Trends and sociodemographic risk factors associated with tumor lysis syndrome in hospitalized multiple myeloma patients: A National Inpatient Sample analysis (2016–2021).

220 Background: Tumor lysis syndrome (TLS) is a metabolic complication that may occur spontaneously in patients with malignancies or following the initiation of anticancer therapy. Most commonly seen in high-proliferation malignancies, TLS has increased its incidence in multiple myeloma (MM) in the last decade. We aim to describe the yearly trends of TLS in patients with MM and sociodemographic characteristics of these patients using the National Inpatient Sample (NIS). Methods: This is a retrospective study obtained from NIS data from 2016 to 2021. We included patients aged 18 years or older who were admitted with a diagnosis of TLS and who also had a diagnosis of MM. Patients with MM were identified using ICD-10 code C90. (C90.00 + C90.01 + C90.02), TLS was defined using code E88.3. Patients who had any other hematological malignancy were excluded from the study. Incidence of TLS was described per year from 2016 to 2021 in patients with MM. Multivariate logistic regression analysis was used to determine sociodemographic factors that acted as risks for developing TLS in patients with MM. Results: A total of 573,870 weighted admissions with MM were identified. Of those, 325 patients had a diagnosis of TLS without a diagnosis of other hematological malignancies. Mean age of patients with MM was 70.6 years (SD = 10.3), while the mean age for patients with MM and TLS was 66.1 years (SD = 9.1). Yearly incidence of TLS is described in Table 1. After running the multivariate logistic regression analysis, we found that Black or African American patients had increased risk of developing TLS (aOR 2.05, 95% CI 1.04-4.01, p = 0.036) compared to Caucasian patients, and patients with Self Pay as expected primary payer had increased risk of developing TLS (aOR 7.94, 95% CI 2.06-30.6, p = 0.003) compared to patients with Medicare. There was no significant difference in other sociodemographic factors. Conclusions: Incidence of TLS in patients with MM is rising, and risk factors for this include African American race compared to Caucasian race and patients primarily expected to self-pay compared to those covered by Medicare. These results suggest underlying differences in risk profiles across patient populations. Yearly incidence of TLS in hospitalized patients with MM. Year TLS Cases (n) Proportion (%) 2016 15 0.05% 2017 35 0.11% 2018 40 0.12% 2019 70 0.22% 2020 80 0.25% 2021 85 0.26% Total 325 1.00% TLS = Tumor Lysis Syndrome; MM = Multiple Myeloma.

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Journal
JCO Oncology Practice
Published
2025-10-01
DOI
https://doi.org/10.1200/op.2025.21.10_suppl.220
Primary Topic
Methemoglobinemia and Tumor Lysis Syndrome
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article
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article

Trends and sociodemographic risk factors associated with tumor lysis syndrome in hospitalized multiple myeloma patients: A National Inpatient Sample analysis (2016–2021).

Joarly Lormil, FRANCISCO GALLEGOS KOYNER, Ivette Vigoda, Jorge Octavio Sanchez Orbe et al.
JCO Oncology Practice
Methemoglobinemia and Tumor Lysis Syndrome
article

Trends and sociodemographic risk factors associated with tumor lysis syndrome in hospitalized multiple myeloma patients: A National Inpatient Sample analysis (2016–2021).

Joarly Lormil, FRANCISCO GALLEGOS KOYNER, Ivette Vigoda, Jorge Octavio Sanchez Orbe, Ignacio Gomez Plascencia
article en

Abstract

220 Background: Tumor lysis syndrome (TLS) is a metabolic complication that may occur spontaneously in patients with malignancies or following the initiation of anticancer therapy. Most commonly seen in high-proliferation malignancies, TLS has increased its incidence in multiple myeloma (MM) in the last decade. We aim to describe the yearly trends of TLS in patients with MM and sociodemographic characteristics of these patients using the National Inpatient Sample (NIS). Methods: This is a retrospective study obtained from NIS data from 2016 to 2021. We included patients aged 18 years or older who were admitted with a diagnosis of TLS and who also had a diagnosis of MM. Patients with MM were identified using ICD-10 code C90. (C90.00 + C90.01 + C90.02), TLS was defined using code E88.3. Patients who had any other hematological malignancy were excluded from the study. Incidence of TLS was described per year from 2016 to 2021 in patients with MM. Multivariate logistic regression analysis was used to determine sociodemographic factors that acted as risks for developing TLS in patients with MM. Results: A total of 573,870 weighted admissions with MM were identified. Of those, 325 patients had a diagnosis of TLS without a diagnosis of other hematological malignancies. Mean age of patients with MM was 70.6 years (SD = 10.3), while the mean age for patients with MM and TLS was 66.1 years (SD = 9.1). Yearly incidence of TLS is described in Table 1. After running the multivariate logistic regression analysis, we found that Black or African American patients had increased risk of developing TLS (aOR 2.05, 95% CI 1.04-4.01, p = 0.036) compared to Caucasian patients, and patients with Self Pay as expected primary payer had increased risk of developing TLS (aOR 7.94, 95% CI 2.06-30.6, p = 0.003) compared to patients with Medicare. There was no significant difference in other sociodemographic factors. Conclusions: Incidence of TLS in patients with MM is rising, and risk factors for this include African American race compared to Caucasian race and patients primarily expected to self-pay compared to those covered by Medicare. These results suggest underlying differences in risk profiles across patient populations. Yearly incidence of TLS in hospitalized patients with MM. Year TLS Cases (n) Proportion (%) 2016 15 0.05% 2017 35 0.11% 2018 40 0.12% 2019 70 0.22% 2020 80 0.25% 2021 85 0.26% Total 325 1.00% TLS = Tumor Lysis Syndrome; MM = Multiple Myeloma.

JCO Oncology PracticeVol. 21(10_suppl)
St. Barnabas Hospital (US)
Openalex Percentile: Top 60%
Methemoglobinemia and Tumor Lysis Syndrome
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