BMC Public Health

, 15:952 | Cite as

Estimating the economic costs of skin cancer in New South Wales, Australia

  • Christopher M. Doran
  • Rod Ling
  • Joshua Byrnes
  • Melanie Crane
  • Andrew Searles
  • Donna Perez
  • Anthony Shakeshaft
Open Access
Research article

Abstract

Background

Skin cancer is one of the most common cancers in the world. The increased incidence of skin cancer, combined with limited health care resources and tight budgetary conditions, has increased the importance of understanding the economic impact of skin cancer. This research estimates the economic cost of skin cancer in the Australian state of New South Wales.

Method

An incidence based approach is used to estimate lifetime costs of skin cancer. Both direct and indirect costs are considered - direct costs include resources associated with the management of skin cancer and indirect costs refer to productivity costs associated with morbidity and premature mortality. Diagnosis of skin cancer was determined according to ICD-10 codes using principal diagnosis. Linked administrative data and regression modelling are used to calculate costs; presented as Australian dollars for the year 2010. The human capital approach is used to value present and future productivity losses.

Results

The lifetime cost of the 150,000 incident cases of skin cancer diagnosed in NSW in 2010 is estimated at $536 million ($44,796 per melanoma and $2459 per non-melanoma). Direct costs accounted for 72 % of costs ($10,230 per melanoma and $2336 per non-melanoma) and indirect costs accounted for 28 % of costs ($34,567 per melanoma and $123 per non-melanoma). Direct costs are, on average, higher for females than males with indirect costs, on average, higher for males than females.

Conclusion

This research provides new evidence on the economic cost of skin cancer and provides policy makers with information of the potential monetary savings that may arise from efforts to reduce the incidence of skin cancer.

Keywords

Economic Cost Skin cancer Epidemiology New South Wales Australia 

Abbreviations

APDC

Admitted patient data collection

AUD

Australian dollar

BCC

Basal cell carcinoma

CCR

Central Cancer Registry

DW

Disability weights

GEE

General estimating equations

ICD-10-AM

International Statistical Classification of Diseases, 10th revision

MBS

Medical Benefits Scheme

NZ

New Zealand

NMSC

Non-melanoma skin cancer

NSW

New South Wales

PBS

Pharmaceutical Benefits Scheme

PYLL

Potential years of life lost

SCC

Squamous cell carcinoma

UK

United Kingdom

UVR

Ultra violet radiation

Background

Skin cancer is one of the most common cancers in the world [1, 2, 3, 4]. The majority of skin cancers develop from exposure to ultraviolet radiation (UVR), particularly from sun exposure. The highest incidence rates of skin cancer worldwide are in Australia and New Zealand, where two out of every three people are likely to be diagnosed in their lifetime [5].

Basal cell carcinoma (BCC) is the most common form of skin cancer followed by squamous cell carcinoma (SCC) [1, 2]. Together, BCC and SCC make up the majority of non-melanoma skin cancers (NMSC). Malignant melanoma accounts for less than five percent of skin cancer cases, yet it represents the vast majority of skin cancer deaths in Australia [6]. The incidence of skin cancer is increasing in Australia, and the incidence rate is greater than breast, prostate, lung and colon cancers combined. In terms of prevalence, more people have been diagnosed with skin cancer than all other cancers combined over the past three decades [7].

The management of skin cancer generally involves diagnosis, treatment and follow-up. Melanoma, SCC and BCC are typically detected opportunistically during specific skin examinations by skin cancer specialists or dermatologists, or during general health checks by a general practitioner. In Australia, the standard treatment for primary melanoma is wide local excision of the skin and subcutaneous tissues around the melanoma. The aim is complete surgical excision of all in situ and invasive melanoma components, confirmed by comprehensive histological examination [8]. Surgery is the prime treatment for NMSC: more than 70 % of the BCC lesions recorded in the 2002 National survey were surgically excised [9]. For BCCs not surgically excised, cryotherapy was more commonly used for upper and lower limb lesions than facial lesions, and 10 % of BCCs were treated with curettage and diathermy. Anecdotal evidence suggests that non-surgical treatment has increased since 2002 for superficial BCC with imiquimod in particular. The majority of SCC lesions, regardless of body site, were treated by surgical excision [9, 10]. Confirmation of complete removal of lesions is an essential part of management [10].

