Negaard, Brianna J

7073 Background: The Optimized HLH Inflammatory (OHI) index (Zoref-Lorenz et al., Blood , 2022), based on serum soluble CD25 (sCD25) and ferritin, is a prognostic tool identifying inflammation in the hemophagocytic lymphohistiocytosis (HLH) spectrum and early mortality risk. Prior studies were retrospective and enriched with HLH-suspected cases. We hypothesized that the OHI index would predict outcomes in unselected diffuse large B-cell lymphoma (DLBCL). Methods: 670 newly diagnosed DLBCL patients from a prospective cohort (2002–2015) were analyzed: 335 for discovery and 335 for validation. Pre-treatment serum sCD25 and ferritin levels were quantified via ELISA, and we evaluated original thresholds (sCD25 ≥ 3,900 U/mL; ferritin ≥ 1,000 ng/mL) and developed DLBCL-optimized thresholds (using receiver operator curves) for predicting 500-day mortality. We also evaluated event-free survival (EFS), EFS at 24 months (EFS24), and overall survival (OS). Results: The median age was 64, and 51% were male. Using original thresholds, 4.2% (n=14) of patients were OHI+, with a 5.6-fold higher risk of 500-day mortality (95% CI 1.6–17; p<0.001). Optimized thresholds identified 23.6% (n=78) as OHI+ with a 9.2-fold higher 500-day mortality risk (95% CI 4.0–24; p<0.001). Optimized OHI+ also had a higher risk of EFS24 failure and inferior EFS and OS (Table). OHI+ patients had higher rates of B symptoms (35% vs. 20%; p=0.027), elevated LDH (76% vs. 34%; p<0.001), worse performance status (ECOG ≥2: 38% vs. 12%; p<0.001), and advanced-stage disease (Stage IV: 57% vs 38%; p<0.001), though IPI scores (3–5) were not significantly different (44% vs 36%; p=0.28). Adjusting for age and IPI, OHI+ independently predicted 500-day mortality (OR=5.0; CI 1.9–13; p=0.001), EFS24 failure (OR=3.2; CI 1.5–6.5; p=0.0018), and inferior long-term EFS (HR=2.2; CI 1.1–4.3; p=0.030) and OS (HR=2.0; CI 1.0–4.0; p=0.040) at a median follow up of 9.8 years in living patients. In validation, optimized OHI predicted 500-day mortality, EFS24 failure, and long-term OS and EFS (Table). Cytokine profiling revealed elevated inflammatory markers in OHI+ patients, including IL1a (p=0.008), CCL2 (p=0.03), CXCL10 (p<0.001), and CXCL9 (p<0.001), reflecting systemic hyperinflammation. Conclusions: The OHI index is a powerful predictor of early and long-term outcomes in DLBCL patients. Optimized thresholds identify a larger OHI+ group, highlighting hyperinflammation’s critical role in poor outcomes. These findings support its use in routine management and clinical trial design for novel therapies. Odds ratios or hazard ratios and p-values for optimized OHI+ and DLBCL prognosis. Outcome Discovery Validation OR for 500-day mortality 9.2; p<0.001 4.0; p=0.002 OR for EFS24 failure 5.2; p <0.001 6.3; p<0.001 HR for OS 2.3; p<0.001 1.8; p=0.006 HR for EFS 2.4; p<0.001 2.5; p<0.001

Background: Positron emission tomography (PET) scan is the imaging modality of choice for initial staging and response assessment of follicular lymphoma (FL). Quantitative parameters such as standardized uptake value (SUV) have been investigated as putative prognosticators in FL, with high baseline SUVmax predicting aggressive disease. To date, there is no data to guide treatment choices in patients (pts) with high SUVmax but with no documented evidence of histologic transformation (HT). Specifically, it remains unclear whether anthracycline-containing regimens, such as R-CHOP, are more beneficial than R-Bendamustine (BR) in these pts. Therefore, we aimed to compare the efficacy of frontline R-CHOP and BR in newly diagnosed FL pts based on the SUVmax at baseline PET (bPET). Patients and