Citations

Background: Human chorionic gonadotropin (hCG) is a marker of placental function, which also stimulates the maternal thyroid gland. Maternal thyroid function can be associated with the pathophysiology of gestational diabetes mellitus (GDM). We aimed to study whether there is an association of hCG concentrations in early pregnancy with GDM and whether it is mediated through maternal thyroid hormones. Methods: This study included 18,683 pregnant women presenting at a tertiary hospital in Shanghai, China, between January 2015 and December 2016. GDM was diagnosed using a 2-hour, 75-g, oral glucose tolerance test (OGTT) according to the American Diabetes Association guidelines. Multivariable logistic or linear regression models were used to identify associations, adjusting for maternal age, education level, family history of diabetes, parity, fetal sex, thyroperoxidase antibody (TPOAb) status, and prepregnancy body–mass index. Results: Higher hCG concentrations were associated with a lower plasma glucose level during the OGTT, but not with fasting plasma glucose or hemoglobin A1c concentrations tested during early pregnancy. hCG in early pregnancy was negatively associated with GDM risk ( p = 0.027). Mediation analysis identified that an estimated 21.4% of the association of hCG-associated GDM risk was mediated through changes in free thyroxine (fT4) concentrations ( p < 0.05). In the sensitivity analysis restricted to TPOAb-positive women, hCG was not associated with GDM ( p = 0.452). Conclusions: Higher hCG levels in early pregnancy are associated with a lower risk of GDM. Maternal fT4 may act as an important mediator in this association.

Abstract Background: Achieving a pathologic complete response (pCR) has been shown on the patient level to predict excellent long-term event-free survival outcomes. Residual cancer burden (RCB) quantifies the extent of residual disease for patients who did not achieve pCR. We have previously observed in the I-SPY 2 TRIAL that while metastatic events outside the central nervous system (CNS) were dramatically reduced in the setting of pCR, the incidence of CNS metastasis remained similar across RCB classes, raising the possibility that these CNS events may be independent of response in the breast. In this study, we evaluate the type and sites of recurrences by RCB in a large pooled dataset, which allows for analysis within subtype, to validate these findings. Methods: 5161 patients pooled across 12 institutions/trials with available RCB and event-free survival (EFS) data were included in this analysis. EFS was calculated as the interval between treatment initiation, and locoregional recurrence, distant recurrence or death from any cause; patients without event are censored at time of last follow-up. The median follow-up is 4.6 years. We summarized the EFS event type, further sub-dividing the distant recurrence events (DR) by their site of relapse (CNS-only, CNS and other sites, Non-CNS). We used a competing risk (Fine-Gray) model to assess which of these site-specific relapses differ between RCB classes and estimated the cumulative incidence of CNS-only and non-CNS events at 5 years. Analyses were performed across the entire study population and within HR/HER2 defined subtypes. Results: Among the 5161 subjects, there were 1164 EFS events, including 92 (7.9%) local recurrences (without distant recurrence and/or death) and 1072 distant recurrence-free survival (DRFS) events. Among the DRFS events, 158 patients died without a distant recurrence. 