Background
Acute myeloid leukaemia (AML) is a tremendously heterogeneous clonal disorder of haemopoietic progenitor cells and is the most common malignant myeloid disorder in adults. Identified ...mutations from genomic data cannot provide information about their therapeutic significance without functional data. Hereby, we applied a pooled shRNA library screen to identify the activated signalling pathways essential for the survival of AML cells.
Methods
Mononuclear cells from seven karyotypically normal AML patients were separated from peripheral blood or bone marrow aspirate at diagnosis and transduced with a pooled shRNA library containing 27500 shRNAs targeting 5000 individual genes (Human Module 1, Decipher, Cellecta). The targeted genes were components of known signalling pathways. At 72h post transduction, 30% of the cells were stored for baseline measurements and the rest were co-cultured with HS-5 stromal cells for the selection period. DNA was then extracted and the shRNA barcodes were sequenced on the Illumina NextSeq platform. The frequency of barcode appearance after the selection period was compared to their prevalence at baseline to calculate the shRNA depletion. The shRNAs were filtered to identify those genes which had multiple shRNA meeting a threshold depletion.
Results
Our data analysis of the 7 AML samples identified various signalling pathways for each of these patients. These data support the notion of heterogeneity in AML. The top 100 depleted genes (with depletion in at least 3 shRNA per gene) in each patient were selected and compared. Our limited initial data showed there to be several activated signalling pathways for each AML sample indicating that inhibition of more than one gene or pathway might be required for efficiently suppressing these leukaemia cells.
Common targets: NOX1 was the most commonly identified therapeutic target among the screened patients being significantly depleted in AML cells from 5/7 patients. This is an important finding as there are available NOX1 inhibitors for treatment of colon cancers and can be investigated as a therapeutic option for acute myeloid leukaemia. The other most common targets were CDK5R1, DISC1, FSCN3, and PSMB7 which were found to be significantly depleted among 3 of the 7 screened patients. The merged data also showed 58 essential genes for AML cell survival were common in at least 2/7 patients. Using Enrichr the activated signalling pathways based on the top selected genes were identified. Various signalling pathways were observed for each patient showcasing the heterogeneity among AML patients (Figure 1). However, some signalling pathways were indeed common among multiple patients - with different genes being responsible for the activation of those pathways among the patients. The most common pathway was the metabolic pathway which was observed among the top 20 essential pathways in 6/7 patients. The JAK-STAT5 signalling pathway, purine metabolism and cAMP signalling pathway were also among the top 20 essential pathways in 3/7 patients while the following pathways: FoxO, PI3K-AKT, HIF-1, P53, Glucagon, and proteasome were observed in 2/7 patients. Identification of several essential survival pathways provides the opportunity to develop personalised therapy through combined targeting of more than one pathway.
Conclusion
The signalling pathways analysis using candidate genes from a pooled shRNA library screen showed patient-specific signalling pathways and also common pathways among these screened patients. Absence of a common gene among the screened patients further highlights the significance of personalised therapy in AML and the necessity of developing diagnostic tools to identify potential targets at diagnosis. Identification of crucial genes such as NOX1 (a gene known to have a role in the survival of leukemic stem cells) and other genes with known significance in the pathogenesis of AML supports the application of this method for identifying therapeutic targets at diagnosis or relapse.
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Knapper:Jazz: Other: Meeting and travel support; Daiichi Sankyo: Other: Meeting and travel support; Chroma Therapeutics: Research Funding; Celgene: Other: Meeting and travel support; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees. Apperley:Pfizer: Honoraria, Speakers Bureau; Incyte: Honoraria, Speakers Bureau; Novartis: Honoraria, Research Funding, Speakers Bureau; BMS: Honoraria, Speakers Bureau.
Introduction:
Ex-Vivo T-Cell Depletion (EX-TCD) has been shown, in multiple cohorts, to markedly decrease the incidence of graft-versus-host-disease (GvHD). This conditioning regime however, has been ...associated with high incidence of disease relapse. This single center, observational 34 year study, demonstrates outcomes of patients who underwent EX-TCD Allogeneic Hematopoietic Stem Cell Transplant (AHSCT) for Chronic Myeloid Leukemia (CML).
