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26 citation(s) found for "Wudhikarn, Kitsada".

A Multi-Institutional Retrospective Analysis of T-Cell Lymphomas with Central Nervous System Relapse
Ganesan, Nivetha , Sokol, Lubomir , Pullarkat, Priyanka, Mehta–Shah, Neha , Prakash, Rishab, Goldin, Caroline, Haverkos, Brad M., Allen, Pamela B. , Gerson, James N. , Svoboda, Jakub , Bhansali, Rahul S. , Stuver, Robert , Horwitz, Steven M. , Wudhikarn, Kitsada , Hwang, Steven R. , Bennani, N. Nora , Chavez, Julio C , Sokol, Lubomir , Saeed, Hayder , Iyer, Swaminathan P. , Olszewski, Adam J. , Haverkos, Bradley M. , Chong, Elise A. , Landsburg, Daniel J. , Nasta, Sunita , Schuster, Stephen J. , Barta, Stefan K

Mayo Clinic

Blood | November 23, 2021 | Volume: 138 | Issue: Supplement 1 | Pages: 1382-1382

10.1182/blood-2021-148868 Get It

Abstract Introduction Central nervous system (CNS) relapse (CNSr) in patients with aggressive non-Hodgkin lymphoma (NHL) occurs uncommonly (estimated incidence 5%) but carries a high morbidity and mortality. Studies have identified risk factors for CNSr such as high tumor burden and extranodal (EN) disease. However, most focus on B-cell NHL with minimal data in T-cell lymphomas (TCL), which are significantly less common and more heterogenous. The few small series of CNSr in TCL report a median overall survival (OS) less than 3 months (mo) with incidence ranging from 2.6-9%. To better define CNSr in TCL, we performed a multi-institutional retrospective analysis of TCL patients with CNSr and herein describe clinicopathologic characteristics and treatment of CNSr. Methods We performed a retrospective observational study using data from 9 US academic centers with IRB approval at individual sites. We included adult patients diagnosed with a mature T-cell neoplasm as per the 2016 WHO classification between 1/1/2009-1/1/2019, who were found to have CNSr at any time after initial diagnosis, and collected patient, disease, and treatment characteristics at time of initial diagnosis as well as at CNSr. Patients with a diagnosis of a precursor T-cell malignancy or with CNS disease identified at initial TCL diagnosis (TCLd) and/or prior to first-line systemic treatment were excluded. Results In this analysis, we report the outcomes of 75 patients (male n=45, female n=30). At TCLd, the median age was 59 years (range 20-81), and 61% of patients (n=46) had an IPI score of at least 3, 92% (n=69) had EN involvement with 37% (n=28) involving at least 2 EN sites, and 59% (n=44) had BM involvement. The most common pathologic diagnoses were peripheral T-cell lymphoma, not otherwise specified (PTCL, NOS; 24%, n=18), angioimmunoblastic T-cell lymphoma (AITL; 17%, n=13), adult T-cell leukemia/lymphoma (ATLL; 17%, n=13), and mycosis fungoides (MF; 12%, n=9) (Figure 1A). First-line systemic therapy for TCL included anthracyclines for 72% (n=54). Autologous and allogenic transplants were performed prior to CNSr in 12% (n=9) and 8% (n=6) of patients, respectively. Prior to CNSr, 48% (n=36) had non-CNS relapse. Some form of CNS prophylaxis was used during initial systemic lymphoma therapy in 24% of patients (n=18), predominantly intrathecal methotrexate (IT MTX; n=16). Median time from TCLd to CNSr was 8.5mo, though this was significantly longer in MF (46.8mo [range 17.5-187.7]) versus PTCL, NOS (7.6mo [range 1.1-58.4], P=0.0002), AITL (21.2mo [range 2.0-61.6, P=0.008), and ATLL (7.3mo [range 0.7-46.4], P=0.0005) (Figure 1B). CNSr developed within 6mo of TCLd in 31% of patients (n=23) and within 12mo in 57% (n=43). Symptoms related to CNSr occurred in 71% of patients (n=53). CNSr patterns were 61% leptomeningeal (n=46), 21% parenchymal (n=16), and 17% both (n=13) with no significant survival difference between leptomeningeal or parenchymal disease alone (HR 1.45, 95% CI 0.78-2.70, P=0.28). Concomitant systemic relapse was observed in 59% of patients (n=44). The most common CNS-directed therapy for CNSr was IT MTX (56%; n=42), though multiple different IT and/or systemic regimens were used. Patients received a median of 1 line of CNS-directed treatment (range 0-5). The overall response rate to initial CNS directed treatment was 32% (16% CR, 16% PR). Median follow up after CNSr was 40.7mo. At last follow up, 83% had died (n=62). Median OS after CNSr was 4.6mo (range 0.1-68.7) (Figure 1C). Those with ATLL had the shortest median OS after CNSr (2.7mo) versus 6.3mo in MF (HR 3.69, 95% CI 1.44-9.42, P=0.005), 6.5mo in AITL (HR 2.16, 95% CI 0.92-5.06, P=0.054), and 4.8mo in PTCL, NOS (HR 1.49, 95% CI 0.70-3.19, P=0.27) (Figure 1D). The most common cause of death was progressive lymphoma (77%; n=48). Conclusions This is to our knowledge the largest series of CNSr in TCL to date. Most CNSr occurred within 12mo, though CNSr occurred later in patients with MF. Although the prognosis after CNSr was generally poor, we found that median OS in CNSr was longer than previously reported, perhaps reflecting more effective treatments for CNS and systemic relapse, inclusion of MF, or lead time bias. Further analysis of the impact of different treatment strategies and outcomes in CNSr was limited by the small sample size and heterogeneity within our cohort, and future analyses in a larger cohort