914 experienced distant recurrences, including 90 (9.8%) with CNS-only, 145 (15.9%) with CNS and other sites, 664 (72.6%) with non-CNS distant recurrence; 15 (1.6%) patients had missing recurrence site information. Table 1 summarizes the cumulative incidence of CNS-only and non-CNS recurrence at 5 years and the proportion of CNS-only recurrences among DR events by RCB class overall and within each HR/HER2 subtypes. The incidence of CNS-only recurrences was low and similar across RCB classes. In contrast, the incidence of non-CNS recurrences increases with increasing RCB. As a result, CNS-only recurrences are proportionally higher within the RCB-0 and RCB-I than in the RCB-II and RCB-III groups, largely because of the low DR event rate and relative low frequency of non-CNS recurrence events within the RCB-0 and RCB-I classes. Overall, 27% of the recurrences in the setting of pCR (RCB-0) are due to CNS-only recurrences.Conclusions: Consistent with previous studies, our large pooled analysis confirmed that CNS-only recurrences are uncommon but appear similar across RCB groups, independent of response, suggesting that the CNS is a treatment sanctuary site. In contrast, non-CNS recurrence rates increase as RCB increases. These findings suggest that inclusion of CNS-only recurrences as an outcome event may impact the association between neoadjuvant therapy response and long-term outcomes in the context of current therapies. Novel therapies that cross the blood brain barrier will be needed to impact CNS recurrence rates. Table 1: Cumulative Incidence of CNS Only and non-CNS Distant Recurrences at 5 years and proportion of CNS-only events among DR eventsRCB Class0IIIIIIpOverall (5161)N16766622017806Cum. Inc. CNS Only2%2%2%1%0.627Cum. Inc. Non-CNS3%6%16%27%&lt;0.001# CNS-Only / # DR events (%)26/96 (27%)14/74 (19%)39/443 (9%)11/301 (4%)HR-HER2- (1774)N770212590202Cum. Inc. CNS Only2%3%2%4%0.298Cum. Inc. Non-CNS4%11%19%42%&lt;0.001# CNS-Only / # DR events (%)13/50 (26%)6/32 (19%)13/148 (9%)8/111 (7%)HR-HER2+ (572)N3766710029Cum. Inc. CNS Only1%5%5%0%0.022Cum. Inc. Non-CNS2%5%18%38%&lt;0.001# CNS-Only / # DR events (%)4/17 (24%)3/10 (30%)6/31 (19%)0/13 (0%)HR+HER2+ (858)N31317229182Cum. Inc. CNS Only1%1%2%0%0.37Cum. Inc. Non-CNS2%3%15%26%&lt;0.001# CNS-Only / # DR events (%)3/10 (30%)2/16 (12%)7/68 (10%)0/29 (0%)HR+HER2- (1957)N2172111036493Cum. Inc. CNS Only3%2%1%0.2%0.087Cum. Inc. Non-CNS5%4%13%20%&lt;0.001# CNS-Only / # DR events (%)6/19 (32%)3/16 (19%)13/196 (7%)3/148 (2%) Citation Format: Sonal Shad, Marieke van der Noordaa, Marie Osdoit, Diane de Croze, Anne-Sophie Hamy, Marick Lae, Fabien Reyal, Miguel Martin, María Del Monte-Millán, Sara López-Tarruella, I-SPY 2 TRIAL Consortium, Judy C Boughey, Matthew P Goetz, Tanya Hoskin, Rebekah Gould, Vicente Valero, Gabe Sonke, Tessa G Steenbruggen, Maartje van Seijen, Jelle Wesseling, John Bartlett, Stephen Edge, Mi-Ok Kim, Jean Abraham, Carlos Caldas, Helena Earl, Elena Provenzano, Stephen-John Sammut, David Cameron, Ashley Graham, Peter Hall, Lorna Mackintosh, Fan Fang, Andrew K Godwin, Kelsey Schwensen, Priyanka Sharma, Angela DeMichele, Janet Dunn, Louise Hiller, Larry Hayward, Jeremy Thomas, Kimberly Cole, Lajos Pusztai, Laura Van't Veer, Fraser Symmans, Laura Esserman, Christina Yau. Site of recurrence after neoadjuvant therapy: A multi-center pooled analysis [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD13-02.

Abstract Background: Pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in patients with breast cancer is associated with improved survival. Further assessment of the extent of residual disease, using the pathological anatomic American Joint Committee on Cancer staging method (ypStage) or the Residual Cancer Burden (RCB) method, have been shown to add prognostic information for patients with residual disease. Neo-Bioscore, an alternate system to classify response to NAC, includes clinical stage at diagnosis and biology and defines eight prognostic groups. The goal of this study was to compared three scoring systems (anatomic ypStage (7th ed), RCB Class and Neo-Bioscore) and assess whether RCB Class and Neo-Bioscore provide additional prognostic value in the context above anatomic ypStage, the most commonly used method for post-neoadjuvant residual disease assessment. Methods: Data from 5161 