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Cancer Res Treat. 2020;52(3):896-906
pISSN 1598-2998, eISSN 2005-9256
https://doi.org/10.4143/crt.2019.398
Open Access
Socioeconomic Burden of Cancer in Korea from 2011 to 2015
Original Article
Purpose
Though the socioeconomic burden of cancer on patients is increasing in South Korea, there
is little research regarding the type of cancer that incurs the highest costs. This study ana-
lyzed the socioeconomic burden on cancer patients from 2011 to 2015 according to sex
and age.
Materials and Methods
A prevalence-based approach was applied utilizing claim data of the National Health Insur-
ance Service in Korea to estimate the socioeconomic burden of cancer on patients. Patients
who received treatment for cancer from 2011 to 2015 were the study subjects. The total
socioeconomic burden of their disease and treatment was divided into direct and indirect
costs.
Results
There was an increase of 50.7% for 5 years, from 821,525 to 1,237,739 cancer patients.
The cancer costs for men and women increased $8,268.4 million to $9,469.7 million and
$3,626.5 million to $4,475.6 million, respectively. Furthermore, the 50-59-year-old age
group accounted for a large portion of the total disease cost. Liver, lung, stomach, and col-
orectal cancers created the heaviest economic burdens on patients.
Conclusion
Overall, this study indicates new policies for cancer prevention, early detection, and post-
cancer treatment management are necessary to help limit the costs associated with cancer,
especially in the elderly, and provides a foundation for establishing cancer-related health
care policies, particularly by defining those cancers with heavier disease burdens.
Key words
Cost of illness, Socioeconomic burden, Cancer, Cancer prevalence
Young Ae Kim, PhD1
Ye-Rin Lee, MPH1
Jeongjoo Park1
In-Hwan Oh, MD, PhD2
Hoseob Kim, MPH1
Seok-Jun Yoon, MD, PhD3
Keeho Park, MD, PhD4
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Correspondence: Keeho Park, MD, PhD
Department of Cancer Control and Population
Health, National Cancer Center Graduate
School of Cancer Science and Policy,
National Cancer Center, 323 Ilsan-ro,
llsandong-gu, Goyang 10408, Korea
Tel: 82-31-920-2160
Fax: 82-31-920-2949
E-mail: khparkmd@ncc.re.kr
Received July 11, 2019
Accepted March 17, 2020
Published Online March 18, 2020
1Division of Cancer Control and Policy,
National Cancer Control Institute, National
Cancer Center, Goyang, 2Department of
Preventive Medicine, Kyung Hee University
College of Medicine, Seoul, 3Department of
Preventive Medicine, Korea University
College of Medicine, Seoul, 4Department of
Cancer Control and Population Health,
National Cancer Center Graduate School of
Cancer Science and Policy, National Cancer
Center, Goyang, Korea
Introduction
The incidence and mortality of cancer are rapidly increas-
ing worldwide. According to the International Agency for
Research on Cancer (IARC), there were 18.1 million new
cases and 9.6 million deaths due to cancer worldwide in 2018
[1]. In the case of South Korea, the incidence of cancer has
been reported since 1999, and the annual average increase in
age-adjusted cancer incidence from 1999 to 2011 was 3.8%.
Since 2011, although the incidence of cancer has decreased
by 3.0% annually (except for a 3.1% increase between 2015
and 2016 [2]), the death rate from cancer has been steadily
increasing. Based on 2017 data, cancer was still the leading
cause of death in South Korea, accounting for 27.8% of all
deaths. Also, the cancer mortality rate was 153.0 per 100,000
population, with a 1.4% increase from the previous year [3].
As Korea became an aged society in 2017 [4], the increase
in the elderly population will lead to higher numbers of the
elderly living with cancer [5]. Although new developments
VOLUME 52 NUMBER 3 JULY 2020 897
in cancer diagnostics and treatment have led to increases in
cancer survival rates, the prevalence of cancer is still increas-
ing [6]. The economic burden on cancer patients has been
growing due to aging, increased survival rates, and increased
use of medical care after diagnosis [7]. However, little is
known about which type of cancer is the costliest in Korea.
Likewise, it is not known what the year-to-year trends in can-
cer costs are in Korea.
According to previous studies, the economic burden of all
cancers in Korea was approximately $9.4 billion in 2002 [8],
about $12.1 billion (14.1 trillion won) in 2005 [9], and $20.9
billion in 2010 [10]. However, it is difficult to directly com-
pare estimates of economic burden across studies because of
differences in methodology, particularly differences related
to calculations used and variables examined. For these rea-
sons, there are very few studies comparing the economic bur-
den of cancer year-to-year using recent data.
Data on the economic burden of disease are significant, as
they can be used for a variety of purposes, such as formation
of medical, health, and economic policies and the generation
of reports on the general health of the population [11]. Fur-
thermore, data regarding the performance of the national
health system could be utilized for the post-evaluation of
policies and comparisons with other countries [12,13], as well
as evaluations of the effectiveness of medical and health
research resource distribution [14]. As such, some countries
routinely assess the economic burden of all diseases at the
national level [15,16].
