Citations

Abstract Recent introduction of 2 different lymphoma classifications has raised concerns about consistency in diagnosis, management, and clinical trial enrollment. Data from a large cohort reflecting real-world clinical practice suggest that differences between the classifications will affect <1% of non-Hodgkin lymphomas.

PURPOSE Chronic lymphocytic leukemia (CLL)–phenotype monoclonal B-cell lymphocytosis (MBL) is a premalignant condition that is roughly 500-fold more common than CLL. It is unknown whether the two-fold increased risk of developing melanoma associated with CLL extends to individuals with MBL. METHODS Using the Mayo Clinic Biobank, we identified participants who were 40 years or older with no previous hematological malignancies, who resided in the 27 counties around Mayo Clinic, and who had available biospecimens for screening. Eight-color flow cytometry was used to screen for MBL. Individuals with MBL were classified as low-count MBL (LC-MBL) or high-count MBL on the basis of clonal B-cell percent. Incident melanomas were identified using International Classification of Diseases codes and confirmed via medical records review. Cox regression models were used to estimate hazard ratios (HRs) and 95% CI. RESULTS Of the 7,334 participants screened, 1,151 were identified with a CD5-positive MBL, of whom 1,098 had LC-MBL. After a median follow-up of 3.2 years (range, 0-13.5), 131 participants developed melanoma, of whom 36 individuals were positive for MBL. The estimated 5-year cumulative incidence of melanoma was 3.4% and 2.0% among those with and without MBL, respectively. After adjusting for age, sex, and history of previous melanoma, individuals with MBL exhibited a 1.86-fold (95% CI, 1.25 to 2.78) risk of melanoma. This elevated risk persisted when analysis was restricted to those without a history of melanoma (HR, 2.05 [95% CI, 1.30 to 3.23]). Individuals with LC-MBL had a 1.92-fold (95% CI, 1.29 to 2.87) increased risk of developing melanoma overall and a 2.74-fold increased risk (95% CI, 1.50 to 5.03) of melanoma in situ compared with those without MBL. CONCLUSION LC-MBL is associated with an approximately two-fold increased risk of melanoma overall and a 2.74-fold increased risk of melanoma in situ.

AbstractBackgroundChronic lymphocytic leukemia (CLL) is a heterogeneous disease. Whereas some patients have an indolent disease, others experience an aggressive course and early death. Our aim was to investigate if modifiable and non‐modifiable medical history and lifestyle factors prior to diagnosis had an impact on the natural course of the disease.MethodIn 1154 CLL patients, we assessed if the weight, physical activity, smoking, and alcohol consumption or non‐modifiable characteristics including family history of lymphoid malignancy and medical history were associated with time‐to‐first‐treatment (TTFT) and adjusted all results for the CLL‐International Prognostic Index (CLL‐IPI).ResultsTTFT was shorter for patients with high/very high‐risk CLL‐IPI than those with low/intermediate risk CLL‐IPI. In the adjusted analysis we did not find additional impact on TTFT besides CLL‐IPI from any environmental characteristics assessed.ConclusionsWe found limited impact of environmental factors on the natural course of CLL (measured as the TTFT in treatment naïve patients) providing valuable knowledge, and potential relief, to share with patients at the time of diagnosis.

Abstract Underrepresentation of racial and ethnic subgroups in cancer clinical trials remains a persistent challenge. Restrictive clinical trial eligibility criteria have been shown to exacerbate this problem. We previously identified that up to 24% of patients treated with standard immunochemotherapy would have been excluded from recent first-line trials in diffuse large B-cell lymphoma (DLBCL) based on 5 laboratory-based criteria. These ineligible patients had worse clinical outcomes and increased deaths related to lymphoma progression, suggesting the potential exclusion of patients who could have benefited most from the novel therapies being evaluated. Using data from the prospectively enrolled Lymphoma Epidemiology Outcomes cohort study, with demographics broadly similar to the US patients diagnosed with lymphoma, we evaluated the impact of laboratory eligibility criteria from recent first-line DLBCL trials across various racial and ethnic backgrounds. There were significant differences in the baseline laboratory values by race/ethnicity with Black/African American (AA) patients having the lowest mean hemoglobin and highest creatinine clearance. Based on recent clinical trial eligibility criteria, AA and Hispanic patients had higher rates of laboratory-based ineligibility than non-Hispanic White patients. The largest gap in the clinical outcomes between eligible and noneligible patients was noted within AA patients with an overall survival hazard ratio based on POLARIX clinical trial criteria of 4.09 (95% confidence interval, 1.83-9.14). A thoughtful approach to the utility of each criterion and cutoffs for eligibility needs to be evaluated in the context of its differential impact across various racial/ethnic groups.