patients treated with NAC was pooled from 12 sites. Patients without clinical and pathological staging were excluded, as were patients with HER2+ breast cancer who did not receive neoadjuvant HER2-targeted therapy, leaving 3730 for analysis. PCR was defined as no residual invasive tumor in breast and nodes, i.e. RCB-0 or ypT0/Tis and ypN0. Patients with discordant pCR status by RCB Class vs ypStage (n=9) were excluded. Associations between each scoring system and event-free survival (EFS) were evaluated using the log rank test. EFS at 5 years was estimated using the Kaplan Meier method. Associations between Neo-Bioscore and EFS were assessed in the pCR group. For patients with residual disease, we assessed RCB and Neo-Bioscore within each ypStage. Analysis was performed overall and within subtype. Subgroups with &lt;5 patients were excluded from the survival analyses. Results: ypAJCC staging, RCB class and Neo-Bioscore were all associated with EFS in the overall population and within each subtype (log rank p&lt;0.0001). Of note, 13 patients with a Neo-Bioscore of 7 all recurred or died within 19 months of follow-up. Overall, 34% (1264/3721) of patients achieved a pCR. Their Neo-Bioscore ranges from 0-5, where 3% (37/1264) has a Neo-Bioscore of 5 despite achieving pCR. The Neo-Bioscore was not associated with EFS in case of a pCR, with EFS estimates at 5 years of 95%, 94%, 92%, 93%, 90% and 92% for Neo-Bioscores 0-5 respectively. As HR and HER2 status are components of the score, the range of Neo-Bioscore in the pCR group differs by subtype. However, similar to the overall analysis, the Neo-Bioscore was not prognostic within subtypes in case of pCR. Overall, among the patients who did not achieve pCR, both RCB class and Neo-Bioscore were associated with EFS within ypStages I, II and III. However, the ypStage within which RCB and Neo-Bioscore are prognostic is different for each subtype. RCB class was prognostic in ypStage I in both HR+ subtypes: patients with ypStage-I/RCB-I had significantly improved survival compared to patients with ypStage-I/RCB-II (5-year EFS: 100% vs 83% in HR+HER2- and 95% vs 77% in HR+HER2+). In contrast, for patients with triple negative breast cancer, RCB class was prognostic within ypStage II and III. Analysis by clinical stage and the components of the three systems that contribute most to prognosis will be presented. Conclusions: The degree of response to NAC adds important information to pCR versus residual disease. The Neo-Bioscore was not prognostic among patients with pCR, suggesting that clinical stage (including subtype and grade) adds little information in the setting of a pCR. In contrast, both RCB and Neo-Bioscore provide additional prognostic information to the conventional ypAJCC staging among non-pCR patients, suggesting that clinical stage, tumor biology as well as extent of residual disease all contribute to prognosis in the setting of residual disease after NAC. Citation Format: Marieke EM van der Noordaa, Christina Yau, Sonal Shad, Marie Osdoit, Tessa G Steenbruggen, Diane de Croze, Anne-Sophie Hamy, Marick Lae, Fabien Reyal, Maria Del Monte-Millán, Miguel Martin, Sara Lopez Tarruella, I-SPY 2 TRIAL Consortium, Judy C Boughey, Matthew Goetz, Tanya Hoskin, Rebecca Gould, Vincent Valero, Gabe Sonke, Maartje van Seijen, Jelle Wesseling, John Bartlett, Stephan Edge, Mi-Ok Kim, Jean Abraham, Carlos Caldas, Helena Earl, Elena Provenzano, Stephen-John Sammut, David Cameron, Ashley Graham, Peter Hall, Lorna MacKintosh, Fang Fan, Andrew K Godwin, Kelsey Schwensen, Priyanka Sharma, Angela DeMichele, Janet Dunn, Louise Hiller, Larry Hayward, Jeremy Thomas, Kimberley Cole, Lajos Pusztai, Laura van 't Veer, Fraser Symmans, Laura Esserman. Assessing prognosis after neoadjuvant therapy: A comparison between anatomic ypAJCC staging, residual cancer burden class and neo-bioscore [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr GS4-07.