The post-treatment follow-up regimen is relatively intensive in Australia with clinical guidelines recommending post melanoma treatment follow-up visits every six-months for five years for patients with stage I disease, three-monthly or four-monthly for five years for patients with stage II or III disease, and yearly thereafter for all patients [8]. NMSC recommendations for follow-up have yet to be established for the detection of further primary tumours, however, some suggestions have been made that six-monthly follow-up for two years may assist in early detection of new primary tumours or of metastatic disease [10].

The incidence of skin cancer increases with age [11, 12]. With most western countries experiencing a demographic transition towards an older cohort, including Australia, the incidence and prevalence of skin cancer is rising, along with the consequential economic impact, even though incidence in younger age groups (i.e., less than 55 years) is stabilising [12, 13, 14].

The economic impact of skin cancer can be considered as a combination of direct and indirect costs. Direct costs include the management of skin cancer from diagnosis, treatment to follow-up, and refer to the utilisation of health care resources such as hospital, medical and allied health care services. Indirect costs reflect the lost productivity resulting from an individual’s inability to work (morbidity costs such as sick leave and early retirement) and premature mortality (defined as death before the age of 65 years, the upper limit of the working age in Australia).

The increased incidence and prevalence of skin cancers, combined with the current fiscal environment of limited health care resources and tight budgetary conditions, has increased the importance of understanding the economic impact of skin cancer. From a policy viewpoint, it is important to understand the resource requirements of the current skin cancer burden and the efficiency of competing strategies that are most likely to lower the incidence of skin cancer and, therefore, reduce its burden. Although several international studies have examined the direct cost of skin cancer treatment [15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26], and two have examined indirect costs [27, 28]; our review of the literature found only four studies that had combined both direct and indirect costs in the same analysis [29, 30, 31, 32]. Morris et al. [31] estimated the cost of skin cancer in England in 2002 at £240 million, equivalent to £4249 per case (AUD$12,567 in 2010 prices). Tinghog et al. [29] estimated the cost of melanoma and NMSC in Sweden in 2005 at €116 million, equivalent to €3019 per case (AUD$5366 in 2010 prices). Eriksson and Tinghog [32] updated the 2005 Swedish estimate and reported a combined cost of melanoma and NMSC at €136 million. The authors did not report incidence rates or average cost per case, but noted that costs had risen by 14 % after adjusting for inflation since 1995 [32]. O’Dea estimated the cost of skin cancer in New Zealand in 2007 at $NZ123.10 million, equivalent to $NZ1,785 per case (AUD$1650 in 2010 prices) [30]. The general trend in these country specific studies is higher direct costs for NMSC (because of their relatively high prevalence) and higher indirect costs for melanoma (because of its relatively greater severity of illness in those of working age). Although the proportion of costs attributable to indirect costs in all three studies to date appears comparable at around 54 %, total costs appear to vary widely partly due to methodological differences.

New South Wales (NSW) is Australia’s most populated state with an estimated population of 7.29 million (34.5 % of the population of Australia). One of the key objectives of the skin cancer prevention strategy for NSW (2012–2015) is to increase and utilise evidence to inform future planning and development of skin cancer prevention strategies with a priority on: increasing the adoption of UVR protection behaviours; increasing shade provision; and improving polices to increase protection from UVR across a range of settings and life stages [33]. Although an understanding of the magnitude of the economic burden of skin cancer in NSW is important given its high incidence, there is currently a clear lack of such evidence. The objective of this study is to estimate the economic cost (both direct and indirect) of skin cancer in NSW. A lifetime approach is adopted, which estimates costs over the management of skin cancer through diagnosis, treatment and follow-up.

Methods

Ethics

Ethics clearance was obtained from the New South Wales Ministry of Health (2012/09/417).

Economic approach

Economic costs may be estimated using either the prevalence or incidence-based approach to costing. A prevalence-based approach provides estimates of costs for the total population for one year, or costs accumulated over a longer time horizon [34]. An incidence-based approach follows a disease cohort for the duration of the disease and estimates discounted costs [34], it is the most commonly used method as it allows policy makers to understand the potential impact of reducing the incidence of a disease by adopting cost-effective strategies. This analysis uses the incidence based approach to estimate lifetime economic costs. This lifetime perspective reflects the recommended clinical management of skin cancer in Australia [8, 10], managing melanoma and NMSC for five and two years respectively, post diagnosis. Total economic costs in 2010 are derived by multiplying the number of incident cases in 2010 by estimates of the average lifetime direct and indirect costs.

