Multilevel Associations Between Patient- and Hospital-Level Factors and In-Hospital Mortality Among Hospitalized Patients With Head and Neck Cancer
| Autor: | Sai D Challapalli, Nosayaba Osazuwa-Peters, Paula Buchanan, Eric Adjei Boakye, Betty Chen, Jay F. Piccirillo, Miao Cai, Betelihem B. Tobo |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Adult
Male medicine.medical_specialty Population Comorbidity Logistic regression Odds 03 medical and health sciences 0302 clinical medicine Sex Factors Risk Factors Internal medicine Survivorship curve Prevalence Medicine Humans Hospital Mortality 030223 otorhinolaryngology education Original Investigation Aged education.field_of_study business.industry Head and neck cancer Odds ratio Nomogram Middle Aged medicine.disease United States Cross-Sectional Studies Otorhinolaryngology Head and Neck Neoplasms 030220 oncology & carcinogenesis Surgery Female business |
| Zdroj: | JAMA Otolaryngol Head Neck Surg |
| Popis: | Importance Risk factors for in-hospital mortality of patients with head and neck cancer (HNC) are multilevel. Studies have examined the effect of patient-level characteristics on in-hospital mortality; however, there is a paucity of data on multilevel correlates of in-hospital mortality. Objective To examine the multilevel associations of patient- and hospital-level factors with in-hospital mortality and develop a nomogram to predict the risk of in-hospital mortality among patients diagnosed with HNC. Design, Setting, and Participants This cross-sectional study used the 2008-2013 National Inpatient Sample database. Hospitalized patients 18 years and older diagnosed (both primary and secondary diagnosis) as having HNC using theInternational Classification of Diseases, Ninth Revision, Clinical Modification codes were included. Analysis began December 2018. Main Outcomes and Measures The primary outcome of interest was in-hospital mortality. A weighted multivariable hierarchical logistic regression model estimated patient- and hospital-level factors associated with in-hospital mortality. Moreover, a multivariable logistic regression analysis was used to build an in-hospital mortality prediction model, presented as a nomogram. Results A total of 85 440 patients (mean [SD] age, 62.2 [13.5] years; 61 281 men [71.1%]) were identified, and 4.2% (n = 3610) died in the hospital. Patient-level risk factors associated with higher odds of in-hospital mortality included age (adjusted odds ratio [aOR], 1.03 per 1-year increase; 95% CI, 1.02-1.03), male sex (aOR, 1.23; 95% CI, 1.12-1.35), higher number of comorbidities (aOR, 1.14; 95% CI, 1.11-1.17), having a metastatic cancer (aOR, 1.49; 95% CI, 1.36- 1.64), having a nonelective admission (aOR, 3.26; 95% CI, 2.83-3.75), and being admitted to the hospital on a weekend (aOR, 1.30; 95% CI, 1.16-1.45). Of the hospital-level factors, admission to a nonteaching hospital (aOR, 1.48; 95% CI, 1.24-1.77) was associated with higher odds of in-hospital mortality. The nomogram showed fair in-hospital mortality discrimination (area under the curve of 72%). Conclusions and Relevance This cross-sectional study found that both patient- and hospital-level factors were associated with in-hospital mortality, and the nomogram estimated with fair accuracy the probability of in-hospital death among patients with HNC. These multilevel factors are critical indicators of survivorship and should thus be considered when planning programs or interventions aimed to improve survival among this unique population. |
| Databáze: | OpenAIRE |
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