Introduction: Elevated pro-inflammatory cytokines are a hallmark feature of myeloproliferative neoplasms (MPNs). The pro-inflammatory cytokine interleukin-8 (IL8) is increased in patients with myelofibrosis (MF) and correlates with adverse outcome, including overall survival. Previously, the Levine/Fang labs identified increased IL8 secretion from individual CD34+ stem cells in a subset of MF patients. The role of IL8 and its cognate receptors CXCR1/2 in MF pathogenesis has not been delineated. Methods: Single-cell cytokine assays were performed on isolated CD34+ cells from 60 clinically annotated MPN patients (20 MF, 20 PV, 20 ET) using a previously described micro-chip platform (Kleppe et al, Can Disc 2013). 10 healthy donors (CD34+ cells from hip replacements) were used as controls. Integrated RNA-Seq and Assay for Transposase-Accessible Chromatin followed by next-generation sequencing (ATAC-Seq) was performed on CD34+ cells from MPN patients with and without expanded IL8 secreting clones for gene expression/chromatin accessibility analysis. To model the role of IL8-CXCR2 on fibrosis in vivo, the human MPLW515L transplant model (hMPLW515L) of MF was used. Specifically, wild-type (WT) murine bone marrow (Creneg-Cxcr2f/f; Cxcr2WT) or marrow lacking the CXCR2 receptor (VavCre-Cxcr2f/f; Cxcr2KO)were retrovirally infected with MSCV-hMPLW515L-IRES-GFP and transplanted into lethally irradiated WT recipient mice and monitored for disease. Blood counts, chimerism, and flow cytometry were assayed. Moribund mice were sacrificed and assayed for grade reticulin fibrosis and overall survival. Results: Single-cell cytokine assays confirmed an increased proportion of IL8-secreting CD34+ cells in MF patients (40%) in comparison to other MPN sub-types (10% PV/0% ET) (Figure 1A). MF patients with expanded IL8 secreting clones (defined as &gt;50% of total CD34+ cells) had increased leukocytosis (p&lt;0.0001), larger spleen sizes (p=0.0004), greater prevalence of constitutional symptoms (p=0.0084), and higher-grade reticulin fibrosis in marrow (Figure 1B) in comparison to MF patients without prevalent IL8 clones. IHC confirmed increased IL8 expression in marrow biopsies from 8/15 MF patients in comparison to 0/4 normal controls (Figure 1C), and high IL8 expression was also observed in MF splenic megakaryocytes (MKs) as well as in splenic stromal/endothelial cells not seen in normal spleen (Figure 1D). Integrated RNA-Seq/ATAC-Seq analysis of IL8-high MF patients confirmed up-regulation of IL8-CXCR2 signaling and enrichment in pro-inflammatory pathways (i.e TNFa, NFkB, etc) by GSEA, as well as increased expression/accessibility of pro-inflammatory genes S100A8 and S100A9-previously implicated in fibrosis development. Flow analysis of IL8-high MF CD34+ cells revealed enhanced surface expression of CXCR2 and its analog CXCR1, such that MF was characterized by increased IL8 ligand and receptor expression (Figure 1E) and coincided with enhanced NFkB pathway activity (Figure 1F). Consistent with this, colony forming assays of cultured MF CD34+ cells revealed enhanced colony output when cultured with IL8 compared to WT CD34+ cells-an effect ameliorated by co-treatment with the CXCR1/2 antagonist Reparixin (Figure 1G). In vivo, hMPLW515L adoptive transplant with Cxcr2KO hematopoietic donor cells demonstrated improved leukocytosis, thrombocytosis (Figure 2A) and splenomegaly in comparison to Cxcr2WT hMPLW515L recipient mice. Pathologic analysis revealed a reduction in reticulin fibrosis in bone marrow (Figure 2B) and spleen, translating into an improvement in overall survival (Figure 2C). Notably, a significant reduction in dysplastic MKs-a hallmark feature of MF-was also observed in Cxcr2KO hMPLW515L mice (Figure 2D) supporting a role for CXCR2 signaling in MK proliferation. Conclusion: IL8 secreting clones are associated with increased symptom severity and fibrosis grade in MF. Gene expression of MF CD34+ IL8 secreting clones shows up-regulation of inflammatory genes S100A8/A9, implicated in myofibroblast proliferation. Cxcr2 KO abrogates fibrosis formation and prolongs survival in the hMPLW515L model, and CXCR1/2 inhibition impairs colony forming capacity of MF CD34+ cells. These data suggest pharmacologic inhibition of this pathway should be investigated as potential therapy in MF and in PV/ET patients at high risk of fibrotic transformation. Disclosures Fan: IsoPlexis: Current Employment, Current equity holder in private company; Singleron Biotechnologies: Current Employment, Current equity holder in private company. Levine:Morphosys: Consultancy; Prelude Therapeutics: Research Funding; Qiagen: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Gilead: Honoraria; Loxo: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy; Amgen: Honoraria; Astellas: Consultancy; Imago: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; C4 Therapeutics: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Isoplexis: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; Lilly: Consultancy, Honoraria; Janssen: Consultancy. Hoffman:Protagonist: Consultancy; Abbvie: Membership on an entity's Board of Directors or advisory committees; Dompe: Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees; Forbius: Consultancy.