Methods: Pts with newly diagnosed, biopsy-proven FL1-2 and FL3A who had a bPET scan and who received either first-line R-CHOP or BR within 6 months of diagnosis between 2002 and 2022 were evaluated. Analysis was restricted to pts with age &lt; 70 years to reduce confounding of age with treatment selection. Cohorts included were the FOLL12 (n=562, Luminari et al JCO 2022) and the R-chemotherapy arm of the RELEVANCE (n=216, Morschhauser et al NEJM 2018) clinical trials, the prospectively enrolled Molecular Epidemiology Resource (MER) and the Lymphoma Epidemiology of Outcomes (LEO) cohorts (n=288) and a retrospective cohort from 13 Australian centers (n=219). Choice of chemotherapy regimen was per treating physician. Maintenance was per protocol (FOLL12/RELEVANCE) or per treating physician (MER/LEO/Australia). Event-free survival (EFS) and overall survival (OS) were defined as time from treatment initiation to progression, relapse, retreatment or death; both were censored at 72 months due to varying follow-up across cohorts. SUVmax was grouped by tertile within each cohort to account for potential differences in SUVmax distributions and patient populations across cohorts. Kaplan Meier curves and multivariable Cox models cohort-stratified and adjusted for clinical factors (FLIPI, ECOG PS, age, grade 3A) were used to evaluate outcomes. Results: The median age at diagnosis was 57 years (IQR 49-64). 651 (51%) pts were treated with R-CHOP and 634 (49%) with BR. Within the study cohorts, there was a prevalence of cases receiving BR compared to R-CHOP in the Australian (90% vs 10%) and MER/LEO (68% vs 32%) cohorts, while the opposite was observed in the RELEVANCE (16% vs 84%) and FOLL12 (37% vs 63; p&lt;0.001) trials. Pts receiving R-CHOP were slightly younger (median 56 vs 58 years, p=0.005), more frequently had grade 3A (17% vs 7%, p&lt;0.001), elevated LDH (27% vs 22%, p=0.029), bulky disease &gt; 7 cm (44% vs 37%, p=0.019), lower ECOG PS (PS &gt;1 7% vs 13%, p&lt;0.001), and higher rate of high risk FLIPI (37% vs 30%, p=0.005). Baseline SUVmax was slightly lower in R-CHOP (median 10.7, IQR 7.9-14.9) vs BR (median 11.0, IQR 8.2-14.2) treated pts (p=0.0045). At a median follow-up of 56 months (range, 1-72 months), 415 pts (32%) had an event and 103 (8%) died. Higher SUVmax was not associated with EFS (middle tertile HR=0.96, 95% CI 0.76-1.22; upper tertile HR=0.86, 95% CI 0.68-1.09; p=0.45) or OS (middle tertile HR=1.28, 95% CI 0.80-2.05; upper tertile HR=0.97, 95% CI 0.59-1.59; p=0.44) in multivariable models stratified on cohort and adjusted for treatment and clinical factors. We then compared outcomes by treatment within tertiles of SUVmax. In multivariable models, R-CHOP had modestly inferior EFS to BR in low (HR=1.27, 95% CI 0.84-1.93) and middle tertiles (HR=1.49, 95% CI 0.99-2.25), and modestly superior OS to BR in low (HR=0.59, 95% CI 0.23-1.47) and middle (HR=0.79, 95% CI 0.37-1.71) tertiles. Both EFS (HR=1.06, 95% CI 0.71-1.58) and OS (HR=1.02, 95% CI 0.45-2.30) for R-CHOP were similar to BR in the highest tertile. No comparisons identified a statistically significant benefit for either therapy in multivariable models when evaluating SUVmax tertile subsets. Conclusions: In this large multicenter study of newly diagnosed FL pts with bPET who received frontline immunochemotherapy, higher baseline SUVmax was not associated with inferior outcomes after adjusting for treatment and clinical factors. Within the caveats of retrospective studies and confounding of treatment selection, these data provide no clear insights for SUVmax-based therapy selection in first-line follicular lymphoma pts treated with immunochemotherapy.