Epidemiological data

In Australia, melanoma is notifiable to cancer registries. To estimate the incidence of melanoma by age and gender, data were obtained from the NSW Central Cancer Registry (CCR) which at the time of writing was available up to 2008 [35]. These data were combined with Australian Bureau of Statistics (ABS) estimates of the resident NSW population in 2010 [36].

Unlike melanoma and other invasive cancers, NMSC is not notifiable by law to cancer registries in Australia, despite being the most commonly diagnosed cancer. Consequently, rates of NMSC have been estimated from population surveys [5, 9, 37, 38]. The most recent survey was conducted by the National Cancer Control Initiative (NCCI) in 2002 [9]. To estimate the incidence of NMSC by age and gender, data from the NCCI survey were combined with ABS estimates of the resident NSW population in 2010 [36].

Calculating direct costs of skin cancer

Data sources

A range of linked data sources (Table 1) were utilised to determine direct costs: the 45 and Up study (45&Up) [39]; NSW CCR [35]; NSW admitted patient data collection (APDC) [40]; ABS mortality [6]; Pharmaceutical Benefit Schedule (PBS) [41]; Medicare Benefit Schedule (MBS) [42]; and, the NSW Registry of Births, Deaths and Marriages (RBDM) [43].
Table 1

Summary of available administrative data

Data source

Abbreviation

Overview of data collected

Period of data collection

Number of possible records

45 and Up survey

45& Up

The 45&Up survey is of individuals aged 45 and over in NSW - the survey includes information on health, lifestyle and other socio-economic factors.

2005-2009

267,119 records (267,119 persons)

NSW Central Cancer Registry

CCR

The CCR includes records for all reported cancer cases from NSW Central Cancer Registry. The CCR records include a range of demographic data items (e.g. date of birth, residential address), staging information, year of diagnosis, plus diagnostic information (e.g. reason for death, Morphology code, Topography Code etc.). The CCR cohort comprises individuals registered on NSW CCR and diagnosed with skin cancer (melanoma, melanoma in situ).

January 1994 – December 2008

63,342 records (60,247 persons)

NSW Admitted Patient Data Collection

APDC

The APDC includes all hospital separations of skin cancer (melanoma, melanoma in situ, non-melanoma) and/or a precursor of skin cancer (sunburn, actinic keratosis or melanocytic naevi) in NSW during the period July 2000-Dec 2011 from all NSW public and private hospitals and day procedure centres. APDC records include a range of demographic data items, administrative items (e.g. admission and separation dates) and diagnostic information (e.g. reason for admission, significant co-morbidities and complications and procedures performed during the admission).

July 2000 – December 2011

406,997 records (256,924 persons)

Australian Bureau of Statistics (ABS) mortality

ABS Mortality

The ABS cohort includes all cases where skin cancer is recorded as the primary or contributing cause of death. Cause of death is coded according to the International Statistical Classification of Diseases and Related Problems (ICD-10-AM).

January 2000 – December 2007

5735 records (5728 persons)

Pharmaceutical Benefit Schedule

PBS

The PBS is administered by Medicare Australia and includes all processing claims and payment benefits for pharmaceutical medications for most medical conditions. This source contains cost and utilisation data by drug for each individual.

2004-2011

35,322,2457 records

Medicare Benefit Schedule

MBS

The MBS is a listing of medical and hospital services that are subsidised by the Australian government. The MBS includes primary care practitioner and specialist consultations and exclude ambulance and allied health services. This source contains costs (including patient out of pocket cost) and utilisation data by service/procedure.

2003-2011

46,012,797 records

NSW Registry of Births, Deaths and Marriages

RBDM deaths

The Registrar of the NSW Registry of Births, Deaths and Marriages (RBDM) is a registry all births and deaths in NSW

RBDM records linked to 45& Up, CCR, APDC and ABS

66,786 records (62,688 persons)

Diagnosis of skin cancer

Diagnosis of melanoma (both in-situ and invasive) was determined by the principal diagnoses codes in the Australian modified International Statistical Classification of Diseases and related health problems, 10th revision (ICD-10-AM), specifically codes C43 (malignant melanoma of skin) and D03 (melanoma in situ) [44]. Diagnosis of NMSC was identified using codes C44 (malignant neoplasm of skin) and D04 (carcinoma in situ of skin). Diagnosis was also derived from MBS and PBS utilisation and self-report data from the 45&Up study.

