Slower early response to treatment and distinct expression profile of childhood high hyperdiploid acute lymphoblastic leukaemia with DNA index < 1.16

2016 ◽  
Vol 55 (9) ◽  
pp. 727-737 ◽  
Author(s):  
Marketa Zaliova ◽  
Lenka Hovorkova ◽  
Martina Vaskova ◽  
Ondrej Hrusak ◽  
Jan Stary ◽  
...  
Keyword(s):  
Acute Lymphoblastic Leukaemia ◽  
Expression Profile ◽  
Lymphoblastic Leukaemia ◽  
Early Response ◽  
Response To Treatment ◽  
Dna Index

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.

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.

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

Use of Morphological Early Response Data to Predict Relapse in Teenage and Young Adult (TYA) Patients with Acute Lymphoblastic Leukaemia (ALL)

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1415-1415
Author(s):  
Caroline L Furness ◽  
Clare Rowntree ◽  
Ajay J. Vora ◽  
Amy A Kirkwood ◽  
Christopher Mitchell ◽  
...  
Keyword(s):  
Young Adult ◽  
High Risk ◽  
Acute Lymphoblastic Leukaemia ◽  
Lymphoblastic Leukaemia ◽  
False Positive ◽  
Risk Group ◽  
Early Response ◽  
Alternative Methods ◽  
Prognosis Group ◽  
Time To Relapse

Abstract Introduction Treatment outcomes for teenage and young adult (TYA) patients with Acute Lymphoblastic Leukaemia (ALL) lag behind those of younger patients when treated on equivalent protocols, with higher rates of toxicity and relapse reported for those aged >10 years. Outcomes of relapsed ALL are poor so more accurate identification of those destined to relapse is required. Whilst minimal residual disease (MRD) is a powerful tool to predict those at low risk and in whom treatment can be de-escalated, improved strategies are required for early identification of high risk patients. This study aimed to determine if the morphological early response assessment could be used as a predictor of relapse in TYA patients with ALL. Methods All patients treated on the national prospective UKALL2003 trial aged 10 - 24 years who had not relapsed by day 35 (i.e. could potentially have treatment escalated) were included in the study. Early response in patients aged >10 years was defined as percentage of blasts by morphology at day 8: rapid early responders had ≤ 25% blasts and slow early responders >25% blasts. We analysed the following patient characteristics which were previously associated with differential outcomes: age at diagnosis, presenting white cell count, rapid or slow early response (RER or SER); MRD status at day 28; immunophenotype (B/T/other) and cytogenetic risk group (high risk, good risk, poor risk, T-ALL, other). Cox regression was used to assess the association of these factors with time to relapse and logistic regression (LR) was used to assess their association with relapse by the end of treatment (EOT: 2.5 years for girls and 3.5 years for boys). Using backwards selection (cut off for inclusion: p=0.1) a multivariable LR model was established and a receiver operating characteristic curve (ROC) was used to assess how well it could predict relapse before the EOT. Results 820 consecutive patients were included in the analysis of whom 597 were aged 10 - 15 years and 223 were aged 16 - 24 years. 332 patients were classified as MRD high risk and 184 as SER on the basis of morphology. RER was significantly associated with a reduced risk of relapse even after adjustment for other factors including MRD, age, WBC and risk status (Hazard Ratio (HR) 0.64 (95% CI 0.42 - 0.97, p<0.001). 697 patients with an outcome available at the EOT could be included in the LR analysis. The final multivariable model included day 28 MRD, day 8 response, age, WBC and cytogenetic risk group. The predictor generated by this model gives a ROC area under the curve of 81.2% (95% CI: 76.8 - 85.6) but there were no cut points which resulted in acceptable detection (DR) and false positive rates (FPR). As the intervention for the poor prognosis group would potentially include an allogeneic transplant with associated high mortality and morbidity a low FPR would be key to clinical utility. In order to achieve a clinically useful DR of 79.5% we would have to accept a false positive rate of 30.5%. As only 11% pf patients relapsed by EOT but 36% of patients fell into our bad prognosis group this would mean that for every 100 patients, ~27 would be transplanted unnecessarily. In the subgroup analysis of those aged 16 - 24 early response was not significantly associated with either time to relapse (HR RER: 0.74 (0.36 - 1.51, p = 0.4) or relapse by the EOT (Odds ratio RER: 0.63 (0.26 - 1.49, p =0.3) Conclusions Slow early response is significantly associated with both time to relapse and relapse by EOT in this patient cohort aged 10 - 24 years and this effect is independent of other prognostic factors including MRD. However, even when over-fit the prognostic model generated (which included SER) resulted in FPRs which were too high to be clinically useful. Future work should focus on novel alternative methods of relapse risk prediction for the adolescent patient with ALL. Figure 1. Figure 1. Disclosures No relevant conflicts of interest to declare.

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