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Abstract Introduction: Hemophagocytic lymphohistiocytosis (HLH) is a rare and life-threatening hyperinflammatory syndrome resulting from immune dysregulation. While diagnostic and therapeutic guidelines (e.g., HLH-2004) are established for pediatric HLH, adult-onset HLH remains both a diagnostic and therapeutic challenge, with limited characterization and sparse outcome data. Here, we conduct a single-institution retrospective cohort study to evaluate clinical features, causes, and prognostic markers associated with outcomes. Methods: We performed a retrospective chart review of all adult patients (≥18 years) first diagnosed with HLH across all Mayo Clinic sites between January 1, 2006 and July 1, 2025. Diagnosis was based on hematologist adjudication at time of care. Patients with prior diagnoses of HLH or HLH related to T-cell therapy (CAR-T) were excluded. Clinical and laboratory variables were extracted from electronic health records. The primary outcome was overall survival (OS), defined as time from diagnosis of HLH to death or last follow-up. OS was estimated using the Kaplan-Meier method. Multivariable analysis to identify independent predictors of mortality was performed using a Cox proportional hazards regression model, adjusting for age at diagnosis, sex, HLH etiology, and relevant clinical and laboratory parameters. Model discrimination was assessed using Harrell's concordance index (c-index). Descriptive statistics were summarized using median and interquartile range (IQR) for continuous variables and frequency with percentages for categorical variables. Results: A total of 203 patients diagnosed with HLH were included. The median age at diagnosis was 55 years (range 18-86). The cohort was predominantly male (n=130, 64%) and White (n=163, 80%). The majority of diagnoses occurred in more recent years, with 75 patients (36.9%) diagnosed between 2021–2025, 61 (30.0%) between 2016–2020, and 43 (21.2%) between 2011–2015. Prior to HLH diagnosis, 86 patients (42.4%) had a history of malignancy, 55 (27.1%) had a history of autoimmune disease, and 28 (13.8%) had a history of transplant. The most common HLH etiologies were malignancy-associated (n=99, 49%), infectious (n=51, 25%), and autoimmune (n=24, 12%), in addition to idiopathic (n=6, 3%), post-transplant lymphoproliferative disease or graft-vs-host disease (n=3, 1%), drug-induced (n=3, 1%), or primary HLH (n=1, 0.5%). The most common malignancies included T-cell (n=35, 17.2%) and diffuse large B-cell lymphoma (n=24, 11.8%). Forty-four cases (21.7%) were associated with Epstein-Barr virus (EBV), either through overt viremia or malignancies with EBV positivity on pathology report. Five patients (2.5%) had COVID-19–associated HLH and 2 (1.0%) were attributed to immune checkpoint inhibitors. Overall, 164 patients (80.8%) met the HLH-2004 diagnostic threshold of ≥5 out of 8 criteria, while 196 (96.6%) met the HLH-2024 ≥4 of 7 modified criteria. Among patients with available information, elevated ferritin was present in 197 of 198 (99.5%), fever in 185 of 202 (91.6%), cytopenias involving ≥2 lineages in 184 of 199 (92.5%), hemophagocytosis in 156 of 182 (85.7%), elevated sCD25 in 117 of 121 (96.7%), hypertriglyceridemia in 117 of 186 (62.9%), hypofibrinogenemia in 118 of 196 (60.2%), splenomegaly in 125 of 188 (66.5%), and impaired NK cell activity in 16 of 25 (64.0%). In addition, hepatomegaly was noted in 57 of 195 patients (29.2%). After a median follow-up of 58.3 months, median OS was 62 days (95% CI 40-110) from day of diagnosis. In a multivariable Cox proportional hazards model with moderate discrimination (c-index=0.75), after adjusting for age at diagnosis and sex, T-cell lymphoma–driven HLH (HR 1.78, 95% CI 1.05–3.00, p = 0.03) and elevated blood urea nitrogen (median 51.0 mg/dL, IQR 27.9–99.1; HR 2.07, 95% CI 1.37–3.13, p < 0.005) were independently associated with shorter OS Conclusions: In this cohort of adult patients with HLH, malignancy was found to be the most common trigger for HLH. T-cell malignancies in particular were strongly correlated with poor survival. Elevated blood urea nitrogen at diagnosis also identified patients at significantly higher risk of death, consistent with other critical illnesses that can present with multi-organ failure. These findings emphasize the need for adult-specific prognostic tools incorporating disease etiology and organ dysfunction markers to better stratify risk and guide clinical management in adult-onset HLH.

