Janda, Guneet

Abstract Introduction: Suboptimal response to therapy, early disease relapse, and limited long-term survival remain critical challenges in a substantial number of patients with multiple myeloma (MM). While cross-sectional imaging studies are commonly obtained in clinical practice, only limited information is currently incorporated into risk stratification efforts and clinical decision making. Here, we investigate the use of novel image-based biomarkers to identify patients at high risk for adverse outcomes. Methods: We obtained the pretreatment 18F-FDG PET/CT scans of patients with newly diagnosed MM with available clinical and laboratory data seen at Mayo Clinic between 2006 and 2022. In this analysis, we included 637 patients with detectable metabolic tumor volume on their pretreatment scan. The native DICOM images were pre-processed and subjected to automated image segmentation using nnU-Net (nnU-Net v1.0, inference using a pre-trained hematologic malignancies model). Limitations of this automated segmentation approach include heterogeneity introduced by varying image quality, technical variability in PET reconstruction, and potential inclusion of non-neoplastic FDG-avid lesions in segmented regions. PyRadiomics was used to extract quantitative radiomics features for clinical prediction modeling. We evaluated the predictive power of tumor size-, shape-, and texture-related radiomics features for identifying high-risk disease (advanced ISS stage at diagnosis, the presence of high-risk FISH abnormalities, failure to achieve a stringent complete response [sCR] to first-line therapy by IWMG criteria, and early mortality). All radiomics features were quantile-normalized for downstream modeling. Forward and backward feature selection as well as testing for multicollinearity were used to remove redundant features. Results: Median age at diagnosis of the 637 myeloma patients was 64 years (range 22–90), and 387 patients (61%) were male. After a median follow-up of 4.4 years (95% CI 0.2–11.7), median overall survival (OS) was 7.3 years (95% CI 6.3–8.3). Increased total tumor volume (upper tertile vs lower tertiles), measured by the total tumor surface area, was associated with advanced ISS stage (III vs I+II; OR 1.73, 95% CI 1.24–2.42, p=0.001, n=637). Increased tumor density (dichotomized at the median), measured by the median gray level intensity (OR 1.93, 95% CI 1.94–3.12, p=0.007, n=303), and decreased tumor heterogeneity (lower tertile vs upper tertiles), measured by the variability of gray-level intensities (OR 1.88, 95% CI 1.49–3.12, p=0.012, n=303), were associated with the presence of high-risk cytogenetics. Both increased total tumor volume (4.9% increase per tertile, 95% CI 2.2–7.6, p<0.001, n=600) and tumor density (8.9% increase per tertile, 95% CI 4.5–13.3, p<0.001, n=600) were independently associated with more extensive bone marrow involvement at diagnosis. Increased tumor heterogeneity (upper tertiles vs lower tertile), as measured by rapid changes of gray level intensities, was associated with failure to achieve a stringent complete response to first-line therapy (OR 0.50, 95% CI 0.30–0.82, p=0.006, n=351). Increased tumor volume was associated with shorter OS (HR 1.35 per tertile, 95% CI 1.11–1.63, p=0.002, n=301), independent of age, sex, ISS stage, and the presence of high-risk cytogenetics. A simple additive score consisting of tertiles of total tumor volume, ISS stage, and plasma cell labeling index ≥2% identified patients at risk of mortality within 3 years of diagnosis (OR 2.00, 95% CI 1.40–2.85, p<0.001, n=126), with moderate discrimination (AUC=0.71). Sensitivity analysis demonstrated total tumor volume and texture as most predictive of overall survival in a random forest survival model (C-index 0.712, 95% CI 0.649–0.775) and tumor texture as most predictive of response to therapy in a random forest classification model (C-index 0.693, 95% CI 0.607–0.779). Conclusions: Automated image segmentation and radiomics feature extraction from 18F-FDG PET/CT scans produces biomarkers that capture disease stage, burden, and risk in newly diagnosed MM. Total tumor volume and heterogeneity are strongly associated with important disease characteristics and can be used to identify patients at high risk for therapeutic resistance, early mortality, and inferior long-term outcomes.

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.