The total cohort consisted of 62 patients; all underwent EX-TCD AHSCT between 1984 and 1988. 58% (n=36) of the total cohort relapsed and 53% of relapsed patients (n=19) went on to have a second AHSCT (non-T-cell depleted) or donor lymphocyte infusion (DLI) with the remaining 47% (n=17) receiving conservative management. Given these differences in management, we used a competing risk model to adjust for the second AHCST or DLI on survival outcomes (using a second AHSCT or DLI as a competing risk).
The aim of this study was to determine from this cohort, which factors were associated with overall survival and survival following disease relapse.
Methods:
Within the relapsed cohort, univariate and multivariate standard Cox proportional hazard regression models were used to analyse various factors, which were hypothesized to be associated with survival. These included; age at relapse, gender and relapse grade. Competing risk model was used to analyse the contribution of a second AHSCT or DLI to survival.
Results:
The cohort underwent EX-TCD AHSCT for CML between 1984 and 1988. Age range of recipients was 15 to 53 years and all were sibling donors. At the 34 year follow-up mark, there was no difference in overall survival between those who relapsed (and received a second AHSCT or DLI) and those patients who did not relapse (p-value 0.86). Of the 26 % (n=16) of patients who remain alive, 50% (n=8) relapsed and received a second AHSCT or DLI. Most recent BCR-ABL polymerase chain reaction (PCR) confirm all patients remain in molecular remission (MR4 or below).
For the whole cohort, relapse was not affected by; donor gender, recipient age, CMV status, GvHD grade, duration of disease prior to AHSCT, Sokal score at diagnosis or duration to relapse following AHSCT. No parameter had a statistically significant association with survival or relapse, suggesting heterogeneity of disease could be an important consideration. 22 % (n=2) of the non-relapsed group and 17% (n=6) of the relapsed group developed acute GvHD. 37% (n= 23) of patients from the whole cohort developed chronic GvHD. Known causes of death included; relapse (36%, n=22), infection (16%, n=10), chronic GvHD (11%, n=7), other (8%, n=5). 26% (n=16) of patients remain alive today and 3% (n=2) were lost to follow-up.
Relapse was graded into 5 categories, mirroring monitoring methods at the time of relapse (prior to the development of BCR-ABL PCR). 6% (n=2) of patients developed a molecular relapse (grade 1), 58% (n=21) developed cytogenetic relapse (grade 2), 25% (n=9) developed hematological relapse (grade 3), 3% (n=1) relapsed as accelerated phase CML (grade 4) and 8% (n=3) relapsed with blast phase CML (grade 5). We divided patients into two groups; relapse grade <2 (cytogenetic or molecular relapse only) and grade >3 (hematological relapse or above). In a multivariate Cox proportional model, relapse grades were significantly associated with subsequent survival (log rank p-value 0.0057). Relapse grade >3 had an 11% increased hazard of death compared to relapse grade <2 (Hazard ratio (HR) 1.11; p-value 0.0068). 46% (6/13) of patients with relapse grade >3 underwent a second AHSCT or received DLI, compared with 56% (13/23) of patients with grade <2. In the competing risk analysis, those patients with relapsed grade <2 had a significantly improved survival with a second AHSCT or DLI (HR 1.34; 95% CI 1.06-13.70; p-value 0.03) whereas patients with a relapse grade >3 had no improvement in survival. (HR 0.96; 95% CI 0.93 to 6.8; p-value 0.07, Figure 1).
Conclusion:
In this cohort, EX-TCD was associated with high rates of relapse. However, patients remain alive from both the non-relapsed and relapsed cohorts. In the relapsed cohort, patients who received a second AHSCT or DLI had improved survival outcomes compared to conservative management. A competing risk analysis demonstrated that patients with lower relapse grades had a statistically significant improvement in survival after a second AHSCT or DLI.
Milojkovic:Incyte: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; BMS: Honoraria, Speakers Bureau; Pfizer: Honoraria, Speakers Bureau. Apperley:Novartis: Honoraria, Research Funding, Speakers Bureau; Incyte: Honoraria, Speakers Bureau; BMS: Honoraria, Speakers Bureau; Pfizer: Honoraria, Speakers Bureau.
