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Koster EAS, von dem Borne PA, van Balen P, Marijt EWA, Tjon JML, Snijders TJF, van Lammeren D, Veelken H, Falkenburg JHF, Halkes CJM, de Wreede LC. Risk factors for graft-versus-host-disease after donor lymphocyte infusion following T-cell depleted allogeneic stem cell transplantation. Front Immunol 2024; 15:1335341. [PMID: 38545096 PMCID: PMC10966113 DOI: 10.3389/fimmu.2024.1335341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 02/13/2024] [Indexed: 04/10/2024] Open
Abstract
Introduction Unmodified donor lymphocyte infusions (DLI) after allogeneic stem cell transplantation (alloSCT) can boost the beneficial Graft-versus-Leukemia (GvL) effect but may also induce severe Graft-versus-Host-Disease (GvHD). To improve the balance between GvL and GvHD, it is crucial to identify factors that influence the alloreactivity of DLI. Methods We investigated the effects of the presence of patient-derived antigen-presenting cells at time of DLI as estimated by the bone marrow (BM) chimerism status, lymphopenia as measured by the absolute lymphocyte count (ALC) at time of DLI, and the presence of a viral infection (de novo or reactivation) close to DLI on the risk of GvHD after DLI. The cohort consisted of patients with acute leukemia or myelodysplastic syndrome who prophylactically or pre-emptively received DLI as standard care after alemtuzumab-based alloSCT. In patients at high risk for relapse, DLI was administered at 3 months after alloSCT (n=88) with a dose of 0.3x106 or 0.15x106 T cells/kg in case of a related or unrelated donor, respectively. All other patients (n=76) received 3x106 or 1.5x106 T cells/kg, respectively, at 6 months after alloSCT. Results For both DLIs, patients with reduced-intensity conditioning and an unrelated donor had the highest risk of GvHD. For DLI given at three months, viral infection within 1 week before and 2 weeks after DLI was an additional significant risk factor (hazard ratio (HR) 3.66 compared to no viral infection) for GvHD. At six months after alloSCT, viral infections were rare and not associated with GvHD. In contrast, mixed BM chimerism (HR 3.63 for ≥5% mixed chimerism compared to full donor) was an important risk factor for GvHD after DLI given at six months after alloSCT. ALC of <1000x106/l showed a trend for association with GvHD after this DLI (HR 2.05 compared to ≥1000x106/l, 95% confidence interval 0.94-4.45). Furthermore, the data suggested that the presence of a viral infection close to the DLI at three months or ≥5% mixed chimerism at time of the DLI at six months correlated with the severity of GvHD, thereby increasing their negative impact on the current GvHD-relapse-free survival. Conclusion These data demonstrate that the risk factors for GvHD after DLI depend on the setting of the DLI.
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Affiliation(s)
- Eva A S Koster
- Department of Hematology, Leiden University Medical Center, Leiden, Netherlands
| | | | - Peter van Balen
- Department of Hematology, Leiden University Medical Center, Leiden, Netherlands
| | - Erik W A Marijt
- Department of Hematology, Leiden University Medical Center, Leiden, Netherlands
| | - Jennifer M L Tjon
- Department of Hematology, Leiden University Medical Center, Leiden, Netherlands
| | | | | | - Hendrik Veelken
- Department of Hematology, Leiden University Medical Center, Leiden, Netherlands
| | | | | | - Liesbeth C de Wreede
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
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Kiwumulo HF, Muwonge H, Ibingira C, Lubwama M, Kirabira JB, Ssekitoleko RT. A di-electrophoretic simulation procedure of iron-oxide micro-particle drug attachment system for leukemia treatment using COMSOL software: a potential treatment reference for LMICs. FRONTIERS IN MEDICAL TECHNOLOGY 2023; 5:1250964. [PMID: 37901748 PMCID: PMC10602814 DOI: 10.3389/fmedt.2023.1250964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 09/29/2023] [Indexed: 10/31/2023] Open
Abstract
Background Leukemia encompasses various subtypes, each with unique characteristics and treatment approaches. The challenge lies in developing targeted therapies that can effectively address the specific genetic mutations or abnormalities associated with each subtype. Some leukemia cases may become resistant to existing treatments over time making them less susceptible to chemotherapy or other standard therapies. Objective Developing new treatment strategies to overcome resistance is an ongoing challenge particularly in Low and Middle Income Countries (LMICs). Computational studies using COMSOL software could provide an economical, fast and resourceful approach to the treatment of complicated cancers like leukemia. Methods Using COMSOL Multiphysics software, a continuous flow microfluidic device capable of delivering anti-leukemia drugs to early-stage leukemia cells has been computationally modeled using dielectrophoresis (DEP). Results The cell size difference enabled the micro-particle drug attachment to the leukemia cells using hydrodynamic focusing from the dielectrophoretic force. This point of care application produced a low voltage from numerically calculated electrical field and flow speed simulations. Conclusion Therefore, such a dielectrophoretic low voltage application model can be used as a computational treatment reference for early-stage leukemia cells with an approximate size of 5 μm.
