Development and validation of an artificial intelligence–based deep learning imaging model for early lung cancer detection: DAVINCI, a retrospective study of 8,962 patients.
8021 Background: Lung cancer is the leading cause of cancer-related mortality worldwide, primarily due to delayed diagnosis and diagnostic variability in histopathological assessment. Advances in deep learning applied to medical imaging offer the potential to enhance early detection accuracy, reduce interobserver variability, and improve diagnostic efficiency in lung cancer. Methods: In this retrospective study, we evaluated DAVINCI using a dataset of 8,962 patients with confirmed lung malignancies. The model utilizes a specialized architecture combining convolutional neural networks (CNNs) and residual blocks to optimize feature extraction from high-resolution pathological slides. Performance was measured via detection accuracy, recall, specificity, and Area Under the Curve (AUC). Results: A total of 8,962 patients were included in the analysis. The DAVINCI model correctly identified lung cancer in 93% of cases, corresponding to 8,334 of 8,962 patients, with a 95% confidence interval (CI) of 86%–100% (7,707–8,962 patients). Model specificity was also 93% (95% CI, 86%–100%), indicating a high true-negative rate. Sensitivity (recall) was 87%, with correct detection in 7,797 patients and a 95% CI of 80%–94% (7,170–8,425 patients). The model demonstrated strong discriminatory performance, achieving an area under the curve (AUC) of 0.91 (95% CI, 0.84–0.98). In comparison, active pathologists achieved a mean diagnostic accuracy of 83%, corresponding to 7,438 of 8,962 cases, with a 95% CI of 76%–90% (6,811–8,066 cases). In terms of efficiency, DAVINCI processed whole-slide images in 16–19 seconds, substantially faster than conventional manual review, which typically requires several minutes per slide. Conclusions: DAVINCI demonstrated superior accuracy, robust discriminatory performance, and markedly faster processing compared with human review, supporting its potential role in early lung cancer detection at scale.
P12.53.B DEVELOPMENT AND VALIDATION OF A PRACTICAL PROGNOSTIC MODEL FOR GLIOBLASTOMA INTEGRATING ICAM1 EXPRESSION, RADIOLOGIC FEATURES, AND CLINICAL DATA
Abstract BACKGROUND Glioblastoma (GBM) is a highly aggressive brain tumour with limited prognostic tools that are broadly implementable in routine clinical settings. Current models often depend on molecular platforms not universally accessible. We aimed to develop and validate a clinically practical prognostic model for GBM that integrates ICAM1 protein expression, imaging-derived tumor morphometrics, and clinical features. MATERIAL AND METHODS We analyzed ICAM1 expression in GBM at the DNA methylation, RNA, and protein levels using public datasets and institutional cohorts, confirming its association with tumor grade and poor survival. ICAM1 protein levels were then quantified via digital pathology in a multi-institutional cohort of 197 newly diagnosed, treatment-naïve GBM patients. Tumor surface irregularity (SIR) was calculated from pre-operative contrast-enhanced MRI using open-source imaging tools. Age at diagnosis was also recorded. These three variables—ICAM1 expression, SIR, and age—were integrated into a Clinical-Imaging-Molecular (CIM) model using multivariable Cox regression. The model was validated in an independent external GBM cohort (n = 20). Survival prediction was assessed using Kaplan-Meier curves, ROC analysis, and concordance index (c-index). RESULTS ICAM1 expression was associated with DNA hypomethylation and significantly correlated with reduced survival at transcriptomic and proteomic levels. Pathway analysis identified associations with immune activation and angiogenesis. In the clinical cohort, high ICAM1 expression, elevated tumor SIR, and older age independently predicted worse survival. The CIM model combining these factors stratified patients into distinct prognostic groups, achieving strong performance (c-index = 0.779, AUC = 0.778). External validation confirmed the model’s predictive utility (median survival difference: 9.1 months, P = 0.009). CONCLUSION We present a validated and clinically applicable prognostic model for GBM that integrates ICAM1 expression, imaging features, and age. The CIM model is scalable, interpretable, and feasible for implementation across academic and community settings, providing a robust tool for patient stratification, treatment planning, and trial design.