Chronic lymphocytic leukemia (CLL) is characterized by multiple copy number alterations (CNAs) and somatic mutations that are central to disease prognosis, risk stratification, and mechanisms of therapy resistance. Fluorescence in situ hybridization (FISH) panels are widely used in clinical applications as the gold standard for screening prognostic chromosomal abnormalities in CLL. DNA sequencing is an alternative approach to identifying CNAs but is not an established method for clinical CNA screening. We sequenced DNA from 509 individuals with CLL or monoclonal B-cell lymphocytosis (MBL), the precursor to CLL, using a targeted sequencing panel of 59 recurrently mutated genes in CLL and additional amplicons across regions affected by clinically relevant CNAs [i.e., del(17p), del(11q), del(13q), and trisomy 12]. We used the PatternCNV algorithm to call CNA and compared the concordance of calling clinically relevant CNAs by targeted sequencing to that of FISH. We found a high accuracy of calling CNAs via sequencing compared to FISH. With FISH as the gold standard, the specificity of targeted sequencing was >95%, sensitivity was >86%, positive predictive value was >90%, and negative predictive value was >84% across the clinically relevant CNAs. Using targeted sequencing, we were also able to identify other common CLL-associated CNAs, including del(6q), del(14q), and gain 8q, as well as complex karyotype, defined as the presence of 3 or more chromosomal abnormalities, in 26 patients. In a single and cost-effective assay that can be performed on stored DNA samples, targeted sequencing can simultaneously detect CNAs, somatic mutations, and complex karyotypes, which are all important prognostic features in CLL.

7011 Background: Monoclonal B-cell lymphocytosis (MBL) is a precursor to chronic lymphocytic leukemia (CLL) but also a risk factor for other lymphoid malignancies. Clonal hematopoiesis (CH), originally defined as the presence of mutations in myeloid driver genes, is a precursor to myeloid malignancies. Recently, CH that includes genes associated with lymphoid malignancies has been reportedly associated with risk of lymphoid malignancies, and particularly CLL. Little is known about the association between CH and MBL and their joint effects on risk of hematological malignancies (HM). Methods: Study participants were from the Mayo Clinic Biobank, a large-scale biorepository of patients who provided a peripheral blood sample. CH at enrollment was determined using whole-exome sequencing (50x coverage). Myeloid-CH (M-CH) was based on mutations located in 56 genes associated with myeloid malignancies. Lymphoid-CH (L-CH) was based on 235 genes associated with lymphoid malignancies. Individuals were screened for MBL using eight-color flow cytometry in two different cohorts of Biobank participants. Cohort 1 (N=3883) included participants who had available sample for MBL screening at enrollment. Cohort 2 (N=5684) were participants recontacted to provide a sample for MBL screening. Incident HM were identified using ICD codes and confirmed via medical record review. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI). Cox regression was used to estimate hazard ratios (HR), with time defined as date between MBL sample and the first of incident HM, death, or 9/30/2023. Analyses were adjusted for age at MBL screening and sex. Results: In total, 9567 individuals (39% male, median age 66 years) were screened for MBL with available CH, of whom 17% were positive for MBL, 7% were positive for M-CH, and 2% were positive for L-CH. We found no evidence of an association between M-CH and MBL (OR=1.11, 95% CI:0.91-1.34) nor L-CH and MBL (OR=1.05, 95% CI:0.70-1.55). When subset to Cohort 1, where the same sample was used for both CH and MBL screening, the results held (M-CH OR=1.11, 95% CI: 0.83-1.48; L-CH OR=0.82, 95% CI:0.40-1.53). Next, we investigated the effect of each of these precursors with incident HM. Median follow-up was 4 years, and 78 individuals developed incident HM (31 myeloid, 49 lymphoid overall, 8 CLL). When modeling both precursors, both L-CH (HR=6.23, 95% CI:2.46-15.79) and MBL (HR=3.89, 95% CI:2.17-6.99) were independently associated with incident lymphoid malignancy. When excluding CLL events, the association held (L-CH: HR=5.94, 95% CI:2.11-16.77; MBL: HR=2.95, 95% CI:1.54-5.66). Only M-CH was significantly associated with incident myeloid malignancies. Conclusions: In the largest cohort with MBL and CH precursors measured, we found no evidence of an association between them. However, both MBL and L-CH were strong independent risk factors for incident lymphoid malignancies.

Abstract Objectives Heart failure (HF) impacts millions of patients worldwide, yet the variability in treatment responses remains a major challenge for healthcare professionals. The current treatment strategies, largely derived from population based evidence, often fail to consider the unique characteristics of individual patients, resulting in suboptimal outcomes. This study aims to develop computational models that are patient-specific in predicting treatment outcomes, by utilizing a large Electronic Health Records (EHR) database. The goal is to improve drug response predictions by identifying specific HF patient subgroups that are likely to benefit from existing HF medications. Materials and Methods A novel, graph-based model capable of predicting treatment responses, combining Graph Neural Network and Transformer was developed. This method differs from conventional approaches by transforming a patient's EHR data into a graph structure. By defining patient subgroups based on this representation via K-Means Clustering, we were able to enhance the performance of drug response predictions. Results Leveraging EHR data from 11 627 Mayo Clinic HF patients, our model significantly outperformed traditional models in predicting drug response using NT-proBNP as a HF biomarker across five medication categories (best RMSE of 0.0043). Four distinct patient subgroups were identified with differential characteristics and outcomes, demonstrating superior predictive capabilities over existing HF subtypes (best mean RMSE of 0.0032). Discussion These results highlight the power of graph-based modeling of EHR in improving HF treatment strategies. The stratification of patients sheds light on particular patient segments that could benefit more significantly from tailored response predictions. Conclusions Longitudinal EHR data have the potential to enhance personalized prognostic predictions through the application of graph-based AI techniques.