The present study was carried out to confirm and compare
the prevalence and economic burden of cancer by cancer
type, age, and sex utilizing claims data of the National Health
Insurance Service (NHIS) of Korea.
Materials and Methods
Yearly economic cost was estimated using claims data of
the NHIS for the period January 1, 2011, to December 31,
2015, which represented the latest available economic and
prevalence data.
The selection criteria for subjects used to calculate disease
cost were as follows. Subjects were defined as patients who
filed claims with the NHIS from 2011 to 2015 for Interna-
tional Classification of Diseases, 10th revision, Clinical Mod-
ification (ICD-10-CM) codes indicating cancer (C00-C97) and
(1) visited the outpatient department three or more times or
(2) were hospitalized one or more times due to same cancer
within 1 year of the diagnosis [8]. Cancer (C00-C97) was clas-
sified into the following 24 types: lip, oral cavity, and phar-
ynx (C00-C14); esophagus (C15); stomach (C16); colon and
rectum (C18-C20); liver (C22); gallbladder (C23-C24); pan-
creas (C25); larynx (C32); lung (C33-C34); breast (C50); cervix
uteri (C53); corpus uteri (C54); ovary (C56); prostate (C61);
testis (C62); kidney (C64); bladder (C67); brain and CNS
(C70-C72); thyroid (C73); Hodgkin’s lymphoma (C81); non-
Hodgkin’s lymphoma (C82-85, C96); multiple myeloma
(C90); leukemia (C91-C95); and other unspecified cancer [17].
The economic burden of disease can be divided into direct
and indirect costs. Direct costs consisted of direct medical
and non-medical costs. NHIS claims data were used to esti-
mate direct medical costs incurred by cancer patients stem-
ming from hospitalization and outpatient care. The non-
benefit service cost was defined as the coinsurance rate of the
non-benefit service of cancer patients, as presented in the
“Survey on the Benefit Coverage Rate of National Health
Insurance” [18].
Direct non-medical costs included transportation and nur-
sing costs. Transportation costs were defined as the expenses
incurred by cancer patients visiting medical institutions for
hospitalization and outpatient treatment. The total annual
transportation cost for cancer patients was calculated by mul-
tiplying the number of annual visits to the outpatient depart-
ment and the number of hospitalizations by the average
round-trip transportation cost for one visit to the hospital.
For this, the annual hospitalization and outpatient trans-
portation costs of cancer patients, per the Korea Health Panel
Survey, were used, and the formula used for the calculations
was as follows [19].
1. Transportation cost calculation
Transportation cost=
{(Number of visits to the outpatient department per year!
The average transportation cost per visit)+
(Number of hospitalizations per year!
The average transportation cost per hospitalization)} (1)
Nursing costs were measured based on the average daily
wage of workers listed in the Financial Supervisory Service
(Ministry of Employment and Labor) database. The average
daily wage was multiplied by the rate of caregiver use, pro-
vided by the Korea Health Panel Survey, to calculate the
average daily nursing cost. Since informal care by family
members and relatives is needed during hospitalization, the
hospitalization nursing cost was calculated by multiplying
the number of hospital visits for hospitalization by the aver-
age daily nursing cost. We calculated the nursing cost only
for patients who were either " 65 years of age or < 20 years
of age and needed help with outpatient care. Each outpatient
visit was weighted to reflect half of 1 day of inpatient hospi-
talization due to the outbreak of productivity loss. The for-
mula used for nursing cost calculations was as follows.
Young Ae Kim, Economic Burden of Cancer for 5 Years
2. Nursing cost calculation
Nursing cost= (2)
, where i is age, j is sex, Dij is length of stay for hospitalization,
Oij is the number of outpatient visits (< 20 years old,
! 65 years old), Iij is the average daily wage for nursing, and
Eij is the caregiver use rate.
Indirect costs are economic costs/losses resulting from the
inability to work due to cancer treatment and productivity
losses due to the premature death of cancer patients [7]. To
calculate indirect costs, we first determined the average daily
wage based on sex and age using raw survey data on work
status by employment type to calculate loss. The age of the
productive population was divided into separate groups for
analysis. We used three groups for examining the productive
population: those aged 60 years (the retirement age for civil
servants) and younger, 64 years (the representative econom-
ically active population) and younger, and 15 years and
older. Those aged 14 years and under were considered as
non-working individuals. The formula for calculating pro-
ductivity loss was as follows.
3. Productivity loss due to outpatient care and hospitaliza-
tion
Productivity loss due to outpatient care
and hospitalization= (3)
, where i is age (15 years or older), j is sex, Dij is length of stay
for hospitalization, Oij is the number of outpatient visits, Iij is
the average daily wage for a given sex and age, and Eij is the
employment rate for a given sex and age.
Productivity loss due to death was defined as the expected
future income had the patient survived and the discount rate
used to evaluate the costs and benefits at different times from
the current perspective. We applied a standard discount rate
of 3%. For the sensitivity analysis, discount rates of 5% and
0% were applied and compared to the standard [20]. Data
from Statistics Korea were used to determine the number of
deaths. Life expectancy values used for analysis were drawn
from age-specific complete life tables (rather than abridged
life tables) for each year and applied to the total number of
deaths due to cancer for that year, multiplied by the total
income the patient would have received during the period
between the time of premature death and the patients’ pre-
dicted life expectancy. The employment rate according to sex
and age for each year was then applied. It was assumed that
there was no income earned for individuals aged 0-14 years,
and calculations were performed using the three aforemen-
tioned groups, with the age of the economically active pop-
ulations being no more than 60 years, no more than 64 years,
and 15 years and older to determine the loss of productivity
due to death.
