Article

The health burden and economic costs of cutaneous melanoma mortality by race/ethnicity–United States, 2000 to 2006

Division of Cancer Prevention and Control, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia 30341, USA.
Journal of the American Academy of Dermatology (Impact Factor: 4.45). 11/2011; 65(5 Suppl 1):S133-43. DOI: 10.1016/j.jaad.2011.04.036
Source: PubMed

ABSTRACT

Cutaneous melanoma is the most deadly form of skin cancer with more than 8000 deaths per year in the United States. The health burden and economic costs associated with melanoma mortality by race/ethnicity have not been appropriately addressed.
We sought to quantify the health burden and economic costs associated with melanoma mortality among racial/ethnic groups in the United States.
We used 2000 to 2006 national mortality data and US life tables to estimate the number of deaths, and years of potential life lost (YPLL). Further, we estimated the economic costs of melanoma mortality in terms of productivity losses. All the estimates were stratified by race/ethnicity and sex.
From 2000 to 2006, we estimated an increase of 13,349 (8.7%) YPLL because of melanoma mortality compared with a 2.8% increase among all malignant cancers across all race/ethnicity. On average, an individual in the United States loses 20.4 years of potential life during their lifetime as a result of melanoma mortality compared with 16.6 years for all malignant cancers. The estimated annual productivity loss attributed to melanoma mortality was $3.5 billion. Our estimates suggest that an individual who died from melanoma in 2000 through 2006 would lose an average of $413,370 in forgone lifetime earnings. YPLL rates and total productivity losses are much higher among non-Hispanic whites as compared with non-Hispanic blacks and Hispanics.
The estimated economic costs did not include treatment, morbidity, and intangible costs.
We estimated substantial YPLL and productivity losses as a result of melanoma mortality during an individual's lifetime. By examining the burden by race/ethnicity, this study provides useful information to assist policy-makers in making informed resource allocation decisions regarding cutaneous melanoma mortality.

Full-text

Available from: Pratibha Nayak
The health burden and economic costs of cutaneous
melanoma mortality by race/ethnicityeUnited
States, 2000 to 2006
Donatus U. Ekwueme, MS, PhD,
a
GeryP.Guy,Jr,MPH,PhD,
a
Chunyu Li, MD, PhD,
a
Sun Hee Rim, MPH,
a
Pratibha Parelkar, MPH,
b
andSuephyC.Chen,MS,MD
c,d
Atlanta, Georgia, and Houston, Texas
Background: Cutaneous melanoma is the most deadly form of skin cancer with more than 8000 deaths per
year in the United States. The health burden and economic costs associated with melanoma mortality by
race/ethnicity have not been appropriately addressed.
Objective: We sought to quantify the health burden and economic costs associated with melanoma
mortality among racial/ethnic groups in the United States.
Methods: We used 2000 to 2006 national mortality data and US life tables to estimate the number
of deaths, and years of potential life lost (YPLL). Further, we estimated the economic costs of
melanoma mortality in terms of productivity losses. All the estimates were stratified by race/ethnicity
and sex.
Results: From 2000 to 2006, we estimated an increase of 13,349 (8.7%) YPLL because of melanoma
mortality compared with a 2.8% increase among all malignant cancers across all race/ethnicity. On average,
an individual in the United States loses 20.4 years of potential life during their lifetime as a result of
melanoma mortality compared with 16.6 years for all malignant cancers. The estimated annual productivity
loss attributed to melanoma mortality was $3.5 billion. Our estimates suggest that an individual who died
from melanoma in 2000 through 2006 would lose an average of $413,370 in forgone lifetime ear nings. YPLL
rates and total productivity losses are much higher among non-Hispanic whites as compared with
non-Hispanic blacks and Hispanics.
Limitations: The estimated economic costs did not include treatment, morbidity, and intangible costs.
Conclusions: We es timated substantial YP LL a nd prod uctivity losses as a result of melanoma mortality
during an individual’s li fetime. By examining the burden b y race/ethnicity, this study provides useful
information to assist policy-makers in making informed resource allocation decisions regarding
cutaneous melanoma mortality. ( J Am Acad Dermatol 2011;65:S133-43.)
Key words: cancer; economic cost; melanoma; mortality; productivity loss; race/ethnicity; years of potential
life lost.
From the Division of Cancer Prevention and Control, National
Center for Chronic Disease Prevention and Health Promotion,
Centers for Disease Control and Prevention, Atlanta
a
; Depart-
ment of Health Promotion and Behavioral Sciences, University
of Texas
b
; Department of Dermatology, Emory University,
Atlanta
c
; and Division of Dermatology, Atlanta Department of
Veterans Affairs Medical Center
d
.
Publication of this supplement to the JAAD was supported by the
Division of Cancer Prevention and Control, Centers for Disease
Control and Prevention (CDC).
Conflicts of interest: None declared.
The opinions or views expressed in this supplement are those of
the authors and do not necessarily reflect the opinions,
recommendations, or official position of the journal editors or
the Centers for Disease Control and Prevention.
Please see Appendix 1 for a glossary of technical terms used in this
article.
Accepted for publication April 20, 2011.
Reprint requests: Donatus U. Ekwueme, PhD, MS, Division of
Cancer Prevention and Control, Centers for Disease Control and
Prevention, 4770 Buford Highway NE, MS K-55, Atlanta, GA
30341. E-mail: dce3@cdc.gov.
0190-9622/$36.00
Ó 2011 by the American Academy of Dermatology, Inc.
doi:10.1016/j.jaad.2011.04.036
S133
Page 1
Cutaneous melanoma (hereafter called mela-
noma) is the third most common form of skin cancer
after basal and squamous cell carcinomas. It is a
deadly form of skin cancer with more than 8000
deaths per year.
1
The average lifetime risk of devel-
oping melanoma in the United States has increased
from 1 in 1500 in 1935 to 1 in 30 in 2009.
2,3
As a
result, the health burden
measured by mortality asso-
ciated with melanoma has
increased over time and is
reported to disproportion-
ately affect non-Hispanic
whites and other racial/eth-
nic groups with fair-skinned
complexion.