Abstract Patients with large B-cell lymphoma (LBCL) that fail to achieve a complete response (CR) or who relapse early after anthracycline-containing immunochemotherapy (IC) have a poor prognosis and are commonly considered to have “primary refractory disease.” However, different definitions of primary refractory disease are used in the literature and clinical practice. In this study, we examined variation in the time to relapse used to define refractory status and association with survival outcomes in patients with primary refractory LBCL in a single-center prospective cohort with validation in an independent multicenter cohort. Patients with newly diagnosed LBCL were enrolled in the Molecular Epidemiological Resource cohort (MER; N = 949) or the Lymphoma Epidemiology of Outcomes cohort (LEO; N = 2755) from September 2002 to May 2021. Primary refractory LBCL was defined as no response (stable disease [SD]) or progressive disease (PD) during, or by the end of, frontline (1L) IC (primary PD; PPD); partial response at end of treatment (EOT PR); or relapse within 3 to 12 months after achieving CR at EOT to 1L IC (early relapse). In the MER cohort, patients with PPD had inferior overall survival (OS; 2-year OS rate: 15% MER, 31% LEO) when compared with other subgroups considered in defining primary refractory disease, EOT PR (2-year OS rate: 38% MER, 50% LEO) and early relapse (2-year OS rate: 44% MER, 58% LEO). Among patients receiving 1L IC with curative intent, we identified that patients with PPD are the key subgroup with poor outcomes. We propose a definition of primary refractory LBCL as SD or PD during, or by the end of, 1L treatment.

Abstract Background: The impact of a prior history of non-hematologic malignancy (NHM) on clinical outcomes among individuals with newly diagnosed chronic lymphocytic leukemia (CLL) or monoclonal B-cell lymphocytosis (MBL), the precursor to CLL, is not well known. Methods: In this prospective study, we identified individuals with CLL/MBL who were seen in the Division of Hematology at the Mayo Clinic, Rochester. Participants provided consent within nine months of diagnosis, had no prior history of hematological malignancy, and completed a self-reported risk-factor questionnaire, including a prior history of NHM. Time to first treatment (TTFT) was defined as the time between the date of diagnosis and the earliest date of the first CLL treatment, death, or the last known treatment-free follow-up date. Overall survival (OS) was defined as the time from diagnosis to death or the last follow-up. We used Cox regression to estimate hazard ratios (HR) and 95% confidence intervals (CI) for associations between a prior history of a NHM with OS and TTFT. We adjusted for sex and the CLL International Prognostic Index (CLL-IPI), a score comprised of five key CLL prognostic factors, including age and Rai stage. Results: Among the 1,090 CLL/MBL individuals, 833 (76%) had CLL. The median age at diagnosis was 64 years (range 24-89), with 65% being men, and 230 (21%) reported a prior history of NHM. The most common tumor was non-melanoma skin cancer (NMSC, 8.9%, 96 individuals), followed by prostate, testicular, and penile tumors (7.3%, 51 individuals), and melanoma (1.9%, 20 individuals). CLL/MBL patients with a prior history of a NHM were more likely to be over 65 years old (29%) than under 65 years old (14%, p < 0.0001). After a median follow-up of 2.9 years (range 0-21), 470 CLL/MBL patients progressed, requiring CLL treatment. CLL/MBL individuals with a prior history of NHM had a longer TTFT compared to those without (HR=0.69; 95% CI: 0.53-0.90; p=0.006). Individuals with a prior history of NHM who had either intermediate or high-very high CLL-IPI score had significantly longer TTFT (HR= 0.55; 95% CI: 0.33-0.92; p=0.02, and HR=0.65; 95% CI: 0.43-0.97; p=0.03, respectively) compared to those without NHM. After a median follow-up of 8.6 years (range 0-21), 359 individuals died. CLL/MBL patients with a prior history of NHM also experienced reduced OS compared to those without (HR=1.46; 95% CI: 1.08-1.97, p=0.013), particularly among those with low (HR=1.70; 95% CI: 0.96-3.00, p=0.07) or intermediate-risk (HR=2.08; 95% CI: 1.24-3.51, p=0.006), according to CLL-IPI. After excluding NMSC, results remained constant. Conclusions: At the time of diagnosis, one out of five CLL/MBL individuals had a prior history of a NHM. These individuals had a longer time to first CLL directed treatment and reduced OS, even after accounting for other important CLL prognostic factors, which deserves additional studies. Citation Format: Bryan A. Vallejo, Cristine Allmer, Kari G. Rabe, Dennis P. Robinson, Yucai Wang, Paul J. Hampel, Esteban D. Braggio, Neil E. Kay, James R. Cerhan, Sameer A. Parikh, Susan L. Slager. The impact of prior history of non-hematologic malignancies on time to first treatment and overall survival among individuals with CLL or MBL [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7450.