4. Productivity loss due to premature death
Productivity loss due to death=
(4)
, where i is age, j is sex, (DN)ij is the number of cancer deaths
by sex and age, t is the age at death, It+n is the average annual
wage in t+n by sex and age, Pt+n is the employment rate in
t+n by sex and age, n is life expectancy "t, and r is the dis-
count rate.
In terms of total cost, $1 was equal to 1,131.52 won in 2015,
according to Statistics Korea [21].
5. Ethical statement
This study was approved by the Institutional Review
Board of the National Cancer Center (approval No. ncc2016-
0076). Informed consent from individual patients was wai-
ved as this study involves only de-identified administrative
data.
Results
The number of patients accessing medical services for can-
cer was 821,525 in 2011, 955,703 in 2012, 1,080,199 in 2013,
1,184,681 in 2014, and 1,237,739 in 2015, showing a continu-
ous, upward trend of approximately 50.7% when comparing
2011 to 2015. In terms of cancer type, thyroid cancer exhibited
the highest prevalence (n=189,711) in 2011, followed by
stomach cancer (n=102,836), colorectal cancer (n=88,730), and
breast cancer (n=88,594). In terms of prevalence by sex, in
2011, the number of female and male cancer patients was
451,427 (54.9%) and 370,098 (45.1%), respectively. In 2015, the
number of female and male patients was 695,293 (56.2%) and
542,446 (43.8%), respectively. Overall, the number of female
patients exceeded that of male patients each year (Table 1).
The number of deaths from cancer was 71,944 in 2011,
74,214 in 2012, 75,848 in 2013, 77,137 in 2014, and 76,854 in
2015. In terms of cancer type, the mortality rate of lung can-
cer was the highest, at 31.8 deaths per 100,000 persons in
2011, followed by liver cancer (22.0 per 100,000), stomach
cancer (19.5 per 100,000), and colorectal cancer (15.4 per
100,000). In 2015, the mortality rate was higher for lung can-
cer (34.1 per 100,000), unchanged for liver cancer (22.2 per
100,000), lower for stomach cancer (16.7 per 100,000), and
∑(Dij+0.5 Oij)×Iij×Eij
∑(Dij+0.5 Oij)×Iij×Eij
∑{(DN)ij×( )}+ ... + +(1+r)
(It+1×Pt+1)ij
(1+r)2
(It+2×Pt+2)ij
(1+r)n
(It+n×Pt+n)ij
Cancer Res Treat. 2020;52(3):896-906
898 CANCER RESEARCH AND TREATMENT
Cancer type
Prevalence (No. of cases) Prevalence rate (per 100,000 persons)
2011 2012 2013 2014 2015 2011 2012 2013 2014 2015
Total: all patients with cancer 821,525 955,703 1,080,199 1,184,681 1,237,739 1,639.4 1,898.3 2,136.5 2,333.7 2,429.2
Male 370,098 425,252 475,855 520,228 542,446 1,475.6 1,688.3 1,882.1 2,050.2 2,130.7
Female 451,427 530,451 604,344 664,453 695,293 1,803.6 2,108.5 2,391.0 2,618.6 2,727.3
Lip, oral cavity, and pharynx 9,837 11,345 12,654 13,891 14,538 19.6 22.5 25.0 27.4 28.5
Esophagus 6,693 7,254 7,958 8,597 8,914 13.4 14.4 15.7 16.9 17.5
Stomach 102,836 119,157 134,209 147,142 149,900 205.2 236.7 265.5 289.9 294.2
Colon and rectum 88,730 104,557 117,520 128,005 132,078 177.1 207.7 232.4 252.2 259.2
Liver 53,908 57,870 61,264 64,305 66,142 107.6 114.9 121.2 126.7 129.8
Gallbladder, etc. 13,682 14,746 15,831 17,389 18,166 27.3 29.3 31.3 34.3 35.7
Pancreas 10,152 11,065 11,642 12,653 13,514 20.3 22.0 23.0 24.9 26.5
Larynx 5,160 5,745 6,344 6,797 6,891 10.3 11.4 12.5 13.4 13.5
Lung 53,630 58,994 64,425 69,623 73,392 107.0 117.2 127.4 137.2 144.0
Breast 88,594 102,950 117,583 132,084 142,123 176.8 204.5 232.6 260.2 278.9
Cervix uteri 19,578 21,797 23,996 25,737 25,778 39.1 43.3 47.5 50.7 50.6
Corpus uteri 7,578 9,142 10,749 12,140 12,949 15.1 18.2 21.3 23.9 25.4
Ovary 9,695 10,971 12,260 13,482 14,308 19.3 21.8 24.2 26.6 28.1
Prostate 37,353 44,048 50,592 56,575 60,787 74.5 87.5 100.1 111.4 119.3
Testis 960 1,156 1,354 1,521 1,648 1.9 2.3 2.7 3.0 3.2
Kidney 13,701 16,563 19,231 21,782 23,300 27.3 32.9 38.0 42.9 45.7
Bladder 18,889 21,468 23,904 26,369 27,677 37.7 42.6 47.3 51.9 54.3
Brain and CNS 9,258 9,795 10,262 10,658 10,879 18.5 19.5 20.3 21.0 21.4
Thyroid 189,711 232,852 273,130 299,967 311,584 378.6 462.5 540.2 590.9 611.5
Hodgkin lymphoma 1,230 1,464 1,626 1,795 1,838 2.5 2.9 3.2 3.5 3.6
Non-Hodgkin lymphoma 14,124 16,369 18,498 20,206 21,374 28.2 32.5 36.6 39.8 41.9
Multiple myeloma 3,948 4,585 5,042 5,647 6,119 7.9 9.1 10.0 11.1 12.0
Leukemia 12,743 14,016 15,408 16,916 18,018 25.4 27.8 30.5 33.3 35.4
Other and unspecified 49,535 57,794 64,717 71,400 75,822 98.8 114.8 128.0 140.7 148.8
CNS, central nervous system.