Objectives
To describe the real‐world effectiveness and safety of bosutinib in patients with chronic myeloid leukemia (CML).
Methods
This was a multi‐center, retrospective, non‐interventional chart ...review study conducted in 10 hospitals in the United Kingdom and the Netherlands.
Results
Eighty‐seven patients were included. Bosutinib was the third‐line tyrosine kinase inhibitor (TKI) in 33 (38%) and fourth‐line in 44 (51%) patients. Median treatment duration was 15.6 months. Among 84 patients in chronic phase (CP) at baseline, 26 (31%) switched to bosutinib due to resistance and 57 (68%) due to intolerance to prior TKIs. Cumulative complete cytogenetic and major molecular response rates in CP patients were 67% and 55%, respectively. After a median follow‐up of 21.5 months, nine (11%) patients in CP died; estimated overall survival rates at 1 and 2 years postbosutinib initiation were 95% and 91%, respectively. Overall, 33/87 (38%) patients discontinued bosutinib due to either lack of efficacy/disease progression (17%), adverse events (14%), death (2%), or other reasons (5%). Eighty‐two (94%) patients experienced ≥1 adverse event possibly related to bosutinib, most commonly diarrhea (52%).
Conclusions
Bosutinib used in routine clinical practice in heavily pretreated patients with CML is an effective treatment for patients in CP and is generally tolerable.
Background: While chronic myeloid leukaemia (CML) originates from a single genetic aberration (BCR-ABL1) remarkably heterogeneity characterises treatment response and outcome. Most CML patients ...respond well to tyrosine kinase inhibitors (TKI), particularly 2nd generation (2G) TKI but a significant minority shows resistance and a proportion experience progression. At diagnosis there are currently no biomarkers for patients at higher risk of progression who could be treated with more effective treatment or be selected for BMT at an early stage of therapy. Such biomarkers may also provide useful prognostic information in addition to the most valid biomarker to date, the BCR-ABL1 IS ratio during the first 3-6-12 months of TKI therapy.
Aims: The aim of our study is to analyse a panel of mutations in epigenetic modifiers in pre-treatment CML-CP using Ion Torrent next-generation sequencing (IONT-NGS) to assess the prognostic value of potential mutations as novel biomarkers of response to 1st and 2G TKI and risk of progression to advanced phase disease.
Methods: 100 samples from untreated patients with newly diagnosed CML-CP were included in the study, 62 from patients treated frontline with imatinib (IM) and 38 with a 2G-TKI (31 dasatinib, 4 nilotinib, 3 bosutinib). The patients were classified as TKI responders (R) (34 IM, 22 2G-TKI) or non-responders (NR) (28 IM, 16 2G-TKI) based on BCR-ABL1 IS ratio at 3 months. DNA was extracted from CD34+ cells isolated from diagnostic samples, while DNA from T cells was used as constitutional non-leukemic control to exclude confounding germline mutations. Samples from healthy donors (n=14) and CML blast crisis (BC) (n=5) patients were used as negative and positive controls, respectively. We used a custom panel covering the coding region of 71 epigenetic enzymes. After sequencing data processing was performed excluding variants of low quality, common in the general population with minor allele frequency (maf) >1% or present in the healthy controls, we analysed the genomic data and integrated them with annotated clinical data.
