The development and validation of a prediction tool for chemotherapy-induced anemia in patients with advanced...

In this study, the development and validation of a cycle-based prediction model for severe anemia [i.e., a hemoglobin (Hb) of

Data on 536 European patients who were receiving palliative chemotherapy were prospectively collected as part of the European Cancer Anemia Survey [Ludwig et al., Eur J Cancer 40:2293-2306, 2004]. The patient sample was then randomly divided into two-thirds model derivation and one-third validation sample. A third external sample consisting of 76 patients treated at the Toronto Sunnybrook Regional Cancer Centre was separately used to externally validate the model. Multivariable logistic regression techniques were applied to develop the initial model. A risk scoring system based on the regression parameters was then created ranging from 0 to 15.

Precycle Hb, patient body surface area, advanced age, poor performance status, recurrent or persistent disease, and the use of platinum or gemcitabine-based chemotherapy were identified as important predictors for anemia. A prechemotherapy risk score of >or=8 to <10 was identified as the optimal cut off to maximize the sensitivity (83.1%) and specificity (67.8%) of the prediction tool. Patients with a score of >or=8 would be considered at high risk for developing anemia after a particular cycle of chemotherapy.

We developed and validated an anemia prediction tool for advanced stage NSCLC patients receiving palliative chemotherapy. To make the model available for easy use and access, we have incorporated it on to our risk prediction website: http://www.PredictPatientEvents.com . It is hoped that this risk model will enhance patient care by optimizing the frequency of Hb testing and/or the use of preventative therapies.