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J Geriatr Oncol. 2018 Jul 5. pii: S1879-4068(18)30157-7. doi: 10.1016/j.jgo.2018.05.015. [Epub ahead of print]

Use of a comprehensive frailty assessment to predict morbidity in patients with multiple myeloma undergoing transplant.

Author information

1
Division of Hematology, The Ohio State University, Columbus, OH, United States. Electronic address: Ashley.Rosko@osumc.edu.
2
Division of Hematology, The Ohio State University, Columbus, OH, United States.
3
Department of Hematology and Oncology, Emory University School of Medicine, Atlanta, GA, United States.
4
Division of Oncology, Washington University School of Medicine, Saint Louis, MO, United States.
5
Division of Medicinal Chemistry, College of Pharmacy, The Ohio State University, Columbus, OH, United States.
6
Cancer Prevention and Control, The Ohio State University, Columbus, OH, United States.
7
Division of Hematology, The Ohio State University, Columbus, OH, United States; Division of Medicinal Chemistry, College of Pharmacy, The Ohio State University, Columbus, OH, United States.
8
Departments of Molecular Genetics and Cancer Biology and Genetics, The Ohio State University, Columbus, OH, United States.

Abstract

Multiple myeloma (MM) is a disease of aging adults and autologous stem cell transplant (ASCT) is considered the standard of care. As the population ages a growing number of older adults will undergo ASCT and an objective approach to estimate physiologic reserve and transplant morbidity risk is warranted. Here, we evaluate assess p16INK4a (p16), a molecular aging biomarker, along with geriatric metrics to determine risk of transplant toxicity.

METHODS:

We prospectively evaluated 100 MM patients for frailty before and after ASCT using a Geriatric Assessment (GA) and collected T-cells for analysis of p16 using a custom nanostring codeset.

RESULTS:

Pre-transplant physical function was predicative of hospital length of stay (LOS). Each one-unit increase in physical function score, the average LOS decreased by 0.52 days (95% CI, -1.03-0.02); p = .04). Similarly, higher self-report of ADL/IADL (Human Activity Profile was associated with shorter LOS (0.65 less days (95% CI -1.15 to -0.15), p = .01). Patients with anxiety/depression (OR = 1.10 (95% CI 1.00-1.22), p = .056), lower handgrip strength (OR = 0.90 (95% CI 0.82-0.98), p = .02), falls (OR = 1.60 (95% CI 1.07-2.38), p = .02), or weight loss (OR = 5.65 (95% CI 1.17-25.24), p = .03) were more likely to be re-admitted. The estimated EFS at 1-year was 85% (95% CI, 75-91) with median follow-up of 15.7 months. Weight loss was a significant predictor of EFS (HR = 3.13 (95% CI 1.15-8.50), p = .03). Frailty assessment by self-reported fatigue minimally correlated with T-cell p16 expression (r = 0.28; p = .02). Age, Karnofsky Performance Status (KPS), or Hematopoietic cell transplantation-specific Co-Morbidity Index (HCT-CI) did not predict hospital LOS or readmissions.

CONCLUSIONS:

Our data illustrate that a GA can identify individuals with MM who are at greater risk for morbidity following ASCT.

PMID:
29983352
PMCID:
PMC6320732
[Available on 2020-01-05]
DOI:
10.1016/j.jgo.2018.05.015

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