Analysis criteria

Costs were calculated for, and compared across, three diagnostic groups: melanoma; NMSC; and, neither melanoma or NMSC. Participants self-reported having either melanoma or NMSC in the 45&Up survey by their responses to the following two questions: “Has a doctor EVER told you that you have melanoma?” “Has a doctor EVER told you that you have skin cancer (not melanoma)?” Self-reported responses were validated by linked records in the CCR, APDC and MBS. Participants without CCR, APDC or MBS records were classified as diagnosis uncertain if their evidence of diagnosis - for either skin cancer - was only self-identification in the 45&Up survey or only relevant MBS records. This group was omitted from analysis due to the ambiguity of their status. The group ‘neither melanoma or NMSC’ had no data relevant to melanoma or NMSC diagnosis and is used as the control group in the regression analysis.

Direct costs

Cost groupings were derived from the following sources (data periods appear in brackets):
  1. 1.

    Primary care medical costs: MBS (04/08/2003 to 31/12/2011)

     
  2. 2.

    Pharmaceutical costs: PBS (01/06/2004 to 31/12/2011)

     
  3. 3.

    Hospital costs: APDC (01/07/2000 to 31/12/2011)

     

Variations in data coverage reflect the nature of linking multiple patient-level data sources. To ensure consistency, data from these files were analysed only for their overlap period, 01/06/2004 to 31/12/2011. MBS, PBS and APDC cost estimates were converted to 2010 prices using appropriate price inflators [45].

Estimation of lifetime direct costs used longitudinal methods to estimate average costs (MBS, PBS and APDC), for each diagnosis group, for each calendar year since diagnosis - for 5 years post diagnosis for melanoma and 2 years post diagnosis for NMSC. A cost per annum from year of diagnosis reflects that any cost difference between those with and without a diagnosis is likely to be most pronounced in the first years of diagnosis. Regression analysis is used to estimate the effect on the cost associated with a diagnosis of either melanoma or NMSC, compared to the control group, i.e., those without a diagnosis. The dependent variable is the average annual cost for the year as identified as the year from diagnosis. The covariates included in this model are listed in Table 2 and include the years from diagnosis as an explanatory variable.
Table 2

Variables used in costing analysis

Variables

Sources

Question/Variable

Data Format

Analysis summary

Medical Charges

APDC

Average costs per AR-DRGs (from government ‘Costs of Care’ reports

Continuous ($)

Averages and totals across diagnosis groups and periods

 

MBS

Charges

Continuous ($)

Averages and totals across diagnosis groups and periods

 

PBS

Gross Price

Continuous ($)

Averages and totals across diagnosis groups and periods

Diagnoses Melanoma

CCR

Inclusion in the CCR

 

Inclusion

 

45& Up

Question: ‘Has a doctor ever told you that you have melanoma’?

Yes/No

Proportions

 

MBS

Relevant MBS Charges

Continuous ($)

Averages and totals across diagnosis groups and periods

 

APDC

Relevant Primary Diagnoses items

Continuous ($)

Averages and totals across diagnosis groups and periods

Diagnosis NMSC

45& Up

Question: ‘Has a doctor ever told you that you have skin cancer (NMSC)’?

Yes/No

Proportions

 

MBS

Relevant MBS Charges

Continuous ($)

Averages and totals across diagnosis groups and periods

 

APDC

Relevant Primary Diagnoses items

Continuous ($)

Averages and totals across diagnosis groups and periods

Diagnosis Calendar Year (melanoma)

CCR

Year of Diagnosis’ variable

Year

 
 

APDC

Date of Separation

Year

 
 

45& Up

Question: ‘At what age were you told you had melanoma?’ (Allows calculation of year with variable ‘Year of Birth’)

Continuous

Averages and totals across diagnosis groups and periods

Diagnosis Calendar Year (NMSC)

45& Up

Question: ‘At what age were you told you had skin cancer (NMSC)’ (Allows calculation of year with variable ‘Year of Birth’)

Continuous

Averages and totals across diagnosis groups and periods

 

APDC

Date of Separation

Year

 

Demographics

45& Up

Year of birth

Year

Year

  

Gender

Female/Male

Proportions

Year of Death

RBDM

Year of death variable

Year

Year

APDC NSW Admitted patient data collection; CCR NSW Central Cancer Registry; MBS Medicate Benefit Schedule; PBS Pharmaceutical Benefit Scheme; RBDM NSW Registry of Births, Deaths and Marriages; 45&UP The 45 and Up study