Abstract Background: Rural/nonmetropolitan (nonmetro) counties face known barriers to comprehensive cancer care compared with metropolitan (metro) counties, which may impact the outcomes for lymphoma patients. We evaluated the impact metro vs nonmetro status on outcomes after a diagnosis of non-Hodgkin lymphoma (NHL) in the context of clinical, demographic, and lifestyle factors. Methods: Of 7724 participants enrolled in the prospective LEO cohort study from 2015-2020, 7610 (98.5%) had their county of residence at diagnosis assigned a RUCC (2013) code. We compared outcomes of participants from metro (defined as RUCC 1-3, which are central counties with ≥1 urban areas of ≥50,000) vs nonmetro counties (RUCC 4-9, which are counties with smaller urban areas as well as completely rural). We estimated hazard ratios (HRs) and 95% confidence intervals (CI) from univariable and multivariable Cox models for associations of metro status with overall survival (OS). Cause of death (lymphoma [including treatment related], non-lymphoma, unknown) was assessed using a competing risk approach. Results: Compared with metro counties (N=6096), LEO participants from nonmetro counties (N=1514) were older (median age 64 vs 62 years; p<0.001), more likely to be non-Hispanic white (94% vs 75%; p<0.001) and married (84% vs 75%; p<0.001), and less likely to have completed graduate or professional school education (16% vs 27%; p<0.001). There were no notable differences (>5%) by metro status for sex, employment status, NHL subtype, stage, performance status, abnormal lactate dehydrogenase (LDH), international prognostic index (IPI), number of comorbidities, time from diagnosis to treatment interval (DTI) or participation in a clinical trial. Compared with LEO participants from metro counties, those from nonmetro counties had inferior OS at 5 years (74.5% vs 78.4%; HR=1.23, CI 1.10-1.37; p<0.001). The OS association only slightly attenuated after adjustment for age, sex, race/ethnicity and NHL subtype (HR=1.20, CI 1.07-1.34; p=0.002), and held in models that adjusted for clinical prognostic factors (stage, NHL subtype, IPI, DTI), socioeconomic status (SES; education, marital status), health status (comorbidity, frailty), or lifestyle factors (smoking, body mass index). Using a competing risk model, the cumulative incidence of death at 5 years due to lymphoma (16.9% vs 14.1%; p=0.002) and non-lymphoma (5.9% vs 3.9%; p=0.002) was higher for participants from nonmetro vs metro counties, respectively. For participants <65 years, nonmetro vs metro status had inferior OS (HR=1.40, CI 1.17-1.67; p<0.001). This association remained after adjustment for age, sex, race/ethnicity and NHL subtype (HR=1.36, CI 1.14-1.63; p<0.001), as well as after adjustment for clinical prognostic, SES, health status, or lifestyle factors. The cumulative incidence of death at 5 years due to lymphoma was higher in participants from nonmetro vs metro counties (15.1% vs 11.5%; p=0.002), while there was no difference by metro status for non-lymphoma related deaths (2.1% vs 1.7%; p=0.47). In contrast, for participants age 65+ years, there was no differences by metro status for OS (HR=1.04, CI 0.91-1.20; p=0.56). After adjustment for age, sex, race/ethnicity and NHL subtype, participants from nonmetro areas had inferior OS (HR=1.12, 0.97-1.29) although this was not statistically significant (p=0.13), and was attenuated in models adjusting for clinical, health status, or lifestyle factors. The cumulative incidence of death at 5 years due to lymphoma was no different in participants from nonmetro vs metro counties (18.9% vs 18.0%; p=0.37), while non-lymphoma related deaths were higher in nonmetro counties (9.9% vs 6.8%; p=0.017). Conclusion: LEO participants from nonmetro vs metro counties had inferior OS overall, although this was predominately observed for younger (<65 years) participants. These associations did not appear to be explained by demographic, NHL subtype, clinical, SES, health status, or lifestyle factors. Of particular note, the risk of death due to lymphoma was higher in nonmetro areas for participants <65 years but not those 65+ years, while the risk of death due to other causes was higher in nonmetro areas for participants 65+ years but not those <65 years. These findings require further study, particularly related to barriers to care, and suggest the potential need for age-specific strategies to optimize outcomes for NHL patients from nonmetro/rural areas.