Results: After using a variant reduction pipeline, 164 non-synonymous variants that affected protein function were identified: 52 somatic and 112 germline. The somatic mutations (including missense, nonsense, frameshift insertions and splice site variants) were confined to 30 genes, with ASXL1, IKZF1, CREBBP beingthe most frequently mutated (n=9, 7 and 4 respectively). The mutations were detected in 34/100 (34%) CML-CP patients (19/62 IM and 15/38 2G-TKI), in higher proportion in NR (19/44, 43%) compared to R (15/56, 27%; p=0.027). We next correlated the presence of mutations with overall survival (OS), TKI failure free survival (TFFS) and progression free survival (PFS). IM patients carrying somatic mutations demonstrated a poorer response to IM HR=2.1 (1-4.4 95% CI), p=0.05 and were more likely to progress to advanced phase HR=3.1 (1-9.4 95% CI), p=0.03 (Figure 1). Nonsense mutations in particular (in ASXL1, IKZF1, DNMT3A, EP300) were found in 4 IM NR vs 1 R and their presence led to poor OS HR= 6.1 (1.6-23 95% CI), p=0.002 and PFS HR= 5.4 (1.4-21 95% CI), p=0.006. As these were observed in 5 patients, further testing is required to corroborate this initial observation. Multivariate analysis revealed that both increased Sokal score and occurrence of somatic mutations negatively influenced outcome: somatic mutations detected in 6/24 low and in 8/13 high Sokal IM patients were associated with worse OS and PFS compared to unmutated patients with the same Sokal score. Among 38 patients treated with 2G-TKI, neither somatic mutations (including nonsense variants) nor combination of somatic mutations with Sokal score had any influence on OS, TFFS, PFS, neither did the presence of germline mutations in either IM or 2G-TKI patients.
Summary/Conclusion: Somatic mutations identified using IONT-NGS on 71 epigenetic modifiers potentially predict 1st generation (IM) patient poor survival, drug failure and progression to advance phase disease. However, the more effective therapeutic effect of 2G-TKI seems to overcome the poor prognostic influence of such mutations though further validation on larger cohort of patients may be required to validate preliminary data. Our results suggest that occurrence of somatic mutations at diagnosis have the potential to identify patients who would benefit from upfront treatment with 2G-TKI.
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Apperley:Incyte: Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Ariad: Honoraria, Speakers Bureau; Pfizer: Honoraria, Speakers Bureau; Bristol Myers Squibb: Honoraria, Speakers Bureau.
Introduction: The survival of patients with chronic myeloid leukaemia (CML) treated with tyrosine kinase inhibitors (TKI) is now almost comparable to that of healthy population. Consequently, the ...financial and personal costs of life-long treatment, molecular monitoring and hospital visits have also increased. The ELN 2013 guidelines recommend molecular monitoring by BCR-ABL1\ABL1 quantitative reverse transcriptase polymerase chain reaction assay (RT-qPCR) every 3 to 6 months after the achievement of the major molecular response. We used our comprehensive institutional database of patients with CML to determine whether there is a group in whom the response is sufficiently deep and sustained so that they might reduce their frequency of hospital interactions.
Methods: We identified patients (pts) who had received TKI and reached a sustained MR4 (sMR4) and/or MR3 (sMR3) defined as a RT-qPCR <0.01% and <0.1% IS, respectively, maintained for at least one year. Patients who had received any chemotherapy (except from hydroxycarbamide), autologous or allogeneic transplants were excluded.
We defined loss of MR3 and MR4 as RT-qPCRs ≥0.1% and ≥0.01%, respectively, in two or more consecutive measurements. We calculated the median time to reach sMR3 and sMR4 from the date of starting TKI until the achievement of the first date of RT-qPCR <0.1% and <0.01% IS, respectively, maintained for at least 1 year. Cumulative incidence (CI) of loss of MR3 and MR4 after the first year of sustained response were calculated using the CI function. Patients were censored at last follow-up if on treatment or at the date of their first documented TKI interruption longer than 7 days.
