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Risk Models for Predicting Chemotherapy-Induced Neutropenia

Health Services and Outcomes Research Program, James P. Wilmot Cancer Center, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA

Correspondence: Correspondence: Gary H. Lyman, M.D., M.P.H., F.R.C.P. (Edin), University of Rochester School of Medicine and Dentistry, 601 Elmwood Avenue, Box 704, Rochester, New York 14642, USA. Telephone: 585-275-3335; Fax: 585-276-1885; e-mail: Gary_Lyman{at}urmc.rochester.edu

Neutropenia and its complications, including febrile neutropenia, are major dose-limiting toxicities of systemic cancer chemotherapy. A number of studies have attempted to identify risk factors for neutropenia and its consequences to develop predictive models capable of identifying patients at greater risk for such complications and to guide more effective and cost-effective applications of the colony-stimulating factors. A systematic review of the literature showed that age, performance status, nutritional status, chemotherapy dose intensity, and low baseline blood cell counts were associated with the risk of severe and febrile neutropenia or reduced chemotherapy dose intensity in multivariate analysis in two or more studies. Similarly, age, diagnosis of leukemia or lymphoma, high temperature or low blood pressure at admission, and i.v. site infection along with low blood cell counts and organ dysfunction were associated with serious medical complications of febrile neutropenia, including bacteremia and death. The available risk model studies, however, had several limitations, including retrospective analyses of small study populations lacking independent validation, frequent missing values, and differences in the predictive factors considered. To overcome the limitations of previous studies, efforts are under way to develop and validate risk models based on large prospective studies in representative populations of patients receiving systemic chemotherapy.

Key Words. Neutropenia • Toxicities • Colony-stimulating factors • Risk model • Chemotherapy

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