4,5
Quantifying health status
in human populations is of-
ten measured by mortality;
however, mortality does not
fully address the issue of pre-
mature deaths, particularly
among younger popula-
tions.
6,7
An alternative mea-
sure to use is years of
potential life lost (YPLL),
which provides a more accu-
rate measure of mortality for
the young and the elderly
population.
7,8
The burden
of melanoma disease mea-
sured by using YPLL by
race/ethnicity has not been
satisfactorily addressed.
The economic costs asso-
ciated with melanoma have
been estimated to be sub-
stantial. Past studies have
reported the costs of melanoma using various eco-
nomic methods.
9-11
For instance, Bickers et al
9
(2006) and Bradley et al
10
(2008) used the human
capital approach (HCA) to estimate the cost of lost
productivity caused by melanoma to range from $2.9
billion in 2004 dollars to $3.3 billion in 2010 dollars.
The HCA values labor and household productivity
that an individual contributes to society.
12
Alternatively, Yabroff et al
11
(2008) used the
willingness-to-pay method to estimate the value of
life lost to society as a result of melanoma to be $15.1
billion in 2000 dollars with a projected increase to
$21.6 billion in 2020. The willingness-to-pay method
measures the amount of money or resources an
individual would pay to reduce the probability of
illness or dying from melanoma.
13
This method is
more comprehensive as it includes costs of lost
productivity and intangible costs such as pain and
suffering caused by melanoma. These economic
studies have provided strong evidence of the sub-
stantial costs attributed to melanoma at the societal
level. However, information on economic costs as-
sociated with melanoma among racial/ethnic gr oups
is not currently available in the literature.
The purpose of this study
is 2-fold: first, we quantified
the health burden associated
with melanoma mortality
measured by YPLL. Second,
we estimated the economic
costs associated with mela-
noma mortality measured by
the value of lifetime produc-
tivity losses. We compared
the findings with estimates
from 4 major cancers (ie, fe-
male breast [breast], prostate,
colorectal, and lung/bron-
chus [lung]) and all malig-
nant cancers. All the
estimates were stratified by
race/ethnicity.
METHODS
We used 3 broad mea-
sures of disease burden to
quantify the magnitude of
melanoma and compared its
impact relative to the 4 major
cancers listed above and
against all malignant cancers.
These burden measures in-
cluded mortality, YPLL, and
the value of productivity los-
ses from mortality. Mortality
associated with melanoma, the 4 major cancers, and
all malignant cancers were used in conjunction with
data from the US life tables, and from the literature to
estimate YPLL and the value of productivity loss
caused by mortality. We constructed a model of
disease burden to estimate foregone lifetime pro-
ductivity lost in terms of incidence-based costs as
opposed to prevalence-based costs.
14-16
Productivity
losses were measured using the HCA.
17-19
This ap-
proach values labor productivity acquired through
an investment in education, on-the-job training, and
work experience,
20
and the value of nonwage labor
productivity performed in the household.
Data sources and extraction
We used the Surveillance, Epidemiology, and End
Results (SEER)*Stat software (Version 6.5.2) to extrac t
CAPSULE SUMMARY
d
An individual who died from mela noma
in the past 7 years (ie, 2000-2006) would
lose an average of $413,370 in forgone
lifetime earnings, whereas for all
malignant cancers an individual would
lose $309,879.
d
On average, women lose 21.4 years of
potential life during their lifetime
because of melanoma compared with
19.0 years for men.
d
Women have higher premature mortality
associated with melanoma tha n men.
d
Non-Hispanic whites have a higher
health burden and economic cost
associated with melanoma mortality.
d
These findings underscore the
importance of prevention, early
detection, and effective treatment.
d
The results presented in this article
should be viewed as one of the best
available estimates to quantify the
burden of melanoma mortality by race/
ethnicity compared with 4 major cancers
and all malignant cancers.
JAM ACAD DERMATOL
NOVEMBER 2011
S134 Ekwueme et al
Page 2
cancer mortality and associated population data that
cover 100% of US deaths.
21
The mortality data from
SEER*Stat for melanoma; breast, prostate, colorectal,
and lung cancer; and for all malignant cancers from
2000 to 2006 were obtained from the Centers fo r
Disease Control and Prevention National Vital
Statistics Surveillance System.
22
Mortality from mel-
anoma and the 4 major cancers were coded as the
underlying cause of death at primary cancer site
using the International Statistical Classification of
Diseases, 10th Revision with C43 for melanoma; C50
for breas t, C61 for prostate, C18 to C21 for colorectal,
and C33 to C34 for lung cancers; and C00 to C97 for
all malignant cancers.
23
The population denominator data from
SEER*Stat were used for calculating crude rates
and age-adjusted rates were obtained from the
2000 US C ens us.
24
All rates are expressed per
100,000 population. We extracted data on individ-
uals aged 15 years or older, by 5-year age groups
andsex.Weexcludedindividualsaged0to14years
because no deaths from melanoma were reported in
this age group. We constructed 4 mutually exclusive
racial/ethnic categories: non-Hispanic white, non-
Hispanic black, non-Hispanic other (ie, Asian/
Pacific Islanders and A merican Indian/Alas ka
Natives), and Hispanic.
Estimation of YPLL, average YPLL, YPLL rates,
and age-adjusted rates
We used the life expectancy method to calculate
YPLL
7,8,16
rather than using an arbitrary age cutoff of
70 or 75 years that has been used in previous
studies.
25-27
This method is defined as the expected
YPLL because of a particular disease, such as mela-
noma, during an individual’s lifetime.
8
We believed
that this approach is appropriate in particular to
cancer where the majority of deaths are highly skewed
toward the elderly population. Based on this method,
we calculated YPLL in each 5-year age group by
the corresponding remaining life expectancy ob-
tained from the 2000 to 2006 US life tables.
28-35
The estimated number of YPLL in each 5-year
age group was summed to obtain the total YPLL
for melanoma, 4 major cancers, and all malignant
cancers in individuals aged 15 years or older. The
estimation was stratified by race/ethnicity and sex.
Because current life tables do not report life expec-
tancy for Asian/Pacific Islanders and American
Indian/Alaska Natives, we used the life tables data
on all races as a proxy for non-Hispanic other.