Abstract Background: In 2022, Medicare alone spent $42.1 billion on prescription drugs, with antineoplastic and classical hematology drugs accounting for 44% and 8% of the total, respectively (2024 MedPAC Data Book). While antineoplastic drugs have been extensively studied, classical hematology drugs have received comparatively little attention. We analyzed US Food and Drug Administration (FDA) approvals of classical hematology drugs over the past 30 years and examined their per-patient costs and annual total US sales. Methods: We identified all classical hematology drugs (those prescribed by hematologist/oncologists for non-malignant indications) approved by the FDA from January 1, 1995 to December 31, 2024, including novel pharmaceuticals (synthesized from chemical compounds), biologics (derived from living organisms), and biosimilars (highly similar, but not identical, to biologics previously approved). Cost estimates for 2024 were based on wholesale acquisition costs (WAC), using annual WAC for continuous-duration treatments and typical course WAC for fixed-duration treatments. WAC and US gross sales data for 2024 were obtained from IPD Analytics (Aventura, FL). Results: A total of 98 classical hematology drugs were approved over the past 30 years—11% in 1995–2004, 26% in 2005–2014, and 63% in 2015–2024. These included pharmaceuticals (36%), biologics (54%), and biosimilars (10%). Six gene therapies received approval: 3 for hemophilia and 1 each for sickle disease, beta thalassemia, and sickle cell disease/beta thalassemia (dual indication). Common categories of indications included bleeding (31%), anemia (30%), neutropenia (9%), and thrombocytopenia (9%). Leading diagnoses were hemophilia (25%), chemotherapy-induced neutropenia (9%), thromboembolism (8%), paroxysmal nocturnal hemoglobinuria (PNH; 7%), anemia of chronic kidney disease (6%), iron deficiency anemia (6%), and immune thrombocytopenia (5%). The median cost for gene therapies was $2.9 million per treatment (range: $2.2 million–$3.5 million). Among non-gene therapies, median costs were $3,000 per course for fixed-duration treatments (range: $64–$378,000) and $467,000 annually for continuous-duration treatments (range: $2,400–$1.8 million). The most expensive fixed-duration treatments targeted hemophagocytic lymphohistiocytosis ($378,000/8-week course), while the most expensive continuous-duration treatments were for hemophilia (median: $630,000/year; range: $270,000–$853,000). Estimated 2024 US gross sales across all drugs exceeded $70 billion. Top-selling indications included thromboembolism ($43.5 billion), hemophilia ($6.9 billion), immune thrombocytopenia ($4.9 billion), PNH ($4.7 billion), chemotherapy-induced neutropenia ($2.8 billion), anemia of chronic kidney disease ($2.0 billion), and iron deficiency anemia ($1.8 billion). Total sales for all gene therapies combined were $143 million. Six drugs have been discontinued (year approved/year discontinued/reason): betrixaban (2017/2020/business), daprodustat (2023/2024/business), fidanacogene elaparvovec (2024/2025/business), oprelvekin (1997/2011/business), peginesatide (2012/2013/safety), and voxelotor (2019/2024/safety). There are limitations to our study. Some drugs have non-classical hematology indications (anticoagulants in atrial fibrillation; luspatercept in myelodysplastic neoplasm) and/or may also be prescribed by non-classical hematologists (erythropoiesis stimulating agents by nephrologists and medical oncologists). We were unable to disaggregate the sales data in these situations. Therefore, the annual sales for certain indications may be overestimated. Conclusions: Classical hematology drugs contribute substantially to US prescription drug spending, with over $70 billion in annual sales and medications for thromboembolism accounting for over half of the costs. Approvals have accelerated over the past three decades, doubling each decade. Biologics and biosimilars now represent two-thirds of approvals. Continuous-duration treatments, particularly for rare hereditary diseases like hemophilia, carry significant financial burden, with annual costs per patient often exceeding $0.5 million. In these conditions, if gene therapies demonstrate durable efficacy, they may prove to be cost-effective alternatives. As more gene therapies are developed, evaluating their long-term value relative to chronic high-cost treatments will be essential for shaping future reimbursement and access strategies.

