Date of Award

January 2016

Document Type


Degree Name

Medical Doctor (MD)



First Advisor

Alfred I. Lee

Second Advisor

David Banach


Background: Febrile Neutropenia (FN) in cancer patients is associated with a high mortality rate, yet identifying patients with FN at highest risk for short term morbidity and mortality remains challenging. The Rothman Index (RI) is a real-time composite measurement of a patient’s condition using 26 clinical variables sensitive to signs of clinical decline. RI has been shown to predict intensive care unit admission, hospital readmission and short-term mortality among inpatients. The aim of this study was to determine if RI at onset of FN is associated with inpatient mortality or discharge to hospice care.

Methods: A retrospective analysis of adult oncology inpatients with FN was

performed. Clinical variables collected included demographics, malignancy type, comorbidities, admission condition and microbiological data related to the FN episode. The primary outcome was in-hospital mortality or discharge to hospice care secondary outcome was ICU admission as a result of FN episode. Variables associated with the primary outcome in univariate analysis were entered into a multivariate logistic regression model for analysis.

Results: Of 411 patients included in the study 308 (74.9%) had hematological malignancies, 259 (63.0%) had FN at admission and 48 (11.7%) died or were discharged to hospice. Controlling for malignancy type, major medical comorbidities and microbiologically confirmed bacterial infection, RI ≤ 70 was independently associated with this outcome. Baseline renal disease, pneumonia, respiratory failure and sepsis were also associated with the primary outcome.

Conclusion: RI is an objective measure that can predict poor outcomes among inpatients with FN. RI can guide clinicians caring for patients with FN in both prognostication and identifying patients at high risk for mortality, which can guide inpatient care. The utility of this scoring system should be compared to existing risk stratification systems used in oncology to identify its optimal use in the clinical setting.


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