28-35
To
compare YPLL across racial/ethnic groups, we esti-
mated crude and age-adjusted rates (YPLL/100,000
population). Age-adjusted rates were calculated by
the direct method, using the 2000 US standard
population by 5-year groups.
36
Further, we examined
mortality from melanoma and other major cancers in
non-Hispanic whites compared with each racial/
ethnic group by calculating rates and rate ratios. We
used the YPLL rates in non-Hispanic whites as the
referent. In addition to the estimation of YPLL, we
also calculated average YPLL, crude rates, and rate
ratios by race/ethnicity. We also calculated absolute
change in mortality and YPLL for 2000 and 2006,
percent change, and percent contribution of each of
the 4 major cancer sites compared with melanoma.
Estimation of mortality costs
Productivity costs caused by premature mortality
from melanoma, 4 other major cancers, and all
malignant cancers were estimated using the number
of deaths in 2006 multiplied by the present value of
future lifetime earnings (PVFLE) stratified by age,
sex, and race/ethnicity. The data on the PVFLE were
obtained from a published study.
37
The PVFLE esti-
mate took into account factors such as life expec-
tancy, labor force participation rate, future growth
rate in productivity, and imputed value of house-
keeping services (eg, cooking, cleaning, childcare).
We applied a 3% discount rate in estimating the
PVFLE and examined how our results changed when
we applied a 0% and a 5% discount rate. The
discount rate was used to convert future earnings
for these people who died to present value.
13
In
addition to estimating the total PVFLE lost caused by
melanoma mortality, we also estimated the total
PVFLE from 4 major cancers and all malignant
cancers. We also estimated the cost of premature
death on an individual level. All costs presented in
this study were standardized to 2006 US dollars.
RESULTS
Years of potential life lost
In 2000 and 2 006, a total of 7419 and 8437
Americans died from melanoma, respectively,
which repr esen ted an increase of 1018 (13.7%)
deaths. These deaths accounted for an estimated
152,912 to 166,261 YPLL, representing an increase
of 13,349 (8.7%) in premature mortality from 2000
to 2006 compared with 2.8% premature mortality
for all malignant cancers (Table I). On average, an
Abbreviations used:
HCA: human capital approach
PVFLE: present value of future lifetime earnings
SEER: Surveillance, Epidemiology, and
End Results
YPLL: years of potential life lost
JAM ACAD DERMATOL
VOLUME 65, NUMBER 5
Ekwueme et al S135
Page 3
Table I. Contribution of individual cancer sites to increase or decrease in deaths and years of potential life lost by sex, 2000 to 2006*
Mortality YPLL
2000-2006
Cancer sites by sex
Total
2000
Total
2006
Absolute
change
%
Change
y
%
Contribution
z
Total
2000
Total
2006
Absolute
change
%
Change
y
%
Contribution
z
Per
deaths
x
Crude
rate
k
Age-
adjusted
rate
k
Male
All malignant
cancers
285,220 289,311 4091 1.43 4,288,300 4,474,493 186,193 4.34 15.4 3962.6 4234.2
Melanoma 4591 5474 883 19.23 18.9 87,739 100,171 12,432 14.17 338.1 19.0 84.6 87.6
Prostate 31,078 28,371 2707 8.71 57.9 297,876 280,960 16,916 5.68 460.1 9.9 262.3 310.2
Colorectal 28,481 26,800 1681 5.90 36.0 413,314 410,030 3284 0.78 89.3 15.1 373.4 400.5
Lung and bronchus 90,407 89,240 1167 1.29 25.0 1,373,535 1,377,627 4092 0.30 111.3 15.5 1245.0 1328.8
Total
{
154,557 149,885 4672 3.33 100.0 2,172,465 2,168,788 3677 7.99 100.0
Female
All malignant
cancers
266,334 269,209 2875 1.08 4,590,923 4,672,555 81,633 1.78 17.5 3957.6 3737.8
Melanoma 2828 2963 135 4.77 15.5 61,131 61,656 525 0.86 1.6 21.4 51.9 50.3
Female breast 41,872 40,819 1053 2.51 121.2 838,987 824,370 14,617 1.74 44.7 20.3 711.8 681.8
Colorectal 28,949 26,395 2554 8.82 293.9 418,186 399,100 19,086 4.56 58.4 14.9 347.7 322.7
Lung and bronchus 65,014 69,355 4341 6.68 499.5 1,122,180 1,188,059 65,879 5.87 201.5 17.4 993.4 934.9
Total
{
138,663 139,532 869 0.11 100.0 2,440,484 2,473,185 32,701 0.42 100.0
Male and female
All malignant
cancers
551,554 558,520 6966 1.26 9,012,445 9,261,924 249,478 2.77 16.6 4015.9 3993.1
Melanoma 7419 8437 1018 13.72 2367.4 152,912 166,261 13,349 8.73 30.8 20.4 69.7 69.3
Colorectal 57,430 53,195 4235 7.37 9848.8 846,087 821,322 24,766 2.93 57.1 15.3 366.3 364.3
Lung and bronchus 155,421 158,595 3174 2.04 7381.4 2,561,079 2,615,885 54,807 2.14 126.3 16.7 1141.2 1135.5
Total
{
220,270 220,227 43 8.39 100.0 3,560,078 3,603,467 43,389 7.94 100.0
Grand total
#
293,320 289,417 3803 1.30 54.6 4,774,536 4,692,358 82,178 1.72 32.9 16.3 2063.3 2052.5
YPLL, Years of potential life lost.
*Data presented are for all races/ethnicities age 151 (5-year age group).
y
Calculated by dividing the absolute change for each cancer site by the number of deaths or YPLL in 2000.
z
The percent contribution is based on each cancer site’s contribution in increasing or decreasing portion of the number of cancer deaths or YPLL divided by the sum of absolute change in mortality
or premature deaths.
x
YPLL per death was calculated by dividing the estimated number of YPLL in each cancer site by the number of deaths that occurred prematurely.
k
Rates and age-adjusted rates are per 100,000 persons. Age-adjusted rates were calculated by the direct method using the 2000 US standard population in 5-year groups (ie, ages 15-19 years, 20-24
years, . . ., 851 years; see Surveillance Epidemiology, and End Results Program 2007).