The analysis can be represented by the following equation:
$$ \mathrm{A}\mathrm{L}\mathrm{C} = \mathrm{N}\mathrm{P}\mathrm{V}\left[{\mathrm{CM}}_{\mathrm{i}}\right]\kern0.1em \times \kern0.1em \left.\mathrm{I}\mathrm{M}\right]\kern0.1em +\kern0.10em \mathrm{N}\mathrm{P}\mathrm{V}\left[{\mathrm{CNMSC}}_{\mathrm{i}}\right] \times \mathrm{INMSC} $$
Where:
  • ALC = average lifetime cost of skin cancers diagnosed in 2010;

    • NPV = net present value

    • CM i  = average annual cost per case of melanoma relative to year of diagnosis i ;

    • CNMSC i  = average annual cost per case of NMSC relative to year of diagnosis i ;

    • IM = incidence of melanoma in 2010;

    • INMSC = incidence of NMSC in 2010.

From each data source (MBS, PBS, APDC) cost data was obtained for each calendar year of the collection period (2004–2011). The data sets were merged on person number and year. The dataset had one record for each participant for each calendar year of the collection period. Records contained fields for calendar year MBS, PBS, APDC costs and, for participants with skin cancer, years since year of diagnosis. Costs are inclusive of patient and government contributions. Participants who died during the collection period only had records for the calendar years in which they were alive. Mortality information was sourced from ABS mortality [6] and the NSW Registry of Births, Deaths and Marriages (RBDM) [43].

Regression modelling for average lifetime direct costs used General Estimating Equations (GEE) analysis. Given a priori evidence of skewed cost data (i.e., large number of zero or small cost observations with a small number of observations with very large costs), GEEs were run with a gamma family and log link. Standard diagnostic tests were conducted (e.g. correlations between independent variables and comparisons of residuals and predicted values). Robust variance estimators were included to ensure more robust estimates of standard errors. Margins (estimates) were derived for average treatment costs for each year from diagnosis by each diagnosis status (melanoma, NMSC) and compared to average annual direct costs for people with no skin cancers. These incremental results were then multiplied by skin cancer incidence figures to derive lifetime direct costs for NSW in 2010.

All regressions were conducted with STATA 12 software. Regression results are available from authors upon request.

Calculating indirect costs of skin cancer

Indirect costs quantified in this analysis include morbidity and premature mortality for those of working age.

Morbidity estimates

The Australian Burden of Disease study provide information on total years lived with a disease and the loss of health (referred to as a disability weight - DW) associated with that disease [46]. Disability weights are based on a scale ranging from 0 to 1 where 0 represents perfect health and 1 represents death [46]. For skin cancer, a range of DWs are used to reflect health states in relation to sequelae. Across the entire disease spectrum, the average DW is 0.19 and 0.06 for melanoma and NMSC, respectively. An estimate of the average health years of life lost due to skin cancer are used as a proxy for morbidity costs in this analysis and are derived by dividing total years lived with skin cancer with the relevant DW.

The human capital approach is used in this analysis to value the loss of productive life. The approach equates the value of a human life to the discounted market value of the output produced by an individual over an expected lifetime. In other words it uses forgone income to estimate forgone productivity [34, 47]. The value of a healthy year of life is equivalent to the average annual earnings in NSW for 2010 - $61,105 for males and $42,238 for females [48]. A further adjustment is made to this value to reflect the likelihood of being employed - 82 % in males and 68 % in females [49].

Premature mortality

Premature mortality costs are derived by valuing potential years of life lost (PYLL) due to skin cancer before the age of 65. The most comprehensive source of skin cancer mortality data in NSW is provided by the ABS [6]. Dividing ABS data on PYLL with number of deaths provides an estimate of average years of life lost per death.

ABS data does not, however, report age of death so an alternate means was required to estimate average years of life lost due to skin cancer before the age of 65. The CCR provides individual level data on age at melanoma diagnosis and age at death [35]. For melanoma, CCR data suggest that 38 and 35 % of total years of life were lost in those dying before the age of 65 years, for males and females respectively. In the absence of similar CCR data for NMSC, this proportion is applied to ABS data on PYLL and deaths to estimate the average years of productive life lost per incident case of skin cancer.