should focus on factors associated with outcomes. Figure 1 Figure 1. Disclosures Horwitz: ADC Therapeutics, Affimed, Aileron, Celgene, Daiichi Sankyo, Forty Seven, Inc., Kyowa Hakko Kirin, Millennium /Takeda, Seattle Genetics, Trillium Therapeutics, and Verastem/SecuraBio.: Consultancy, Research Funding; Affimed: Research Funding; Aileron: Research Funding; Acrotech Biopharma, Affimed, ADC Therapeutics, Astex, Merck, Portola Pharma, C4 Therapeutics, Celgene, Janssen, Kura Oncology, Kyowa Hakko Kirin, Myeloid Therapeutics, ONO Pharmaceuticals, Seattle Genetics, Shoreline Biosciences, Inc, Takeda, Trillium Th: Consultancy; Celgene: Research Funding; C4 Therapeutics: Consultancy; Crispr Therapeutics: Research Funding; Daiichi Sankyo: Research Funding; Forty Seven, Inc.: Research Funding; Kura Oncology: Consultancy; Kyowa Hakko Kirin: Consultancy, Research Funding; Millennium/Takeda: Research Funding; Myeloid Therapeutics: Consultancy; ONO Pharmaceuticals: Consultancy; Seattle Genetics: Consultancy, Research Funding; Secura Bio: Consultancy; Shoreline Biosciences, Inc.: Consultancy; Takeda: Consultancy; Trillium Therapeutics: Consultancy, Research Funding; Tubulis: Consultancy; Verastem/Securabio: Research Funding. Bennani: Purdue Pharma: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Vividion: Other: Advisory Board; Kymera: Other: Advisory Board; Verastem: Other: Advisory Board. Chavez: AstraZeneca: Research Funding; ADC Therapeutics: Consultancy, Research Funding; Merk: Research Funding; MorphoSys, AstraZeneca, BeiGene, Genentech, Kite, a Gilead Company, and Epizyme: Speakers Bureau; MorphoSys, Bayer, Karyopharm, Kite, a Gilead Company, Novartis, Janssen, AbbVie, TeneoBio, and Pfizer: Consultancy; BMS: Speakers Bureau. Sokol: Dren Bio: Membership on an entity's Board of Directors or advisory committees; Kyowa-Kirin: Membership on an entity's Board of Directors or advisory committees. Saeed: Nektar Therapeutics: Consultancy, Other: research investigator; MEI Pharma Inc: Consultancy, Other: investigator; Celgene Corporation: Consultancy, Other: investigator; MorphoSys AG: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb Company: Consultancy; sano-aventis U.S.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen Pharmaceutica Products, LP: Consultancy, Other: investigator; Kite Pharma: Consultancy, Other: investigator; Other-TG therapeutics: Consultancy, Other: investigator; Other-Epizyme, Inc.: Consultancy; Other-Secura Bio, Inc.: Consultancy; Seattle Genetics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Mehta-Shah: Kiowa Hakko Kirin: Consultancy; C4 Therapeutics: Consultancy; Verastem: Research Funding; Karyopharm: Consultancy; Ono Pharmaceuticals: Consultancy; Secura Bio: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; AstraZeneca: Research Funding; Bristol Myers Squibb: Research Funding; Celgene: Research Funding; Innate Pharmaceuticals: Research Funding; Roche/Genentech: Research Funding; Corvus Pharmaceuticals: Research Funding. Olszewski: TG Therapeutics: Research Funding; PrecisionBio: Research Funding; Celldex Therapeutics: Research Funding; Acrotech Pharma: Research Funding; Genentech, Inc.: Research Funding; Genmab: Research Funding. Allen: Epizyme: Consultancy; MorphoSys: Consultancy; ADC Therapeutics: Consultancy; Secure Bio: Consultancy; Kyowa Kirin: Consultancy. Gerson: Abbvie: Consultancy; Kite: Consultancy; TG Therapeutics: Consultancy; Pharmacyclics: Consultancy. Landsburg: Triphase: Research Funding; Takeda: Research Funding; Curis: Research Funding; ADCT: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Other: DSMB member; Incyte: Membership on an entity's Board of Directors or advisory committees; Morphosys: Membership on an entity's Board of Directors or advisory committees. Schuster: Adaptive Biotechnologies: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding; Genentech/Roche: Consultancy, Research Funding; Tessa Theraputics: Consultancy; Juno Theraputics: Consultancy, Research Funding; Loxo Oncology: Consultancy; BeiGene: Consultancy; Alimera Sciences: Consultancy; Acerta Pharma/AstraZeneca: Consultancy; Abbvie: Consultancy, Research Funding; Nordic Nanovector: Consultancy; Novartis: Consultancy, Honoraria, Patents & Royalties, Research Funding; Incyte: Research Funding; TG Theraputics: Research Funding; Celgene: Consultancy, Honoraria, Research Funding. Svoboda: Atara: Consultancy; Adaptive: Consultancy, Research Funding; Astra Zeneca: Consultancy, Research Funding; Imbrium: Consultancy; Pharmacyclics: Consultancy, Research Funding; Genmab: Consultancy; Merck: Research Funding; Incyte: Research Funding; BMS: Consultancy, Research Funding; TG: Research Funding; Seattle Genetics: Consultancy, Research Funding. Barta: Kyowa Kirin: Honoraria; Acrotech: Honoraria; Daiichi Sankyo: Honoraria; Seagen: Honoraria.
Age defining immune effector cell associated neurotoxicity syndromes in aggressive large B cell lymphoma patients treated with axicabtagene ciloleucel
Wudhikarn, Kitsada , Bansal, Radhika , Khurana, Arushi , Hathcock, Matthew , Braksick, Sherri A. , Wang, Yucai , Johnston, Patrick B. , Ansell, Stephen M. , Lin, Yi , Paludo, Jonas , Wang, Yucai , Ansell, Stephen M , Lin, Yi , Bennani, N. Nora , Paludo, Jonas , Villasboas, José C.

