A Cost Analysis of Hematopoietic Colony-Stimulating Factors

Introduction

Myelosuppression remains the major dose-limiting toxicity of systemic cancer chemotherapy. The risk of infection and infection-related mortality increases in direct proportion to the degree and duration of neutropenia observed [1]. The onset of fever in the setting of neutropenia generally requires immediate hospitalization and administration of broad-spectrum antibiotic therapy [2]. Previous efforts to enhance hematologic recovery following systemic chemotherapy have had only limited success [3].

Several hematopoietic colony-stimulating factors (CSFs) have been characterized over the past decade [4], and two are now readily available: human recombinant granulocyte-colony stimulating factor (G-CSF, filgrastim(Drug information on filgrastim), Neupogen) and yeast-derived granulocyte-macrophage colony-stimulating factor [GM-CSF, sargramostim(Drug information on sargramostim), Leukine] [5,6]. Several studies have shown that these agents can reduce the severity and duration of neutropenia associated with cancer chemotherapy [7-11]. A prospective, double-blind, placebo-controlled trial of G-CSF utilized prophylactically has demonstrated a significant reduction in the risk of febrile neutropenia and need for hospitalization in patients with solid malignancies receiving combination chemotherapy [12]. Randomized clinical trials have demonstrated that CSFs administered after the onset of febrile neutropenia accelerate myeloid recovery, reducing the duration of neutropenia [13]. It remains uncertain, however, to what degree CSFs so administered reduce duration of fever or hospitalization.

The approval of the hematopoietic CSFs for use in patients receiving cancer chemotherapy has resulted in widescale use of these agents in a variety of clinical settings, contributing to increasing health care costs. As further studies define additional indications for CSFs, even greater utilization of these agents can be anticipated. Nevertheless, clinical and economic uncertainty exists as to the optimal use of CSFs in patients receiving different cancer chemotherapy regimens in each tumor type, considering the wide variation in patients' risk for neutropenia. Recent cost studies have been conducted in an effort to define, measure, and compare the relevant positive and negative economic consequences of the use of CSFs to prevent infections in patients receiving chemotherapy [14-16].

The American Society of Clinical Oncology (ASCO) has recently adopted general guidelines for the use of CSFs based on these and other studies in the literature [17]. This paper reviews and extends the cost model previously presented for the use of hematopoietic CSFs in patients receiving cancer chemotherapy and presents specific guidelines based on this model. The administration of hematopoietic CSFs may be associated with a reduction in health care costs for hospitalization due to febrile neutropenia if utilized within the specific guidelines presented.

Methods

A standard model based on decision theory was developed for this cost analysis of the use of hematopoietic CSFs in patients receiving systemic cancer chemotherapy (Table 1). The decision choices consisted of no CSF; CSF
administered prophylactically after the completion of chemotherapy with continuation through the period of neutropenia; and CSF administered therapeutically only if febrile neutropenia occurs. The model assumes that all patients experiencing febrile neutropenia will be hospitalized and treated empirically with parenteral antibiotics. The role for outpatient management of selected patients with febrile neutropenia has not yet been fully defined.

Baseline probabilities for hospitalization risk and survival with and without CSF, along with the durations of hospitalization and CSF administration, were based on the prospective randomized trial of G-CSF in patients with small-cell lung cancer receiving systemic chemotherapy [12]. Baseline probabilities of hospitalization and survival in patients with febrile neutropenia receiving therapeutic CSF are assumed to be the same as for patients receiving no CSF (Table 2). Since there was no reduction in the median duration of hospitalization in patients treated with G-CSF in either the prophylactic or therapeutic randomized trials, no reduction in hospitalization duration was assumed at baseline with either choice [12,13]. As with all variables studied in this model, this baseline assumption was then varied over the range of possible values in a sensitivity analysis.

Costs considered in this model include the cost of hospitalization for febrile neutropenia and the cost of CSF per treatment cycle. Baseline daily costs of hospitalization were estimated from data available at our own institution, based on fixed daily costs for room, antibiotics, fluids and tubing, and professional fees. These represent minimal cost estimates, since they do not reflect the cost of diagnostic and monitoring tests (x-rays, scans, blood tests), cultures, drug levels, and consultations, which can increase the hospitalization costs substantially. Baseline CSF costs include agent and administration costs derived from our own institution.

