Tibben, N.E. (Nienke) (2015) Risk stratification in patients presenting with (non-) neutropenic fever, based on clinical and biochemical parameters. thesis, Medicine.
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Abstract
Background; Cancer patients undergoing chemotherapy are at increased risk of developing infection, especially in the neutropenic phase. Therefore patients who develop fever during neutropenia receive aggressive treatment with intravenous antibiotics. However, recent studies show that half of the patients with fever after chemotherapy do not have an infection. The challenge is to distinguish patients at low-risk for infection from those with high risk for infection. The aim of this study is to analyse whether the biomarkers CRP, IL-8, IL-6, PCT and CD64 can predict infection and secondary patient’s outcome. In addition, the aim is to validate the MASCC-risk index score and the new scoring system of Ahn. Methods; Patients presented at the emergency room with fever after chemotherapy were included. Due to the low number of eligible patients, both neutropenic and non-neutropenic patients were included. Patients were hospitalized and treated according to protocol with intravenous antibiotics. In addition to routine blood tests, the biomarkers mentioned above were determined. Retrospectively the patients were categorized in a low and high risk group using the two clinical scoring systems. The primary endpoint was infection. Secondary endpoints were duration of hospitalisation, fever, neutropenia and intravenous antibiotics. Results; 32 patients were included, 14 were neutropenic. Of these patients 20 had an infection and 12 had fever of unknown origin. When using the cut-off values of respectively 60ng/L and 90ng/L, IL-8 and IL-6 were significant higher in the infection group. IL-8 and IL-6 correlated with three of the four secondary endpoints. The scoring systems were not significant different for the endpoint infection, but scored different for secondary endpoints. Conclusion; Biomarkers IL-8 and IL-6 seem to be promising predictors for infection and patient’s outcome. The risk models were not predictive for infection, but appeared predictive for patient’s outcome.
| Item Type: | Thesis (Thesis) |
|---|---|
| Supervisor name: | Supervisor: and Wymenga, Dr. A.N.M. Medical Oncologist and and and Slomp, Dr. J. Clinical chemist |
| Faculty: | Medical Sciences |
| Date Deposited: | 25 Jun 2020 10:51 |
| Last Modified: | 25 Jun 2020 10:51 |
| URI: | https://umcg.studenttheses.ub.rug.nl/id/eprint/1240 |
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