Hypomagnesemia in Large B cell Lymphoma patients receiving CAR T cell therapy correlates with immune dysregulation and decreased PFS: results from the ZUMA-1 trial and Mayo Clinic cohort
Abstract Background Hypomagnesemia has been correlated with inferior outcomes in patients with large B cell lymphoma (LBCL) undergoing stem cell transplants. As T-cell and myeloid cell dysfunction have been associated with low magnesium conditions, we investigated whether serum magnesium (Mg) levels could predict clinical outcomes in LBCL patients who received chimeric antigen receptor T-cell therapy. Methods Patients with LBCL who received axi-cel under the ZUMA-1 trial or as FDA approved therapy at Mayo Clinic were examined. Serum samples were obtained at specified time points and cytokine analysis was performed. Single cell RNA sequencing was performed on peripheral blood mononuclear cells. The Student T-test, Kruskal Wallis, or Fisher's Exact Tests were used to compare differences in demographics across Mg levels. Survival curves were plotted using the Kaplan-Meier methodology and compared using the Wilcoxon test. Results We found that hypomagnesemia before lymphodepletion chemotherapy predicted for inferior progression-free and overall survival in the pivotal study ZUMA-1 (NCT02348216). These results were validated in an independent cohort of LBCL patients receiving axicabtagene ciloleucel (axi-cel) at Mayo Clinic. Hypomagnesemia correlated with increased inflammatory serum markers and cytokine levels including ferritin, IL-6, IL1Ra, IL-8, and MIP1a. scRNAseq analysis unveiled altered immune interactions between monocytes and T cells with a concordant immune suppressive transcriptome. Conclusions Hypomagnesemia at the time of CAR-T infusion associates with an unfavorable inflammatory profile and decreased response and survival in LBCL patients receiving axi-cel. These findings suggest a potentially actionable prognostic factor for patients with large cell lymphoma undergoing CAR-T.
Incidence of thrombosis in relapsed/refractory B-cell lymphoma treated with axicabtagene ciloleucel: Mayo Clinic experience
Abstract Aims Conotruncal anomalies share common embryogenic defects of the outflow tracts and great arteries, which result in a predisposition to aortic aneurysms. The purpose of this study was to describe the prevalence and risk of progressive aortic aneurysms in adults with conotruncal anomalies. Methods and results Retrospective study of adults with conotruncal anomalies that underwent cross-sectional imaging 2003–20. Aneurysm was defined as aortic root/mid-ascending aorta >2.1 mm/m2/>1.9 mm/m2, progressive aneurysm as increase by >2 mm, and severe aneurysm as dimension >50 mm. Of 2261 patients (38 ± 12 years; male 58%), 1167 (52%) had an aortic aneurysm, and 205 (14%) had a severe aortic aneurysm. Mean annual increase in aortic root/mid-ascending aorta was 0.3 ± 0.1 mm/0.2 ± 0.1 mm. The 3-, 5-, and 7-year cumulative incidence of the progressive aortic aneurysm was 4%, 7%, and 9%, respectively. The rate of aneurysm growth decreased with age, with no significant growth after age 40 years. There was an excellent correlation between aortic indices from cross-sectional imaging and echocardiography. Of 950 females, 184 had ≥1 pregnancy, and 81 (44%) of the 184 patients had aortic aneurysm prior to pregnancy. There was no aortic dissection or progression of the aortic aneurysm during pregnancy. Overall, there was no aortic dissection during 7984 patient-years of follow-up. Conclusions Aortic aneurysm was common in patients with conotruncal anomalies. However, the risk of progressive aneurysm or dissection was low. Collectively, these data suggest a benign natural history and perhaps a less frequent need for cross-sectional imaging. Further studies are required to determine the optimal timing for surgical intervention in this population.
