Race and ethnic differences affect the disease characteristics and clinical outcomes in many tumors, including acute myeloid leukemia (Byrne et al. AJCO, 2011). While earlier population-based studies reported no significant impact of race on survival outcomes in myelodysplastic syndromes (MDS) (Ma et al. Cancer, 2007), this study had a limited number of patients, short duration of follow-up including patients diagnosed from 2001-2003 prior to the approval and routine use of hypomethylating agents (HMA). We hypothesized that there are racial differences in the clinical characteristics and outcomes of patients with MDS. We thus analyzed the differences in disease characteristics and survival outcomes based on race and ethnic background in patients with MDS over 13 years.
We used the Surveillance, Epidemiology, and End Results (SEER) database to identify adult patients diagnosed with MDS between 2004 and 2016. Disease characteristics and patient outcomes were analyzed among three groups based on race/ethnicity: non-Hispanic white (NHW), non-Hispanic black (NHB) and Hispanics, Fisher exact test and chi-square test were used to compare categorical variables. SEER*Stat version 8.3.6 was used to calculate the incidence rate (IR) and incidence rate ratio (IRR) for NHW, NHB, and Hispanics. Univariate survival analysis was estimated using the Kaplan-Meier method, and groups were compared using a log-rank test. Multivariable survival analyses were performed using the Cox-proportional regression model after adjusting for age, gender, insurance status, histologic risk classification, marital status, and treatment with chemotherapy. Cause-specific survival (CSS) was calculated from the date of diagnosis to the date of MDS-related death and compared amongst the three groups.
A total of 52,031 patients with MDS were included in this study; 83.4% were NHW, 8.5% were NHB, and 8.2% Hispanics. The incidence was 7.81, 6.46, and 5.17 per 100,000 among NHW, NHB, and Hispanic patients, respectively. Compared to NHW, NHB and Hispanic patients had a significantly lower incidence rate among the overall population (p<.001) in both genders (p<.001) and in older age groups ≥ 50 years (p<.001). However, NHB patients had a significantly higher IRR in the younger age group (<50 years) with an increased incidence by 49% (95% confidence interval [CI] 1.32-1.67) as compared to NHW patients. [Table 1] Hispanic and NHB patients had a higher percentage of female gender (p<.001) and were more likely to be insured (p<.001) as compared to NHW patients. This was mostly attributed to a high proportion of "unknown" insurance status in the NHW population (28%). Hispanic patients were more likely to present with MDS with excess blasts (p<.001), and thus a higher proportion of patients received chemotherapy for myelodysplastic syndromes as compared to NHW/NHB patients (p<.001). Overall survival was significantly affected by race/ethnicity; NHB patients had a longer median overall survival (mOS) as compared to Hispanic and NHW patients (mOS 33 vs 28 vs 25 months, respectively; p<.001). After adjusting for confounding variables, the hazard ratio (HR) for death was 1.11 (95% CI 1.05-1.18) for Hispanics (p<.001) and 1.12 (95% CI 1.07-1.16) for NHW (p<.001) as compared to NHB. Moreover, a total of 25.6% of patients had MDS-related deaths. NHB patients had longer CSS compared to Hispanic and NHW patients (5-year CSS 72.2% vs 63% vs 62% respectively, p<.001). This difference was further confirmed using a multivariable Cox-proportional regression model with an HR for death of 1.35 (95% CI 1.24-1.48) and HR 1.24 (95% CI 1.15-1.33) for Hispanics and NHW, respectively, p<.001. [Figure 1]
Myelodysplastic syndromes have significant differences in age at presentation, disease risk, and survival outcomes based on racial and ethnic backgrounds. To our knowledge, this study represents the largest population-based analysis with the longest follow-up, specifically looking at such differences in patients with MDS. Further studies are warranted that incorporate treatment patterns and genomic data in order to identify factors that may account for these differences.
Wang:Celgene/BMS: Research Funding. Patel:France Foundation: Honoraria; Agios: Consultancy; DAVA Pharmaceuticals: Honoraria; Celgene: Consultancy, Speakers Bureau. Zeidan:Astellas: Consultancy, Honoraria; Taiho: Consultancy, Honoraria; Cardinal Health: Consultancy, Honoraria; Otsuka: Consultancy, Honoraria; MedImmune/Astrazeneca: Research Funding; Astex: Research Funding; CCITLA: Other; Leukemia and Lymphoma Society: Other; Epizyme: Consultancy, Honoraria; Boehringer-Ingelheim: Consultancy, Honoraria, Research Funding; Cardiff Oncology: Consultancy, Honoraria, Other; Ionis: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Research Funding; Acceleron: Consultancy, Honoraria; ADC Therapeutics: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; BeyondSpring: Consultancy, Honoraria; Daiichi Sankyo: Consultancy, Honoraria; Celgene / BMS: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Trovagene: Consultancy, Honoraria, Research Funding; Aprea: Research Funding; Agios: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Incyte: Consultancy, Honoraria, Research Funding; Jazz: Consultancy, Honoraria.
Asterisk with author names denotes non-ASH members.