Background: Financial toxicity (FT), or the negative impact of medical expenses experienced by patients, is a known adverse effect of cancer treatment that result in worse health outcomes for patients. However, there is limited literature investigating FT in lymphoma with even less data on predictors such as age, gender, and socioeconomic factors. As lymphoma treatment options expand, it is vital to understand the impact of these treatments on patients' financial well-being. We investigate FT through patient reported outcomes from the Lymphoma Epidemiology of Outcomes (LEO), a large multi-institution prospective cohort study of non-Hodgkin lymphoma (NHL). Methods: Patients with newly diagnosed NHL were enrolled into the LEO cohort from 2015-2020. Clinical, pathology and treatment data were abstracted from medical records, and participants were offered self-administered surveys at enrollment and selected follow-up time points. Participants were included if they completed at least four of six survey questions on FT adapted from the Medical Expenditure Panel Survey (MEPS) within the first year after diagnosis. Questions focused on either material hardship (unable to cover costs; file for bankruptcy; borrow money; work extra job or hours) or psychological stress (worried about paying large medical bills). We evaluated FT as answering positively to any question (any vs none). Associations with FT were evaluated using chi-squared tests. All analyses were performed using R (v4.2.2). Results: 3202 patients completed at least four survey questions relating to FT. Mean age at diagnosis was 62 years (18-94), 56% were male, and majority identified as white (90%). Characteristics associated with FT are reported (p&lt;0.001). FT was more likely in younger patients: 18-25 years (64%, 30/47), 26-44 years (73%, 299/313), and 45-64 years (58%, 799/1375) as compared to those 65-79 years (36%, 459/1272) and ≥80 years (35%, 69/195). FT was highest in patients without a high school diploma (54%, 45/84), followed by patients with a high school diploma (52%, 209/402), and an associate's degree (57%, 358/627). It was lowest in patients with a bachelor's (45%, 224/296) or post-graduate degree (39.6%, 216/545). Higher FT was seen in those receiving disability income (65%, 47/72); whereas less FT was seen in retired patients (36%, 299/828). FT rates inversely correlated with income: 65% for income &lt; $21,000 (184/283), 61% for $21,000- $39,999 (224/370) and 60% for $40,000-$65,999 (293/491). Lower FT noted for income range of $66,000-$106,000 (47%, 323/681) or &gt; $106,000 (37%, 324/872). Patients separated from a partner (82.9%, 19/23) had the highest FT, followed by patients living with a partner (64%, 48/75), divorced (56%, 103/184), and never married (53.4%, 79/148). Patients who were married (47%, 793/1672) or widowed (41%, 60/146) reported the lowest FT. Higher FT was reported in DLBCL (55%, 631/1146), MCL (55%, 172/315), and TCL (53%, 119/226) when compared to FL (44%, 327/746), MZL (44%, 137/316), and other NHL (44%, 200/453). This is likely related to treatment as more FT was seen in patients who received an anthracycline and/or alkylator containing therapy (54%, 1066/1963) versus non-systemic (43%, 120/278) and observation (35%, 168/483). In multivariable analyses, FT strongly correlated with age at diagnosis, household income, and treatment type. The odds ratio and 95% confidence intervals for the most significant category within each variable are as follows: age per 1 year (0.96, [0.95-0.97]), income &gt; $106,000 vs &lt; $21,000 (0.28, [0.21-0.38]), and observation vs anthracycline and/or alkylator (0.56, [0.44-0.71]). Conclusion: Nearly 50% of patients with lymphoma experience FT, seen as material hardship and psychological stress, within the first year of diagnosis. Patients with a younger age (18-44), less education, and lower household income reported higher levels of FT; whereas those who were retired or married/widowed reported lower FT. Lymphoma subtypes that require more anthracycline and/or alkylator containing therapy imposed higher FT. Understanding these risk factors can help clinicians identify patients who may benefit from additional resources during lymphoma management.

Background: FL3B is the least common among FL subtypes, accounting for 5-10% of cases. Almost half of FL3B tumors have concurrent diffuse large B cell lymphoma (DLBCL) in the diagnostic tissue biopsy, while FL3B rarely coexists with FL1-2 or FL3A. Several lines of evidence suggest that FL3B displays distinct biological and clinical characteristics resembling aggressive DLBCL rather than the indolent FL1-3A. Accordingly, DLBCL anthracycline-containing regimens, such as R-CHOP, are the mainstay of therapy for FL3B with or without coexisting DLBCL. However, while some studies show that R-CHOP therapy in FL3B was associated with 5-year overall survival (OS) rate of 54%, others report outcomes comparable to FL3A with 79-90% survival. Additional controversy involves the clinical implication of pure FL3B (FL3Bp) vs FL3B with concurrent DLBCL (FL3Bc). Thus, it remains unclear if FL3B clinically resembles DLBCL or lower-grade FL