Table 1. Prevalence of cancer by type in 2011-2015
Young Ae Kim, Economic Burden of Cancer for 5 Years
VOLUME 52 NUMBER 3 JULY 2020 899
Cancer type
No. of deaths Mortality rate (per 100,000 persons)
2011 2012 2013 2014 2015 2011 2012 2013 2014 2015
Total cancer 71,944 74,214 75,848 77,137 76,854 143.6 147.4 150.0 152.0 150.8
Lip, oral cavity, and pharynx 943 1,039 1,082 1,100 1,170 1.9 2.1 2.1 2.2 2.3
Esophagus 1,517 1,413 1,463 1,552 1,531 3.0 2.8 2.9 3.1 3.0
Stomach 9,764 9,403 9,243 8,988 8,525 19.5 18.7 18.3 17.7 16.7
Colon and rectum 7,698 8,182 8,253 8,393 8,301 15.4 16.3 16.3 16.5 16.3
Liver 11,017 11,399 11,477 11,653 11,311 22.0 22.6 22.7 23.0 22.2
Gallbladder, etc. 3,713 3,708 3,802 3,955 4,211 7.4 7.4 7.5 7.8 8.3
Pancreas 4,406 4,809 4,865 5,150 5,439 8.8 9.6 9.6 10.1 10.7
Larynx 388 414 406 411 344 0.8 0.8 0.8 0.8 0.7
Lung 15,942 16,743 17,294 17,548 17,399 31.8 33.3 34.2 34.6 34.1
Breast 2,027 2,032 2,262 2,283 2,354 4.0 4.0 4.5 4.5 4.6
Cervix uteri 992 890 896 962 967 2.0 1.8 1.8 1.9 1.9
Corpus uteri 218 245 249 266 319 0.4 0.5 0.5 0.5 0.6
Ovary 909 914 1,043 1,024 1,055 1.8 1.8 2.1 2.0 2.1
Prostate 1,411 1,467 1,642 1,675 1,700 2.8 2.9 3.2 3.3 3.3
Testis 20 13 19 14 10 0.0 0.0 0.0 0.0 0.0
Kidney 838 924 944 953 952 1.7 1.8 1.9 1.9 1.9
Bladder 1,172 1,232 1,287 1,358 1,299 2.3 2.4 2.5 2.7 2.5
Brain and CNS 1,216 1,188 1,199 1,289 1,266 2.4 2.4 2.4 2.5 2.5
Thyroid 390 377 394 348 341 0.8 0.7 0.8 0.7 0.7
Hodgkin lymphoma 49 64 63 70 49 0.1 0.1 0.1 0.1 0.1
Non-Hodgkin lymphoma 1,393 1,532 1,598 1,580 1,693 2.8 3.0 3.2 3.1 3.3
Multiple myeloma 663 824 807 869 889 1.3 1.6 1.6 1.7 1.7
Leukemia 1,563 1,673 1,599 1,684 1,720 3.1 3.3 3.2 3.3 3.4
Other and unspecified 3,695 3,729 3,961 4,012 4,009 7.4 7.4 7.8 7.9 7.9
CNS, central nervous system.