Lines of therapy before autologous stem cell transplant and CAR‐T affect outcomes in aggressive Non‐Hodgkin's lymphoma
AbstractIntroductionHypoalbuminemia is a known adverse prognostic factor in lymphomas. Yet, it is unknown if axicabtagene ciloleucel (axi‐cel) overcomes the adverse prognostic impact of hypoalbuminemia in relapsed/refractory large B‐cell lymphoma.MethodsWe conducted a retrospective analysis across three Mayo Clinic centers to assess the relationship of hypoalbuminemia (defined as a serum albumin (SA) levels ≤ 3.5 g/dL) on outcomes of patients treated with axi‐cel.ResultsThis analysis included 81 patients. Two patients had no available SA levels preceding axi‐cel infusion. Eighteen patients (22.8%) had hypoalbuminemia with a median SA of 3.3 g/dL. Patients with normal SA had a statistically higher ORR than those without hypoalbuminemia (P = .018). There was no difference in 1‐year PFS and OS between the group with hypoalbuminemia and the group with normal SA levels (48% vs 49%, P = .81) and (74% vs 73%, P = .97), respectively. There was no difference in the severity or median duration of cytokine release syndrome or neurotoxicity between the two groups.ConclusionNotwithstanding the limitations related to the relatively small sample size, axi‐cel therapy appears to overcome the adverse effect of hypoalbuminemia on OS and PFS. Large multicenter clinical studies are certainly needed to validate these findings.
Lines of Therapy before Autologous Stem Cell Transplant (ASCT) and CAR-T Infusion Affect Outcomes in Aggressive Non-Hodgkin's Lymphoma (NHL)
Background: Anti CD-19 chimeric antigen receptor T-cell therapy (CAR-T) is approved to treat relapsed/refractory (R/R) aggressive NHL after 2 or more lines of therapy. Randomized clinical trials are ongoing comparing CAR-T and autologous stem cell transplant (ASCT) in second line. In standard of care practice, patients refractory to second line chemotherapy are sometimes treated with third line chemotherapy and taken to ASCT if disease is chemo-sensitive. Current study aims to evaluate the impact of prior lines of therapy on the efficacy of CAR-T and ASCT. Methods: A retrospective review of patients who received ASCT and/or axicabtagene ciloleucel (axi-cel) for R/R aggressive NHL from June 2016 - January 2020 at Mayo Clinic, Rochester was performed. The lymphoma types included in the study were DLBCL, transformed lymphoma (TFL), high grade B-cell lymphoma (HGBL), and primary mediastinal large B-cell lymphoma (PMBCL). Response to all lymphoma-directed therapy was evaluated using 2014 Lugano criteria. Overall survival (OS) was defined as time from CAR-T or ASCT infusion to death, and progression free survival (PFS) was defined as time from CAR-T or ASCT infusion to disease progression, or next treatment. Categorical data was analyzed as Chi-square or fishers exact test as appropriate. Continuous variables were analyzed using Wilcoxon Rank Sum test. Analysis was performed in R3.6.3. Results: A total of 105 patients underwent ASCT and 53 patients underwent CAR-T therapy in the study period with at least 6 months follow-up. Of the 105 ASCT patients, 87 received ASCT after 2 lines of chemotherapy, ASCT(2), and 18 received ASCT after 3 lines of chemotherapy, ASCT(3). Twenty six of the ASCT [n=19, ASCT(2) and n=7, ASCT(3)] patients received CART in subsequent therapy. Baseline characteristics were comparable between the two groups except ASCT(3) had higher percent of refractory disease after first line (table 1). With a median follow up of 17.4 months, the PFS was significantly longer for the ASCT(2) group with a trend toward longer OS (Figure 1; PFS @ 1 year: ASCT(2) 67%, 95%CI 58-79%; ASCT(3) 27%, 95%CI 27-74%; p = 0.036). Among the CAR-T recipients, only 18 (33%) patients received CAR-T in the earliest possible indication, CAR-T(2): after 2 lines of chemotherapy (n=12) and/or after ASCT(2) (n=6), table 1. Compared to patients who received CAR-T in later lines (CAR-T 3+), OS was significantly longer for patients who received CAR-T(2), with a trend toward longer PFS (Figure 1; OS @ 1 year: CAR-T (2) 82%, 95%CI 65-100%; CAR-T later lines 62%, 95%CI 47-82%; p = 0.05). Additionally, 12 (23%) of