Background
Febrile neutropenia (FN) is a common complication in cancer patients receiving myelosuppressive chemotherapy. A recent study conducted by our research group [
1] reported that even if cancer patients were given prophylactic myeloid growth factor support, 16.6% of the patients suffered at least one breakthrough FN episode during their chemotherapy. FN is also potentially life-threatening. Inpatient mortality rates of between 4.7% and 9.5% were recently reported [
2‐
4]. FN often leads to a chemotherapy dose reduction and to treatment delays, which may affect the patients’ long-term clinical outcomes [
3,
5‐
7]. A previous study [
8] indicated that patients who received a reduced chemotherapy intensity (relative dose intensity ≤ 90%) achieved significantly less survival years than patients who received the optimal chemotherapy dose intensity.
Aside from its clinical consequences, FN also has a substantial economic effect, particularly in the inpatient setting [
9]. Three U.S. studies [
3,
10,
11] estimated that the average costs of FN inpatient management ranged from US$18,880 to US$22,086. The direct costs for outpatient management were considerably lower than inpatient care, at US$985 per episode [
11]. Similar trends with a different cost burden degree were observed in Europe. A German prospective study [
12] analyzed the influence of FN on the use of health resources and costs for patients with both solid cancers and lymphoma and found that the estimated mean direct cost per FN episode requiring hospital care was €3,950. A Spanish study [
13] found a mean direct cost per episode attributable to FN of €3,841 in a similar patient population. In a recent study conducted in Ireland [
14], the mean cost per FN episode in the inpatient setting was estimated to be €8,915. The cost of FN therefore varies greatly across different countries and health care systems.
In Singapore, limited data have been reported on the cost of the management of FN on cancer patients. Cost studies are therefore needed to make accurate estimates of the cost of FN on patients with various types of cancers. This knowledge can be used to develop further economic evaluations of the current FN management strategies, which may help in clinical decision-making. Therefore, the primary objective of this study was to describe the total direct inpatient costs among the solid tumor and lymphoma patients who received inpatient management of chemotherapy-induced febrile neutropenia (FN) and the factors that were associated with higher direct cost. The secondary objective was to describe the out-of-pocket patient payments and the factors that were associated with the higher out-of-pocket patient payments. We expected this study to provide an accurate estimate of the cost of FN, reflecting the local management in Singapore. This study is a fundamental requirement for the development of further economic evaluations of the current FN management strategies and for reducing the cost of FN on cancer patients in Singapore
Results
Patient population
Three hundred and sixty seven adult cancer patients were documented with FN-related hospitalizations between 2009 and 2012. The average patient age was 54.8 years (range, 18–79), 37.9% of the patients were male, and 77.1% were of Chinese ethnicity. The most common primary cancer types were breast cancer (36.8%), followed by lymphoma (21.5%), gastrointestinal cancer (10.6%), head and neck cancer (9.3%), and lung cancer (8.4%) (Table
1). GCSF was used as a therapeutic treatment (86.9%) in the majority of the FN episodes. Inpatient care commonly occurred (78.7%) in the subsidized wards (Class B2, Class C) (Table
2). The majority of the patients (90.5%) were Singapore citizens or permanent residents.