Table 2. Number of deaths due to cancer in 2011-2015
Cancer Res Treat. 2020;52(3):896-906
900 CANCER RESEARCH AND TREATMENT
2011 2012 2013 2014 2015
Men Women Men Women Men Women Men Women Men Women
Cost % Cost % Cost % Cost % Cost % Cost % Cost % Cost % Cost % Cost %
Total 8,268.4 100.00 3,626.5 100.00 8,810.9 100.00 3,924.9 100.00 9,224.8 100.00 4,201.8 100.00 9,315.8 100.00 4,403.2 100.00 9,469.7 100.00 4,475.6 100.00
Lip, oral cavity, 168.7 2.04 31.3 0.86 207.4 2.35 33.2 0.85 212.9 2.31 42.2 1.00 221.2 2.37 41.7 0.95 247.0 2.61 42.5 0.95
and pharynx
Esophagus 199.8 2.42 9.2 0.25 193.6 2.20 10.0 0.25 215.7 2.34 10.9 0.26 231.8 2.49 11.8 0.27 230.4 2.43 10.5 0.23
Stomach 1,191.8 14.41 359.6 9.92 1,208.8 13.72 362.2 9.23 1,265.6 13.72 381.1 9.07 1,201.9 12.90 372.3 8.45 1,167.6 12.33 379.7 8.48
Colon and 918.4 11.11 395.2 10.90 990.3 11.24 412.3 10.50 1,034.0 11.21 420.9 10.02 1,048.3 11.25 434.5 9.87 1,051.9 11.11 459.0 10.26
rectum
Liver 1,881.1 22.75 220.8 6.09 1,996.3 22.66 240.9 6.14 2,043.4 22.15 251.1 5.98 2,062.5 22.14 252.2 5.73 2,020.3 21.33 245.8 5.49
Gallbladder, etc. 216.2 2.61 97.9 2.70 223.4 2.54 108.0 2.75 230.6 2.50 106.0 2.52 250.3 2.69 116.9 2.65 274.2 2.90 127.1 2.84
Pancreas 354.8 4.29 107.8 2.97 388.5 4.41 122.3 3.12 417.9 4.53 130.0 3.09 423.8 4.55 144.3 3.28 458.3 4.84 153.6 3.43
Larynx 53.1 0.64 2.4 0.07 61.0 0.69 2.1 0.05 63.0 0.68 2.5 0.06 59.4 0.64 3.1 0.07 60.2 0.64 2.6 0.06
Lung 1,310.2 15.85 310.8 8.57 1,428.8 16.22 334.3 8.52 1,516.4 16.44 357.6 8.51 1,476.8 15.85 382.9 8.70 1,538.6 16.25 390.1 8.72
Breast 4.3 0.05 780.1 21.51 3.9 0.04 851.7 21.70 3.4 0.04 963.1 22.92 4.2 0.05 1,019.0 23.14 5.1 0.05 1,044.3 23.33
Cervix uteri 0 0.00 174.1 4.80 0 0.00 176.0 4.48 0 0.00 189.6 4.51 0 0.00 202.3 4.59 0 0.00 197.3 4.41
Corpus uteri 0 0.00 47.3 1.30 0 0.00 56.8 1.45 0 0.00 59.3 1.41 0 0.00 72.5 1.65 0 0.00 74.6 1.67
Ovary 0 0.00 156.0 4.30 0 0.00 170.6 4.35 0 0.00 189.4 4.51 0 0.00 197.2 4.48 0 0.00 201.9 4.51
Prostate 231.7 2.80 0 0.00 240.8 2.73 0 0.00 265.0 2.87 0 0.00 277.1 2.98 0 0.00 294.1 3.11 0 0.00
Testis 12.2 0.15 0 0.00 11.0 0.13 0 0.00 13.3 0.14 0 0.00 13.5 0.15 0 0.00 11.2 0.12 0 0.00
Kidney 131.2 1.59 29.0 0.80 151.2 1.72 31.7 0.81 150.0 1.63 32.4 0.77 154.5 1.66 36.7 0.83 170.6 1.80 37.4 0.83
Bladder 117.8 1.42 20.3 0.56 123.7 1.40 21.0 0.54 134.5 1.46 21.4 0.51 156.8 1.68 26.8 0.61 153.1 1.62 28.6 0.64
Brain and CNS 239.3 2.89 96.3 2.66 242.5 2.75 106.7 2.72 239.1 2.59 109.1 2.60 263.5 2.83 109.4 2.48 278.1 2.94 121.8 2.72
Thyroid 72.1 0.87 254.3 7.01 85.7 0.97 298.7 7.61 102.3 1.11 320.7 7.63 91.7 0.98 317.8 7.22 77.2 0.81 249.6 5.58
Hodgkin 14.7 0.18 5.0 0.14 17.8 0.20 5.9 0.15 16.5 0.18 6.2 0.15 19.5 0.21 6.4 0.15 14.2 0.15 5.0 0.11
lymphoma
Non-Hodgkin 217.2 2.63 88.7 2.44 247.0 2.80 97.3 2.48 251.0 2.72 100.5 2.39 252.6 2.71 104.1 2.36 284.8 3.01 116.4 2.60
lymphoma
Multiple 75.4 0.91 42.6 1.18 100.0 1.13 49.1 1.25 101.4 1.10 54.0 1.29 115.1 1.24 64.7 1.47 122.0 1.29 71.6 1.60
myeloma
Leukemia 370.7 4.48 169.3 4.67 396.7 4.50 184.1 4.69 397.4 4.31 178.4 4.24 421.2 4.52 186.8 4.24 421.2 4.45 196.4 4.39
Other and 487.6 5.90 228.5 6.30 492.4 5.59 250.1 6.37 551.5 5.98 275.6 6.56 570.1 6.12 300.0 6.81 589.9 6.23 319.5 7.14
unspecified
CNS, central nervous system.
