Impact of socioeconomic status on disease phenotype, genomic landscape and outcomes in myelodysplastic syndromes

Francesca Mastaglio, Khaled Bedair, Elli Papaemmanuil, Michael J. Groves, Ann Hyslop, Norene Keenan, Eleanor J. Hothersall, Peter J. Campbell, David T. Bowen, Sudhir Tauro

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2 Citations (Scopus)
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Abstract

Genetic and epigenetic alterations contribute to the biological and clinical characteristics of myelodysplastic syndromes (MDS), but a role for socioeconomic environment remains unclear. Here, socioeconomic status (SES) for 283 MDS patients was estimated using the Scottish Index of Multiple Deprivation tool. Indices were assigned to quintile categorical indicators ranked from SES1 (lowest) to SES5 (highest). Clinicopathological features and outcomes between SES quintiles containing 15%, 20%, 19%, 30% and 16% of patients were compared. Prognostic scores identified lower-risk MDS in 82% of patients, with higher-risk disease in 18%. SES quintiles did not associate with age, gender, cytogenetics, International Prognostic scores or, in sub-analysis (n = 95), driver mutations. The odds ratio of a diagnosis of refractory anaemia was greater than other MDS sub-types in SES5 (OR 1·9, P = 0·024). Most patients (91%) exclusively received supportive care. SES did not associate with leukaemic transformation or cause of death. Cox regression models confirmed male gender (P <0·05), disease-risk (P <0·0001) and age (P <0·01) as independent predictors of leukaemia-free survival, with leukaemic transformation an additional determinant of overall survival (P = 0·07). Thus, if access to healthcare is equitable, SES does not determine disease biology or survival in MDS patients receiving supportive treatment; additional studies are required to determine whether outcomes following disease-modifying therapies are influenced by SES.

Original languageEnglish
Pages (from-to)227-234
Number of pages8
JournalBritish Journal of Haematology
Volume174
Issue number2
Early online date20 Apr 2016
DOIs
Publication statusPublished - Jul 2016

Keywords

  • Genomic
  • Healthcare
  • International Prognostic Scoring System
  • Myelodysplastic syndromes
  • Outcomes
  • Socioeconomic status

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