Table 1
Clinical and demographic characteristics of the subjects
Age in years
| |
Mean (SD) | 54.8 (12.2) |
18-40 (%) | 41 (11.2%) |
41-60 (%) | 202 (55.0%) |
61-80 (%) | 124 (33.8%) |
Gender
| |
Male (%) | 139 (37.9%) |
Female (%) | 228 (62.1%) |
Ethnicity
| |
Chinese (%) | 283 (77.1%) |
Malay (%) | 38 (10.4%) |
Indian (%) | 20 (5.4%) |
Other (%) | 26 (7.1%) |
Cancer Type
| |
Breast CA (%) | 135 (36.8%) |
Lymphoma (%) | 79 (21.5%) |
Gastrointestinal CA (%) | 39 (10.6%) |
Head and Neck CA (%) | 34 (9.3%) |
Lung CA (%) | 31 (8.5%) |
Sarcoma (%) | 16 (4.4%) |
Genitourinary CA (%) | 15 (4.1%) |
Gynecologic CA (%) | 13 (3.5%) |
Other/Unknown CA (%) | 5 (1.4%) |
MASCC Risk
| |
Low (%) | 300 (81.7%) |
High (%) | 67 (18.3%) |
Outcome
| |
Death (%) | 14 (3.8%) |
Recover (%) | 353 (96.2%) |
Table 2
Descriptive analysis of the total hospital cost and the out-of-pocket patient payments (n = 367)
All subjects
| 367 (100%) | 4,193 (±414) | | 2,837 | 2,230 (±254) | | 1,405 |
Age in years
| | | | | | | |
18-40 | 41 (11.2%) | 5,160 (±1,791) | 0.182 @
| 3,456 | 3,031 (±730) | 0.001 @
| 2,468 |
41-60 | 202 (55.0%) | 4,089 (±544) | 2,723 | 2,105 (±303) | 1,337 |
61-80 | 124 (33.8%) | 4,044 (±624) | 3,022 | 2,167 (±514) | 1,369 |
Gender
| | | | | | | |
Male | 139 (37.9%) | 5,286 (±864) | < 0.001 #
| 3,432 | 2,795 (±558) | 0.006 #
| 1,510 |
Female | 228 (62.1%) | 3,527 (±389) | 2,651 | 1,885 (±218) | 1,334 |
Cancer type
| | | | | | | |
Breast CA | 135 (36.8%) | 2,898 (±369) | < 0.001 @
| 2,208 | 1,567 (±249) | < 0.001 @
| 1,167 |
Lymphoma | 79 (21.5%) | 6,560 (±1,362) | 4,159 | 3,389 (±827) | 1,972 |
Gastrointestinal CA | 39 (10.6%) | 4,145 (±859) | 3,432 | 1,927 (±541) | 1,349 |
Head and Neck CA | 34 (9.3%) | 4,565 (±1,665) | 3,150 | 2,502 (±867) | 1,486 |
Lung CA | 31 (8.4%) | 3,353 (±912) | 2,314 | 1,861 (±947) | 1,097 |
Sarcoma | 16 (4.4%) | 3,857 (±1,119) | 3,479 | 2,331 (±701) | 2,194 |
Genitourinary CA | 15 (4.1%) | 4,898 (±2,803) | 2,654 | 2,629 (±1,498) | 1,340 |
Gynecologic CA | 13 (3.5%) | 4,615 (±1,482) | 3,858 | 2,877 (±1,317) | 2,251 |
Other/Unknown CA | 5 (1.4%) | 2,707 (±1,199) | 2,359 | 1,403 (±677) | 1,364 |
Therapeutic GCSF
| | | | | | | |
No | 48 (13.1%) | 3,752 (±1,088) | 0.064 #
| 2,392 | 1,544 (±384) | 0.007 #
| 1,181 |
Yes | 319 (86.9%) | 4,267 (±450) | 2,950 | 2,338 (±286) | 1,487 |
Admission source
| | | | | | | |
ED | 195 (53.1%) | 3,721 (±503) | < 0.001 @
| 2,577 | 1,979 (±259) | 0.001 @
| 1,302 |
NCCS clinic | 121 (33.0%) | 3,671 (±594) | 2,451 | 2,069 (±409) | 1,377 |
Inpatient referral | 51 (13.9%) | 7,238 (±1,601) | 4,436 | 3,570 (±1,163) | 2,112 |
Severe sepsis
| | | | | | | |
No | 315 (85.8%) | 3,590 (±350) | < 0.001 #
| 2,571 | 2,044 (±264) | < 0.001 #
| 1,283 |
Yes | 52 (14.2%) | 7,879 (±1,744) | 6,105 | 3,358 (±772) | 2,073 |
MASCC risk
