Abstract
Introduction:
Comorbidities have a significant impact on the prognosis and survival of patients with MDS (Naqvi et al, JCO. 2011). Separately, CHIP associated mutations (TET2, DNMT3A, JAK2 and ASXL1) have also been noted to be associated with comorbidities, particularly atherosclerotic heart disease (Ebert et al. NEJM. 2017). This association is however not well studied in patients in MDS. The objective of this study was to determine the association of these CHIP mutations including TP53 with comorbidities in patients with MDS.
Patients and Methods:
We conducted a retrospective analysis of 566 consecutive patients with MDS who presented to MD Anderson Cancer Center from August 2013 to December 2016. The Adult Comorbidity Evaluation-27 (ACE-27) scale was used to assess the severity of comorbid conditions. Data on the demographics and International Prognostic Scoring System Revised (IPSS-R) were collected. We used next-generation sequencing to detect the presence of CHIP mutations in bone marrow samples. Spearman's correlation coefficient was used to assess the association between CHIP associated gene mutations as binary variables by the presence of mutations, and continuous variables by variant allele frequency (VAF) and comorbidities. Kaplan-Meier methods and Cox regression were used to assess survival. A prognostic model incorporating the IPSS-R, comorbidities by ACE-27 and TP53 mutation status (I-RAT) was developed to predict survival.
Results:
Of the 566 patients included in this study, 66% were male, and 82% were white; median age at presentation was 69 years (range: 22-93). A total of 334 (58%) patients had an IPSS-R of Intermediate, low and very low; complex karyotype was noted in 128 (23%) patients. The ACE-27 comorbidity scores were as follows: none, 101 (17%); mild, 214 (38%); moderate, 146 (26%); and severe, 105 (19%). Mutations in DNMT3A, ASXL1, TET2, JAK2 and TP53 were noted in 9%, 18%, 20%, 2% and 21% patients respectively. Two hundred and fifty (44%) MDS patients had no CHIP-associated mutations. With respect to the cardiovascular system, patients harboring DNMT3A were noted to have a higher incidence of myocardial infarction than those without DNMT3A mutation (14% vs 6%; p= 0.03). As expected, patients with a JAK2 mutation had higher number of venous thromboembolic events (18% vs 4%; p= 0.013). TET2, ASXL1 and TP53 mutations however were not associated with increased cardiovascular events in our patients. TP53 mutations were highly associated with history of prior malignancy: solid tumors, 44% vs 21%; p= <0.001; myeloma, 9% vs 3%; p= 0.003; lymphoma, 17% vs 3%; p= <0.001. Patients with respiratory disease and diabetes mellitus were also noted to most likely harbor TP53 mutations: 16% vs 9%; p= 0.016 and 27% vs 16%; p= 0.009 respectively. Patients with ASXL1 were less likely to have prior malignancy (18% vs 27%; p= 0.057). Despite this association, the level of VAF of DNMT3A, JAK2, ASXL1 and TP53 were only weakly associated with the respective comorbidities. A trend towards higher ACE-27 comorbidity scores and increased number of mutations was noted (p= 0.075). CHIP-associated mutations were associated with higher ACE-27 comorbidity scores (p=0.036) and an overall inferior median survival (26.1 months versus 65.8 months; p=0.005). A final prognostic model including IPSS-R, ACE-27 score and TP53 mutation (I-RAT) predicted median survival of 66, 16, and 12 months for intermediate, high and very high-risk groups, respectively (p<0.001). Median survival for very low and low-risk groups was not reached.
Conclusion:
Patients with MDS harboring CHIP associated mutations, mainly DNMT3A, have a higher incidence of myocardial infarction. This advocates for early intervention and optimization of the modifiable cardiovascular risk factors, such as hypertension, obesity and hyperlipidemia in patients with CHIP and MDS. Additionally incorporating IPSS-R with ACE-27 comorbidity score and TP53 mutation (I-RAT model) further improves the prediction for survival in patients with MDS.
Sasaki:Otsuka Pharmaceutical: Honoraria. Short:Takeda Oncology: Consultancy. Jabbour:Novartis: Research Funding; Takeda: Consultancy, Research Funding; Abbvie: Research Funding; Pfizer: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding. Ravandi:Amgen: Honoraria, Research Funding, Speakers Bureau; Abbvie: Research Funding; Orsenix: Honoraria; Astellas Pharmaceuticals: Consultancy, Honoraria; Macrogenix: Honoraria, Research Funding; Xencor: Research Funding; Astellas Pharmaceuticals: Consultancy, Honoraria; Seattle Genetics: Research Funding; Jazz: Honoraria; Bristol-Myers Squibb: Research Funding; Abbvie: Research Funding; Bristol-Myers Squibb: Research Funding; Amgen: Honoraria, Research Funding, Speakers Bureau; Sunesis: Honoraria; Sunesis: Honoraria; Orsenix: Honoraria; Seattle Genetics: Research Funding; Macrogenix: Honoraria, Research Funding; Xencor: Research Funding; Jazz: Honoraria. Kadia:Pfizer: Consultancy, Research Funding; BMS: Research Funding; Amgen: Consultancy, Research Funding; Novartis: Consultancy; Jazz: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy; Takeda: Consultancy; Takeda: Consultancy; Abbvie: Consultancy; Celgene: Research Funding; Celgene: Research Funding; BMS: Research Funding; Amgen: Consultancy, Research Funding; Jazz: Consultancy, Research Funding; Abbvie: Consultancy.
Author notes
Asterisk with author names denotes non-ASH members.