21
{
Total excludes data from all malignant cancers.
#
Grand total is the combination of the following major cancers: melanoma, breast, colorectal, prostate, and lung and bronchus. For the four major cancers (ie, breast, colorectal, prostate, and lung
and bronchus) the estimated YPLL per death was 16.2.
JAM ACAD DERMATOL
NOVEMBER 2011
S136 Ekwueme et al
Page 4
individual in the United States could lose 20.4 years
of potential life during his or her lifetim e because of
melanoma mortality, which is greater than 16.2
years for the 4 major cancers (ie, breast, prostate,
colorectal, and lung), and 16.6 years for all malig-
nant c ancers.
For men, we estimated an increase of 883 deaths
caused by melanoma and an estimated increase of
12,432 YPLL. This estimate represents an 18.9%
increase in melanoma contribution to mortality
among the 4 major cancers. These 4 major cancers
contributed to a 25% to 58% decrease in cancer
mortality (Table I). For women, we estimated an
increase of 135 melanoma deaths and an estimated
increase of 525 YPLL . For the 7-year period (2000-
2006), we estimated 21.4 YPLL per death caused by
melanoma compared with YPLL per death ranging
from 14.9 for colorectal cancer to 20.3 for breast
cancer. In both men and women, the estimated
overall age-adjusted YPLL rate for melanoma was
69.3 per 100,000, 87.6 per 100,000 for men, and 50.3
per 100,000 for women.
In general, men had a 6.5 times (883/135) higher
mortality from melanoma than women. However, on
an individual basis, the impact of premature mortal-
ity measured by YPLL per death was higher in
women (21.4) than in men (19.0). This implies that
although men may have higher mortality burden
associated with melanoma, the disease affects
women at a younger age. This point is clearly
illustrated in Fig 1, which demonstrates that the
proportion of YPLL as a result of melanoma relative
to YPLL from all malignant cancers varied by age and
sex. Overall, men had the largest relative contribu-
tion to YPLL starting from age 25 yea rs through the
remainder of their lives, with the greatest contribu-
tion at age 30 to 34 years. On the other hand, women
have relative contributions to YPLL starting at age 20
years through the remainder of their lives, with the
greatest contribution at age 25 to 29 years.
We estimated 1.1 million (95.5%) YPLL as a result
of melanoma in non-Hispanic whites, 25,337 (2.3%)
in Hispanics, and 14,861 (1.3%) in non-Hispan ic
blacks (Table II ). For non-Hispanic whites, the
estimated YPLL rate was 87.7 per 100,000. Using
non-Hispanic whites as the reference group the
estimated YPLL rate ratio ranged from 0.1 to 0.2 for
non-Hispanic blacks and Hispanics, respectively.
Melanoma accounted for 1.8% of the estimated
63.6 million YPLL among all malignant cancers.
Among the 4 major cancers and melanoma, we
estimated a total of 32.8 million YPLL from 2000 to
2006; of which, melanoma accounted for 3.4%.
Prostate accounted for 6.1%, colorectal and breast
cancers each accounted for 17.6%, and lung
accounted for 55.2% (Table II). In the past 7 years,
these 4 major cancers and melanoma accou nted for
an average of 52.6% of mortality and 51.6% of YPLL
that have occurred among all malignant cancers
(data not shown). The relative contributions of
each of these 4 cancer sites to mortality and YPLL
are presented in Appendix 2.
Mortality-related productivity costs
In 2006, the estimated lifetime cost associated
with melanoma mortality discounted at 3% rate was
$3.5 billion (discount rate range from 5%-0%: $2.9-
$5.1 billion) (Table III). At an individual level, we
estimated this cost to be $413,370 (discount rate
range from 5%-0%: $338,469-$602,265) per death.
Deaths among men accounted for $2.4 billion (dis-
count rate range from 5%-0%: $2.0-$3.5 billion) of
lost productivity (or 67.1% of the total), with an
average cos t per death of $441,903 (discount rate
range from 5%-0%: $365,268-$630,438). Deaths
among wome n accounted for $1.2 billion (discount
rate range from 5%-0%: $0.9-$1.8 billion) of lost
productivity (or 32.9% of the total), with an average
cost per death of $401,046 (discount rate range from
5%-0%: $324,925-$598,214).
In the order of lowest to highest, the estimated
racial/ethnic-specific lifetime mortality cost associ-
ated with melanoma was $28.6 million (discount rate
range from 5%-0%: $23.1-$43.3 million) with an
average cos t per death of $461,795 (discount rate
range from 5%-0% : $372,372-$697,735) for non-
Hispanic other; $50.9 million (discount rate range
from 5%-0%: $41.5-$75.1 million) with average cost
per death of $413,913 (discount rate range from
5%-0%: $337,063-$610,804) for non-Hispanic blacks;
$110.8 million (discount rate range from 5%-0%:
$88.4-$170.5 million) with average cost per death of
Fig 1. Proportion of years of potential life lost (YPLL)
because of melanoma relative to years of potential life lost
because of all malignant cancers, by age at death and
sexeUnited States, 2000 to 2006.
JAM ACAD DERMATOL
VOLUME 65, NUMBER 5
Ekwueme et al S137
Page 5
$545,795 (discount rate range from 5%-0%: $435,604-
$840,317) for Hispanics; and $3.3 billion (discount
rate range from 5%-0%: $2.7-$4.8 billion) with aver-
age cost per death of $409,814 (discount rate range
from 5%-0%: $335,910-$595,654) for non-Hispanic
whites.
DISCUSSION
In this study, we quantified the burden of mela-
noma mortality measured by YPLL and the associ-
ated economic costs by race/ethnicity from 2000 to
2006. The results were summarized in two broad
measures of cancer disease burden. First, for men
and women, we estimated an increase in YPLL of
13,349 or 8.7% between 2000 to 2006 as a result of
melanoma compared with a 2.8% increase in all
malignant cancers. On the other hand, there was a
decrease in YPLL of 2.0% among the 4 major cancers
confirming reports that melanoma mor tality has
increased in recent years compared with other can-
cer sites.