| | | | | | | |
Low | 300 (81.7%) | 3,790 (±412) | < 0.001 #
| 2,571 | 2,162 (±283) | 0.034 #
| 1,316 |
High | 67 (18.3%) | 5,998 (±1,249) | 4,436 | 2,533 (±574) | 1,711 |
Ward class
| | | | | | | |
Class A1 | 30 (8.2%) | 5,879 (±1,875) | 0.039 @
| 4,086 | 5,245 (±1,889) | < 0.001 @
| 3,828 |
Class B1 | 48 (13.1%) | 3,699 (±784) | 2,479 | 3,749 (±835) | 2,512 |
Class B2 | 194 (52.9%) | 3,855 (±540) | 2,727 | 1,696 (±205) | 1,256 |
Class C | 95 (25.8%) | 4,602 (±923) | 3,185 | 1,600 (±313) | 1,100 |
Total hospital cost
The mean and median total hospital cost per FN episode for all of the hospitalizations were US$4,193 (95% CI: US$3,779-4,607) and US$2,837, respectively. A subgroup analysis by cancer type showed that the patients with lymphoma had the highest mean total hospital cost of US$6, 560 (95% CI: US$5,198-7,922), followed by patients with genitourinary cancer (US$4,898, 95% CI: US$2,095-7,701), and gynecologic cancer (US$4, 615, 95% CI: US$3,133-6,097). Breast cancer patients had the lowest mean total hospital cost (US$2, 898, 95% CI: US$2,529-3,267) of the identified cancer types (Table
2).
FN episodes that manifested with severe sepsis had a considerably higher mean cost (US$7,879, 95% CI: US$6, 135-9,623) than those without sepsis (US$3,590, 95% CI: US$3,240-3,940). Other factors associated with a higher mean total hospital cost were inpatient referrals (US$7,238, 95%CI: US$5,637-8,839) and a low MASCC score (US$5,998, 95% CI: US$4,749-7,247).
Out-of-pocket patient payments
The mean and median out-of-pocket patient payments per FN episode were US$2,230 (95% CI: US$1,976-2,484) and US$1,405, respectively. A subgroup analysis by cancer type revealed that the patients with lymphoma had the highest mean out-of-pocket patient payments of US$3,389 (95% CI: US$2,562-4,216), followed by patients with gynecologic cancer (US$2,877, 95% CI: US$1,560-4,194), and genitourinary cancer (US$2,629, 95% CI: US$1,131-4,127). Breast cancer patients had the lowest mean out-of-pocket patient payments (US$1,567, 95% CI: US$1,318-1,816) of the known cancer types (Table
2).
The mean out-of-pocket patient payments of FN episodes with severe sepsis (US$3,358, 95% CI: US$2,586-4,130) was higher than without sepsis (US$2,044, 95% CI: US$1,780-2,308). Higher FN out-of-pocket patient payments were associated with the use of therapeutic GCSF (US$2,338, 95% CI: US$2,052-2,624) and the private wards (Class A (US$5,245, 95% CI: US$3,356-7,134) and Class B1 (US$3,749, 95% CI: US$2,914-4,584)). The main cost component identified in the out-of-pocket patient payments was the prescription charges (35.2%), followed by the ward charges (18.4%) and the laboratory cost (13.3%). Approximately one quarter of the total out-of-pocket patient payments was unclassified (29.4%) (Table
3).