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Affiliation(s)
- Henry Fenekansi Kiwumulo
- Department of Medical Physiology, Biomedical Engineering Program, Makerere University, Kampala, Uganda
| | - Haruna Muwonge
- Department of Medical Physiology, Biomedical Engineering Program, Makerere University, Kampala, Uganda
- Habib Medical School, Islamic University in Uganda (IUIU), Kampala, Uganda
| | - Charles Ibingira
- Department of Human Anatomy, Makerere University, Kampala, Uganda
| | - Michael Lubwama
- Department of Mechanical Engineering, Makerere University, Kampala, Uganda
| | | | - Robert Tamale Ssekitoleko
- Department of Medical Physiology, Biomedical Engineering Program, Makerere University, Kampala, Uganda
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van der Zouwen B, Koster EAS, von dem Borne PA, Oosten LEM, Roza-Scholten MWI, Snijders TJF, van Lammeren D, van Balen P, Marijt WAF, Veelken H, Falkenburg JHF, de Wreede LC, Halkes CJM. Feasibility, safety, and efficacy of early prophylactic donor lymphocyte infusion after T cell-depleted allogeneic stem cell transplantation in acute leukemia patients. Ann Hematol 2023; 102:1203-1213. [PMID: 36881136 PMCID: PMC10102042 DOI: 10.1007/s00277-023-05145-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Accepted: 02/21/2023] [Indexed: 03/08/2023]
Abstract
Prophylactic donor lymphocyte infusion (DLI) starting at 6 months after T cell-depleted allogeneic stem cell transplantation (TCD-alloSCT) can introduce a graft-versus-leukemia (GvL) effects with low risk of severe graft-versus-host-disease (GvHD). We established a policy to apply low-dose early DLI at 3 months after alloSCT to prevent early relapse. This study analyzes this strategy retrospectively. Of 220 consecutive acute leukemia patients undergoing TCD-alloSCT, 83 were prospectively classified to have a high relapse risk and 43 were scheduled for early DLI. 95% of these patients received freshly harvested DLI within 2 weeks of the planned date. In patients transplanted with reduced intensity conditioning and an unrelated donor, we found an increased cumulative incidence of GvHD between 3 and 6 months after TCD-alloSCT for patients receiving DLI at 3 months compared to patients who did not receive this DLI (0.42 (95%Confidence Interval (95% CI): 0.14-0.70) vs 0). Treatment success was defined as being alive without relapse or need for systemic immunosuppressive GvHD treatment. The five-year treatment success in patients with acute lymphatic leukemia was comparable between high- and non-high-risk disease (0.55 (95% CI: 0.42-0.74) and 0.59 (95% CI: 0.42-0.84)). It remained lower in high-risk acute myeloid leukemia (AML) (0.29 (95% CI: 0.18-0.46)) than in non-high-risk AML (0.47 (95% CI: 0.42-0.84)) due to an increased relapse rate despite early DLI.