3,38,39
In general, the increase in melanoma
mortality and YPLL is substantially higher in men
than in women. However, on an individual basis and
in all race/ethnicity, YPLL per melanoma death is
higher among women, which implies that this cancer
affects women at a younger age than men. This
finding is consistent with other published studies that
have reported primarily on melanoma in adolescent
and young adults.
40,41
The observed difference in
premature deaths cau sed by melanoma in young
women and men may be a result of the increased use
of indoor tanning particularly by white females aged
Table II. Years of potential life lost, rate, and rate ratio by sex, cancer site, and race/ethnicityeUnited States,
2000 to 2006
Cancer site by race/
ethnicity
Male Female Total*
No. of
YPLL
YPLL rate/
100,000
Rate
ratio
No. of
YPLL
YPLL rate/
100,000
Rate
ratio
No. of
YPLL
YPLL rate/
100,000
Rate
ratio
Melanoma of skin
Non-Hispanic white 638,306 110.1 1.00 405,365 63.9 1.00 1,072,150 87.7 1.00
Non-Hispanic black 6722 9.6 0.09 7945 8.8 0.14 14,861 9.3 0.11
Non-Hispanic other
y
3727 11.3 0.10 3906 9.8 0.15 7714 10.6 0.12
Hispanic 13,514 19.9 0.18 11,228 15.1 0.24 25,337 17.7 0.20
Prostate
Non-Hispanic white 1,526,865 279.3 1.00 eeeeee
Non-Hispanic black 360,060 701.8 2.51 eeeeee
Non-Hispanic other
y
29,550 132.0 0.47 eeee ee
Hispanic 90,587 235.9 0.84 eeee ee
Female breast
Non-Hispanic white eee4,430,911 668.7 1.00 eee
Non-Hispanic black eee890,571 947.5 1.42 eee
Non-Hispanic other
y
eee157,940 390.6 0.58 eee
Hispanic eee314,905 433.1 0.65 eee
Colorectal
Non-Hispanic white 2,276,469 393.2 1.00 2,194,289 311.8 1.00 4,547,584 355.4 1.00
Non-Hispanic black 359,571 551.7 1.40 413,951 466.3 1.50 787,242 510.8 1.44
Non-Hispanic other
y
80,392 264.8 0.67 81,514 221.6 0.71 164,122 244.4 0.69
Hispanic 148,854 274.5 0.70 141,987 475.9 1.53 297,489 249.6 0.70
Lung and bronchus
Non-Hispanic white 8,009,140 1363.1 1.00 6,982,839 1010.9 1.00 15,299,351 1191.8 1.00
Non-Hispanic black 1,100,515 1683.1 1.23 817,253 921.2 0.91 1,993,514 1288.4 1.08
Non-Hispanic other
y
196,756 682.0 0.50 156,075 435.4 0.43 361,363 558.3 0.47
Hispanic 275,255 269.6 0.20 176,761 288.6 0.29 471,798 424.6 0.36
All malignant cancers
Non-Hispanic white 24,633,682 4243.1 1.00 25,807,186 3786.3 1.00 51,129,883 4022.9 1.00
Non-Hispanic black 3,542,571 5417.0 1.28 3,992,467 4408.8 1.16 7,675,704 4887.4 1.21
Non-Hispanic other
y
791,498 2600.1 0.61 886,985 2357.4 0.62 1,695,035 2486.5 0.62
Hispanic 1,481,043 2652.0 0.63 1,610,858 2371.1 0.63 3,141,607 2518.3 0.63
YPLL, Years of potential life lost.
Data presented are for all age groups starting from age 151 (5-year age group).
*Total includes male and female.
y
Includes Asian/Pacific Islanders and American Indian/Alaska natives.
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S138 Ekwueme et al
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Table III. Estimated present value of future lifetime lost productivity by sex, cancer site, and race/ethnicityeUnited States, 2006
Male
Female Total
Cancer site by
race/ethnicity
Discounted
total cost, $ 3 10
6
3% (5%-0%)
Discounted total
cost per death
3% (5%-0%)
Discounted total
cost, $ 3 10
6
3% (5%-0%)
Discounted total
cost per death
3% (5%-0%)
Discounted total
cost, $ 3 10
6
3% (5%-0%)
Discounted total
cost per death
3% (5%-0%)
Melanoma of skin
All race/ethnicity
2419.0 (1999.5-3451.0) 441,903 (365,268-630438) 1188.3 (962.8-1772.5) 401,046 (324,925-598,214) 3487.6 (2855.7-5081.3) 413,370 (338,469-602,265)
Non-Hispanic white
2306.1 (1908.1-3282.4) 437,751 (362,212-623,076) 1105.3 (896.4-1644.6) 398,156 (322,921-592,432) 3296.5 (2702.1-4791.4) 409,814 (335,910-595,654)
Non-Hispanic black
30.6 (25.0-44.8) 471,292 (385,351-689,398) 21.6 (17.5-32.1) 372,262 (302,134-553,169) 50.9 (41.5-75.1) 413,913 (337,063-610,804)
Non-Hispanic other*
13.8 (11.3-20.2) 461,389 (377,042-674,340) 14.9 (11.9-23.3) 466,896 (371,739-727,428) 28.6 (23.1-43.3) 461,795 (372,372-697,735)
Hispanic
68.2 (54.8-103.3) 625,822 (502,686-948,158) 46.0 (36.5-71.9) 489,165 (387,961-764,977) 110.8 (88.4-170.6) 545,795 (435,604-840,317)
Prostate
All race/ethnicity
4753.7 (4151.7-6026.0) 167,556 (146,335-212,401) ee e e
Non-Hispanic white
3462.2 (3031.3-4365.8) 158,569 (138,832-199,953) ee e e
Non-Hispanic black
943.2 (817.1-1216.0) 202,876 (175,767-261,559) ee e e
Non-Hispanic other*
77.5 (67.8-97.7) 167,691 (146,764-211,457) ee e e
Hispanic
262.8 (228.4-336.5) 191,410 (166,335-245,063) ee e e
Female breast
All race/ethnicity
ee15,490.5 (12,704.8-22,427.5) 379,491 (311,248-549,438) ee
Non-Hispanic white
ee11,157.3 (9202.6-15,958.1) 347,439 (286,571-496,935) ee
Non-Hispanic black
ee2766.4 (2237.6-4123.4) 491,281 (397,372-732,261) ee
Non-Hispanic other*
ee481.2 (390.5-711.7) 499,649 (405,528-739,032) ee
Hispanic
ee1064.9 (857.0-1605.1) 518,462 (417,215-781,445) ee
Colorectal
All race/ethnicity
