title: Non-hematologic predictors of mortality improve the prognostic value of the international prognostic scoring system for MDS in older adults.
abstract: OBJECTIVE
  The International Prognostic Scoring System (IPSS) is commonly used to predict survival and assign treatment for the myelodysplastic syndromes (MDS). We explored whether self-reported and readily available non-hematologic predictors of survival add independent prognostic information to the IPSS.
  
  
  METHODS
  Retrospective cohort study of consecutive MDS patients ≥age 65 who presented to Dana-Farber Cancer Institute between 2006 and 2011 and completed a baseline quality of life questionnaire. Questions corresponding to functional status and symptoms and extracted clinical-pathologic data from medical records. Kaplan-Meier and Cox proportional hazards models were used to estimate survival.
  
  
  RESULTS
  One hundred fourteen patients consented and were available for analysis. Median age was 73 years, and the majority of patients were White, were male, and had a Charlson comorbidity score of <2. Few patients (24%) had an IPSS score consistent with lower-risk disease and the majority received chemotherapy. In addition to IPSS score and history of prior chemotherapy or radiation, significant univariate predictors of survival included low serum albumin, Charlson score, performance status, ability to take a long walk, and interference of physical symptoms in family life. The multivariate model that best predicted mortality included low serum albumin (HR=2.3; 95% CI: 1.06-5.14), therapy-related MDS (HR=2.1; 95% CI: 1.16-4.24), IPSS score (HR=1.7; 95% CI: 1.14-2.49), and ease taking a long walk (HR=0.44; 95% CI: 0.23-0.90).
  
  
  CONCLUSIONS
  In this study of older adults with MDS, we found that low serum albumin and physical function added important prognostic information to the IPSS score. Self-reported physical function was more predictive than physician-assigned performance status.
authors.affiliation: College of Medicine-Phoenix, University of Arizona, Phoenix, AZ, United States.
authors.forename: K Rebecca
authors.initials: KR
authors.lastname: Fega
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States.
authors.forename: Gregory A
authors.initials: GA
authors.lastname: Abel
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States.
authors.forename: Gabriela
authors.initials: G
authors.lastname: Motyckova
authors.affiliation: College of Medicine, University of Cincinnati, Cincinnati, OH, United States.
authors.forename: Alexander E
authors.initials: AE
authors.lastname: Sherman
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: DeAngelo
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States.
authors.forename: David P
authors.initials: DP
authors.lastname: Steensma
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States.
authors.forename: Ilene
authors.initials: I
authors.lastname: Galinsky
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States.
authors.forename: Martha
authors.initials: M
authors.lastname: Wadleigh
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States.
authors.forename: Richard M
authors.initials: RM
authors.lastname: Stone
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States; Geriatric Research Education and Clinical Center, VA Boston Medical Center, Boston, MA, United States; Division of Aging, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States. Electronic address: jdriver@partners.org.
authors.forename: Jane A
authors.initials: JA
authors.lastname: Driver
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D015897:Comorbidity; D005260:Female; D015577:Geriatric Assessment / Q000379:methods / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D009190:Myelodysplastic Syndromes / Q000175:diagnosis* / Q000401:mortality*; D011379:Prognosis; D016016:Proportional Hazards Models; D012189:Retrospective Studies; D012307:Risk Factors; D057566:Self Report; D011795:Surveys and Questionnaires; D016019:Survival Analysis
keywords: Elderly; Geriatric; Myelodysplastic syndromes; Oncology; Prediction; Prognosis