Mayo Clinic

American Journal of Hematology | August 23, 2021 | Volume: 96 | Issue: 11 | Pages: No page available

10.1002/ajh.26330 | PMID 34424554 Get It

Spectrum of hematological malignancies, clonal evolution and outcomes in 144 Mayo Clinic patients with germline predisposition syndromes
Martin, Emma C. St. , Mangaonkar, Abhishek A. , Khan, Shakila P. , Kohorst, Mira A. , Joshi, Avni Y. , Olteanu, Horatiu , Moyer, Ann M. , Al‐Kali, Aref , Tefferi, Ayalew , Chen, Dong , Wudhikarn, Kitsada , Viswanatha, David S., He, Rong , Nguyen, Phuong L., Oliveira, Jennifer L. , Gangat, Naseema , Patnaik, Mrinal M. , Herrick, Jennifer L. , St Martin, Emma C , Mangaonkar, Abhishek A. , Tefferi, Ayalew , Chen, Dong , Viswanatha, David, He, Rong , Patnaik, Mrinal , Ferrer, Alejandro , Hogan, William J. , Go, Ronald S. , Ketterling, Rhett P. , Lasho, Terra L.

Mayo Clinic

American Journal of Hematology | August 14, 2021 | Volume: 96 | Issue: 11 | Pages: 1450-1460

