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Modelling Predictors of Molecular Response to Frontline Imatinib for Patients with Chronic Myeloid Leukaemia.

ABSTRACT: BACKGROUND:Treatment of patients with chronic myeloid leukaemia (CML) has become increasingly difficult in recent years due to the variety of treatment options available and challenge deciding on the most appropriate treatment strategy for an individual patient. To facilitate the treatment strategy decision, disease assessment should involve molecular response to initial treatment for an individual patient. Patients predicted not to achieve major molecular response (MMR) at 24 months to frontline imatinib may be better treated with alternative frontline therapies, such as nilotinib or dasatinib. The aims of this study were to i) understand the clinical prediction 'rules' for predicting MMR at 24 months for CML patients treated with imatinib using clinical, molecular, and cell count observations (predictive factors collected at diagnosis and categorised based on available knowledge) and ii) develop a predictive model for CML treatment management. This predictive model was developed, based on CML patients undergoing imatinib therapy enrolled in the TIDEL II clinical trial with an experimentally identified achieving MMR group and non-achieving MMR group, by addressing the challenge as a machine learning problem. The recommended model was validated externally using an independent data set from King Faisal Specialist Hospital and Research Centre, Saudi Arabia. PRINCIPLE FINDINGS:The common prognostic scores yielded similar sensitivity performance in testing and validation datasets and are therefore good predictors of the positive group. The G-mean and F-score values in our models outperformed the common prognostic scores in testing and validation datasets and are therefore good predictors for both the positive and negative groups. Furthermore, a high PPV above 65% indicated that our models are appropriate for making decisions at diagnosis and pre-therapy. Study limitations include that prior knowledge may change based on varying expert opinions; hence, representing the category boundaries of each predictive factor could dramatically change performance of the models.

SUBMITTER: Banjar H

PROVIDER: S-EPMC5207707 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Modelling Predictors of Molecular Response to Frontline Imatinib for Patients with Chronic Myeloid Leukaemia.

Banjar Haneen H Ranasinghe Damith D Brown Fred F Adelson David D Kroger Trent T Leclercq Tamara T White Deborah D Hughes Timothy T Chaudhri Naeem N

PloS one 20170103 1

<h4>Background</h4>Treatment of patients with chronic myeloid leukaemia (CML) has become increasingly difficult in recent years due to the variety of treatment options available and challenge deciding on the most appropriate treatment strategy for an individual patient. To facilitate the treatment strategy decision, disease assessment should involve molecular response to initial treatment for an individual patient. Patients predicted not to achieve major molecular response (MMR) at 24 months to ...[more]

PMID: 28045960

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Project description:BackgroundThe FAS mediated apoptosis pathway involving the FAS and FASL genes plays a crucial role in the regulation of apoptotic cell death and imatinib mesylate (IM) mechanism of action. Promoter polymorphisms FAS-670 A>G and FAS-844 T>C which alter the transcriptional activity of these genes may grant a risk to develop cancer and revamp the drug activities towards the cancer cell. We investigated the association of these two polymorphisms with the susceptibility risk and IM treatment response in Malaysian chronic myeloid leukaemia (CML) patients.MethodsThis is a retrospective study, which included 93 CML patients and 98 controls. The polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) method was used to genotype the FAS and FASL polymorphisms. Data nanlysis was done using SPSS Version 22. The associations of the genotypes with susceptibility risk and IM response in CML patients were assessed by means of logistic regression analysis and deriving odds ratio with 95% CI.ResultsWe observed a significant association between FASL-844T>C polymorphism and CML susceptibility risk and IM response. Variant C allele and FASL-844 CC variant genotype carriers had significantly higher risk for CML susceptibility (OR 1.756, CI 1.163-2.652, p=0.007 and OR 2.261, CI 1.013-5.047, p=0.047 respectively). Conversely, the heterozygous genotype FASL-844 TC conferred lower risk for CML susceptibility (OR 0.379, CI 0.176-0.816, p=0.013). The heterozygous and homozygous variant genotypes and variant C alleles were found to confer a lower risk for the development of IM resistance with OR 0.129 (95% CI: 0.034-0.489 p=0.003), OR 0.257 (95% CI: 0.081-0.818, p=0.021), and OR 0.486 (95% CI: 0.262-0.899, p=0.021) respectively. We also found that FAS-670 A>G polymorphism was not associated with CML susceptibility risk or IM response.ConclusionThe genetic polymorphism FASL-844 T>C may contribute to the CML susceptibility risk and also IM treatment response in CML patients. Accodringly, it may be useful as a biomarker for predicting CML susceptibility risk and IM resistance.

