Prospective validation of a risk model for first cycle neutropenic complications in patients receiving cancer chemotherapy

Abstract

8561 Background: A nationwide, prospective cohort study was undertaken to develop and validate a risk model for neutropenic complications (NC) in cancer patients receiving chemotherapy. Methods: 3,596 patients initiating a new chemotherapy regimen with solid tumors or lymphoma were registered at 115 randomly selected sites. Data on at least 1 cycle of chemotherapy were available on 3,468. A logistic regression model for cycle 1 NC was derived and then validated using a split sample random selection process. Results: The risk of cycle 1 NC ranged from 5.5%-30.2%, averaging 18.5% across tumor types. No significant differences in distribution of NC or predictive factors were observed between the derivation dataset (n=2,592) or the validation dataset (n=876). Major independent baseline clinical risk factors for cycle 1 NC in the derivation model include: prior chemotherapy (P=.044), number of myelosuppressive agents (P<.0001), anthracycline-based regimens (P<.0001), planned delivery >85% of standard (P<.0001), cancer type (P<.0001), concurrent antibiotics (P=.023) or phenothiazines (P=.006), abnormal alkaline phosphatase (P=.002), elevated bilirubin (P=.031), low platelets (P=.004), elevated glucose (P=.023) and reduced glomerular filtration rate (P=.013). Reduced risk of cycle 1 NC was associated with primary prophylaxis with a myeloid growth factor (P<.0001). Model R2 was 0.273 and c-statistic 0.80 [95% CI: 0.78–0.82; P<.0001]. At the median predicted risk of cycle 1 NC of 11%, model test performance consisted of: sensitivity 84%; specificity 57% and diagnostic odds ratio (DOR) 7.2 while cycle 1 NC risk was 31% and 6% among high risk and low risk half, respectively. The model performed well in the smaller validation dataset with a model R2 of 0.354 and c-statistic of 0.84 [95% CI: 0.81–0.87, P<.0001]. Test performance of the model in the validation sample included: sensitivity 90%; specificity 62%; DOR 14.1 and risks of 35% and 4% in high risk and low risk patients, respectively. Conclusions: Validation in a randomly selected patient sample suggests that this model has general applicability in identifying patients at increased risk for NC. Further validation in other independent cancer patient populations receiving chemotherapy is planned. [Table: see text]