Abstract Diffuse Large B Cell Lymphoma (DLBCL), the most common subtype of aggressive B-cell Non-Hodgkin Lymphoma (NHL), accounts for 30-40% of newly diagnosed NHL cases. Despite recent progress improving our understanding of molecular features of DLBCL, there is still a high relapse rate (~45%) among patients who undergo standard treatment (R-CHOP). Several groups have identified reproducible molecular clusters of DLBCL although, the biologic significance of many of the specific gene mutations within these clusters is poorly understood. DTX1 mutations are a feature of the BN2/C1 DLBCL classifiers and are among the mutations with unknown significance. BN2/C1 DLBCL are a mixture of ABC, GCB, and Unclassified cell of origin (COO) with a common signature being the presence of genetic alterations in genes known to regulate the NOTCH pathway; yet, these tumors lack transcriptional signatures of traditional NOTCH activation, suggesting a unique and undefined biology driven through non-canonical NOTCH pathway activation. DTX1 is an E3 ubiquitin ligase which directly binds the intracellular domain of the NOTCH receptor (NICD), targeting it for degradation, resulting in suppression of NOTCH pathway activity. We therefore hypothesize that DTX1 mutations lead to NOTCH pathway dysregulation and are a critical driver for a subset of BN2/C1 DLBCLs. Using whole exome sequencing (WES) data from 404 newly diagnosed DLBCL patients, we found 8% of patients with mutations in DTX1. Alterations in DTX1 were localized to the NICD binding domain, WWE1. In silico Alphafold modeling of DTX1 WWE1-interaction with NICD revealed that patient mutations clustered within predicted interacting surfaces with NICD. These findings lead to the hypothesis that mutations in the DTX1 WWE1 domain suppress its ability to bind to and degrade NICD, enhancing NOTCH pathway activation in DLBCL. To address this question, we first compared DTX1 protein expression by immunoblot in DTX1 WWE1 mutant (OCI-Ly3 and SUDHL2) and wildtype (WT) (OCI-Ly7, OCI-Ly19, SUDHL6, and U2932) DLBCL cell lines. We found higher expression of NICD1 (p=0.03) in OCI-Ly3 and NICD2 (p<0.0001) in SUDHL2 cell lines compared to WT. This increase was accompanied by an increase in NOTCH surface expression with higher NOTCH1 (p<0.0001) and NOTCH2 (p<0.0001) expression on OCI-Ly3 and SUDHL2 cells, respectively, compared to WT. To remove variability across cell lines we next used CRISPR to generate DTX1 knock out (KO) models using WT DTX1 DLBCL cell lines U2932 and OCI-Ly19. Analysis of NICD and NOTCH receptor protein expression confirmed our initial finding, showing an 8.5 and 4.8-fold increase of NICD1 and a 6 and 2.5-fold increase of NICD2 expression in the U2932 and OCI-Ly19 DTX1 KO cell lines, respectively, compared to empty vector (EV) controls. An increase in surface NOTCH1, and to a lesser extent NOTCH2, was seen in U2932 (p=0.01 and p=0.07, respectively) and OCI-Ly19 (p=0.001 and p=0.2, respectively) KO cells compared to EV controls. To identify pathways affected by DTX1 mutations, we next performed RNAseq on U2932 EV and KO cell lines. Of interest, we did not detect any significant changes in classical NOTCH driven genes (Hes1, Hey1, etc.), supporting prior studies on BN2/C1 tumors. However, we did identify potential non-canonical NOTCH-target genes that may contribute to lymphomagenesis. Gene expression in KO cells showed upregulation of genes involved in germinal center (GC) processes (AICDA, IRF4; p<0.001) and cellular growth and survival (IL6R, CCND2, STAT5B, BCL2; p<0.0001). Measurement of IL6R by flow cytometry and CyclinD2 by immunoblot further verified DTX1-mediated upregulation of IL6R (p<0.01) and CyclinD2 (p<0.01) for U2932 KO cells compared to EV control. We also observed downregulation