Hospitalization and definitive radiotherapy in lung cancer: Incidence, risk factors and survival impact

Sarah Z. Hazell, Nicholas Mai, Wei Fu, Chen Hu, Cole Friedes, Alex Negron, Khinh Ranh Voong, Josephine L. Feliciano, Peijin Han, Samantha Myers, Todd R. McNutt, Russell K. Hales

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Unplanned hospitalization during cancer treatment is costly, can disrupt treatment, and affect patient quality of life. However, incidence and risks factors for hospitalization during lung cancer radiotherapy are not well characterized. Methods: Patients treated with definitive intent radiation (≥45 Gy) for lung cancer between 2008 and 2018 at a tertiary academic institution were identified. In addition to patient, tumor, and treatment related characteristics, specific baseline frailty markers (Charlson comorbidity index, ECOG, patient reported weight loss, BMI, hemoglobin, creatinine, albumin) were recorded. All cancer-related hospitalizations during or within 30 days of completing radiation were identified. Associations between baseline variables and any hospitalization, number of hospitalizations, and overall survival were identified using multivariable linear regression and multivariable Cox proportional-hazards models, respectively. Results: Of 270 patients included: median age was 66.6 years (31-88), 50.4% of patients were male (n = 136), 62% were Caucasian (n = 168). Cancer-related hospitalization incidence was 17% (n = 47), of which 21% of patients hospitalized (n = 10/47) had > 1 hospitalization. On multivariable analysis, each 1 g/dL baseline drop in albumin was associated with a 2.4 times higher risk of any hospitalization (95% confidence interval (CI) 1.2-5.0, P = 0.01), and baseline hemoglobin ≤10 was associated with, on average, 2.7 more hospitalizations than having pre-treatment hemoglobin > 10 (95% CI 1.3-5.4, P = 0.01). After controlling for baseline variables, cancer-related hospitalization was associated with 1.8 times increased risk of all-cause death (95% CI: 1.02-3.1, P = 0.04). Conclusions: Our data show baseline factors can predict those who may be at increased risk for hospitalization, which was independently associated with increased mortality. Taken together, these data support the need for developing further studies aimed at early and aggressive interventions to decrease hospitalizations during treatment.

Original languageEnglish (US)
Article number334
JournalBMC cancer
Volume20
Issue number1
DOIs
StatePublished - Apr 19 2020

Keywords

  • Hospitalization
  • Lung cancer
  • Mortality
  • Nomogram
  • Radiation

ASJC Scopus subject areas

  • Genetics
  • Oncology
  • Cancer Research

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