10.1002/ajh.26321 | PMID 34390506 Get It

AbstractGermline predisposition syndromes (GPS) result from constitutional aberrations in tumor suppressive and homeostatic genes, increasing risk for neoplasia in affected kindred. In this study, we present clinical and genomic data on 144 Mayo Clinic patients with GPS; 59 evaluated prospectively using an algorithm‐based diagnostic approach in the setting of a dedicated GPS/ inherited bone marrow failure syndrome (IBMFS) clinic. Seventy‐two (50%) patients had IBMFS (telomere biology disorders‐32,Fanconi anemia‐18, Diamond Blackfan Anemia – 11, congenital neutropenia–5, Schwachman‐Diamond Syndrome‐5 and Bloom Syndrome‐1), 27 (19%) had GPS with antecedent thrombocytopenia (RUNX1‐FPD‐15, ANKRD26‐6, ETV6‐2, GATA1‐1, MPL‐3), 28 (19%) had GPS without antecedent thrombocytopenia (GATA2 haploinsufficiency‐16, DDX41‐10, CBL‐1 and CEBPA‐1) and 17 (12%) had general cancer predisposition syndromes (ataxia telangiectasia‐7, heterozygous ATM variants‐3, CHEK2‐2, TP53‐2, CDK2NA‐1, NF1‐1 and Nijmegen Breakage Syndrome‐1). Homozygous and heterozygous ATM pathogenic variants were exclusively associated with lymphoproliferative disorders (LPD), while DDX41 GPS was associated with LPD and myeloid neoplasms. The use of somatic NGS‐testing identified clonal evolution in GPS patients, with ASXL1, RAS pathway genes, SRSF2 and TET2 being most frequently mutated. Fifty‐two (91%) of 59 prospectively identified GPS patients had a change in their management approach, including additional GPS‐related screening in 42 (71%), referral for allogenic HSCT workup and screening of related donors in 16 (27%), medication initiation and selection of specific conditioning regimens in 14 (24%), and genetic counseling with specific intent of fertility preservation and preconceptual counseling in 10 (17%) patients; highlighting the importance of dedicated GPS screening, detection and management programs for patients with hematological neoplasms.
Characteristics, outcomes, and risk factors of ICANS after axicabtagene ciloleucel: Does age matter?
Bansal, Radhika , Khurana, Arushi , Hathcock, Matthew , Ruff, Michael W. , Carabenciov, Ivan D. , Braksick, Sherri A. , Johnston, Patrick B. , Ansell, Stephen M. , Wudhikarn, Kitsada , Bennani, N. Nora , Paludo, Jonas , Villasboas, José C. , Wang, Yucai , Lin, Yi

Mayo Clinic

Journal of Clinical Oncology | June 2, 2021 | Volume: 39 | Issue: 15_suppl | Pages: e19556-e19556

10.1200/jco.2021.39.15_suppl.e19556 Get It

e19556 Background: CD19 chimeric antigen receptor T cell therapy possesses unique side effects including cytokine release syndrome (CRS) and immune effector cell associated neurotoxicity syndrome (ICANS). Age is a major risk factor for ICANS. However, whether ICANS in older patients is different compared to younger patients is unknown. Herein, we report clinical course, outcomes and risk factors for ICANS in older patients with large B cell lymphoma (LBCL) treated with axicabtagene ciloleucel (axi-cel). Methods: We comprehensively reviewed detailed clinical courses of ICANS in 78 adult patients with LBCL treated with axi-cel between June 2016 and October 2020. Incidence, manifestation, risk factors, treatment, and outcomes of ICANS were compared between patients age ≥60 (n=32) and <60 (n=46) years old. Results: Baseline characteristics were comparable between older and younger patients except higher proportion of high international prognostic index and underlying cerebral microvascular disease in older patients. ICANS was observed in 16 patients in the older and 24 patients in the younger age group, with a 30-day incidence of 52% and 50%, respectively. Median time to CRS and ICANS were similar between 2 age groups. The most common initial neurological findings included aphasia, dysgraphia and encephalopathy in both age groups. Table summarizes the characteristics, clinical course and interventions of ICANS in older and younger patients. In Cox regression model, the presence of CRS was the only factor associated with ICANS in both age groups. Age, history of central nervous system involvement and cerebral microvascular disease were not associated with ICANS. Importantly, all patients had complete resolution of ICANS. No elderly patients in our cohort experienced seizure as a manifestation of ICANS. Conclusions: In our study, older age was not a risk factor for ICANS. CRS was the only factor associated with ICANS in both younger and older patients. Incidence, clinical course and neurological outcomes of ICANS in older patients treated with axi-cel were comparable to younger patients. [Table: see text]
The impact of body weight and body mass index on outcomes of diffuse large B-cell lymphoma treated with axicabtagene ciloleucel.
Bansal, Radhika , Khurana, Arushi , Hathcock, Matthew , Johnston, Patrick B. , Ansell, Stephen M. , Wudhikarn, Kitsada , Bennani, N. Nora , Paludo, Jonas , Villasboas, José C. , Wang, Yucai , Lin, Yi

Mayo Clinic

Journal of Clinical Oncology | June 2, 2021 | Volume: 39 | Issue: 15_suppl | Pages: e19554-e19554