8753.6 (7389.9-11,928.6) 326,626 (275,743-445,098) 6927.4 (5780.5-9687.0) 262,451 (219,000-367,003) 15,345.1 (12,866.2-21,227.1) 288,468 (241,869-399,043)
Non-Hispanic white
6489.3 (5496.4-8782.7) 305,811 (259,021-413,886) 5090.4 (4270.7-7033.5) 242,541 (203,485-335,122) 11,328.2 (9537.8-15,530.2) 268,390 (225,972-367,944)
Non-Hispanic black
1379.7 (1155.4-1909.9) 406,508 (340,431-562,743) 1130.6 (932.5-1619.2) 333,914 (275,388-478,199) 2456.5 (2040.5-3463.1) 362,322 (300,955-510,776)
Non-Hispanic other*
498.8 (412.4-711.3) 362,472 (299,724-516,951) 236.0 (193.2-344.5) 344,552 (282,082-502,877) 498.8 (412.4-711.3) 362,472 (299,724-516,951)
Hispanic
588.0 (489.9-824.7) 408,925 (340,654-573,530) 462.0 (377.3-677.9) 352,412 (287,769-517,105) 1029.5 (848.8-1478.0) 374,514 (308,760-537,641)
Lung and bronchus
All race/ethnicity
27,310.2 (23,295.0-36,347.6) 306,031 (261,037-407,301) 19,367.8 (16,229.8-26,736.2) 279,257 (234,011-385,497) 45,735.9 (38,636.9-62,097.0) 288,381 (243,620-391,545)
Non-Hispanic white
21,898.1 (18,711.2-29,037.8) 293,336 (250,645-388,976) 16,124.5 (13,540.8-22,152.9) 270,091 (226,814-371,071) 37,300.8 (31,570.7-50,436.0) 277,635 (234,985-375,402)
Non-Hispanic black
3814.0 (3227.2-5160.5) 391,900 (331,612-530,265) 2306.7 (1911.6-3260.5) 348,543 (288,849-492,665) 5958.6 (4987.8-8247.5 364,438 (305,067-504,435)
Non-Hispanic other*
662.0 (561.3-892.4) 340,017 (288,305-458,342) 427.7 (354.9-604.1) 317,769 (263,644-448,794) 1065.4 (893.4-1470.9) 323,549 (271,299-446,672)
Hispanic
882.1 (749.2-1185.1) 321,242 (272,841-431,585) 487.0 (404.1-688.4) 302,891 (251,329-428,110) 1337.6 (1122.8-1842.8) 307,204 (257,879-423,250)
All malignant cancers
All race/ethnicity
94,258.7 (79,460.3-129,101.7) 325,804 (274,653-446,239) 81,518.1 (67,524.8-115,794.4) 302,806 (250,827-430,128) 173,073.5 (144,555.6-241,634.1) 309,879 (258,819-432,633)
Non-Hispanic white
72,427.7 (61,284.2-98,378.4) 306,972 (259,743-416,960) 62,179.4 (51,756.7-87,361.2) 283,621 (236,080-398,484) 132,489.5 (111,124.4-183,236.4) 291,073 (244,135-402,562)
Non-Hispanic black
13,052.8 (10,925.4-18,133.4) 406,187 (339,984-564,288) 11,486.1 (9398.9-16,739.1) 381,229 (311,954-555,582) 24,175.3 (20,000.7-34,420.3) 388,271 (321,224-552,812)
Non-Hispanic other*
2761.5 (2297.0-3894.6) 393,484 (327,296-554,947) 2606.3 (2126.0-3829.9) 379,591 (309,648-557,806) 5302.2 (4366.9-7635.1) 381,893 (314,525-549,919)
Hispanic
5831.7 (4797.7-8442.1) 425,642 (350,174-616,170) 45,144.4 (4158.5-7721.0) 406,739 (328,785-610,450) 10,827.6 (8830.3-15,954.7) 410,931 (335,130-605,515)
Data presented are for all age groups starting from age 151 (5-year age group).
*Includes Asian/Pacific Islanders and American Indian/Alaska natives.
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Ekwueme et al S139
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16 to 49 years.
42-44
A recent study reported that
individuals who used indoor tanning before age 35
years have a 75% increased risk of developing
melanoma
45
and women are more likely to use
indoor tanning than men.
46
Second, we estimated the annual cost associated
with melanoma mortality to be $3.5 billion. Our
estimates suggest that an individual who died from
melanoma in 2000 throug h 2006 would lose an
average of $413,370 in forgone lifetime earnings.
On average, this estimate is 1.6 times higher than the
estimates from the 4 major cancers. For all malignant
cancers, the productivity loss per death was
$309,879, which is 1.3 times lower than the estimate
from melanoma. These findings provided consistent
evidence that the economic burden of melanoma
disease is substantial
9-11
and represents a serious
public health concern. Further, a recent systematic
review study presented a comparative melanoma
disease burden between the United States and other
countries.
47
The study showed that in both YPLL and
productivity loss, the estimates were relatively higher
in the United States compared with other industrial-
ized countries.
Although this study demonstrates the substantial
costs of melanoma to each racial/ethnic group, with
non-Hispanic whites accounting for 95.1% of the
estimated total melanoma costs and Hispanics ac-
counting for 2.3%, it also highlights the potential
costs that could be saved if prevention programs
were designed to reduce the burden of melanoma
disease among these racial/ethnic groups. In the
past decade, prevention programs have been initi-
ated to reduce the burden of melanoma. Such
prevention programs have focused on reducing
exposure to ultraviolet radiat ion by increasing
knowledge and awareness through educational
programs, media campaigns, and by implementing
policy initiatives that encourage sun-safety prac-
tices.
48
According to the US Preventive Services
Task Force, currently there is insufficient evidence
to recommend for or against regular skin cancer
screening including self-examination for early de-
tection of melanoma in the adult general popula-
tion.
