In this study, we created and internally validated a clinical prediction model for development of FN in the first cycle of chemotherapy among elderly patients with four common malignancies. With increasingly aggressive efforts to treat malignancies within this population, the model has the potential to help clinicians identify those patients at greatest risk of FN prior to initiation of myelosuppressive chemotherapy. Efforts were made to maintain the simplicity of the model by keeping myelosuppressive chemotherapy as a dichotomous variable and using a total number of comorbid conditions, to assure that it could be easily used with information readily available within the clinic setting. Ultimately, the model provided moderate predictive power to identify patients at higher risk of developing FN.
To our knowledge, a clinical prediction model of this nature has not previously been published. Given the difficulty in identifying a high-risk patient population, past studies have attempted to find predictors of FN and have identified patient specific factors as well as therapy and disease-related effects. Similar to previous studies, we found that increased risk of FN was associated with more advanced stage at diagnosis and comorbid conditions [24
]. Previous studies have found that persons older than 65 years have a higher risk of FN than those who are younger [24
]. Although we expected that the risk might increase with increasing age in the elderly, we did not find an association between age and FN among a sample of persons older than 65 years. Although the reason for this finding is not clear from our analysis, it may reflect the use of lower doses or less aggressive chemotherapy regimens for older persons. Alternatively, the risk of FN may be greater for those 65 years and older compared with those under age 65 years, but FN risk may not vary substantially among those older than 65 years.
A recent national cohort of prospectively enrolled patients undergoing chemotherapy found that neutropenic complications, defined as an absolute neutrophil count less than 500 or infection, were associated with anthracycline chemotherapy regimens, pre-treatment cytopenia, prior chemotherapy, low performance status, elevated blood urea nitrogen, and elevated alkaline phosphatase [30
]. We found a number of other agents in addition to anthracycline drugs associated with FN, which suggests that the elderly may have a different risk of FN with these agents than younger patients. However, a recent publication which summarized available clinical data noted a greater than 10% incidence of febrile neutropenia for numerous non-anthracycline based chemotherapeutic regimens [6
]. We suspect that our extensive database also allowed us to identify other agents not normally captured in smaller studies. Our study lacked some of the clinical detail included in the prospective cohort; however, it is based upon a population-based sample and thus is less subject to selection bias that may result when practices and patients have to agree to participate.
Cancer type was also associated with FN in our multivariate analysis and was included in the prediction model. Numerous past studies that have evaluated risk factors for FN have focused on a single cancer type such as NHL and breast cancer [22
]. Patients with hematologic malignancies have been demonstrated to have an increased risk of FN [6
]. The prospective study previously outlined did include a variety of solid tumor diagnosis, but they were not noted to be associated with FN in published results [31
]. We suspect that the influence of cancer type on episodes of FN is related to both individual patient factors, such as overall health and performance status not captured with our comorbid illness score, as well as difference in treatment regimens that were not captured by our chemotherapy variables.
While the chemotherapy interval was not associated with FN, receiving chemotherapy within 1 month (as compared with 1–3 months or >3 months) of diagnosis was associated with a higher risk of FN. To our knowledge, timing of chemotherapy initiation has not been examined in past studies as a risk factor for development of FN. Although we do not have any supporting evidence, we suspect that timing of chemotherapy initiation may be a reflection of disease severity (i.e., more rapid therapy for more aggressive disease) or a proxy for patient-related factors that influence the choice or intensity of chemotherapy regimens.
It is important to note that the current study only identified episodes of FN in the first 28 days in order to approximate the first cycle of chemotherapy. We limited our prediction model to the first cycle because clinicians often make changes to the chemotherapy dose based upon patients' experience in the first cycle, and our dataset would not capture these changes. In addition, the decision to use G-CSF should ideally occur at the start of the first cycle since that is when half or more of the FN episodes occur and therefore should be based upon the data available to the clinician at that time [23
Given that approximately 50% of episodes of FN occur after initial chemotherapy cycle [30
], we chose FN risk of 10% in the study as cutoff for our clinical prediction rule. This cutoff is based on the assumption that those with risk greater than 10% after initial cycle are similar to the population with cumulative risk greater than 20% across all cycles of chemotherapy. If the prediction rule is utilized across all four malignancies, any patient with a prediction score of 10 or greater would have 10% or greater predicted risk of developing FN with the initial chemotherapy cycle and should be considered for prophylactic growth factor administration.
This study has a number of limitations common to analysis of administrative datasets [32
]. We identified chemotherapy through Medicare claims which do not accurately capture dose, which may be especially important in an elderly population where physicians may be more apt to reduce dose to avoid toxicity. Claims also lack clinical data, such as neutrophil count or functional status, which have been shown to be predictive of FN.
Because no specific ICD-9 codes exist for FN, we defined FN as a hospitalization for fever, infection, or neutropenia immediately following use of chemotherapy. Chen-Hardee used SEER-Medicare data and chart reviews to study FN in patients with non-Hodgkin's lymphoma [33
]. With chart review data as the comparison, they found the ICD-9 code for neutropenia (288.0) from the Medicare data had 80% sensitivity for FN. Our definition of FN is likely more sensitive, but may misclassify others who have infections without neutropenia. However, the definition of FN did not appear to bias our estimates of the risk of FN, as the results were similar when the definition of FN was varied in a sensitivity analysis.
Despite these limitations, the current study provides important information and a potentially useful tool for clinicians treating elderly patients with chemotherapy. The clinical prediction model can easily be used with available data prior to initiation of chemotherapy. Ongoing efforts should be made with prospective cohorts with more detailed clinical data to improve the accuracy of prediction model. Specifically, laboratory data, performance status, and more detailed information on chemotherapy dosing will likely be valuable components to a final model. Before our model is used in clinical practice, our current prediction model should be tested in other cohorts to examine its performance and clarify its overall utility. Ultimately, implementation of an accurate prediction model into clinical practice would help further define the role of G-CSF on an individual patient basis and improve the appropriate use of growth factors to prevent FN after chemotherapy use.