range 12-89) and 79% of the patients were male. When patients with abnormalities involving PDGFRA and PDGFRB were excluded from the analysis, the male predominance was significantly lower at 62% (p<0.001, Fisher's exact test as compared to the data set as a whole). The overall pattern of organ system involvement was similar irrespective of the underlying genetic abnormality with a few notable exceptions. Cardiac involvement was most common in patients with FIP1L1:: PDGFRA, abnormalities involving JAK2 or without pathologic alterations identified (reported in 22%, 32% and 30%, respectively); whereas skin and gastrointestinal involvement, lymphadenopathy and splenomegaly were most frequent in patients with KIT D816V. Laboratory abnormalities also differed between groups. Whereas anemia was the most common blood abnormality (reported in >50% of patients), erythrocytosis was noted primarily in patients with abnormalities involving JAK2. In contrast, circulating blasts were identified in 70% of patient with BCR::ABL1 and 29% of patients with chromosomal abnormalities or KIT D816V, but in <15% of patients in any of the other groups. Whereas peak AEC alone did not discriminate between the different patient groups, the AEC/tryptase ratio was increased in patients with PDGFRA-associated myeloid neoplasms, molecular abnormalities involving JAK2, or chromosomal abnormalities as compared to those with KIT mutations (Figure 2). Conclusions. Despite the limitations of retrospective data analysis, the data from this large multicenter cohort of patients with HES due to a chronic myeloid neoplasm suggest that routine demographic, clinical and laboratory features vary depending on the underlying molecular abnormality. This approach could ultimately help guide empiric therapy when molecular studies are negative or unavailable.