49
However, the Task Force on Community
Preventive Services found sufficient evidence to
recommend intervention programs that promote
and improve awareness of melanoma and other
skin cancers in primary schools and recreational or
tourism settings.
48
These and similar efforts from
public and private health agencies and institutions
may be contributing to improving the awareness of
skin cancer diseases. However, thes e efforts may
not be enough. For example, in 1935 the average
lifetime risk of an Amer ican developing melanoma
was 1 in 1500 and in 2009, this probability has
increased to 1 in 30.
2,3
The increasing risk of melanoma underscores
the importance of public and private health agencies
and institutions working together to develop and
implement cost-effective risk-reduction programs.
Fortunately, such interventions may be currently
available. For example, the US Environmental
Protection Agency developed and implemented a
SunWise school-based program designed to teach
children how to protect themselves from overexpo-
sure to sun.
50
This program has been reported to be
cost-effective with a return on investment of $2 to $4
saved in medical care costs and productivity losses
for every dollar invested and could prevent more
than 50 premature deaths associated with melanoma
by 2015.
50
This and other prevention programs that
might include changes in personal behaviors and
government policies designed to reduce exposure to
artificial sunlight, such as the use of indoor tannin g
beds, may help in reducing the mortality burden
associated with melanoma.
Limitations
This study has some limitations. First, in estimat-
ing YPLL as a result of melanoma mortality, we used
life table data on all race/ethnicity as a proxy for life
expectancy of non-Hispanic other. This approach
may have introduced some uncertainty in our esti-
mates. Second, we used the HCA to estimate PVFLE.
This approach assumes that an individual produces a
stream of earnings that is valued only through
employment. Therefore, it fails to recognize the costs
of intangibles, which includes pain and suffering, the
psychosocial consequences of cancer disease, and
reductions in the quality of life.
13
Third, our analysis
excludes morbidit y costs associated with melanoma,
which includes the productivity loss from individuals
with melanoma before they die, costs of medical
treatment, nonmedical costs (eg, those associated
with time spent seeking cancer treatment and care),
and product ivity losses for caregivers. These costs
represent a substantial amount of resources lost or
spent because of melanoma.
CONCLUSIONS
Despite these limitations, the health burden mea-
sured by YPLL and economic cost estimates pre-
sented in this article provide evidence of significant
numbers of premature deaths and substantial mor-
tality costs associated with cutaneous melanoma
during an individual’s lifetime. Given the increasing
incidence rate and mortality associated with mela-
noma in an era of declining mortality among other
major cancers, it appears that current prevention
JAM ACAD DERMATOL
NOVEMBER 2011
S140 Ekwueme et al
Page 8
efforts may not be adequate. Hence, it has been
suggested that perhaps new prevention strate gies
that involve a multifaceted approach should be
adopted.
51
This approach would include social mar-
keting, policy change, education, and sustained
intervention programs that ma y be required to mea-
surably shift knowledge, attitudes, and behaviors of
the population.
51
In the past, estimates of hea lth burden and eco-
nomic costs of diseases including cancer have
proven useful to guide health care policy debates
in the popula tion.
21,52
We hope that the information
reported in this article would be helpful in mobiliz-
ing interests and guiding resources to enable public
health decision makers to develop the right health
policy and comprehensive intervention programs to
decrease the burden of melanoma mortality in the
United States.
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APPENDIX 1: GLOSSARY OF TECHNICAL
TERMS USED IN ARTICLE
Years of potential life lost (YPLL): The ex-
pected years of potential life lost because of a
particular d isease during an individual’s lifetime. It
is part of the descriptive epidemiology that provides
information on the overall burden of a disease in the
population. Calculating YPLL provides an indication
of the impact of premature death from a particular
illness or inju ry on society. The information from
YPLL can be useful in establishing public health
priorities and policies.
Average years of life lost: This is the total YPLL
associated with a particular disease or injury in the
population for a given year divided by the number of
deaths from an illness or injury in the population in
that year.
YPLL rate: It is a rate used to compare the
estimated number of YPLL for two pop ulations of
different sizes (eg, white and black). It is usually
expressed as per 100,000. It is calculated as: total
YPLL in a given year divided by the population and
then multiplied by 100,000.
Age-adjusted YPLL rate: It is a rate used to
compare the estimated number of YPLL between two
or more different populations (eg, racial/ethnic
groups) to eliminate the effects of different age
structures among these different populations. It is
calculated by the direct method, using the 2000 US
standard population. Like the crude rate, it is also
expressed as per 100,000.
Incidence-based cost: The lifetime costs result-
ing from new cases of an illness or injury that
occurred during a specified time period. It is one of
the methods used to calculate indirect (productivity)
costs of an illness or injury.
Prevalence-based cost: The total c osts associ-
ated with existin g ca ses o f an illness or inju ry th at
occurredinaspecifictimeperioddividedbythe
total populatio n. It is ano ther method used to
calculate indirect (productivity) costs of an illness
or injury.
Human capital approach (HCA): Used to assess
the indirect costs or productivity losses from an
illness or injury as measured by forgone earnings
as a result of morbidity or premature mortality.
Willingness to pay: A method of measuring the
value an individual places on a good, service, or
reduction in the risk of death from an illness or injury
by estimat ing the maximum dollar an individual
would pay to obtain the good, service, or risk
reduction.
Present value of futur e lifetime earnings
(PVFLE): The discounted value of future lifetime
earnings lost as a result of premature death from an
illness or injury.
Productivity loss: Measure of resources forgone
to participate in an intervention, to seek care for a
health condition, for care giving, and as a result of
morbidity or premature mortality.
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S142 Ekwueme et al
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Discount rate: Used to convert future dollars and
future health outcomes to their present value.