Project description:Several tyrosine kinase inhibitors (TKIs) are available for treatment of patients with chronic myeloid leukaemia in chronic phase (CML-CP). We analysed long-term molecular and cytogenetic response and survival outcomes for four TKI modalities used as frontline therapy for CML-CP.In a retrospective cohort analysis, we included data from patients with CML-CP treated in prospective clinical trials with frontline TKI modalities at a single institution between July 31, 2000, and Sept 10, 2013. The main aim of the study was to determine whether achievement of complete cytogenetic response or major molecular response had similar prognostic implications irrespective of the frontline TKI modality used. We analysed each TKI modality for response assessment and analysed survival endpoints (event-free, failure-free, transformation-free, and overall survival) with the Kaplan-Meier method. Univariate and multivariate analyses were done with Cox proportional hazard regression.Our analysis included 482 patients who were treated with imatinib 400 mg daily (n=68), imatinib 800 mg daily (n=200), dasatinib 50 mg twice daily or 100 mg daily (n=106), or nilotinib 400 mg twice daily (n=108). More patients receiving imatinib 800 mg or second-generation TKIs (ie, dasatinib or nilotinib) achieved complete cytogenetic response (58 [87%] of 67 for imatinib 400 mg vs 180 [90%] of 199 for imatinib 800 mg, vs 100 [96%] of 104 for dasatinib vs 99 [93%] of 107 for nilotinib), major molecular response (51 [76%] vs 171 [86%] vs 93 [90%] vs 97 [91%]), and 4·5 log or higher reduction in BCR-ABL transcripts (MR(4·5) response 38 [57%] vs 148 [74%] vs 76 [71%] vs 76 [71%]). This finding was consistent over time (3-60 months). 5-year event free survival significantly differed between the imatinib 400 mg group and the other TKI groups (imatinib 800 mg p=0·029, dasatinib p=0·003, nilotinib p=0·031). There was no significant difference in 5-year failure-free survival (p=0·32, p=0·075, p=0·332), transformation-free survival (p=0·053, p=0·038, p=0·493), or overall survival (p=0·563, p=0·162, p=0·981). Multivariate analysis showed that therapy with imatinib 800 mg (HR 0·51, 95% CI 0·29-0·88, p=0·016), dasatinib (0·28, 0·12-0·66, p=0·004), or nilotinib (0·42, 0·20-0·89, p=0·024) predicted for better event-free survival compared with imatinib 400 mg, but that failure-free, transformation-free, and overall survival were similar irrespective of the TKI used. 28 (41%) patients receiving imatinib 400 mg, 85 (43%) receiving imatinib 800 mg, 23 (21%) receiving dasatinib, and 27 (25%) receiving nilotinib discontinued treatment for any reason.Treatment with imatinib 800 mg or the second-generation TKIs dasatinib or nilotinib resulted in superior and deeper responses than did standard-dose imatinib, which were maintained after 5 years of follow-up. Results with imatinib 800 mg were similar to those with second-generation TKIs, although more patients discontinued therapy.MD Anderson Cancer Center, National Cancer Institute.

Dataset Information

Modelling Predictors of Molecular Response to Frontline Imatinib for Patients with Chronic Myeloid Leukaemia.

Publications

Modelling Predictors of Molecular Response to Frontline Imatinib for Patients with Chronic Myeloid Leukaemia.

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