Background: To evaluate differences in the proportion of uterine fibroid (UF) treatments that are uterine-sparing between Black women and White women and identify factors that could explain disparities. Methods: Women at age 18–54 years who were enrolled from 10 clinical sites in the United States into the Comparing Options for Management: Patient-Centered Results for UFs (COMPARE-UF) treatment registry completed questionnaires before their UF procedure. UF symptoms and quality of life were assessed by questionnaires. Details on UF imaging and treatment (hysterectomy, myomectomy, or uterine artery embolization [UAE]) were collected from each patient's medical record. Random-effects logistic regression was used to assess the association between race and the odds of having a uterine-sparing procedure versus hysterectomy. Subgroup analyses compared each uterine-sparing procedure with hysterectomy. Results: In this cohort of 1141 White women and 1196 Black women, Black women tended to be younger (median 41.0 vs. 42.0 years) and report worse symptoms, pain, and function on every scale compared with White women. Black women were more likely to have had a prior UF treatment compared with White women (22.8% vs. 14.6%). White women had more hysterectomies (43.6% vs. 32.2%) and myomectomies (50.9% vs. 50.2%) versus Black women. Black women had more UAEs (15.1% vs. 4.7%) than White women. After adjusting for clinical site and other variables, Black women had greater odds than White women of having a myomectomy (odds ratio [OR] = 2.41, 95% confidence interval [CI] = 1.63–3.56) or a UAE versus hysterectomy (OR = 4.24, 95% CI = 2.41–7.46). Conclusion: In these participants, Black women were more likely to schedule a uterine-sparing UF treatment and a nonsurgical UF treatment than their White counterparts; this may not be true for all women. Longer comparative effectiveness studies are needed to inform women about the durability of UF treatments. Greater understanding of factors influencing treatment selection is needed as are studies that include women without access to tertiary care centers. Clinical Trial Registration: Clinicaltrials.gov, NCT02260752 (enrollment start: November 2015).

Abstract Pancreatic neuroendocrine tumors (PNETs) are the second most common neoplasm of the pancreas after ductal adenocarcinoma. The clinical behavior of PNETs is very difficult to predict, especially for well-differentiated PNETs. Several classification systems have been developed to differentiate benign from malignant PNETs. The current 5th edition WHO (2019) updated the grading system of PNETs which is now entirely based on proliferative rate (either mitotic count or Ki-67 index). In this article, we systemically reviewed the evolution of the histologic classification and grading systems for well-differentiated PNETs. Meanwhile, we also report a comprehensive summary of immunohistochemical and molecular prognostic factors for PNETs patients, including CK19, KIT, PD-L1/PD-L1, UCH-L1 and CNPY2. We believe that more reliable grading systems and prognostic markers are emerging and will change the landscape of treatment for well-differentiated PNETs.

AbstractClinical decision-making is based on knowledge, expertise, and authority, with clinicians approving almost every intervention—the starting point for delivery of “All the right care, but only the right care,” an unachieved healthcare quality improvement goal. Unaided clinicians suffer from human cognitive limitations and biases when decisions are based only on their training, expertise, and experience. Electronic health records (EHRs) could improve healthcare with robust decision-support tools that reduce unwarranted variation of clinician decisions and actions. Current EHRs, focused on results review, documentation, and accounting, are awkward, time-consuming, and contribute to clinician stress and burnout. Decision-support tools could reduce clinician burden and enable replicable clinician decisions and actions that personalize patient care. Most current clinical decision-support tools or aids lack detail and neither reduce burden nor enable replicable actions. Clinicians must provide subjective interpretation and missing logic, thus introducing personal biases and mindless, unwarranted, variation from evidence-based practice. Replicability occurs when different clinicians, with the same patient information and context, come to the same decision and action. We propose a feasible subset of therapeutic decision-support tools based on credible clinical outcome evidence: computer protocols leading to replicable clinician actions (eActions). eActions enable different clinicians to make consistent decisions and actions when faced with the same patient input data. eActions embrace good everyday decision-making informed by evidence, experience, EHR data, and individual patient status. eActions can reduce unwarranted variation, increase quality of clinical care and research, reduce EHR noise, and could enable a learning healthcare system.