Table 3
Cost breakdown of the total out-of-pocket patient payments (n=367)
Ward | 230 (145–504) | 432 (375–488) | 18.4% |
Laboratory | 171 (120–260) | 314 (266–362) | 13.3% |
Radiology | 17 (8–64) | 88 (66–110) | 3.7% |
Prescription | 507 (319–891) | 829 (720–937) | 35.2% |
Other/Unknown | 383 (226–661) | 692 (585–800) | 29.4% |
Total | 1,405 (901–2,442) | 2,230 (1,976-2,483) | 100% |
Univariate analysis
The association of cancer types with the total hospital cost was evaluated. Patients with lymphoma had a significantly higher cost (p < 0.001) than patients with other cancer types. Male patients had a significantly higher total hospital cost (p < 0.001) than female patients. Other factors associated with a significantly higher total hospital cost were inpatient referrals (p < 0.001), severe sepsis (p < 0.001), and a low MASCC score (p < 0.001) (Tables
2 and
4). In the correlation analysis, a higher total hospital cost was also significantly associated with a longer length of stay (r = 0.86, p < 0.01), a lower ANC at presentation (r = 0.17, p < 0.01), and a longer time to recover the ANC (r = 0.16, p < 0.01).
Table 4
Comparisons of costs among subsets of variables identified in univariate analysis (n=367)
Cancer type | Lymphoma | Breast CA | 1,822 | < 0.001* | 3,662 | < 0.001* |
Gastrointestinal CA | 1,462 | 0.411 | 2,415 | 0.634 |
Head & Neck CA | 887 | 0.999 | 1,995 | 0.94 |
Lung CA | 1,528 | 0.098 | 3,207 | 0.072 |
Sarcoma | 1,058 | 1 | 2,703 | 0.988 |
Genitourinary CA | 760 | 0.952 | 1,662 | 0.804 |
Gynecologic CA | 512 | 1 | 1,945 | 1 |
Other/Unknown CA | 1,986 | 0.969 | 3,853 | 0.87 |
Admission source | Inpatient referral | NCCS clinic | 1,501 | 0.002* | 3,567 | < 0.001* |
ED admission | 1,591 | 0.003* | 3,517 | < 0.001* |
Age in years | 18-40 yrs | 41-60 yrs | 926 | 0.002* | | |
61-80 yrs | 864 | 0.005* |
Ward class | A1 | B1 | 1,496 | 0.763 | | |
B2 | 3,549 | < 0.001* | | |
C | 3,645 | < 0.001* | | |
B1 | A1 | -1,496 | 0.763 | | |
B2 | 2,053 | < 0.001* | | |
C | 2,149 | < 0.001* | | |
The association of cancer types with the out-of-pocket patient payments was also evaluated. The lymphoma group again had a significant higher cost (p < 0.001) than the other cancer types. The patients in the 18–40 years age group (p < 0.01) and male patients (p < 0.01) also had a significantly higher cost than older patients and female patients, respectively. Other factors associated with higher out-of-pocket patient payments were treatment with therapeutic GCSF (p < 0.01), inpatient referrals (p < 0.01), severe sepsis (p < 0.001), and a lower MASCC score (p < 0.05). Patients staying in private wards (Class A/B1) were associated with a significantly higher out-of-pocket patient payments (p < 0.001) than those in the subsided wards (Class B2/C) (Tables
2 and
4). The correlation analysis revealed that the out-of-pocket patient payments was positively correlated with a longer length of stay (r = 0.63, p < 0.01), a lower ANC at presentation (r = 0.11, p < 0.05), and a longer time to recover the ANC (r = 0.127, p < 0.05).
Multivariate analysis
Table
5 shows the factors that were found to be significantly associated with a higher total hospital cost. The factors were the length of stay (coefficient = 0.061, 95% CI: 0.056 ~ 0.065, p < 0.001), lymphoma (coefficient = 0.105, 95% CI: 0.064-0.146, p < 0.001), and severe sepsis (coefficient = -0.131, 95% CI: 0.086-0.176, p < 0.001). This multivariate model for the total hospital cost had an adjusted R
2 of 0.782 (p < 0.001) (Table
5).