APPENDIX 2: THE RELATIVE
CONTRIBUTIONS OF EACH OF FOUR
MAJOR CANCER SITES TO MORTALITY
AND YPLL
We estimated the ratio of the relative contributions
of each of the 4 major cancer sites (ie, breast, prostate,
colorectal, and lung), melanoma, and all malignant
cancers to years of potential life lost (YPLL) and
mortality in the population. We used all malignant
cancers as reference. The numerator of the ratio was
the YPLL for each cancer site divided by the YPLL for
all malignant cancers and expressed as a percent. The
denominator was the number of deaths caused by
each cancer site divided by the number of deaths
caused by all malignant cancers and expressed as a
percent (ie, % YPLL/% mortality). The 45-degree line
(y = x) represents the line of equality, which indicates
a cancer site’s equal relative contribution to YPLL and
mortality. A cancer site with a ratio less than 1 indi-
cates that cancer contributes more to mortality than
to the number of YPLL. On the other hand, a ratio
greater than 1 indicates that cancer contributes more
to YPLL than to the number of deaths.
Fig 2 shows that melanoma and breast cancer
contributed more to YPLL than to mortality with
ratios of 1.23 and 1.22, respectively. On the other
hand, prostate cancer contributed more to mortality
than to YPLL with a ratio of 0.59.
Fig 2. Years of potential life lost and mortality ratios for 4
major cancer sites, melanoma, and all malignant cancerse
United States, 2000 to 2006.
JAM ACAD DERMATOL
VOLUME 65, NUMBER 5
Ekwueme et al S143
Page 11
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    • "This discrepancy is reported to be related to overdiagnosis [2e4] and/or to the fact that most melanoma deaths are due to fast-growing melanomas, the incidence of the latter being stable because rarely identified during screenings [5,6]. Due to its relatively low mean age at diagnosis, melanoma ranks among the most devastating adult cancers in terms of years of life lost (YLL) per death [7,8]. Nevertheless, the emergence of new, yet expensive treatments for metastatic melanoma kindles hope for a decreased mortality in the coming decades, despite being associated with longer disease durations. "
    [Show abstract] [Hide abstract] ABSTRACT: Background: The total burden of melanoma has already been studied but little is known about the distribution of this burden amongst localised, node metastatic and distant metastatic stages. Methods: Disability-adjusted life years (DALY) assesses disease burden, being the sum of years of life with disability (YLD) and years of life lost (YLL). A melanoma disease model was developed in order to predict the evolution of patients from diagnosis until death. The model was applied to a large cohort of 8016 melanoma patients recorded by the Belgian Cancer Registry for incidence years 2009-2011. DALYs were calculated for each American Joint Committee on Cancer stage, considering stage at diagnosis on the one hand and time spent in localised, node metastatic and visceral metastatic stages on the other. Probabilistic sensitivity analyses and scenario analyses were performed to explore uncertainty. Findings: Our analyses resulted in 3.67 DALYs per melanoma, 90.81 per 100,000 inhabitants, or 32.67 per death due to melanoma. The total YLL accounted for 80.4% of the total DALY. Stages I, II, III and IV patients at diagnosis generated, respectively, 27.8%, 32.7%, 26.2% and 13.3% of the total YLL. For the time spent in each stage, localised melanomas, node metastatic melanomas, and distant metastatic accounted, respectively, for 34.8%, 52.6% and 12.6% of the total YLD. Parametric uncertainty was very limited, but the influence of using pre-2010 Global Burden of Disease approaches was substantial. Interpretation: The total DALY for melanoma was consistent with the previous studies. Our results in terms of proportions of DALY/YLL/YLD per stage could be extrapolated to other high-income countries. YLDs generated by localised melanoma which will never metastasize were inferior to YLLs resulting from stage IA melanomas. This result supports the hypothesis that efforts for an earlier diagnosis of melanoma are important. Funding: None.
    Full-text · Article · Jan 2016 · European journal of cancer (Oxford, England: 1990)
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    • "In fact, it is the most common form of cancer in young adults ages 25 to 29 years old, and the second most common cancer in those ages 15 to 24 years old. [1] Melanoma has a further predilection for higher socioeconomic groups and has an estimated annual productivity loss due to mortality of $3.5 billion [2]. Most of the melanoma cases diagnosed are in early stages of disease and have an excellent prognosis with 86-95% 10 year survival with appropriate therapy. "
    [Show abstract] [Hide abstract] ABSTRACT: Neoadjuvant therapy is an under-utilized regimen for the treatment of metastatic melanoma. The use of this approach has been increasing in other tumor types. Neoadjuvant therapy may reduce occult circulating tumor cell burden in the face of bulky disease and afford a real time evaluation of treatment effectiveness. Neoadjuvant approach can also provide preoperative histologic and molecular analysis of treated tissue that may guide the postoperative treatment planning in patients with resectable metastatic melanoma lesions. The putative benefits of better margin control and clearance of occult systemic disease would theoretically improve surgical outcome. With the advent of effective agents against metastatic melanoma, this common approach to the treatment of rectal cancer, metastatic colon cancer, and breast cancer should also be evaluated as a viable treatment strategy for advanced stage melanoma.
    Full-text · Article · Nov 2013
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    • "Therefore, information material designed to educate on Public (Skin) Health issues serve as important communication tools of decision-making in doctors-patients relationship and preventive medicine [7]. Preventive efforts reduce mid- and long-term costs for public medical care of all types of UV radiation-related skin diseases [8,9]. "
    [Show abstract] [Hide abstract] ABSTRACT: Unprotected leisure time exposure to ultraviolet radiation from the sun or artificial tanning beds is the most important environmental risk factor for melanoma, a malignant skin cancer with increasing incidences over the past decades. The aim of the present study was to assess the impact of skin health information provided by several sources and different publishing issues on knowledge, risk perception, and sun protective behavior of sunbathers. A cross-sectional questionnaire survey was conducted among Austrian residents (n=563) spending leisure time outdoors in August 2010. Print media, television, and family were perceived as the most relevant sources of information on skin health, whereas the source physician was only ranked as fourth important source. Compared to other sources, information provided by doctors positively influenced participants' knowledge on skin risk and sun protective behavior resulting in higher scores in the knowledge test (p=0.009), higher risk perception (p<0.001), and more sun protection (p<0.001). Regarding gender differences, internet was more often used by males as health information source, whereas females were more familiar with printed information material in general. The results of this survey put emphasis on the demand for information provided by medical professionals in order to attain effective, long-lasting promotion of photoprotective habits.
    Full-text · Article · Mar 2013
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