Results: 412 pts reached a sMR3 at any time of their TKI therapy (Table). Of these, 315 pts further improved their response to sMR4. The median time to achievement of sMR3 was 427 days (range 54-5533) and to sMR4 was 948 days (range 100-5164). Furthermore, pts who achieved sMR4 had achieved sMR3 more rapidly (median time 385 days vs 729 days, respectively). The median follow-up after the achievement of sMR3 was 1634 days (range 171-4391) for pts achieving MR3 only and 3115 days (range 199-5762) for those who reached sMR4. At last follow-up 42/412 pts had lost sMR3, 20 of whom had never achieved sMR4: only 1 of these 20 was on standard dose (SD) TKI. Of pts in sMR4, 54 lost sMR4 (including 22 who also lost sMR3). None of these 22 was on SD TKI at the time of loss of response. The TKI status at the time of loss of sMR3 or sMR4 is given in Figure 1. The CI of loss of sMR3 was 0.7%, 3.9% and 5.9% at 2, 5 and 10 years respectively (Figure 2A). The CI of loss of sMR4 was 1.4%, 6.6% and 14.8% at 2, 5 and 10 years respectively (Figure 2B). The CI of loss of sMR3 in those pts who had reached a sMR4 was 0%, 2.8% and 4.1% at 2, 5 and 10 years respectively (Figure 2C). After a median follow-up of 1172 days (range, 154-4422) from loss of sMR3, 3 of 42 pts had also lost CCyR. One of these lately progressed to blast crisis six years after starting first line Nilotinib and 1705 days after achieving sMR4, while on a reduced Nilotinib dose. One patient of the 97 who achieved only sMR3 but not sMR4 lost sMR3 whilst on SD TKI. None of the pts who lost sMR3 from sMR4 were on SD TKI at the time of loss. Although loss of sMR4 was seen in 4 pts on SD TKI, all 4 had previously received higher doses of TKI after evidence of resistance.
Conclusion: We chose loss of MR3 as our outcome as this is currently regarded as the measure of failure in trials of TKI discontinuation. We have shown that loss of MR3 remains unusual in pts with CML who have achieved deep and sustained responses, particularly in those who remain on standard dose TKI, who have not demonstrated prior resistance and who are known to be compliant. We are reluctant to suggest that sMR3 is a ‘safe haven’ for deep response, first because one such patient lost sMR3 on SD TKI and second because we have demonstrated that achievement of MR3 is slower in those destined to achieve only sMR3 and not sMR4, suggesting less responsive disease. We do however consider that sMR4 is a level of response that may justify less frequent monitoring in pts who are not considering a trial of treatment discontinuation.
If applied to clinical practise, our findings may have considerable impact on patient perception of disease and quality of life. Furthermore, it could provide financial savings.
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Milojkovic:Novartis: Consultancy, Honoraria; ARIAD: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Incyte: Honoraria, Speakers Bureau; Pfizer: Consultancy, Honoraria. Foroni:Incyte: Honoraria, Research Funding; Ariad: Honoraria, Research Funding. Apperley:Bristol Myers Squibb: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Ariad: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Therakos: Honoraria; Novartis: Consultancy, Honoraria, Other: travel, accommodations, expenses , Research Funding, Speakers Bureau; Incyte: Honoraria; Sun Pharma: Honoraria.
Background: Imatinib remains the most frequently prescribed tyrosine kinase inhibitor (TKI) for patients (pts) newly diagnosed with chronic myeloid leukemia (CML). However, 40-45% patients need to ...switch to alternative drug because of resistance (20-25%) or intolerance (20%). The mechanism of resistance, although unknown in the majority of cases, is caused by the presence of BCR-ABL1 tyrosine kinase domain (TKD) mutations in approximately 20-30% of pts. Phase II clinical studies of second- and third-generation TKIs (2GTKI and 3GTKI) in imatinib resistance have shown that approximately 50% of pts achieve durable cytogenetic and molecular responses. The differential sensitivities of TKD mutations to the various TKI now allow ‘tailored‘-therapy if mutations are present. We report the long-term outcome of pts who developed imatinib resistance.
Methods: From our institutional database we identified pts who failed imatinib at 400mg daily as first-line therapy for CML in chronic phase (CP). Because the definitions of optimal response and resistance have changed over time, we confined our analysis to those pts whose therapy was changed because of resistance and who had TKD mutation testing at the time of resistance. We further stratified pts according to their reverse transcriptase polymerase chain reaction assay (RT-qPCR) at the time of resistance into three groups: group 1: RT-qPCR >0.1% <1%; group 2: 1-10%; group 3: >10%.
Overall survival (OS) and progression-free survival (PFS) were estimated using the Kaplan-Mayer function and the outcomes between groups were investigated with long-rank test. The OS was calculated from the date of diagnosis till the date of last contact; PFS, defined as progression to accelerated or blastic phases or death without progression, was calculated from the imatinib start date till the date of last contact.
Results: 119 pts satisfied our eligibility criteria: baseline characteristics and outcome are shown in the Table 1.