Table 5
Factors associated with the total hospital cost in a regression model (n=367)
a
Length of stay | 0.061 | 0.056 | 0.065 | 0.002 | 0.763 |
< 0.001
|
Time to ANC recovery | 0.003 | -0.003 | 0.009 | 0.003 | 0.024 | 0.363 |
ANC at presentation | 0.008 | -0.054 | 0.070 | 0.031 | 0.007 | 0.797 |
MASCC score < 21 | -0.013 | -0.052 | 0.026 | 0.020 | -0.017 | 0.513 |
Lymphoma | 0.105 | 0.064 | 0.146 | 0.021 | 0.141 |
< 0.001
|
Male gender | 0.026 | -0.006 | 0.059 | 0.016 | 0.042 | 0.110 |
Severe sepsis | 0.131 | 0.086 | 0.176 | 0.023 | 0.154 |
< 0.001
|
Inpatient referral | 0.038 | -0.008 | 0.083 | 0.023 | 0.043 | 0.107 |
A separate multivariate model was used to identify the significant predictors for higher out-of-pocket patient payments, which are shown in Table
6. The factors were the length of stay (coefficient = 0.054, 95% CI: 0.049-0.060, p < 0.001), lymphoma (coefficient = 0.067, 95% CI: 0.012-0.121, p = 0.017), severe sepsis (coefficient = 0.081, 95% CI: 0.020-0.142, p = 0.009), 18–40 years age group (coefficient = 0.082, 95% CI: 0.019-0.144, p = 0.011), treatment with therapeutic GCSF (coefficient = 0.101, 95% CI: 0.041-0.161, p = 0.001), and staying on a private ward (coefficient = 0.408, 95% CI: 0.359-0.457, p < 0.001). The regression model had an adjusted R
2 of 0.691 (Table
6).
Table 6
Factors associated with higher out-of-pocket patient payments in a regression model (n=367)
a
Length of stay | 0.054 | 0.049 | 0.060 | 0.003 | 0.614 |
< 0.001
|
Time to ANC recovery | 0.004 | -0.004 | 0.013 | 0.004 | 0.031 | 0.320 |
ANC at presentation | -0.003 | -0.085 | 0.080 | 0.042 | -0.002 | 0.948 |
MASCC score < 21 | 0.019 | -0.033 | 0.072 | 0.027 | 0.022 | 0.473 |
Lymphoma | 0.067 | 0.012 | 0.121 | 0.028 | 0.080 |
0.017
|
Male gender | 0.017 | -0.027 | 0.060 | 0.022 | 0.024 | 0.452 |
Severe sepsis | 0.081 | 0.020 | 0.142 | 0.031 | 0.085 |
0.009
|
Inpatient referral | 0.013 | -0.048 | 0.074 | 0.031 | 0.013 | 0.683 |
18-40 year age group | 0.082 | 0.019 | 0.144 | 0.032 | 0.078 |
0.011
|
Therapeutic GCSF treatment | 0.101 | 0.041 | 0.161 | 0.030 | 0.100 |
0.001
|
Private Ward (Class A or B1) | 0.408 | 0.359 | 0.457 | 0.025 | 0.499 |
< 0.001
|
Discussion
In this study, we described the total hospital cost and out-of-pocket patient payments among solid tumor and lymphoma patients who received inpatient management of chemotherapy-induced FN in Singapore. The factors associated with the total hospital cost and out-of-pocket patient payments were also identified. The factors that were found to be associated with a higher total hospital cost for FN treatment were a longer length of stay, severe sepsis, and lymphoma. The factors associated with a higher out-of-pocket patient payments were a longer length of stay, severe sepsis, lymphoma, the age group 18–40 years, treatment with therapeutic GCSF during admission, and staying on a private ward (Class A or B1).