of genes contributing to cell death (ex. BAX, CASP8, FAS; p<0.05) in KO cells compared to EV. Together, these novel findings support our hypothesis that DTX1 WWE1 mutations lead to dysregulation of the NOTCH pathway by driving overexpression of NICD and NOTCH, resulting in dysregulated expression of proteins involved in cell cycle, GC reaction, and apoptosis. We further provide new biologic insight into BN2/C1 DLBCL, ultimately highlighting a path toward novel therapeutic targets and the advancement of personalized medicine, as patients harboring these mutations may benefit from new therapies targeting inflammatory pathways, such as CELMoDs.

Abstract Background: Gastrointestinal (GI) symptoms are frequent in patients (pts) with systemic light chain amyloidosis (AL), yet their clinical significance remains poorly defined. We investigated the role of symptomatic GI involvement in disease burden, survival, and organ-specific outcomes in a large single-center cohort. Methods From 2010–2025, 4,396 AL pts were evaluated at our center; 560 pts (13%) had provider-attributed symptomatic GI AL. Pts with localized AL or positive biopsy without GI symptoms were excluded (n=38). We analyzed relationships between GI symptoms, anatomic/histologic involvement, laboratory parameters, survival, and need for nutritional support using Wilcoxon rank-sum, Chi-square, Kaplan-Meier, and logistic regression tests. Results GI symptoms included early satiety (n=320/57%), diarrhea (n=189/34%), nausea (n=184/33%), abdominal pain (n=148/26%), dysphagia (n=119/21%), vomiting (n=75/13%), GI bleeding (n=74/13%), and heartburn (n=71/13%). Only nausea and GI bleeding were not associated with cardiac (n=366/65%) renal (n=274/49%) or hepatic (n=84/15%) AL, whereas dysphagia, early satiety and heartburn were more frequent with cardiac (all OR=1.7), abdominal pain and diarrhea with hepatic (OR=2 and 1.6, respectively), and vomiting with renal involvement (OR=2; all p<0.04). Autonomic involvement impacted GI symptoms, often without proof of parenchymal GI amyloid. Of the 124 pts with formal autonomic testing, only 44 (35%) had positive GI biopsies as compared to AL GI pts without proven autonomic involvement (240/436, 55%). Pts with autonomic involvement were more symptomatic than pts with positive GI biopsies, suffering more often from dysphagia (29% vs 19%), diarrhea (41% vs 32%), and gastroparesis (34% vs 9%, all p<0.001). We screened changes in body weight, calcium, VitB12, Hb, PO4, and albumin at diagnosis. Of the 175 pts with documented weight loss in this cohort, pts with GI AL lost more weight compared to those with other organ involvement (21% vs 14% of weight, p=0.002), and had lower phosphate (3.7 vs 4.0 mg/dL, p=0.06). In our cohort of pts with GI symptoms, 298 (53%) had a positive GI biopsy. Biopsy-proven anatomic involvement dictated symptoms (all p<0.05): Of the 20 pts with positive esophageal biopsy, dysphagia was present in 45%; only 33% of the pts without an esophageal biopsy had dysphagia. Similar patterns were seen for the 170 pts with a positive gastric biopsy (n=170) in terms of heartburn (21% vs 11%), for the 165 pts with positive small bowel biopsies in terms of abdominal pain (68% vs 32%), and for the 130 pts with positive colon biopsies and diarrhea (46% vs 33%). Specific histopathological patterns were prognostic. Mucosal involvement (n=161) was an independent risk factor for survival compared to submucosal (n=64) and vascular (n=102) involvement throughout the GI tract (HR 1.83; p=0.03). Three-layer GI infiltration was associated with inferior mOS (2.4 vs 5.1 vs 7.8 y for 3 vs 2 vs 1-layer involvement, HR 3.19/1.56/1; p<0.05). Counterintuitively, vascular involvement had the lowest risk of bleeding in all GI anatomic sites (p=0.02). In the colon, only mucosal involvement was associated with a higher risk of bleeding (OR=5; p=0.04). GI involvement in AL pts did not worsen prognosis (mOS 10.0/6.3y, p=0.02), and pts with isolated GI AL (n=74/13%) had an even better survival (55% surviving at 10 y). Cachexia (n=120; mOS 3.5 vs 7.8 y, p<0.001), need for nutritional support (n=36; mOS 0.9 vs 7.0 y, p<0.001), and diarrhea (mOS 5.8 vs 6.9 y, p=0.06) were risk factors for death. In pts with hematologic response (≥PR), bleeding did not recur within 3 y (n=27), but even with response, diarrhea (n=160) persisted in 39%. Resolution was less frequent without hematologic response (persistence in 69%, OR=3.5). Improvement was most often due to treatment of bacterial overgrowth (11/35 pts; 68%) and loperamide (54/59 pts; 91%). Conclusion In AL, meaningful GI involvement is defined by nausea, diarrhea, occurrence of bleeding, and malnutrition. These are primarily associated with mucosal infiltration. GI symptoms can occur in the face of autonomic involvement. While long-term persistence of GI bleeding is rare after serologic response, cachexia and persistent diarrhea drive morbidity, need for nutritional support, and poor survival.

Abstract Background: Four bispecific antibodies (bsAbs), teclistamab, elranatamab, talquetamab, and linvoseltamab have been approved for use in the U.S. in patients (pts) with relapsed/refractory (R/R) multiple myeloma (MM). The objective of this analysis was to describe healthcare resources utilization (HCRU) in Medicare pts initiating treatment (≥1 medical claim) with teclistamab for R/R MM, and to explore how HCRU differs for pts who initiate in the inpatient (IP) vs outpatient (OP) setting. We focused only on teclistamab due to insufficient follow-up for robust analyses of other bsAbs. Methods: The study used data from a 100% sample of fee-for-service Medicare enrollment and medical (Parts A and B) claims data during the “study period” spanning from 12 months prior to the approval of teclistamab to the end of availability of claims data (Oct 25, 2021–Sep 30, 2024). The study population included all pts in the database with ≥1 diagnosis of MM and ≥1 claim for teclistamab ≥30 days prior to the end of the study period. Patients were required to be continuously enrolled for Medicare medical benefits for the 12 months up to and including the 1st claim for teclistamab (the “index date”). Other main eligibility criteria included: 1) index date on/after availability of both IP and OP procedure codes for teclistamab; 2) no claims for MM treatment other than teclistamab or a corticosteroid within 0–30 days post index date; 3) if 1st administration of teclistamab was in the OP setting, dosage was consistent with first step up dose (SUD) and 4) ≥65 years of age as of index date. For each patient, the follow-up period was defined as the period from the index date to first occurrence of death, end of continuous enrollment, or end of study period. Setting of initiation of treatment was defined based on the setting of the first claim for teclistamab (IP or OP). For pts who initiated teclistamab in the IP setting, completion of SUD was defined as ≥1 OP administration with a full treatment dose of teclistamab (i.e., not an SUD) that occurred ≥10 days post index date. For those who initiated teclistamab in an OP setting, completion of SUD was defined as ≥2 OP administrations of teclistamab at a full treatment dose. The number of hospitalizations and physicians' office and hospital OP visits during teclistamab treatment were calculated on a per patient per month (PPPM) basis. Results: A total of 2,185 pts had ≥1 claim for teclistamab during the study period. Of these, 1,373 met all eligibility criteria. Mean (median) age at index date was 75 (74) years and 49% were female. Mean (median [range]) follow-up was 8.2 (7 [0.2–22.7]) months. Overall, 87% of pts initiated teclistamab in an IP setting, with a mean length of stay (LOS) for the index hospitalization of 9.3 days. Among those initiating teclistamab in an OP setting, 41% were hospitalized within 1 month of treatment initiation. Among all pts (IP or OP initiation of treatment), the Kaplan–Meier estimated median duration of teclistamab treatment was 6.1 months; 87% of pts completed SUD. Patients had a mean (median) of 0.72 (0.32) hospitalizations PPPM and 6.4 (5.8) hospital outpatient or physician's office visits PPPM during teclistamab treatment. Conclusions:Most pts with MM receiving teclistamab initiate treatment in an IP setting, with hospital LOS consistent with dosing guidance from the prescribing information. A substantial proportion of those who initiate teclistamab in an OP setting are hospitalized within 30 days. Treatment duration and percentage of pts completing SUD were consistent with values in other real-world studies of teclistamab. Patients receiving teclistamab have a high hospitalization burden during treatment initiation and frequent hospitalizations and OP visits over the course of treatment. These results highlight the need for novel treatments, administration models, and/or implementation of standardized supportive care guidelines to reduce the hospital burden and increase time on treatment for pts receiving bsAbs in real world settings.

Key Points Genetic testing in CKD showed diagnostic and clinical utility in the year following reporting of test results. Genetic testing was helpful for or changed management in 86% of patients with a positive finding and 42% with a negative finding. Clinical utility was seen across 12 clinical cohorts, including CKD of unknown etiology and hypertension or diabetes-related nephropathy. Background CKD is a significant public health burden, affecting >800 million people worldwide with significant cost to the health care system. CKD is a disease process with substantial genetic and phenotypic heterogeneity that can obscure a definitive diagnosis, resulting in suboptimal management. Recent guidelines support greater adoption of genetic testing in CKD. We assessed the diagnostic and clinical utility in the year following broad-panel CKD genetic testing. Methods The Renasight Clinical Application, Review, and Evaluation (RenaCARE) study (NCT05846113) was a single-arm, interventional, prospective, multicenter study evaluating the utility of genetic testing with a 385-gene panel on the diagnosis and management of CKD. Clinical history was collected before testing, and nephrologists responded to questionnaires at both 1 month and 1 year after testing. The impact of genetic testing on CKD diagnosis and management were assessed in active study patients at the 1-year time point. Results In a cohort of 1388 CKD patients with 13 pretest clinical categories of CKD, 335 (24%) patients had a positive genetic finding; 1174 had a questionnaire completed at 1 year and were included in the analysis. Genetic testing was reported helpful for clinical management and/or led to a change in management in 86% of patients with a positive test finding and 42% of patients with a negative test finding. In addition, genetic testing resulted in a change in the physician estimation of the 5-year prognosis for 55% of patients with a positive test finding and 18% of those with a negative test finding. Conclusions Supporting the previous results of the RenaCARE study at 1 month, this report demonstrated that genetic testing was helpful in the clinical management and estimated prognosis of patients with CKD. Clinical Trial registry name and registration number: ClinicalTrials.gov, NCT05846113.