Table 3. Cost of cancer by sex in millions of US dollars for 2011-2015
Young Ae Kim, Economic Burden of Cancer for 5 Years
VOLUME 52 NUMBER 3 JULY 2020 901
higher for colorectal cancer (16.3 per 100,000) (Table 2).
The cost for all cancer patients was $11,894.9 million in
2011, $12,735.8 million in 2012, $13,426.6 million in 2013,
$13,719.0 million in 2014, and $13,945.3 million in 2015, exhi-
biting a steady increase from 2011-2015 of ~17% (Table 3). In
2011, the direct cost of disease was $5,054.9 million, and the
indirect cost was $6,839.9 million. In 2015, the direct cost was
$5,955.1 million, and the indirect cost was $7,990.2 million.
Thus, the indirect cost was relatively higher than the direct
cost (Fig. 1).
Broken down by sex, the cost for male and female patients
was $8,268.4 million and $3,626.5 million, respectively, in
2011. In 2015, the cost for men was $9,469.7 million, roughly
2.12 times the cost for women ($4,475.6 million). From 2011
to 2015, the economic burden continued to increase for both
sexes (Table 3).
In 2011, the most expensive cancers for men were liver can-
cer ($1,881.1 million), lung cancer ($1,310.2 million), stomach
cancer ($1,191.8 million), and colorectal cancer ($918.4 mil-
lion). This was also true in 2015: the cost of liver cancer was
the highest ($2,020.3 million), followed by lung cancer
($1,538.6 million), stomach cancer ($1,167.6 million), and col-
orectal cancer ($1,051.9 million). The cost of colorectal cancer
continued to increase from 2011 to 2015; the cost of lung can-
cer increased until 2013, decreased in 2014, and increased in
2015; and the cost of liver cancer increased until 2014, when
it declined modestly. The cost of stomach cancer increased
until 2013 and began decreasing in 2014.
For women, in 2011, the cost was highest for breast cancer
($780.1 million), followed by colorectal cancer ($395.2 mil-
lion), stomach cancer ($359.6 million), and lung cancer ($310.8
million). In 2015, the cost was highest for breast cancer
($1,044.3 million), followed by colorectal cancer ($459.0 mil-
lion), lung cancer ($390.1 million), and stomach cancer ($379.7
million). Since 2014, lung cancer has been more economically
burdensome than stomach cancer (Table 3).
When costs were ranked based on age, the highest costs
were incurred by those 50-59 years old ($36,464.7 million,
30.7% of all cancer costs), followed by those 40-49 years old
($2,491.1 million, 20.9%), 60-69 years old ($2,365.9 million,
19.9%), and ! 70 years old ($1,969.0 million, 16.6%). In 2015,
those 50-59 years old accounted for the highest costs ($4,309.0
million, 30.9%), followed by those 60-69 years old ($2,853.2
million, 20.5%), ! 70 years old ($2,731.0 million, 19.6%), and
40-49 years old ($2,619.0 million, 18.8%) (Fig. 2).
When a discount rate of 3% was applied (the standard for
this study) to the indirect cost calculation, the productivity
loss due to medical treatment in 2015 was $474.7 million for
the economically active population of 60 years old and
younger, $539.6 million for the population 64 years old and
younger, and $622.2 million for the population ! 65 years old.
The premature death cost for these age groups was $3,530.7
million, $4,671.9 million, and $7,367.9 million, respectively.
For the sensitivity analysis, discount rates of 5%, 3%, and 0%
were applied to calculate the economic loss due to premature
death. When a discount rate of 5% was applied to each of the
three age groups, the premature death cost was $3,140.6 mil-
lion, $4,155.8 million, and $6,447.4 million, respectively.
When no discount rate was applied (0%), the premature
death cost was $4,392.1 million, $5,806.6 million, and $9,442.9
million, respectively. Thus, the premature death cost differ-
ence was $6,302.3 million, depending on to the methodology
used. When a friction cost approach rather than human cap-
ital approach was used to calculate indirect costs, the prema-
ture death cost for the three age groups in 2015 was $176.0
USD (million)
16,000
0
4,000
Year
2011 2012 20152013 2014
12,000
8,000
Total costc)
6,839.9
11,894.9
12,735.8 13,426.6 13,719.0 13,945.3
7,361.0 7,851.6 7,787.7 7,990.2
5,054.9
5,374.9 5,574,9 5,931.3 5,955.1
Direct costa)
Indirect costb)
Fig. 1. Economic burden of cancer in millions of US dol-
lars for 2011-2015. a)Direct cost=Direct medical+Non-med-
ical costs, b)Indirect cost=Productivity+Premature death
costs, c)Total cost=Direct+Indirect costs.
USD (million)
4,000
0
1,000
Year
2011 2012 20152013 2014
3,000
2,000
0-29
30-39
40-49
50-59
60-69
≥ 70
536.7
885.5
3,646.7
1,969.0
3,954.1
4,231.7
523.7
918.7
2,254.2
2,556.7
513.2
2,458.6
922.9
504.2
924.1
2,592.4
2,688.1
4,344.8
518.3
914.8
2,619.0
2,853.2
4,309.0
2,491.1 2,731.0
2,365.9
2,528.4 2,649.4 2,665.4
2,650.9
Fig. 2. Economic burden of cancer by age group in mil-
lions of US dollars for 2011-2015.