When analyzed by cancer type, the mean total hospital cost was US$6,560 for lymphoma patients, US$2,898 for breast cancer patients, and ranged from US$3,353 to US$4,898 for patients with other identified cancers. A similar pattern was found in previous studies [
11,
12,
23]. Among cancer patients who received inpatient care, the Bennett [
23] study estimated that the mean direct cost was US$21,601 for lymphoma patients, which was much more costly than that of breast cancer (US$13,186) or other cancers (US$12,150). A recently published Spanish retrospective study [
13] reported that the cost was highest when lymphoma was the underlying cancer (€4,514), followed by breast cancer (€3,518) and lung cancer (€3,310). This difference was probably related to a longer length of stay due to lymphoma patients suffering FN episodes [
10]. One study showed that lymphoma patients had the longest length of stay (10.1 days) and patients with female breast cancer had the shortest mean length of stay (5.9 days) [
10]. The length of stay result was consistent with the cost, as lymphoma had the highest mean total hospital cost (US$24,218) and female breast cancer had the lowest mean cost (US$11,132). As the length of stay was directly associated with the total hospital cost, interventions to improve FN management in future should focus on decreasing the duration of the hospital stay.
A lower out-of-pocket patient payment was associated with the Class B2 and C wards. The majority of the patients were citizens or residents and they received more subsidies in these wards than in the other ward classes. The government only subsidizes 0% to 20% of the total hospital bill for Singapore citizens and permanent residents in the private Class A and Class B wards [
20]. In contrast, citizens and permanent residents in the Class B2 and Class C wards can receive a subsidy of up to 80% of their total bill [
20]. As the patients’ choice of ward class may reflect their preference or values as well as their socioeconomic status, which are an important determinant in clinical decision-making, future cost-effective analysis or cost-utility analysis studies should collect the willingness to pay value separately, based on the different ward classes.
Prescription charges were the largest component of the overall out-of-pocket patient payments of FN, followed by the ward charges, and the laboratory cost. The medication costs and ward costs were therefore the main cost drivers in the inpatient management of FN. A micro-costing method can be used to account for the cost of the ward and medication, if a more accurate estimate of the direct medical cost of FN is required. Prescription charges were identified as the largest component in the out-of-pocket patient payments because the reimbursement of healthcare resources in Singapore differs from other countries. The government subsidy for cancer patients mainly focuses on the hospitalization charges and the chemotherapy charges [
24]. Certain costly supportive care medications that are frequently used in the management of FN, such as G-CSF, are not fully covered for reimbursement. Therefore, cost-effective analysis on those medications may be useful to formulate the strategies to reduce patients’ out-of-pocket payments. In addition, it has been demonstrated that medication errors (such as inappropriate medication dosing) in the management of infectious diseases may contribute to higher medication costs among patients [
25]. Future studies should aim to lower the cost burden of FN by focusing on interventions that can improve medication management, such as having a clinical pharmacist to review prescribed medications to reduce potential medication errors, and to optimize the medication management strategies [
25].
There are a number of limitations to this study. A large proportion of the expenses in the total out-of-pocket patient payments could not be classified. This may introduce some variability in identifying the main cost drivers of the cost of FN. We did not capture patients’ comorbidities in detail, hence we were unable to analyze the contribution of comorbidities to the cost burden of FN. Our inclusion criteria were stricter than other studies, which makes comparisons of the cost estimates difficult [
1,
3,
10,
26]. The cost was calculated from the start date of an FN episode until the discharge date. Additional costs due to comorbidity or cancer-related morbidity and mortality were not considered. Those patients whose discharge date was more than 10 days after both their fever and ANC recovered were excluded from the analysis. These criteria were applied so that we only studied the cost of the management of FN, not the other costs that are associated with the management of comorbidities or cancer due to an extended hospital stay. Due to the unavailability of data breakdown, micro-costing on the total hospital cost was not feasible. However, the average cost-per-case estimates were used to evaluate the total hospital cost of FN in this study.
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Competing interests
The authors have declared no competing interests for this article.
Authors’ contributions
XJW conceived of the study, participated in the design of the study, performed the statistical analysis, interpreted data, and drafted the manuscript. MW participated in the design of the study and acquisition of data. LYH contributed substantially to the design of the study and acquisition of data. AC participated in the conception and design of the study, coordinated and helped to draft the manuscript. All authors read and approved the final manuscript.