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212 Role of Neutrophil Lymphocyte Ratio [NLR] As a Biomarker of Frailty and Predictor of Survival Among Older Adults with Multiple Myeloma (MM)

Program: Oral and Poster Abstracts
Type: Oral
Session: 905. Outcomes Research—Malignant Conditions (Lymphoid Disease): Outcomes Research Real World Data Healthcare Disparities
Hematology Disease Topics & Pathways:
Elderly, Study Population
Saturday, December 5, 2020: 1:15 PM

Smith Giri, MD1, Susan Bal, MD, MBBS2, Kelly N. Godby, MD1*, Joshua Richman, MD, PhD3*, Adam J Olszewski, MD4, Grant R Williams5*, Luciano J. Costa, MD, PhD6 and Smita Bhatia, MD, MPH5

1University of Alabama at Birmingham, Birmingham, AL
2O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL
3Institute for Cancer Outcomes and Survivorship, University of Alabama Birmingham, Birmingham, AL
4Brown University, Providence, RI
5Institute for Cancer Outcomes and Survivorship, University of Alabama at Birmingham, Birmingham, AL
6Division of Hematology and Oncology, University of Alabama at Birmingham, Birmingham, AL

Introduction: NLR combines a marker of inflammation (neutrophilia) and immune senescence (lymphopenia) to reflect aging related alterations in the immune systems. Prior studies have shown that NLR can serve as a marker of frailty and predict survival among older adults with solid tumors and lymphomas, its role among older adults with MM remains unclear.

Methods: We used the Flatiron Health electronic health record-derived de-identified database to source older adults (age ≥60y) with incident MM diagnosed between 1/1/2011 and 2/1/2020. We limited our study cohort with known first line therapy and absolute neutrophil and lymphocyte count (cells//µL) up to 90 days before the start of treatment. We constructed a modified frailty index (Facon et al Leukemia 2020) at MM diagnosis combining age, comorbidity and ECOG performance status, captured within 90 days from the start of first line therapy categorizing patients into frail vs nonfrail. We examined the association between NLR (stratified into quartiles, Q1-Q4) and frailty using logistic regression model adjusted for age, sex and race/ethnicity. We used Kaplan Meier methods and multivariable Cox regression to assess the impact of NLR on overall survival adjusting for age, sex, race/ethnicity, international staging system (ISS) stage, high-risk cytogenetics (HRCA; del17p, t4;14 or t14;16), and first-line therapy.

Results: Of 2792 eligible patients, the median age at MM diagnosis was 73y (IQR: 67-78y), with 53% males and 61% non-Hispanic whites. Of these, 56% had IgG isotype, 22% ISS stage-III and 13% had HRCA. The median NLR was 2.29 (IQR: 1.5 to 3.59). Of the 1,743 evaluable for frailty, 1042 patients (59.8%) were frail. Overall, 45% received proteasome inhibitor (PI) + Immunomodulatory agent (Imid) based first line therapy and 19% received autologous stem cell transplantation. Patients in the highest NLR quartile were at a 2.1-fold higher odds of being frail (95% CI 1.52-2.86; p <0.001) when compared with those in the lowest NLR quartile (after adjusting for age, sex and race/ethnicity). NLR was poorly correlated with age (Pearson’s r= 0.02). Patients in the highest NLR quartile had an inferior overall survival vs those in the lowest quartile (median OS/3y-OS in Q4 3.3y/53% vs 4.7y/69% in Q1; log-rank p <0.01). Similar results were seen when limiting to patients receiving first line PI & Imid triplet and PI or Imid based doublet regimens (Fig 1). In a multivariable analysis, patients in the highest NLR quartile had a 1.5 times increased hazards of death (95% CI 1.28-1.85, p <0.001) when compared with those in the lowest NLR quartile, after adjusting for potential confounders (Table 1).

Conclusion: NLR is an easily available laboratory biomarker associated with frailty as well as inferior overall survival among older adults with MM. Future studies should explore its value as a screening tool to identify frail older adults with MM and guide appropriate treatment selection and targeted interventions to prevent excess toxicities and improve outcomes.

Disclosures: Giri: Pack Health: Research Funding; Carevive Systems: Research Funding; Carevive Systems: Honoraria. Olszewski: Genentech, Inc.: Research Funding; Spectrum Pharmaceuticals: Research Funding; TG Therapeutics: Research Funding; Adaptive Biotechnologies: Research Funding. Costa: Amgen: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria; AbbVie: Consultancy; Celgene: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Genentech: Consultancy.

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