Background: Ciltacabtagene autoleucel (cilta-cel; JNJ-68284528; LCAR-B38M CAR-T cells) is a chimeric antigen receptor T (CAR-T) cell therapy with 2 B-cell maturation antigen-targeting single-domain antibodies designed to confer avidity. In the phase 1 LEGEND-2 study in China, LCAR-B38M yielded deep, durable responses with a manageable safety profile in patients (pts) with relapsed/refractory multiple myeloma (R/R MM). The phase 1b/2 CARTITUDE-1 study (NCT03548207) is further evaluating cilta-cel in this pt population in the US. We present updated data from the phase 1b portion along with initial phase 2 data. Methods: Eligible pts (aged ≥18 y) were diagnosed with MM per International Myeloma Working Group (IMWG) criteria and had measurable disease, Eastern Cooperative Oncology Group performance status ≤1, received ≥3 prior regimens or were double-refractory to a proteasome inhibitor and immunomodulatory drug, and received an anti-CD38 antibody. After apheresis, bridging therapy was permitted. Cyclophosphamide 300 mg/m2 and fludarabine 30 mg/m2 daily for 3 d were used for lymphodepletion. A single infusion of cilta-cel at a target dose of 0.75×106 (range 0.5-1.0×106) CAR+ viable T cells/kg was administered 5-7 d after start of lymphodepletion. The primary objective of the phase 1b portion was to characterize cilta-cel safety and establish the recommended phase 2 dose; the primary objective of the phase 2 portion was to evaluate cilta-cel efficacy. Response was assessed per IMWG criteria and minimal residual disease (MRD) by next-generation sequencing. Adverse events (AEs) were graded using CTCAE v5.0. In the phase 1b portion, cytokine release syndrome (CRS) was graded by Lee et al (Blood 2014) and neurotoxicity by CTCAE v5.0; in the phase 2 portion, CRS and neurotoxicity were graded by American Society for Transplantation and Cellular Therapy (ASTCT) criteria. In this combined analysis, Lee et al and CTCAE v5.0 were mapped to ASTCT criteria for CRS and immune effector cell-associated neurotoxicity syndrome (ICANS), respectively. Results: As of the May 20, 2020 clinical cutoff, 97 pts (58.8% male; median age 61.0 y [range 43-78]) with R/R MM received cilta-cel (29 in phase 1b; 68 in phase 2). Median follow-up duration was 8.8 mo (range 1.5-20.4). Pts had received a median of 6 prior lines of therapy (range 3-18); 83.5% were penta-exposed, 87.6% were triple-refractory, 41.2% were penta-refractory, and 97.9% were refractory to last line of therapy. Overall response rate per independent review committee (primary endpoint) was 94.8% (95% CI 88.4-98.3), with a stringent complete response rate of 55.7% (95% CI 45.2-65.8), very good partial response rate of 32.0% (95% CI 22.9-42.2), and partial response rate of 7.2% (95% CI 3.0-14.3). All pts achieved a reduction in M-protein. Median time to first response was 1.0 mo (range 0.9-5.8; 80.4% ≤1.0 mo), and median time to complete response or better was 1.8 mo (range 0.9-12.5; 74.1% ≤3.0 mo); responses deepened over time (Figure). Median duration of response was not reached (NR). Of 52 MRD-evaluable pts, 94.2% were MRD-negative at 10-5. The 6-mo progression-free survival (PFS) and overall survival (OS) rates (95% CI) were 87.4% (78.9-92.7) and 93.8% (86.7-97.2), respectively; median PFS and OS were NR. Ten deaths occurred during the study; 8 were due to AEs (both related and unrelated; CRS/hemophagocytic lymphohistiocytosis, neurotoxicity, respiratory failure, sepsis, septic shock, pneumonia, lung abscess, and acute myelogenous leukemia [n=1 each]), and 2 due to progressive disease. AEs reported in &gt;70% of pts were CRS (94.8%; grade [gr] 3/4 4.1%), neutropenia (90.7%; gr 3/4 90.7%), anemia (81.4%; gr 3/4 68.0%), and thrombocytopenia (79.4%; gr 3/4 59.8%). Median time to CRS onset was 7.0 d (range 1-12) and median duration 4.0 d (range 1-27, excluding n=1 with 97 d). CAR-T cell-related neurotoxicity was reported in 20.6% of pts (gr 3/4 10.3%). Cilta-cel CAR+ T cells showed maximum peripheral expansion at 14 d (range 9-43). Among pts with 6 mo' individual follow-up, 67% had cilta-cel CAR+ T cells below the level of quantification (2 cells/µL) in peripheral blood. Conclusions: Preliminary phase 1b/2 data from CARTITUDE-1 indicate a single low-dose infusion of cilta-cel leads to early, deep, and durable responses in heavily pretreated pts with MM with a safety profile consistent with LEGEND-2. Further