patients received CAR-T immediately after ASCT (9 after ASCT(2), 3 after ASCT(3)). Baseline demographics in these 12 patients, CAR-T(ASCT), were comparable to the others who had chemoimmunotherapy as the last salvage therapy prior to CAR-T [CAR-T(chemo)], except a smaller proportion received bridging therapy (33% vs. 73%, p = 0.01). The CAR-T (ASCT) group had significantly prolonged PFS (median PFS - not reached [95%CI 3-not reached (NR)] vs. 3 months [95% CI 3-4 months]), and OS (median OS - NR, [95%CI 10.34-NR] vs. 15.1 months, [95%CI 11.9 - NR], p = 0.03). Updated analysis will be presented at the meeting with longer follow up (Figure 1). Conclusion: CAR-T use at the earliest current approved indication may confer survival advantage. Referral for earlier use of CAR-T remains low at only one third of our CAR-T practice volume. CAR-T use for relapse immediately after ASCT appear to have longer PFS and OS than after other systemic salvage therapy, although contributing parameters such as the need for bridging therapy requires further study. While patients who are chemo-refractory to second line chemotherapy may demonstrate chemo sensitivity with third line chemotherapy, PFS is shorter for ASCT(3). Comparison between ASCT(3) and CAR-T (2, chemorefractory) require larger cohorts with longer follow-up. Disclosures Bennani: Affimed: Research Funding; Purdue Pharma: Other: Advisory Board; Kite/Gilead: Research Funding; Verastem: Other: Advisory Board. Ansell:Takeda: Research Funding; ADC Therapeutics: Research Funding; Trillium: Research Funding; Bristol Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; AI Therapeutics: Research Funding. Lin:Juno: Consultancy; Legend BioTech: Consultancy; Merck: Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding.
Response to Bridging Therapy (BT) before CAR-T Cell Infusion Predicts Outcomes for Relapsed/Refractory (R/R) Aggressive B-Cell Non-Hodgkin Lymphoma (NHL)
Background: Real world multi-institutional data of anti-CD19 CAR-T therapy from across the US shows similar response rates and toxicities as that of the registration trials. For axicabtagene ciloleucel (axi-cel), bridging therapy (BT) during CAR-T manufacturing was not allowed. Real world data shows that patients who received BT had lower complete remission (CR) rates, duraiton of response (DOR) and overall survival (OS). Whether the poorer outcome is due to the effect of the BT or the aggressive biology of the disease is unknown. Patients with lower disease burden had higher response rate in the registration study ZUMA-1 for axi-cel. We examined the impact of response to BT on CAR-T outcome. Specifically, we also describe our experience using polatuzumab vedotin, bendamustine and rituximab (Pola-BR), also a recently approved therapy for relapsed/refractory diffuse large B-cell lymphoma (DLBCL), prior to CAR-T as salvage (ST) and BT. Methods: A retrospective review of 63 patients who received axi-cel for NHL from June 2016 - March 2020 at Mayo Clinic, Rochester was performed. ST was defined as the last therapy prior to leukapheresis and grouped into categories - autologous stem cell transplant (ASCT), and non-ASCT (chemotherapy and immunotherapy) . BT was defined as lymphoma-directed therapy given between leukapheresis and CAR-T infusion. Response to all lymphoma-directed therapy was evaluated using 2014 Lugano criteria. Event free survival (EFS) was defined as time from axi-cel infusion to progression, next treatment, or death. Overall survival (OS) was defined as time from axi-cel infusion to death. Results: Patients received BT if there were concerns for symptomatic progression of disease during CAR-T manufacturing that would reduce the likelihood of eligibility to receive CAR-T. The decision and choice of BT was at the discretion of the treating physician. Sixty-eight percent (n=43) of the patients received BT (19 chemo, 24 immunotherapy). Demographics of the patients based on their response to BT are shown in table 1. More patients in the BT responder group had received chemotherapy as type of bridge (58% vs. 33%). With a median follow up of 12-months for those still alive, significant improvement in EFS was seen in patients who had partial