The median follow-up from start of imatinib first-line was 110 months (range 18-230). Thirty-one (26%) pts received non-TKI therapy after imatinib failure, of whom 26 (21.8%) received allogeneic transplant. Fifteen pts (12.6%) died (9 of CML progression, 5 due to transplant complications and 1 of mesothelioma). Of the 119 pts, 24 had a TKD mutation (Table 2) at the time of imatinib resistance. Thirteen of 51 pts (25.5%) diagnosed from 2007 onwards had a TKD mutation at time resistance, compared to 11/68 (16.2%) diagnosed between 2000 and 2006 (p=0.25, Chi-squared test). Also, looking at the number of pts mutated at any time during the follow-up, there was no statistically significant difference among the different years of diagnosis (18 out of 51, 35.3%, from 2007 onwards compared to 14 out of 68, 20.9%, before 2007; p= 0.097, Chi-squared test).
The 10-year estimated OS and PFS for the entire cohort were 86.2% and 74.5%, respectively. At last follow-up, 85 of 104 (81.7%) surviving pts were in MR3 or deeper response. OS and PFS were not influenced by TKD mutation status, transcript type or year of diagnosis. However, outcome was affected by the level of RT-qPCR at the time of resistance: 10-year OS was 100%, 86.6% and 70.9% for groups 1, 2 and 3 respectively (p = 0.004); 10-year PFS was 97.1%, 86.6% and 70.9% for group 1, 2 and 3 respectively (p < 0.001).
In order to understand whether the importance of the molecular response was valid across different treatment periods, we further analysed the cohort after splitting it in pts diagnosed before and after 2007. Interestingly, the difference was no longer significant for pts diagnosed more recently, where the 10-year OS was 100%, 88.9% and 83.1% (p = 0.28) and the 10-year PFS was 90.9%, 90% and 71.1% (p = 0.082), respectively, for each of the above mentioned RT-qPCR groups (Figure).
Conclusion: our study has found an unexpected high OS in pts failing imatinib front-line for resistance. Mutational status did not impact OS and PFS. After stratifying pts according to the degree of response to imatinib, it seems that the ready availability of 2GTKI and 3TGKI in the more recent years could be responsible for the positive effect on the outcome, rescuing pts with a higher grade of resistance from progression and death. Finally, our results confirm prior observations that the achievement of complete cytogenetic response on imatinib (RT-qPCR <1%IS) confers an excellent outcome, irrespective of subsequent therapy.
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Shacham Abulafia:Ariad: Other: recieved grant from ariad. Milojkovic:Novartis: Consultancy, Honoraria; ARIAD: Consultancy, Honoraria; Incyte: Honoraria, Speakers Bureau; Pfizer: Consultancy, Honoraria; BMS: Consultancy, Honoraria. Foroni:Incyte: Honoraria, Research Funding; Ariad: Honoraria, Research Funding. Apperley:Therakos: Honoraria; Incyte: Honoraria; Novartis: Consultancy, Honoraria, Other: travel, accommodations, expenses , Research Funding, Speakers Bureau; Bristol Myers Squibb: Consultancy, Honoraria, Research Funding; Ariad: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Sun Pharma: Honoraria.
Background: Treatment free remission (TFR) is now a realistic goal of treatment for CML. Approximately 50% of patients (pts) who discontinue tyrosine kinase inhibitors (TKI) after achieving deep ...molecular responses (DMR) are able to remain off treatment without losing major molecular response (MR3). Data from the largest available TKI stopping trial, EURO-SKI, showed that the most important variable associated with prolonged TFR is the duration of DMR. However, to date no clinical tool exists to guide clinicians and patients in predicting the likelihood of success of TFR attempt.