Cancer Res Treat. 2020;52(3):896-906
902 CANCER RESEARCH AND TREATMENT
million, $210.9 million, and $278.0 million, respectively, for
the economically active populations of 60 years and younger,
64 years and younger, and 15 years and older (Table 4).
Discussion
This study estimated the socioeconomic costs for cancer
patients from 2011 to 2015 using NHIS claims data. The num-
ber of patients who received medical treatment for cancer
was 821,525 in 2011 and 1,237,739 in 2015, an increase of
approximately 50%. From 2011 to 2015, the total annual costs
for cancer patients increased by 17%, from $11,894.9 million
to $13,945.3 million. Ongoing studies of the socioeconomic
burden of cancer indicate that in countries that rank highly
on the Human Development Index, cancer is already a lead-
ing cause of death and will soon become a major cause of
death worldwide. By 2030, global cancer incidence is expec-
ted to increase by 75%, leading to an enormous increase in
the economic burden of cancer [22].
The prevalence rate of cancer in Korea increased from
1,639.4 to 2,429.2 cases per 100,000 persons between 2011 and
2015, with thyroid, stomach, breast, and colorectal cancers
being the four most common types, in that order. However,
the economic burden of disease in 2015 was the highest for
liver, lung, stomach, colorectal, and breast cancers, in that
order. Thus, the most common cancers do not necessarily
incur the highest costs. Indeed, from 2011 to 2015, liver can-
cer was the most burdensome, but it was not among the most
common cancers overall. The economic burden of liver and
stomach cancers has decreased since 2013, whereas the eco-
nomic burden of colorectal and breast cancers has steadily
increased since 2014. Although liver cancer was not one of
the most common cancers between 2011 and 2015, it had the
highest economic burden for men, followed by lung cancer,
stomach cancer, and colorectal cancer. For women, breast
cancer imparted the highest economic burden, followed by
colorectal cancer, liver cancer, and stomach cancer. Thus, the
economic burden of various cancers differs according to sex.
It is therefore necessary to consider sex when establishing
relevant policies and identify risk factors for particular can-
cer types in order to develop effective intervention and pre-
vention strategies. According to Globocan 2018, lung cancer
has the highest incidence and mortality rate of all cancers
worldwide, and one in four women is affected by breast can-
cer [1]. In light of these data, the government of South Korea
included lung cancer on the National Cancer Screening Pro-
gram form for 2019.
The economic burden of cancer among patients over 60
years old has continued to grow over time. The proportion
15-60 years old 15-64 years old ! 15 years old
Productivity loss due to Productivity loss due to Productivity loss due to
Year Productivity premature death Productivity premature death Productivity premature death
lossa)
0%b) 3%b) 5%b) Friction lossa)
0%b) 3%b) 5%b) Friction lossa)
0%b) 3%b) 5%b) Friction
costc) costc) costc)
2011 351.8 4,194.5 3,346.4 2,967.0 155.5 397.4 5,332.1 4,246.7 3,759.6 184.3 452.9 8,241.9 6,387.1 5,572.7 237.1
2012 419.5 4,266.8 3,411.4 3,028.0 162.3 473.5 5,507.3 4,397.4 3,898.0 192.3 542.8 8,790.5 6,818.2 5,950.9 252.5
2013 450.2 4,445.5 3,563.4 3,165.8 171.8 509.1 5,802.0 4,647.9 4,125.8 205.2 584.7 9,338.9 7,266.9 6,350.4 269.9
2014 474.1 4,420.4 3,559.4 3,168.9 176.8 535.2 5,773.6 4,647.3 4,134.4 210.1 610.6 9,184.1 7,177.1 6,284.7 272.9
2015 474.7 4,392.1 3,530.7 3,140.6 176.0 539.6 5,806.6 4,671.9 4,155.8 210.9 622.2 9,442.9 7,367.9 6,447.4 278.0
a)Productivity loss (opportunity costs incurred due to the time spent at outpatient visits and hospitalization), b)% indicates the applied discount rate, c)The friction
cost represents losses incurred by an employer during the defined friction period.
Table 4. Sensitivity analysis of the indirect cost of cancer in millions of US dollars for 2011-2015
Young Ae Kim, Economic Burden of Cancer for 5 Years
VOLUME 52 NUMBER 3 JULY 2020 903
of the total cost of cancer for patients aged 60 years and older
increased from 36.4% in 2011 to 40.0% in 2015, an increase of
3.6%. This trend is thought to result from increases in life
expectancy and the overall aging of the Korean population
[23], combined with higher cancer survival rates due to
advances in treatment [2]. Regardless of the reason, however,
this finding reveals that policy interventions may be required
to mitigate rising cancer costs.
The indirect costs associated with cancer increased steadily
from $6,839.9 million in 2011 to $7,990.2 million in 2015, an
increase of approximately 16.9%. Although the socioeco-
nomic cost of the disease varies according to the applied vari-
able, indirect costs could also vary depending upon how the
age of the productive population is defined. In the case of
premature death costs, a time discount rate can be applied
to calculate future costs; however, the results could vary
depending on whether a human capital approach or a fric-
tion cost approach is applied.