response (PR) or stable disease (SD) to BT than patients who continued to progress (median 12 months vs. 3 months, p = 0.01) [Figure 1A]. OS however, was not significant between the two groups (median OS 18 months - responders vs. 12 months non-responders, p = 0.19) [Figure 1B]. We also describe in the case series below 11 patients who received Pola-BR in salvage setting (ST) and/or BT (Table 2). Due to the lymphopenic effects of bendamustine, it was avoided before T-cell collection if possible. Two patients, however, received bendamustine as part of Pola-BR for salvage therapy as its need was determined per the managing physician. Axi-cel was successfully manufactured for all 10 patients. One patient did not have measurable disease after Pola-BR BT and remains on observation. A second patient died before CAR-T infusion from progressive disease. Four of the nine patients treated with CAR-T remained in response. Updated outcome will be presented. Conclusion: While patients who received BT have worse EFS than those who didn't, having some control of lymphoma after BT was associated with better EFS compared to patients who continued to have progressive disease after BT. Preliminary data from Pola-BR case series shows 60% (6/10) patients achieved PR/SD before CAR-T infusion, but requires longer follow up for its impact on survival. Disclosures Bennani: Purdue Pharma: Other: Advisory Board; Kite/Gilead: Research Funding; Affimed: Research Funding; Verastem: Other: Advisory Board. Ansell:AI Therapeutics: Research Funding; Takeda: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Bristol Myers Squibb: Research Funding; ADC Therapeutics: Research Funding; Trillium: Research Funding. Lin:Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Novartis: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Juno: Consultancy; Legend BioTech: Consultancy; Merck: Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy.
Impact of type of salvage therapy (ST) and response to bridging therapy (BT) on CAR-T therapy outcomes for relapsed/refractory aggressive B-cell non-Hodgkin lymphoma (NHL).
e15020 Background: Durable responses were seen in registration trials for CAR-T in NHL across poor prognostic groups including early relapse post stem cell transplant (ASCT). Multi-center reports of real-world practice noted patients who received BT prior to CAR-T had decreased survival. The impact of last ST and response to BT on clinical outcome are examined here. Methods: Retrospective chart review was performed on 47 patients who received axicabtagene ciloleucel from June 2016 – September 2019 at Mayo Clinic, Rochester. ST was defined as last therapy prior to leukapheresis and grouped into categories – non-ASCT (chemotherapy, and immunotherapy), and ASCT. BT was defined as therapy given between leukapheresis and CAR-T. Response to therapy was evaluated using 2014 Lugano criteria. Event free survival (EFS) was defined as time from CAR-T infusion to progression, next treatment, or death. Results: The ST distribution was 77% non-ASCT [chemo 66% (31), and immunotherapy 11% (5)], and 23% (11) ASCT. EFS was significantly prolonged for the ASCT (median not reached) vs non-ASCT (median 3.8 months, p = 0.03) despite no difference in median prior lines of therapy. This may reflect more aggressive disease in the non-ASCT arm, as time from start of ST to leukapheresis was shorter (median non-ASCT 2.2 months vs. ASCT 4.4 months, p = 0.0008). Patients received BT if there were concerns for symptomatic progression during CAR-T manufacturing that would reduce the likelihood to receive CAR-T. Sixty-two percent (29) patients received BT (11 chemo, and 18 immunotherapy). The EFS did not differ between the type of BT. However, patients who progressed after BT had worse EFS than those who achieved stable disease or partial response (median 2.8 vs 8.7 months, p = 0.03). Conclusions: Patients who received CAR-T as the next treatment after ASCT had better EFS than those after other types of ST. While patients who received BT have worse survival than those who didn’t, having some control of lymphoma progression with BT was associated with better EFS than those who continued to have progressive disease.