The expected excess cost for each specific choice was calculated from the sum of the products of the costs and probabilities of each outcome. The expected cost per treatment cycle represents the excess cost associated with hospitalization for febrile neutropenia and treatment with CSFs. Chemotherapy costs and other items likely to be identical in the three treatment choices were not considered.

Sensitivity analysis provides an estimate of the expected cost for a range of values of one or more variables for each decision choice. Sensitivity analysis permits the calculation of thresholds when the expected cost for two treatment options are the same. In multiway sensitivity analysis, each function or curve represents a series of thresholds for a combination of two variables indicated on the axes. A family of threshold curves may be generated as the value of a third factor is varied.

Using Monte Carlo analysis, the model was analyzed repeatedly, each time sampling from the assumed distributions of the main variables. Probability distributions for the main variables were derived from the randomized controlled trial and local institutional data. Monte Carlo simulations consisted of 1,000 sequential samples. In this study, the distributions of outcomes or thresholds then serve as a measure of variability upon which to base a level of confidence in the decision outcome or threshold estimate. The distribution function of the differences in outcome between two choices is distributed as sample mean differences, allowing for statistical inference. Tests of significance were based on a t statistic with n-1 degrees of freedom, with n representing the number of samples in the simulation.

Results

Utilizing the baseline probability and cost assumptions in Table 2, the model generated an expected excess cost per treatment cycle of $5,500 for no CSF, $4,750 for prophylactic CSF, and $6,875 for therapeutic CSF. Sensitivity analyses for the three choices were performed for each of the study variables. Figure 1 displays one-way sensitivity analyses for the control probability of hospitalization (Figure 1A) and for the cost of hospitalization per day (Figure 1B). The excess cost associated with prophylactic CSF increases at a slower rate than with the other two strategies for both variables. The thresholds for each variable are the values at the point where the cost line for prophylactic CSF crosses each of the other lines. At these points, the total excess cost is the same for each group being compared.

Model thresholds for the decision between no CSF and prophylactic CSF are presented in Table 3, and those for the decision between prophylactic CSF and therapeutic CSF are shown in Table 4. The strategy favored on a cost basis at values above the threshold is indicated in the tables to the right of the thresholds, while the strategy favored at values below the threshold is indicated to the left of the thresholds.

Figure 2 displays three-way sensitivity analyses based on variations in daily hospital cost and duration of hospitalization. The region above each threshold curve represents values of the variables favoring the use of the hematopoietic CSFs on a cost basis. Figure 2A varies the risk of hospitalization in the prophylactic group as a proportion of the control risk. Conditions favoring the use of CSF represented by the area above each curve increase as the risk of hospitalization in patients receiving CSF decreases. Alternatively, as the proportional risk of hospitalization with prophylactic CSF increases, the conditions associated with a net cost advantage for CSF lessen. The incremental change in the area above the threshold curve is greater with higher proportional risk of hospitalization. Figure 2B varies the cost of CSFs per day. The conditions favoring the use of CSF on a cost basis increase as the daily cost of CSF lessens. The area above the threshold curves favoring the use of CSF in this setting increases at approximately equal increments as the daily cost of CSF decreases.

Estimates of excess cost per treatment cycle based on Monte Carlo analysis were $7,923 ± $484 (SEM), $6,612 ± $289, and $9,812 ± $533 for the control, prophylactic, and therapeutic CSF arms, respectively. The distribution of cost differences based on Monte Carlo analysis favors prophylactic CSF over no CSF, with a median difference of $1,070 (Figure 3A). The distribution of cost differences also favors prophylactic CSF over therapeutic CSF, with a median difference of $2,671 (Figure 3B). Neither of these differences was statistically significant, however, based on the assumed variability of each parameter.

Threshold analysis based on Monte Carlo simulation also demonstrated considerable variability in threshold measures of the main variables (Table 5). The distribution of threshold estimates for each of the variables in the model was studied. Each of the distributions was skewed, suggesting that the median probably represents a better measure of central tendency than the mean.