10.1200/jco.2021.39.15_suppl.e19554 Get It

e19554 Background: Obesity is associated with a pro-inflammatory state and immune dysregulation. Retrospective studies indicate that obesity could affect toxicities and outcomes after immunotherapies including checkpoint inhibitors and allogeneic stem cell transplant. Currently, there are no data specifically on outcomes for obese patients who receive chimeric antigen receptor T (CAR-T) cells. We described the clinical outcome in obese patients with large B cell lymphoma (LBCL) who received axicabtagene ciloleucel (axi-cel). Methods: We analyzed the effect of body weight (BW) and body mass index (BMI) on toxicities and outcomes of 78 adults with LBCL who received axi-cel between June 2016 and October 2020 at Mayo Clinic. Obesity was defined as having BMI of 30 or higher. Results: Of 78 patients, 22 (28%) and 19 (24%) were classified as overweight (BMI 25-29.99 kg/m2) and obese (BMI ≥30 kg/m2), respectively. Baseline characteristics were not statistically significantly different between non-obese and obese patients. The median delivered dose of fludarabine was similar between non-obese and obese patients (89 [0-105] vs 88 [56-94] mg/m2, P=0.32) whereas the median delivered dose of cyclophosphamide was lower in non-obese patients (1503 [1077-1525] vs 1512 [1021-1660] mg/m2, P=0.01). The 30-days cumulative incidence of CRS and ICANS were similar between non-obese and obese patients. BW and BMI were not associated with CRS or ICANS. The overall response rate was 66% (CR 47%) and 68% (CR 53%) in non-obese and obese group, respectively ( P=0.83). The 1-year event free survival (EFS) and overall survival (OS) was 34.6% and 64.5%, neither were different between non-obese and obese patients (EFS 35.8% vs. 30.7%, P=0.60; OS 59.4% vs. 83.9%, P=0.18). The 1-year cumulative incidence of relapse and non-relapse mortality was comparable (60.8% vs. 69.0%, P=0.40 and 3.4% vs. 0%, P=0.42). In the Cox proportional hazards model, higher dose of fludarabine, but not cyclophosphamide, was associated with better EFS and OS; however, neither obesity nor BW were associated with toxicities and outcomes. Conclusions: In our study, Obesity was not associated with risk of toxicities or adverse survival outcomes. The effect of obesity on the pattern of LD chemotherapy dosing including toxicities and outcomes after CAR-T warrants further exploration. [Table: see text]
Clinical features and survival outcomes in patients with chronic myelomonocytic leukemia arising in the context of germline predisposition syndromes
Martin, Emma C. St. , Wudhikarn, Kitsada , Mangaonkar, Abhishek A. , Tefferi, Ayalew , Gangat, Naseema , Altman, Jessica K. , Godley, Lucy A. , Patnaik, Mrinal M. , St Martin, Emma C , Mangaonkar, Abhishek A. , Hogan, William, Tefferi, Ayalew , Patnaik, Mrinal , Godley, Lucy A , Ferrer, Alejandro , Hogan, William J. , Lasho, Terra L.

Mayo Clinic

American Journal of Hematology | May 24, 2021 | Volume: 96 | Issue: 9 | Pages: No page available

10.1002/ajh.26250 | PMID 34028844 Get It

Clinical correlates and prognostic impact of clonal hematopoiesis in multiple myeloma patients receiving post‐autologous stem cell transplantation lenalidomide maintenance therapy
Wudhikarn, Kitsada , Padrnos, Leslie , LaPlant, Betsy, Kumar, Shaji , Lacy, Martha Q. , Rajkumar, S. Vincent , Gertz, Morie A. , Mangaonkar, Abhishek A. , Shi, Chang‐Xin, Stewart, A. Keith , Patnaik, Mrinal M. , Dispenzieri, Angela , Lacy, Martha, Rajkumar, S Vincent , Gertz, Morie A , Mangaonkar, Abhishek A. , Gonsalves, Wilson , Patnaik, Mrinal , Lasho, Terra L. , Dispenzieri, Angela , Gonsalves, Wilson I. , Ketterling, Rhett P. , Fonseca, Rafaël

Mayo Clinic

American Journal of Hematology | February 14, 2021 | Volume: 96 | Issue: 5 | Pages: No page available

10.1002/ajh.26125 | PMID 33580975 Get It

Spectrum of Antiphospholipid Antibodies and Associated Thrombotic and Obstetric Events among Patients with Antiphospholipid Syndrome
Patnaik, Mrinal M. , Shroff, Monal M, Killeen, Anthony A. , Wudhikarn, Kitsada , Reding, Mark T. , Kasthuri, Raj S.

