scholarly journals Adult acute lymphoblastic leukaemia: A study of prognostic features and response to treatment over a ten year period

1986 ◽  
Vol 53 (2) ◽  
pp. 175-180 ◽  
Author(s):  
R E Marcus ◽  
D Catovsky ◽  
S A Johnson ◽  
W M Gregory ◽  
J G Talavera ◽  
...  
Keyword(s):  
Acute Lymphoblastic Leukaemia ◽  
Lymphoblastic Leukaemia ◽  
Response To Treatment ◽  
Prognostic Features

scholarly journals The presence of CD56/CD16 in T-cell acute lymphoblastic leukaemia correlates with the expression of cytotoxic molecules and is associated with worse response to treatment

2009 ◽  
Vol 144 (2) ◽  
pp. 223-229 ◽  
Author(s):  
Leandro F. F. Dalmazzo ◽  
Rafael H. Jácomo ◽  
André F. Marinato ◽  
Lorena L. Figueiredo-Pontes ◽  
Renato L. G. Cunha ◽  
...  
Keyword(s):  
T Cell ◽  
Acute Lymphoblastic Leukaemia ◽  
Lymphoblastic Leukaemia ◽  
Response To Treatment ◽  
Cytotoxic Molecules

scholarly journals A study on the predictability of acute lymphoblastic leukaemia response to treatment using a hybrid oncosimulator

2017 ◽  
Vol 8 (1) ◽  
pp. 20160163 ◽  
Author(s):  
Eleftherios Ouzounoglou ◽  
Eleni Kolokotroni ◽  
Martin Stanulla ◽  
Georgios S. Stamatakos
Keyword(s):  
Acute Lymphoblastic Leukaemia ◽  
Treatment Response ◽  
Lymphoblastic Leukaemia ◽  
Mechanistic Model ◽  
Response Prediction ◽  
Response To Treatment ◽  
Computational Optimization ◽  
Model Parameterization ◽  
Number Of Patients ◽  
Parameter Values

Efficient use of Virtual Physiological Human (VPH)-type models for personalized treatment response prediction purposes requires a precise model parameterization. In the case where the available personalized data are not sufficient to fully determine the parameter values, an appropriate prediction task may be followed. This study, a hybrid combination of computational optimization and machine learning methods with an already developed mechanistic model called the acute lymphoblastic leukaemia (ALL) Oncosimulator which simulates ALL progression and treatment response is presented. These methods are used in order for the parameters of the model to be estimated for retrospective cases and to be predicted for prospective ones. The parameter value prediction is based on a regression model trained on retrospective cases. The proposed Hybrid ALL Oncosimulator system has been evaluated when predicting the pre-phase treatment outcome in ALL. This has been correctly achieved for a significant percentage of patient cases tested (approx. 70% of patients). Moreover, the system is capable of denying the classification of cases for which the results are not trustworthy enough. In that case, potentially misleading predictions for a number of patients are avoided, while the classification accuracy for the remaining patient cases further increases. The results obtained are particularly encouraging regarding the soundness of the proposed methodologies and their relevance to the process of achieving clinical applicability of the proposed Hybrid ALL Oncosimulator system and VPH models in general.

Predictive Value of Flow Cytometric MRD Analysis in Childhood Acute Lymphoblastic Leukaemia at the End of Remission Induction Therapy.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 4267-4267
Author(s):  
J. Motwani ◽  
J. Jesson ◽  
E. Sturch ◽  
L. Eyre ◽  
P. Short ◽  
...  
Keyword(s):  
Acute Lymphoblastic Leukaemia ◽  
Induction Therapy ◽  
Lymphoblastic Leukaemia ◽  
Residual Disease ◽  
Flow Cytometric Analysis ◽  
Treatment Protocol ◽  
Early Response ◽  
Response To Treatment ◽  
Remission Induction ◽  
Flow Cytometric

Abstract Patients with acute lymphoblastic leukaemia (ALL) in morphological remission may still have up to 1010 residual malignant cells. Detection of minimal residual disease (MRD) at the end of induction therapy allows better estimation of the leukaemic burden and can help selection of appropriate therapeutic strategies. Flow cytometric (FC) detection of MRD is based on the identification of immunophenotypic combinations expressed on leukaemic cells but not on normal hematopoietic cells - leukaemia associated immunophenotypes (LAIPs). We prospectively analysed bone marrow samples from 77 patients who presented with ALL to our unit between 1999–2003 and attained morphological remission. These patients were treated on a standard protocol. Multiparameter FC identification of LAIPs was performed at various time points, as dictated by the treatment protocol. Our results show that flow cytometric MRD at the end of induction therapy is an independent and the most significant predictor of relapse, both on univariate and multivariate analysis. The relapse risk was 4% if day 28 MRD was <0.01% and 50% if day 28 MRD was >0.01% (p<0.05). We conclude that flow cytometric based MRD assays can be used to assess early response to treatment and predict relapse in a similar way to molecular MRD analysis at the end of induction therapy. Flow cytometric analysis of MRD offers the advantages of being cheaper, more widely available and has quicker turnaround times.

Bone Marrow Necrosis in Acute Lymphoblastic Leukaemia

1987 ◽  
Vol 32 (6) ◽  
pp. 177-180 ◽  
Author(s):  
H.W. Habboush ◽  
I.M. Hann
Keyword(s):  
Bone Marrow ◽  
Complete Remission ◽  
Acute Lymphoblastic Leukaemia ◽  
Lymphoblastic Leukaemia ◽  
Bone Marrow Necrosis ◽  
Prognostic Features ◽  
Remission Duration ◽  
Prognostic Feature ◽  
Poor Prognostic Feature ◽  
Low Rate

Bone marrow necrosis, an uncommon finding in acute lymphoblastic leukaemia, has previously been regarded as a poor prognostic feature. It has been associated with difficulty in establishing the diagnosis, a low rate of remission as well as short remission duration. We report a case of bone marrow necrosis in a girl with acute lymphoblastic leukaemia and good prognostic features who attained complete remission uneventfully and will discuss previous reports of this association in the literature.

Acute leukaemias

2016 ◽  
pp. 699-753
Author(s):  
Adele K. Fielding ◽  
Charles G. Mullighan ◽  
Dieter Hoelzer ◽  
Eytan M. Stein ◽  
Ghada Zakout ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Acute Myeloid Leukaemia ◽  
Acute Lymphoblastic Leukaemia ◽  
Myeloid Leukaemia ◽  
Lymphoblastic Leukaemia ◽  
Treatment Strategies ◽  
Response To Treatment ◽  
Current Standard ◽  
Two Phases ◽  
Acute Myeloid

This chapter covers acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL), and includes information on prognostic factors, current standard of care, basic biology, epidemiology, clinical presentation, diagnosis, pathophysiology, aetiology, and management. Although the majority of patients with acute myeloid leukaemia (AML) achieve complete remission with induction chemotherapy, relapse after achievement of clinical remission remains the most critical clinical challenge facing AML patients and clinicians today, with a pressing need to improve prognostication. Prognostic factors in acute lymphoblastic leukaemia is to stratify patients into good- and poor-risk groups and to adapt different treatment strategies accordingly. There are principally two phases to evaluating prognostic factors; the first is the patient characteristics at diagnosis and the second is the response to treatment.

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