As above for morbidity, average annual earnings, adjusted for employment, is used as a proxy for the value of a productive year. All future costs are converted to present value using a 3 % discount rate.

Results

Epidemiology

Table 3 provides an overview of skin cancer epidemiology in NSW. In 2010, there were an estimated 3797 new cases of melanoma (2295 male and 1502 female) and 148,610 new cases of NMSC (86,812 male and 61,798 female). Equivalent age-standardised incidence rates are, for melanoma, 65 and 42 per 100,000 males and females, respectively; and, for NMSC, 2449 and 1716 per 100,000 males and females, respectively. For melanoma, the average years of healthy life lost are 3.66 for males (equivalent to 254 days) and 1.77 years for females (equivalent to 123 days). For NMSC, the average years of healthy life lost are 0.05 years for males (equivalent to 16 days) and 0.02 years for females (equivalent to 6 days).
Table 3

Epidemiology of skin cancer in New South Wales, 2010

 

Melanoma

NMSC

 

Males

Females

Males

Females

Incidence

    

 Incident cases

2295

1502

86,812a

61,798a

 Incidence rate per 100,000

65

42

2449

1716

Morbidity

    

 Total years lived with disease

19,332

7089

9933

2533

 Average healthy years of life lost due to disease

3.66

1.77

0.05

0.02

Mortality

    

 Deaths (2010)

359

155

104

41

 Total years of life lost

3353

1571

566

104

 Average years of life lost

9.34

10.14

5.44

2.53

Mortality before the age of 65 years

    

 Average years of productive life lost

4.52

5.14

2.07

0.88

aNMSC is estimated from a 2002 NCCI report - the incident rate is assumed steady for 2010 and has not risen

In 2010, 359 men and 155 women lost their lives to melanoma corresponding to an age-standardised death rate of 9.8 and 3.6 per 100,000 for males and females, respectively. NMSC claimed the lives of 104 men and 41 females, corresponding to an age-standardised death rate of 2.9 and 0.8 per 100,000 for males and females, respectively. For melanoma, PYLL per death are 9.34 years for males and 10.14 years for females. For NMSC, PYLL per death are 5.44 years for males and 2.53 for females. For those dying of melanoma before the age of 65 years (i.e., 38 % males and 35 % of females), the average years of productive life lost are 4.52 years for males and 5.14 years for females. For those dying of NMSC before the age of 65 years (i.e., 38 % males and 35 % of females), the average years of productive life lost are 2.07 years for males and 0.88 years for females.

Economic cost of skin cancer

The lifetime economic cost of skin cancer cases in NSW in 2010 is estimated at AUD$536 million or AUD$3514 per incident case (Table 4). Each incident melanoma case costs an average AUD$44,796 compared with AUD$2459 per NMSC case. NMSC costs account for 68 % (AUD$365 million) of total lifetime economic costs. Direct lifetime costs are estimated at AUD$386 million (AUD$2533 per case), with NMSC representing 90 % of total direct costs - AUD$347 million (AUD$2336 per case) and melanoma 10 % of total direct costs - AUD$39 million (AUD$10,230 per case). Indirect lifetime costs are estimated at AUD$150 million (AUD$981 per case) with melanoma representing 88 % of total indirect costs - AUD$131 million (AUD$34,567 per case) and NMSC 12 % of total indirect costs - AUD$18 million (AUD$123 per case). Direct lifetime costs are, on average, higher for females than males with indirect costs, on average, higher for males than females.
Table 4

Incident cases, direct cost, indirect cost and total cost of skin cancer in NSW, 2010a

 

Melanoma

NMSC

Total

Incident cases

   

 Female

1502

61,798b

63,300

 Males

2295

86,812b

89,106

 Total

3797

148,610b

152,407

Direct costs

   

 Females

$16,349,530

$230,717,528

$247,067,059

 Cost per female incident case

$10,882

$3733

$3903

 Males

$22,494,516

$116,426,574

$138,921,090

 Cost per male incident case

$9803

$1341

$1559

 Total

$38,844,046

$347,144,102

$385,988,148

 Cost per incident case

$10,230

$2336

$2533

Indirect costs

   

 Females

$34,928,193

$2,259,156

$37,187,349

 Cost per female incident case

$23,249

$37

$587

 Males

$96,325,255

$16,016,487

$112,341,742

 Cost per male incident case

$41,977

$184

$1261

 Total

$131,253,448

$18,275,643

$149,529,091

 Cost per incident case

$34,567

$123

$981

Total costs

$170,097,494

$365,419,746

$535,517,240

 Cost per incident case

$44,796

$2459

$3514

aAverage cost may not equate to total cost divided with cases due to rounding

bNMSC is estimated from a 2002 NCCI report - the incident rate is assumed steady for 2010 and has not risen

Discussion

In conducting this study a range of data sources and methods were used. As such, a number of potential limitations and strengths of the analysis need to be considered.