Mayo Clinic

Blood | April 19, 2020 | Volume: 112 | Issue: 11 | Pages: 5343-5343

10.1182/blood.v112.11.5343.5343 Get It

Abstract Introduction: Antiphospholipid antibody syndrome (APS) is characterized by arterial or venous thrombosis, and/or adverse obstetric outcomes in the presence of persistent antiphospholipid antibodies (APab). Between 2–10% of all patients with APS are reported to present solely with anti beta-2 glycoprotein 1 antibodies (b2GP1 abs) (ref 1). In 2006 the Sapporo criteria were revised to include b2GP1 abs to the panel of diagnostic tests. While presence of a lupus anticoagulant (LA) has been found to correlate well with occurrence of thromboses, the prognostic and predictive roles of b2GP1 abs and anticardiolipin antibodies (ACLA) need better definition. Previous studies suggest both the severity of the initial event and the risk for recurrent events is greater among patients demonstrating presence of more than one APab on laboratory testing (ref 2 and 3), but this aspect needs further confirmation. Objectives: To identify the spectrum of clinical thrombotic and obstetric manifestations associated with the different APab profiles; To determine the prevalence and clinical significance of the b2GP1 ab positive and ACLA/LA negative phenotype; and To evaluate the significance of IgM b2GP1 ab and IgM ACLA. Methods: Medical records of patients tested for all three antiphospholipid antibodies at the University of Minnesota Medical Center from Dec 2000 to Dec 2005 were reviewed. Patients that met the modified criteria for APS were included. IgG and IgM ACLA were measured using the Diamedix kit (VAX diagnostics) and IgG and IgM b2GP1 abs using the Inovalite kit (NOVA diagnostics). LA was determined using standard protocol. Results: Over the 5 year period, all three laboratory assays were obtained in 560 individuals, but only 76 (13.5%) patients who met both the clinical and laboratory criteria for APS were included in this study. Seven of the 76 patients (9.2%) had isolated, persistently positive b2GP1 abs. LA alone was present in 21 patients (27.6%). Twenty nine patients (38%) had all three APabs, and had a higher incidence of thrombosis at multiple sites at the time of diagnosis as well as increased rate of recurrent events, in comparison to those with two or less than two APab. Isolated ACLA was present in only 2 patients (2.6%). Interestingly, both IgM (47%) and IgG (50%) b2GP1 abs were associated with thrombosis, whereas only IgG ACLA was found to be associated with thrombosis. Conclusion: The presence of b2GP1 abs as the sole laboratory anomaly is uncommon, but is noted in patients with APS, thus warranting it’s testing at the time of clinical suspicion. Amongst the different antibody types LA seems to be the strongest predictor for thrombotic events and ACLA seems to have a weaker link, consistent with the results of previous studies (ref 4). The presence of all three AP antibodies does increase the risk for recurrent and multiple thromboses.
Correlation of chemotherapy delivery and survival outcomes of follicular lymphoma in the immunchemotherapy era.
Smith, Brian J., Thompson, Carrie A. , Wudhikarn, Kitsada , Button, Anna M. , Smith, Brian J., Habermann, Thomas M. , Cerhan, James R. , Link, Brian K.

Mayo Clinic

Journal of Clinical Oncology | March 12, 2020 | Volume: 31 | Issue: 15_suppl | Pages: 8563-8563