e13042 Background: The conventional treatment paradigm for metastatic breast cancer (MBC) is to continue systemic therapy until disease progression. With improved systemic therapy options, some patients (pts) with MBC attain radiographic remission. Tumor-informed circulating tumor (ct)DNA detects molecular disease burden and may guide decision-making. We report on an institutional cohort of pts with MBC in which tumor-informed ctDNA testing was utilized prospectively to guide decisions on systemic therapy or surveillance imaging frequency. Methods: Utilizing an IRB-approved protocol, we retrospectively identified pts monitored with tumor-informed ctDNA using the Signatera™ mPCR-NGS assay (Natera, Inc) as part of routine clinical care in Mayo Clinic, Rochester. We then identified a subset with biopsy-proven MBC who attained radiographic remission of disease following systemic therapy, deemed by the treating medical oncologist as “exceptional responders”. Real-time ctDNA testing was used to inform a decision to either discontinue systemic therapy, treatment de-escalation (remove a component of multi-drug therapy), increase the time interval between restaging scans, or stay off therapy previously stopped due to toxicity . Data on breast cancer characteristics, imaging results, ctDNA test results, and outcomes were collected. Descriptive statistics were used to analyze the data. Results: 10 pts met our study criteria. The median age at MBC diagnosis was 42 years (range 28-61); 5 pts had TNBC, 3 pts had HER2+, and 2 pts with ER+/HER2- MBC. Most pts (60%) were on first or second line therapy (range 1-5). The median duration of the most recent regimen was 27.5 months (range 10-70 months). All pts were without radiographic evidence of active cancer at the time of ctDNA testing with negative results (0 MTM/mL) at the time of clinical decision-making. 4 pts stopped all systemic therapy and proceeded with observation (1 trastuzumab, 1 trastuzumab deruxtecan, 1 pembrolizumab, and 1 talazoparib). 2 pts discontinued a targeted therapy (1 olaparib, 1 abemaciclib) while continuing endocrine therapy. 1 patient stopped targeted therapy (abemaciclib) due to a blood clot, and ctDNA testing guided the decision to not start another CDK4/6 inhibitor while continuing endocrine therapy. In 3 pts the frequency of restaging scans was decreased to either annually or semi-annually. The median follow-up after a ctDNA-informed decision was 11 months (range 1-41 months). At this time, no patient has converted to ctDNA-positivity, experienced resurgence or progression of disease, needed to change systemic therapy or increase imaging frequency. Conclusions: Tumor-informed ctDNA may offer additional confidence to oncologists and pts to deescalate systemic therapy or decrease the interval of imaging frequency in exceptional responders with MBC. Additional data to support this approach is needed.

This cross-sectional study assesses published research articles about medical items and services approved by the Coverage With Evidence Development program to characterize their scientific impact.

Introduction In 2005, the Centers for Medicare and Medicaid Services introduced the Coverage with Evidence Development program for items and services with limited evidence of benefit and harm for Medicare beneficiaries, aiming to generate evidence to determine whether they meet the statutory “reasonable and necessary” criteria for coverage. Coverage with Evidence Development requires participation in clinical studies approved by the Centers for Medicare and Medicaid Services (i.e. Coverage with Evidence Development-approved studies) as a condition of coverage. We examined the quality of evidence generated by Coverage with Evidence Development-approved studies compared with those that informed Centers for Medicare and Medicaid Services’ initial Coverage with Evidence Development decisions (i.e. National Coverage Determination studies). Methods Using Centers for Medicare and Medicaid Services’ webpage, we identified all items and services covered under Coverage with Evidence Development and their Coverage with Evidence Development-approved studies. Through searching PubMed and Google Scholar, we identified original research articles that reported results for primary endpoints of Coverage with Evidence Development-approved studies. We then reviewed the initial Coverage with Evidence Development decision memos and identified National Coverage Determination studies that were original research.We characterized and compared Coverage with Evidence Development-approved studies and National Coverage Determination studies. Results From 2005 to 2023, 26 items and services were covered under the Coverage with Evidence Development program, associated with 196 National Coverage Determination studies (170 (86.7%) clinical trials and 26 (13.3%) registries) and 116 unique Coverage with Evidence Development-approved studies (86 (74.1%) clinical trials, 23 (19.8%) registries, 4 (3.4%) claims-based studies, and 3 (2.6%) expanded access studies). Among clinical trial studies, National Coverage Determination studies and Coverage with Evidence Development-approved studies did not differ with respect to multi-arm design (59.4% vs 68.6%; p = 0.15). However, among multi-arm clinical trial studies, National Coverage Determination studies were less likely than Coverage with Evidence Development-approved studies to be randomized (52.5% vs 93.2%; p < 0.001). Overall, National Coverage Determination studies less frequently had ≥ 1 primary endpoint focused on a clinical outcome measure (65.8% vs 87.9%; p = 0.006) and less frequently exclusively enrolled Medicare beneficiaries (3.1% vs 25.9%; p < 0.001). In addition, National Coverage Determination studies had smaller population sizes than Coverage with Evidence Development-approved studies (median 100 (interquartile range, 45–414) vs 302 (interquartile range, 93–1000) patients; p = 0.002). Among Coverage with Evidence Development-approved studies, 59 (50.9%) had not yet publicly reported results for the primary endpoint. Discussion Studies required under Medicare’s Coverage with Evidence Development program more often used randomized study designs, had larger patient populations, enrolled US patients, and focused on clinical outcomes as primary endpoints than studies used to inform initial National Coverage Determinations. However, not all Coverage with Evidence Development-approved studies have thus far reported results, which could create uncertainty for patients, physicians, and payers regarding the clinical benefits of covered items and services. Conclusion The Centers for Medicare and Medicaid Services’ Coverage with Evidence Development program has successfully prompted generation of more robustly designed clinical studies to better inform clinical, regulatory, and coverage decisions compared to studies informing initial coverage decisions. Yet, opportunities exist to further strengthen the design and dissemination of studies required under this program.