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Affiliation(s)
- Boris van der Zouwen
- Department of Hematology, Leiden University Medical Center, C2R, 2300 RC, Leiden, 9600, The Netherlands.
| | - E A S Koster
- Department of Hematology, Leiden University Medical Center, C2R, 2300 RC, Leiden, 9600, The Netherlands
| | - P A von dem Borne
- Department of Hematology, Leiden University Medical Center, C2R, 2300 RC, Leiden, 9600, The Netherlands
| | - L E M Oosten
- Department of Hematology, Leiden University Medical Center, C2R, 2300 RC, Leiden, 9600, The Netherlands
| | - M W I Roza-Scholten
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - T J F Snijders
- Department of Hematology, Medical Spectrum Twente, Enschede, The Netherlands
| | - D van Lammeren
- Department of Hematology, HagaZiekenhuis, The Hague, The Netherlands
| | - P van Balen
- Department of Hematology, Leiden University Medical Center, C2R, 2300 RC, Leiden, 9600, The Netherlands
| | - W A F Marijt
- Department of Hematology, Leiden University Medical Center, C2R, 2300 RC, Leiden, 9600, The Netherlands
| | - H Veelken
- Department of Hematology, Leiden University Medical Center, C2R, 2300 RC, Leiden, 9600, The Netherlands
| | - J H F Falkenburg
- Department of Hematology, Leiden University Medical Center, C2R, 2300 RC, Leiden, 9600, The Netherlands
| | - L C de Wreede
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - C J M Halkes
- Department of Hematology, Leiden University Medical Center, C2R, 2300 RC, Leiden, 9600, The Netherlands
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Zhang X, Solomon SR, Sizemore C. Inferences for current chronic graft-versus-host-disease free and relapse free survival. BMC Med Res Methodol 2022; 22:318. [PMID: 36513966 PMCID: PMC9746208 DOI: 10.1186/s12874-022-01771-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 10/25/2022] [Indexed: 12/15/2022] Open
Abstract
This paper provides the methodologies of a new summary curve that measures the dynamic outcome following allogenic hematopoietic cell transplantation. This new summary curve computes the probabilities that a patient is alive in remission and free of severe-to-moderate chronic graft-versus-host disease (GVHD) over time. The probability is called Current chronic GVHD-free, Relapse-Free Survival (CGRFS). Based on a multistate model depicting the possible states that a patient may experience after transplant, CGRFS can be formulated as a linear combination of five survival functions. This method is known as the model-free approach. In this paper we provide the inferences of the model-free approach, including estimation of CGRFS, precision evaluation and comparison of CGRFS between two independent samples.
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Affiliation(s)
- Xu Zhang
- grid.267308.80000 0000 9206 2401Center for Clinical and Translational Sciences, The University of Texas Health Science Center at Houston, Houston, TX, US
| | - Scott R. Solomon
- grid.416555.60000 0004 0371 5941The Blood and Marrow Transplant Program at Northside Hospital, Atlanta, GA, US
| | - Connie Sizemore
- grid.416555.60000 0004 0371 5941The Blood and Marrow Transplant Program at Northside Hospital, Atlanta, GA, US
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Beyersmann J, Friede T, Schmoor C. Design aspects of COVID-19 treatment trials: Improving probability and time of favorable events. Biom J 2022; 64:440-460. [PMID: 34677829 PMCID: PMC8653377 DOI: 10.1002/bimj.202000359] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 08/13/2021] [Accepted: 09/04/2021] [Indexed: 12/24/2022]
Abstract
As a reaction to the pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a multitude of clinical trials for the treatment of SARS-CoV-2 or the resulting corona disease 2019 (COVID-19) are globally at various stages from planning to completion. Although some attempts were made to standardize study designs, this was hindered by the ferocity of the pandemic and the need to set up clinical trials quickly. We take the view that a successful treatment of COVID-19 patients (i) increases the probability of a recovery or improvement within a certain time interval, say 28 days; (ii) aims to expedite favorable events within this time frame; and (iii) does not increase mortality over this time period. On this background, we discuss the choice of endpoint and its analysis. Furthermore, we consider consequences of this choice for other design aspects including sample size and power and provide some guidance on the application of adaptive designs in this particular context.