10.1200/jco.2013.31.15_suppl.8563 Get It

8563 Background: Optimal initial treatment of follicular lymphoma (FL) is unknown. Rituximab as monotherapy (R) or as a component of immunochemotherapy (R+Chemo) is established as effective and it is now reasonable to re-examine the role of chemotherapy dosing. We explored clinical features, systemic treatment and chemotherapy delivery with comparative effectiveness of delivered dose intensity (DDI) on outcomes. Methods: We reviewed the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource database along with medical records on newly diagnosed grade I-IIIa FL who received systemic therapy from 2002 to 2009. Presenting clinicopathologic factors, outcomes and systemic therapy details including doses of chemotherapy were collected. The event-free (EFS) and overall survival (OS) effects of systemic therapy and chemotherapy DDI were analyzed with multivariate Cox regression. Confounding effects of FLIPI, grade, stage, and age were considered in the analysis. Results: From 2002 to 2009, 631 newly diagnosed FL were enrolled. Median follow up duration was 52.7 months. We identified 322 grade I-IIIa FL treated with systemic therapy including 93 R and 229 R+Chemo. Age and stage were similarly distributed between the R and R+Chemo groups; however, patients in the R group had lower grade (p<0.01) and FLIPI (p=0.03). Multivariate analysis showed no significant differences in EFS (HR=1.24, p=0.28) or OS (HR=0.55, p=0.13) for R compared to R+Chemo. Among R-CVP or R-CHOP treated FL, DDI data were collected for 73 doxorubicin (dox) and 137 cyclophosphamide (cyc) patients. Eighty-five percent of patients received 90% or more pre-planned DDI. After controlling for confounding factors, higher cycDDI was associated with improved EFS (HR 0.55, P=0.04) and OS (HR 0.74, P=0.03). No significant OS or EFS effects of doxDDI were observed. Conclusions: Addition of chemotherapy to rituximab was not associated with a detectable difference in survival outcomes in grade I-IIIa FL at a median follow-up of 52.7 months. Among R+Chemo treated FL, chemotherapy was delivered completely in most patients and more completed delivery of cyclophosphamide was associated with improved EFS and OS.
The MAGIC Algorithm Probability (MAP): A Novel Laboratory Biomarker for the Response to Treatment of Acute Graft-Versus-Host Disease
Özbek, Umut , Kapoor, Urvi , Ayuk, Francis , Aziz, Mina, Ben-David, Kaitlyn , Choe, Hannah , DeFilipp, Zachariah , Etra, Aaron , Hartwell, Matthew J. , Kowalyk, Steven, Lin, Jung-Yi, Major-Monfried, Hannah , Mielke, Stephan , Morales, George , Ordemann, Rainer, Reddy, Pavan, Roesler, Wolf, Sandhu, Karamjeet , Schechter‐Finkelstein, Tal, Weber, Daniela , Wölfl, Matthias , Young, Rachel , Ferrara, James L.M. , Mielke, Stephan , Srinagesh, Hrishikesh K. , Grupp, Stephan A. , Hexner, Elizabeth O. , Hogan, William J. , Kitko, Carrie L. , Merli, Pietro , Pulsipher, Michael A. , Qayed, Muna , Reshef, Ran , Shah, Jay, Sigel, Keith Magnus , Wudhikarn, Kitsada , Levine, John E.