investigation of cilta-cel in other MM populations is underway. Disclosures Madduri: Celgene: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Foundation Medicine: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Legend: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; Kinevant: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau. Berdeja:Teva: Research Funding; Bluebird: Research Funding; Bioclinica: Consultancy; Celgene: Consultancy, Research Funding; EMD Sorono: Research Funding; Kite Pharma: Consultancy; Prothena: Consultancy; Cellularity: Research Funding; Karyopharm: Consultancy; Servier: Consultancy; Legend: Consultancy; Poseida: Research Funding; Lilly: Research Funding; Acetylon: Research Funding; CURIS: Research Funding; Janssen: Consultancy, Research Funding; Genentech, Inc.: Research Funding; Glenmark: Research Funding; Takeda: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Constellation: Research Funding; CRISPR Therapeutics: Consultancy, Research Funding; Vivolux: Research Funding; Abbvie: Research Funding; Amgen: Consultancy, Research Funding; Kesios: Research Funding; Novartis: Research Funding. Usmani:Celgene: Other; BMS, Celgene: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; GSK: Consultancy, Research Funding; Pharmacyclics: Research Funding; Merck: Consultancy, Research Funding; Abbvie: Consultancy; Sanofi: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; Janssen: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; SkylineDX: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Incyte: Research Funding; Array Biopharma: Research Funding; Amgen: Consultancy, Honoraria, Other: Speaking Fees, Research Funding. Jakubowiak:Adaptive, Juno: Consultancy, Honoraria; AbbVie, Amgen, BMS/Celgene, GSK, Janssen, Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Cohen:Celgene: Membership on an entity's Board of Directors or advisory committees; Takeda,: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Genentech/Roche: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Other: Patents/Intellectual property licensed, Research Funding. Stewart:Janssen, BMS, Sanofi-Aventis, GSK: Honoraria; Tempus, Inc., Genomics England LLC: Membership on an entity's Board of Directors or advisory committees. Hari:Amgen: Consultancy; BMS: Consultancy; GSK: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Incyte Corporation: Consultancy. Htut:City of Hope Medical Center: Current Employment. Munshi:OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; BMS: Consultancy; Janssen: Consultancy; Adaptive: Consultancy; Legend: Consultancy; Amgen: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy; AbbVie: Consultancy; C4: Current equity holder in private company. Deol:Novartis: Consultancy; Kite, a Gilead Company: Consultancy. Lesokhin:BMS: Consultancy, Honoraria, Research Funding; Genentech: Research Funding; Janssen: Research Funding; Juno: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Serametrix Inc.: Patents & Royalties; GenMab: Consultancy, Honoraria. Singh:Janssen: Current Employment. Zudaire:Janssen: Current Employment. Yeh:Janssen: Current Employment. Allred:Janssen: Current Employment. Olyslager:Janssen: Current Employment. Banerjee:Janssen: Current Employment. Goldberg:Johnson & Johnson: Current Employment, Current equity holder in publicly-traded company. Schecter:Janssen: Current Employment. Jackson:Janssen: Current Employment; Memorial Sloan Kettering Cancer Center: Consultancy. Deraedt:Janssen: Current Employment, Current equity holder in publicly-traded company. Zhuang:Janssen: Current Employment. Infante:Janssen: Current Employment. Geng:Legend Biotech USA Inc.: Current Employment. Wu:Legend Biotech USA Inc.: Current Employment. Carrasco:Legend Biotech USA Inc.: Current Employment. Akram:Legend Biotech USA Inc.: Current Employment. Hossain:Legend Biotech USA Inc.: Current Employment. Rizvi:Legend Biotech USA Inc.: Current Employment. Fan:Legend Biotech USA Inc.: Current Employment. Jagannath:BMS, Janssen, Karyopharm, Legend Biotech, Sanofi, Takeda: Consultancy. Lin:Kite, a Gilead Company: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Merck: Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Vineti: Consultancy; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees. Martin:AMGEN: Research Funding; Seattle Genetics: Research Funding; Janssen: Research Funding; GSK: Consultancy; Sanofi: Research Funding.