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Affiliation(s)
| | - Tim Friede
- Institut für Medizinische StatistikUniversitätsmedizin GöttingenGöttingenGermany
- Deutsches Zentrum für Herz‐Kreislaufforschung (DZHK)Standort GöttingenGöttingenGermany
| | - Claudia Schmoor
- Zentrum Klinische Studien, Universitätsklinikum Freiburg, Medizinische FakultätAlbert‐Ludwigs Universität FreiburgFreiburg im BreisgauGermany
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Bakunina K, Putter H, Versluis J, Koster EAS, van der Holt B, Manz MG, Breems DA, Gjertsen BT, Cloos J, Valk PJM, Passweg J, Pabst T, Ossenkoppele GJ, Löwenberg B, Cornelissen JJ, de Wreede LC. The added value of multi-state modelling in a randomized controlled trial: The HOVON 102 study re-analyzed. Cancer Med 2021; 11:630-640. [PMID: 34953042 PMCID: PMC8817075 DOI: 10.1002/cam4.4392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 09/20/2021] [Accepted: 09/23/2021] [Indexed: 11/07/2022] Open
Abstract
Clofarabine is an active antileukemic drug for subgroups of patients with acute myeloid leukemia (AML). Multi-state models can provide additional insights to supplement the original intention-to-treat analysis of randomized controlled trials (RCT). We re-analyzed the HOVON102/SAKK30/09 phase III RCT for newly diagnosed AML patients, which randomized between standard induction chemotherapy with or without clofarabine. Using multi-state models, we evaluated the effects of induction chemotherapy outcomes (complete remission [CR], measurable residual disease [MRD]), and post-remission therapy with allogeneic stem cell transplantation [alloSCT] on relapse and death. Through the latter a consistent reduction in the hazard of relapse in the clofarabine arm compared to the standard arm was found, which occurred irrespective of MRD status or post-remission treatment with alloSCT, demonstrating a strong and persistent antileukemic effect of clofarabine. During the time period between achieving CR and possible post-remission treatment with alloSCT, non-relapse mortality was higher in patients receiving clofarabine. An overall net benefit of treatment with clofarabine was identified using the composite endpoint current leukemia-free survival (CLFS). In conclusion, these results enforce and extend the earlier reported beneficial effect of clofarabine in AML and show that multi-state models further detail the effect of treatment on competing and series of events.
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Affiliation(s)
- Katerina Bakunina
- Department of Hematology, HOVON Data Center, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Hein Putter
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Jurjen Versluis
- Department of Hematology, Erasmus University Medical Center Cancer Institute, Rotterdam, The Netherlands
| | - Eva A S Koster
- Department of Hematology, Leiden University Medical Center, Leiden, The Netherlands
| | - Bronno van der Holt
- Department of Hematology, HOVON Data Center, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Markus G Manz
- Department of Medical Oncology and Hematology, University Hospital Zurich, Zurich, Switzerland
| | - Dimitri A Breems
- Department of Hematology, Hospital Network Antwerp Stuivenberg/Middelheim, Antwerp, Belgium
| | - Bjorn T Gjertsen
- Department of Internal Medicine, Hematology section, Haukeland University Hospital, Bergen, Norway.,Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Jacqueline Cloos
- Department of Hematology, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Peter J M Valk
- Department of Hematology, Erasmus University Medical Center Cancer Institute, Rotterdam, The Netherlands
| | - Jakob Passweg
- Department of Hematology, University Hospital Basel, Basel, Switzerland
| | - Thomas Pabst
- Department of Medical Oncology, University Hospital/Inselspital, Bern, Switzerland
| | - Gert J Ossenkoppele
- Department of Hematology, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Bob Löwenberg
- Department of Hematology, Erasmus University Medical Center Cancer Institute, Rotterdam, The Netherlands
| | - Jan J Cornelissen
- Department of Hematology, Erasmus University Medical Center Cancer Institute, Rotterdam, The Netherlands
| | - Liesbeth C de Wreede
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
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