Mayo Clinic

Blood | February 14, 2020 | Volume: 134 | Issue: Supplement_1 | Pages: 367-367

10.1182/blood-2019-122011 Get It

Systemic glucocorticoids are the principal treatment for acute graft-versus-host disease (GVHD), which remains the major cause of non-relapse mortality (NRM) after allogeneic hematopoietic cell transplantation (HCT). However, there are no validated biomarkers that measure a patient's response to glucocorticoid therapy, and thus response is evaluated by the change in clinical symptom severity. A major weakness in the predictive power of clinical responses is that changes to all organs are weighted equally even though the major driver of NRM is irreversible damage to the crypts of the GI tract. Recent studies from the Mount Sinai Acute GVHD International Consortium (MAGIC) have validated an algorithm probability (MAP) that combines serum concentrations of two biomarkers of GVHD (REG3α and ST2) to generate an estimated probability of 6 month NRM for individual patients. The MAP has been considered a "liquid biopsy" that estimates the damage caused by GVHD to crypts throughout the lower GI tract (Hartwell et al., JCI Insight, 2017; Major-Monfried et al., Blood, 2018). We hypothesized that the change in MAP between start of treatment and 28 days later could serve as a response biomarker for GVHD and might compare favorably to the change in clinical symptoms that measures response to GVHD treatment, which is widely used as a surrogate for long term survival and is the primary endpoint in most GVHD treatment trials (Martin et al., BBMT, 2009; MacMillan et al., Blood, 2010). We prospectively collected serum samples and clinical staging from 368 sequential HCT patients who received systemic treatment for acute GVHD in one of 20 MAGIC centers between January 2016 and February 2018. We measured the serum concentrations of REG3α and ST2 before and after systemic therapy for acute GVHD and computed MAPs, the changes in MAPs, and clinical responses for each patient. MAPs of patients who experienced 6 month NRM showed significantly greater increases than MAPs of patients who survived (p=0.0004). In patients whose MAPs at the start of treatment were low (Ann Arbor 1, MAP &lt; 0.141) or intermediate (Ann Arbor 2, 0.141 ≤ MAP ≤ 0.290), 6 month NRM clustered among those who had the greatest increases in MAP after 28 days (Fig 1A,B). In patients with high MAPs at the start of treatment (Ann Arbor 3, MAP &gt; 0.290), those who survived tended to have the largest decreases in MAP (Fig 1C). These changes in MAP suggested crossing a single threshold could predict risk of mortality. We found that patients whose MAPs rose above a threshold MAP of 0.290 (5% of Ann Arbor 1, 27% of Ann Arbor 2) had significantly worse survival compared to those who remained below it, whereas the large number patients with initially high MAPs that remained above the threshold (66% of Ann Arbor 3) had a large increases in mortality (Fig 2). When measured at day 28, the MAP was significantly more accurate in predicting NRM than the gold standard of the clinical response, with areas under the receiver operating characteristic curve (AUC) of 0.86 and 0.70, respectively (p&lt;0.0001). An algorithm that combined clinical response with biomarkers generated the same AUC as the MAP alone (0.83 v 0.86, p = NS). We next tested whether the same MAP threshold of 0.290 could predict risk within clinical response subsets. A significant minority (10%) of clinical responders had high MAPs and experienced three-fold greater NRM than those with low MAPs (40% v 12%, p&lt;0.0001) whereas the majority (57%) of non-responders had low MAPs and experienced almost three-fold lower NRM than those with high MAPs (24% v 65%, p&lt;0.0001) (Fig 3). Thus the MAP provides important prognostic information over and above the change in clinical symptoms, further stratifying both responders and non-responders at four weeks of treatment. The MAP threshold classified patients both with and without significant lower GI symptoms because the MAP is a more specific measure of irreversible cryptic damage in patients with copious diarrhea and more sensitive in patients with less than 0.5 liters of daily diarrhea (Fig 4). We conclude that the MAP is, to our knowledge, the first validated laboratory test to serve as response biomarker for the treatment for acute GVHD and a more accurate predictor of survival than clinical response after four weeks of treatment. The MAP may serve as a novel endpoint and an important complement to changes in clinical symptom severity in future trials of GVHD treatment. Disclosures Srinagesh: National Institutes of Health: Research Funding. Ozbek:Viracor: Patents & Royalties: Biomarker Patent. Ayuk:Novartis: Honoraria, Other: Advisory Board, Research Funding. Aziz:Doris Duke Charitable Foundation: Research Funding. Defilipp:Incyte: Research Funding. Grupp:Novartis: Consultancy, Research Funding; Roche: Consultancy; GSK: Consultancy; CBMG: Consultancy; Novartis: Research Funding; Kite: Research Funding; Servier: Research Funding; Jazz: Other: study steering committees or scientific advisory boards; Adaptimmune: Other: study steering committees or scientific advisory boards; Cure Genetics: Consultancy; Humanigen: Consultancy. Hexner:novartis: Research Funding. Kitko:Mallinckrodt: Honoraria; Novartis: Consultancy, Honoraria. Mielke:EBMT/EHA: Other: Travel support; ISCT: Other: Travel support; Miltenyi: Consultancy, Honoraria, Other: Travel and speakers fee (via institution), Speakers Bureau; Jazz Pharma: Honoraria, Other: Travel support, Speakers Bureau; IACH: Other: Travel support; Kiadis Pharma: Consultancy, Honoraria, Other: Travel support (via institution), Speakers Bureau; DGHO: Other: Travel support; Bellicum: Consultancy, Honoraria, Other: Travel (via institution); GILEAD: Consultancy, Honoraria, Other: travel (via institution), Speakers Bureau; Celgene: Honoraria, Other: Travel support (via institution), Speakers Bureau. Merli:Sobi: Consultancy; Amgen: Honoraria; Novartis: Honoraria; Bellicum: Consultancy. Pulsipher:Amgen: Other: Lecture; Miltenyi: Research Funding; Bellicum: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz: Other: Education for employees; CSL Behring: Membership on an entity's Board of Directors or advisory committees; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Medac: Honoraria. Qayed:Bristol-Myers Squibb: Honoraria. Reshef:Pfizer: Consultancy; Magenta: Consultancy; Kite: Consultancy, Research Funding; Atara: Consultancy, Research Funding; BMS: Consultancy; Pharmacyclics: Consultancy, Research Funding; Incyte: Consultancy, Research Funding; Celgene: Research Funding; Shire: Research Funding. Levine:Incyte: Consultancy, Research Funding; Biogen: Other: non-financial support; Viracor: Patents & Royalties: biomarker patent; Ironwood: Honoraria; bluebird bio: Consultancy; National Cancer Institute: Research Funding; Novartis: Honoraria; Kamada: Research Funding. Ferrara:National Institutes of Health: Research Funding; ViraCor: Consultancy; Incyte: Consultancy; Kamada: Consultancy; Mallinckrodt: Consultancy; Enlivex: Consultancy; Xenikos: Consultancy; CSL Behring: Consultancy.