Limitations

First, while the CCR data informed the incidence of melanoma in NSW, partial data sources were relied on to develop an understanding of the incidence of NMSC. These data sources are dated and may not reflect recent changes in incidence of NMSC. Second, our analysis did not consider the cost of skin cancer by stage of diagnosis, type of treatment, treatment provider or socio-economic status. Evidence suggests that there are variations in costs across these categories [15, 16, 17, 18]. In our study, although CCR provided information on staging of disease at time of diagnosis, no other data set had comparable data. Third, the base year for the analysis is 2010. This year is appropriate given data availability but it is acknowledged that skin cancer management may have changed over recent years. Fourth, a limitation of productivity estimates is a lack of complete Industry data. A recent study conducted by Safe Work Australia on exposure to direct sunlight and the provision of sun exposure controls in Australian workplaces, provides evidence that certain workers have a higher likelihood of being exposed to direct sunlight [50]. Further, the report suggests that the provision of sun protection (i.e. sunscreen, protective clothing, hats, sunglasses and being able to reorganise work outside peak UVR hours) was affected by worker employment and demographic characteristics [50]. The lack of data precludes a more robust assessment of Industry-related costs due to skin cancer in this analysis. Fifth, the analysis did not value the contribution made by carers. A report by Access Economics for Carer’s Australia examined and valued the amount of informal care being provided in Australia [51]. The report suggests that in 2010, over 1 in 8 Australians (2.87 million people) were estimated to be providing informal care with each carer providing up to 9 h per week in informal care. In the absence of any data related to the number of carers’ for skin cancer patients, carer costs were excluded.

Strengths

A strength of the analysis is the use of linked epidemiological data. Data linkage transforms routinely collected administrative data into a powerful resource for research. For the current study, the linking of administrative data provided a rich source of complementary information on: diagnosis of melanoma (CCR); costs associated with skin cancer (MBS, PBS and the APDC); and skin cancer mortality (CCR, APDC). Second, maximising the utility of the linked data set required a flexible data analysis that was logical and robust. The linkage process followed a sequential strategy that aimed to minimise the number of false positive records. The diagnosis criteria for melanoma and NMSC were informed using relevant international classification of disease coding. The statistical approach enabled a comprehensive and rigorous assessment of the lifetime costs of skin cancer in NSW. The costing approach was broadly consistent with other studies analysing Medicare-linked population-based databases in the United States [15, 16, 17, 18, 52]. Third, consistent with other costing studies, our analysis has attempted to place a monetary value on indirect costs [27, 28, 29, 53]. Our analysis only considers the economic value of productive years of life lost is a conservative estimate of mortality. Other studies quantify the economic value of all years of life lost, not just that before the age of 65 years [28].

Comparability with other studies

In spite of methodological differences, the estimated cost of skin cancer in NSW is generally consistent with previous Australian and International studies (Table 5) [29, 30, 31, 54, 55]. Compared with our estimate of the average cost per incident case of melanoma (AUD$44,796), the English study calculated AUD$67,567 [31], the Swedish study AUD$66,738 [29], and the New Zealand study AUD$30,326 [30]. Compared with our estimate of the average cost per incident case of NMSC (AUD$2459), the English study calculated AUD$5955 [31], the Swedish study AUD$1775 [29], and the New Zealand study AUD$802 [30].
Table 5

Summary of skin cancer costing studies, Australia, England, Sweden and New Zealand

Study

Country

Year and currency

Cases

Direct cost (million)

Indirect costs (million)

Total cost (million)

Cost per case

Equivalent AUD $2010

Morris

England

2002 UK pounds

      

Melanoma

  

6062

£24

£114

£138

£22,835

$67,537

NMSC

  

50,394

£97

£5

£101

£2014

$5955

Skin cancer

  

56,456

£121

£119

£240

£4249

$12,567

Tinghog

Sweden

2005 Euros

      

Melanoma

  

