AML consolidation therapy: timing matters

Reimann, Arthur F.; Schalk, Enrico; Jost, Felix; Mougiakakos, Dimitrios; Weber, Daniela; Döhner, Hartmut; Récher, Christian; Dumas, Pierre‐Yves; Ditzhaus, Marc; Fischer, Thomas; Säger, Sebastian

doi:10.1007/s00432-023-05115-0

Cited by 3 publications

(2 citation statements)

References 23 publications

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“…The function 𝐹 ∶  ×  ↦ ℝ couples the effect of the PK and PD models and models the feedback relation : . 6 This reflects the treatment steady-state of the system. Unlike [1], we effectively choose the model M4 with initial conditions I2.…”

Section: Baseline Modelmentioning

confidence: 99%

“…This encompasses the absorption, distribution, metabolism, and excretion of drugs within the body (pharmacokinetics) and their impact on the subject's intrinsic metabolism (pharmacodynamics). Common applications of these models include the design of preclinical test campaigns, simulation studies on the effects of drugs [5], [6], or the investigation and derivation of (optimal) treatment schedules [7]- [9]. These rigorously validated models are crucial for predictive analytics and strategic decision making in drug development and clinical practice.…”

Section: Introductionmentioning

confidence: 99%

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Data-Driven Discovery of Feedback Mechanisms in Acute Myeloid Leukaemia: Alternatives to classical models using Deep Nonlinear Mixed Effect modeling and Symbolic Regression

Martensen,

Korsbo,

Ivaturi

et al. 2024

Preprint

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In pharmacometrics, developing and selecting models is crucial for quantitatively assessing drug-biological interactions, treatment planning, and gaining insights into underlying processes. These validated models are essential for predictive analytics and strategic decision-making in drug development and clinical practice. Unlike traditional methods, machine learning (ML) offers a data-driven alternative to conventional, first-principle approaches. This paper presents an automatic method to derive unknown or uncertain (sub)models using longitudinal, heterogeneous data. Initially, we employ deep nonlinear mixed effect (DeepNLME) to train a neural network as a universal approximator, which then generates a parameterized representation of the underlying process. Subsequently, we apply symbolic regression to identify a set of potential models expressed as equations. Within the study parameters, the proposed method outperforms the baseline models and demonstrates the validity of both the DeepNLME approach and the symbolic regression approach.

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Section: Baseline Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Data-Driven Discovery of Feedback Mechanisms in Acute Myeloid Leukaemia: Alternatives to classical models using Deep Nonlinear Mixed Effect modeling and Symbolic Regression

Martensen,

Korsbo,

Ivaturi

et al. 2024

Preprint

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Patient digital twins: an introduction based on a scoping review (Preprint)

Drummond,

Gonsard

2024

Preprint

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UNSTRUCTURED The concept of digital twins, widely adopted in industry, is entering healthcare. In this scoping review, we analysed definitions and characteristics of patient digital twins being developed for clinical use. Searching for studies claiming digital twin development/evaluation until August 2023, we identified 86 articles representing 80 unique claimed digital twins, nearly all (98%) in preclinical phases. From the analysis of definitions and characteristics, we propose to define patient digital twin as “a viewable digital replica of a patient, organ, or biological system that contains multidimensional, patient-specific information”. Two main forms were found: simulation digital twins using computational modelling of patient anatomy/physiology to run personalised outcome predictions and therapy evaluations, mostly for one-time assessments; and monitoring digital twins harnessing aggregated patient data for continuous risk/outcome forecasting over time and care optimisation. As patient digital twins rapidly emerge, the proposed definitions and subtypes offer a framework to guide research into realising the potential of these personalised, integrative technologies to advance clinical care.

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The Outcome of Outpatient Intermediate and High Dose Cytarabine Consolidation Chemotherapy in Patients with Acute Myeloid Leukemia. The Experience of King Fahad Specialist Hospital in Dammam, Saudi Arabia

Khalid Ahmed,

Alsaeed,

Kanfer

et al. 2024

J Stem Cell Ther Transplant

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Background: Adult patients with Acute Myeloid Leukemia (AML) have traditionally been hospitalized for the duration of intensive consolidation chemotherapy until blood count recovery to avoid complications. Recently, there has been a trend to shift the care of AML patients treated with intensive chemotherapy from inpatient to outpatient settings to reduce treatment costs and save beds. Methods and materials: A retrospective study of AML patients who received cytarabine consolidation chemotherapy between the 1st of August 2016 and the 31st of December 2023 at King Fahad Specialist Hospital in Dammam, Saudi Arabia was performed. Results: Over a period of 7 years and 4 months, 62 patients received a total of 127 cycles of intensive consolidation chemotherapy at outpatient setting. At diagnosis: 12 patients had extramedullary disease, and 17 patients had adverse cytogenetic abnormalities. Following the 127 cycles of chemotherapy, 38 episodes of febrile neutropenia were encountered, and 46 hospital admissions were required. No complications were encountered following 62.2% of the cycles of consolidation therapy and no early mortality due to intensive consolidation therapy was reported. Out of 62 patients studied, 36 patients underwent various forms of hematopoietic stem cell transplantation. Disease relapses were encountered in 24 patients and the 5-year incidence of relapse for the entire group of patients was 42%. The 5-year leukemia-free survival for the: entire study patients, transplanted patients, and non-transplanted patients were: 43%, 38%, and 50% respectively. The 5-year overall survival for the: entire study patients, transplanted patients, and non-transplanted patients were: 44%, 34%, and 65% respectively. At the end of follow-up: 37 patients (59.68%) were alive, 24 patients (38.71%) were dead, and the fate of 1 patient (1.61%) was unknown as the patient moved to another hospital. Conclusion: Administration of intensive consolidation chemotherapy for patients with AML at outpatient setting is safe, feasible, and cost-effective. The incidence of infectious complications was relatively low. No early treatment-related mortality due to intensive consolidation therapy was encountered. Outpatient administration of intensive consolidation therapy can save beds, reduce hospital costs, and is associated with short-term and long-term outcomes that are comparable to inpatient administration of consolidation therapy.

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AML consolidation therapy: timing matters

Cited by 3 publications

References 23 publications

Data-Driven Discovery of Feedback Mechanisms in Acute Myeloid Leukaemia: Alternatives to classical models using Deep Nonlinear Mixed Effect modeling and Symbolic Regression

Data-Driven Discovery of Feedback Mechanisms in Acute Myeloid Leukaemia: Alternatives to classical models using Deep Nonlinear Mixed Effect modeling and Symbolic Regression

Patient digital twins: an introduction based on a scoping review (Preprint)

The Outcome of Outpatient Intermediate and High Dose Cytarabine Consolidation Chemotherapy in Patients with Acute Myeloid Leukemia. The Experience of King Fahad Specialist Hospital in Dammam, Saudi Arabia

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