When calculating the socioeconomic burden of disease,
there is considerable debate surrounding methodologies for
calculating the wages of the elderly. Most studies consider
those over 65 years of age as being economically inactive
[10,20]. However, when recent wage and employment rate
data for this group were included, the economic costs increa-
sed by 22% to 28% for males and 52% to 54% for females. Fur-
thermore, when the elderly population was included, the
productive population among all age groups increased
sharply [24]; consequently, the assumption that those over
65 years of age earn no income results in underestimation of
the economic burden of disease. Therefore, we used the Min-
istry of Employment and Labor’s raw survey data to deter-
mine the actual work status of and wages earned by men and
women aged 65 years and older. The employment rate was
calculated by applying the results of the survey to the actual
work status of the elderly.
The retirement age for public servants in Korea is 60 years
[25], but not all individuals retire at that age. Therefore, in
this study, three productive population groups were consid-
ered: those 60 years old and younger, those 64 years old and
younger, and those 15 years old and older. Additionally, we
compared the results obtained by applying time discount
rates of 0%, 3%, and 5% for our sensitivity analyses. In this
study, we applied the basic discount rate of 3% to the income
of those aged ! 15 years ($13,945.3 million). The socioeco-
nomic burden of cancer ranged from $9,570.4 million (5%, 60
years old and younger) to $16,020.3 million (0%, 15 years old
and older) in 2015, a difference of 60%, depending on the
methodology used.
The friction cost approach can also be applied to the indi-
rect cost calculation, in addition to the human capital appro-
ach [26] applied in this study. The human capital approach
estimates the expected income lost due to disease morbidity
or premature death from the patient’s perspective, whereas
the friction cost approach calculates costs from an employer’s
perspective. Therefore, the friction cost approach calculates
the losses incurred until the patient’s workload is reassigned
or a replacement is hired [27], and it only reflects the value
of the substitute employee during the friction period. The
human capital approach has the limitation that the loss could
be overestimated because it measures potential loss without
considering the possibility of labor substitution [28]. How-
ever, the friction period can vary from 3-4 months to 22 weeks,
or to 58 days based on country, occupation, and specific dis-
ease [15].
Canada, which periodically calculates the economic bur-
den of all diseases, recently reported these costs for 2005-2008
and 2010 calculated using the friction cost approach [15]. In
Canada, the cost of premature death due to cancer was $278
million in 2010. Unfortunately, there were not enough Korean
data available to accurately determine a friction period in the
present study; therefore, the Canadian friction period was
used to calculate a friction cost of $278 million in 2015 for
those ! 15 years of age in Korea. When defining the age of
the economically active population as those under 60 years
old, the friction cost was $176 million. A comparison of the
friction cost for those under 60 years old to the highest cost
of premature death in our study ($9,442.9 million) showed
that estimated costs can vary by up to 192.8%, depending on
the applied variables.
This study has several limitations. First, the data used in
this study were limited. Only NHIS insurance claims data
were used to calculate the cost of cancer to patients, and these
data are limited because the system was created for the pur-
pose of claims processing [29]; thus, the scope and scale of
any non-benefit service items could not be determined [30].
To compensate for this limitation, non-benefit service costs
were estimated using the coinsurance rate of non-benefit
services based on the “Report on the Actual Status of Medical
Service Cost of Health Insurance Patients,” published by the
NHIS. Moreover, this study failed to consider differences in
economic activities and wages earned between women and
men. In the case of women, if a wider range of costs is app-
lied by including household activities (such as childrearing)
in addition to economic activities, the socioeconomic burden
of cancer is expected to be higher. There are also limitations
related to cost items. In this study, all other costs, including
informal medical costs, were excluded from the calculations.
Therefore, there were limitations in estimating the costs of
purchasing assistive devices and medicines, costs of exercise
and diet management, and the use of medical services, such
as complementary, alternative, and traditional medicine. Fol-
low-up studies should determine a more precise scale of
costs.
Despite these limitations, this study estimated the socioe-
Cancer Res Treat. 2020;52(3):896-906
904 CANCER RESEARCH AND TREATMENT
conomic burden on cancer patients from 2011 to 2015 using
the latest Korean data— the NHIS claims data and Statistics
Korea’s death data. The economic burden for each of 24 can-
cer types was also determined based on indirect cost calcu-
lations. During the period 2011 to 2015, the economic burden
of cancer increased and is expected to increase further. Fol-
low-up studies aimed at predicting the future economic bur-
den of cancer in Korea using trend analyses could be desig-
ned based on the results of this study. The results of these
follow-up studies could then be used as the basis for allocat-
ing limited health care resources and guiding the decisions
of policymakers. To reduce the disease burden of cancer, it
will be necessary to emphasize changes in lifestyle and pro-
mote early cancer detection and treatment [21]. Social and
national efforts should continue to establish measures and
policies for improving the quality of life for patients and
reducing their psychological pain and economic burden.
Conflicts of Interest
Conflict of interest relevant to this article was not reported.
Acknowledgments
This work was supported by grants from the National Cancer
Center, Republic of Korea (grant numbers 16103103 and 19101711).
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