Methods: We performed a retrospective analysis of clinical data from 172 pts with CML in whom treatment was discontinued in 6 hospital centres in order to identify factors associated with TFR. Data analysis started with a training set (TS) derived from pts treated at a single centre which was then validated on a validation set (VS) derived from the 5 other centres. Eligibility criteria included diagnosis of CML in chronic phase, a minimum duration of treatment with TKI of 3 years and discontinuation of TKI after achievement of confirmed ≥MR4. Patients diagnosed in accelerated phase CML and/or who underwent prior allogeneic stem cell transplant were excluded. Kaplan-Meier method was used for univariate analysis, with log-rank test for group comparison. A Cox proportional hazards model was employed with the purpose of choosing the most influential prognostic predictors on the probability of TFR in MR3 (pTFR3) and TFR in MR4 (pTFR4) on the TS. Variables with a p-value ≤0.1 entered in the multivariate analysis (MVA). Proportional hazard assumptions were tested for the final model. A prognostic TFR score was built from the combination of the predictors identified by the Cox model and validated on the VS.
Results: The TS included 118 pts, while the VS 54 pts (Table 1). In the TS, the 2-year pTFR3 was 67.4% (95% CI 66.5-68.3%) and the 2-y pTFR4 was 56.8% (95% CI, 55.9-57.7%). The median time to MR3 loss was 3.8 months (range 1-31), and for MR4 loss was 3.2 months (range 0.8-24.5). After loss of MR4, the 1-year probability of MR3 loss was 77% (95% CI, 70.8-73.2%). However, 10 pts (8.5%) resumed TKI after MR4 loss and were not evaluable for time to loss of MR3. In univariate analysis, the variables most significantly associated with higher pTFR3 and pTFR4 were age at diagnosis >40 years (p=0.029 and p=0.002), absence of previous TKI resistance (p=0.003 and p= 0.068), longer duration of MR4 (p=0.003 and p<0.0001) and ≥MR4.5 at stopping (p=0.026 and p= 0.004). Variables entered into the MVA were age at diagnosis, BCR-ABL1 transcript type, Sokal score, dose of TKI at stopping, previous TKI resistance, duration of MR4 at stopping, depth of response at stopping. The Cox model suggested the inclusion of the following variables, for both pTFR3 and pTFR4: duration of MR4, previous TKI resistance, age at diagnosis and transcript type. Using these variables we developed a predictive score (Figure 1a), which was able to identify a good risk population (2-y pTFR3 81.8%, 2-y pTFR4 80%); intermediate (66.6% and 61.5%) and poor risk (42.3% and 30.8%) (overall log-rank test p=0.00092 and p <0.0001 for pTFR3 and pTFR4, respectively)(Figure 1b). The score was tested on the VS of 54 pts. In this population, the overall 2-y pTFR3 and pTFR4 were 61.3% (95% CI, 59.8-62.7%) and 42.6% (95% CI, 41.2-44%), respectively. Despite the small sample size, our score was still able to predict different 2-y TFR probabilities (Figure 1c) in the three risk groups. Of the pts who lost MR3 in the TS (n=39), 37 regained ≥MR3 after resuming TKI; 1 patient did not restart TKI and died from an unrelated cause; 1 patient had only 2 months follow-up after TKI resumption. In the VS, 15 of 21 pts losing MR3 achieved ≥MR3 again after TKI resumption; 3 pts had a follow-up <3 months after MR3 loss, 2 were lost to follow-up and 1 had not yet re-gained MR3 6 months after restarting TKI. In both cohorts no case of disease progression had occurred at last follow-up.
Conclusions:This retrospective study confirms the safety of TFR attempt and identifies variables strongly associated with prolonged TFR. The resulting predictive score presented here, if validated in larger patient cohorts, might help in tailoring the choice of TKI discontinuation to the individual patient. Also, most pts who lose MR4 inevitably lose MR3, suggesting the importance of a more intense monitoring strategy in this subgroup.
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Claudiani:Pfizer: Honoraria; Incyte: Honoraria. Byrne:Ariad/Incyte: Honoraria, Speakers Bureau. Rothwell:Incyte: Speakers Bureau; Novartis: Honoraria, Other: advisory board; Pfizer: Speakers Bureau. Copland:Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Astellas: Honoraria, Speakers Bureau; Cyclacel: Research Funding; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Clark:Ariad/Incyte: Honoraria; Pfizer: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Milojkovic:BMS: Honoraria, Speakers Bureau; Pfizer: Honoraria, Speakers Bureau; Incyte: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau. Apperley:Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.
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