and whether FL3Bp has a different prognosis from FL3Bc. To address these questions, we performed a pooled study of two large prospective multicenter study cohorts to compare the clinical characteristics and outcomes of newly diagnosed FL3B with FL1-2, FL3A and DLBCL patients, all of whom were uniformly treated with frontline R-CHOP. Patients and Methods: Weevaluated 469 newly diagnosed patients with FL1-2 (n=216), FL3A (n=170) and FL3B (n=83) who received R-CHOP within 6 months of diagnosis and 739 de novo DLBCL (GCB n=455 and non-GCB n=284) who were prospectively enrolled into the Molecular Epidemiology Resource (MER) and the Lymphoma Epidemiology of Outcomes (LEO) cohorts between 2002 and 2021. FL3B cases were designated as FL3Bc and FL3Bp based on the presence or absence of coexisting DLBCL, respectively. Histologic diagnosis was determined by an expert pathologist at each participating center and centrally reviewed. Event free survival (EFS) and OS were defined as time from diagnosis to progression, relapse, retreatment or death, and early progression defined as failing to achieve EFS at 24 months (EFS24). Associations between clinical features and EFS or OS were evaluated using Kaplan Meier curves and Cox proportional hazards models unadjusted and adjusted for age and FLIPI (comparisons with FL1-2 and FL3A) or IPI (comparisons with DLBCL). Results: The median age was 61 years (range, 18-94 years). Among FL3B patients, 21 (25%) had FL3Bc and 62 (75%) FL3Bp. Baseline characteristics and outcomes were broadly similar between the two FL3B subtypes. We then compared all FL3B patients to those with lower-grade FL. Patients with FL3B showed similar clinical features to those with FL1-2 and FL3A, with exception for a lower tumor burden. After R-CHOP, FL1-2 patients had an inferior EFS (HR 2.13 95%CI 1.31-3.46) than those with FL3B, whereas there was no difference compared to FL3A. OS was similar across all FL grades. Although FL1-2 patients failed to achieve EFS24 more frequently than FL3B and FL3A (34% vs 18% and 15%, p&lt;0.001), FL3B patients who did fail EFS24 had almost three folds higher risk of subsequent mortality (HR 2.84 95%CI 1.35-6.01) than other FLs. At 5-year follow-up, FL3B patients had twice the risk of relapse with an aggressive subtype (i.e., DLBCL, high-grade B-cell lymphoma) than those with FL1-2 and FL3A, who instead often recurred with indolent disease (i.e., FL1-2, FL3A; p&lt;0.001). We further compared FL3B patients to those with DLBCL classified based on cell-of-origin into GCB and non-GCB subtypes. At diagnosis, patients with FL3B had more favorable clinical features than those with GCB and non-GCB DLBCL. Compared to FL3B, patients with non-GCB DLBCL had an inferior EFS (HR 1.73 95%CI 1.07-2.79) and OS (HR 2.04 95%CI 1.11-3.75), while those with GCB DLBCL did not show a significant difference in EFS (HR 1.41 95%CI 0.88-2.25) or OS (HR 1.69, 95%CI 0.93-3.06) likely due to insufficient statistical power. Patients with FL3B failed EFS24 less frequently than patients with GCB or non-GCB DLBCL (17% vs 25% and 32%; p=0.01). Among patients who failed EFS24, those with FL3B had a similar subsequent OS as both GCB (HR 1.41 95%CI 0.73-2.72) and non-GCB DLBCL (HR 1.27 95%CI 0.65-2.47). Conclusions: We report that FL3Bp and FL3Bc appear clinically similar. While most FL3B patients have a prognosis comparable to FL1-2 and FL3A, 18% exhibit aggressive behavior with poor outcome reminiscent of DLBCL. Future studies with a larger population will be needed to confirm our findings.

Introduction: Non-invasive assays are needed to better discriminate patients with prostate cancer (PCa) to avoid over-treatment of indolent disease. We analyzed 14 methylated DNA markers (MDMs) from urine samples of patients with biopsy-proven PCa relative to healthy controls and further studied discrimination of clinically significant PCa (csPCa) from healthy controls and Gleason 6 cancers. Methods: To evaluate the panel, urine from 24 healthy male volunteers with no clinical suspicion for PCa and 24 men with biopsy-confirmed disease across all Gleason scores was collected. Blinded to clinical status, DNA from the supernatant was analyzed for methylation signal within specific DNA sequences across 14 genes (HES5, ZNF655, ITPRIPL1, MAX.chr3.6187, SLCO3A1, CHST11, SERPINB9, WNT3A, KCNB2, GAS6, AKR1B1, MAX.chr3.8028, GRASP, ST6GALNAC2) by target enrichment long-probe quantitative-amplified signal assays. Results: Utilizing an overall specificity cut-off of 100% for discriminating normal controls from PCa cases across the MDM panel resulted in 71% sensitivity (95% CI: 49–87%) for PCa detection (4/7 Gleason 6, 8/12 Gleason 7, 5/5 Gleason 8+) and 76% (50–92%) for csPCa (Gleason ≥ 7). At 100% specificity for controls and Gleason 6 patients combined, MDM panel sensitivity was 59% (33–81%) for csPCa (5/12 Gleason 7, 5/5 Gleason 8+). Conclusions: MDMs assayed in urine offer high sensitivity and specificity for detection of clinically significant prostate cancer. Prospective evaluation is necessary to estimate discrimination of patients as first-line screening and as an adjunct to prostate-specific antigen (PSA) testing.