2122

€ 22

€ 58

€ 80

€ 37,545

$66,738

NMSC

  

36,262

€ 31

€ 5

€ 36

€ 998

$1775

Skin cancer

  

38,384

€ 53

€ 63

€ 116

€ 3019

$5366

O’Dea

New Zealand

2007/8 NZ dollar

      

Melanoma

  

1982

$6

$59

$65

$32,795

$30,326

NMSC

  

67,000

$51

$7

$58

$867

$802

Skin cancer

  

68,982

$57

$66

$123

$1785

$1650

AIHW

Australia

1993-94 AUD

      

Melanoma

  

6954

$66

 

$66

$9433

$14,805

NMSC

  

243,691

$232

 

$232

$953

$1496

Skin cancer

  

250,645

$298

 

$298

$1189

$1865

AIHW

Australia

2000-01 AUD

      

Melanoma

  

8885

$30

 

$30

$3376

$4561

NMSC

  

364,140

$264

 

$264

$725

$979

Skin cancer

  

373,025

$294

 

$294

$788

$1065

Source: Morris et al. (2009) [31], Tinghog et al. (2008) [29], O’Dea (2009) [30]

Previous estimates for the cost of skin cancer in Australia only valued direct costs. Compared with our estimate of the average direct cost per incident case of melanoma (AUD$10,230), other Australian estimates ranged from AUD$14,805 in a 1993–94 study [55] to AUD$4561 in a 2000–01 study [54]. Compared with our estimate of the average direct cost per incident case NMSC (AUD$2336), other Australian estimates ranged from AUD$1496 for the 1993–94 study [55] and AUD$979 for the 2000–01 study [54].

Conclusion

This study provides new evidence on the economic costs associated with skin cancer in NSW, Australia. Although this analysis is based on the latest epidemiological and economic evidence, there are still large knowledge gaps in understanding the wider impact of skin cancer on society. This lack of data means that the study most likely under-estimates the true cost of skin cancer in NSW.

A key factor underpinning the strategic plan of the Cancer Institute NSW is the knowledge that both melanoma and NMSC are highly preventable. The most effective means of reducing risk of developing skin cancer is to avoid direct exposure to UVR during the time of day when solar UVR levels are moderate to extreme. As a consequence of this analysis, we are in a better position to quantify the savings to society of reducing the incidence of skin cancer through preventive strategies such as sunscreen or mass media campaigns efforts. These savings are likely to be significant given the average lifetime cost of skin cancer in NSW is AUD$44,796 per melanoma case and AUD$2459 per NMSC case.

Notes

Acknowledgments

The research team would like to acknowledge the support and funding received from Cancer Institute NSW to access linked data and conduct the study. We would like to thank the Centre for Health Record Linkage for performing data linkage and NSW Ministry of Health, the Sax Institute and the Cancer Institute for providing access to their datasets. We would also like to thank State Cover Mutual Ltd and the Skin Cancer Audit and Research Database (SCARD) for access to their datasets. Prof Bruce Armstrong, Dr Anne Cust, Dr Tim Dobbins from the University of Sydney and Nicola Creighton from the Cancer Institute provided valuable assistance and insight throughout the project. Thanks also to Prof Rachel Morton, Caroline Watts and Alecia Brookes. Dr Stephen Begg from La Trobe University and Professor Theo Vos from the University of Washington provided advice on the epidemiological data. Kim Edmunds from HMRI provided editorial assistance. The team at SURE provided clarification and access to linked data. Any omissions or errors in analysis or interpretation of data rest solely with authors.

References

  1. 1.
    American Cancer Society. Cancer Facts & Figures 2013. http://www.cancer.org/acs/groups/content/@epidemiologysurveilance/documents/document/acspc-036845.pdf. Accessed January 31, 2013.
  2. 2.
    Australian Institute of Health and Welfare. Cancer in Australia: an overview, 2012. Cancer series no. 74. Cat. No. CAN 70. Canberra: AIHW; 2012.Google Scholar
  3. 3.
    Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM. GLOBOCAN 2008 v1.2: Cancer Incidence and Mortality Worldwide: IARC Cancer base No.10. Lyon, France: International Agency for Research on Cancer; 2010.Google Scholar
  4. 4.
    Rogers HW, Weinstock MA, Harris AR, Hinckley MR, Feldman SR, Fleischer AB, et al. Incidence estimate of nonmelanoma skin cancer in the United States, 2006. Arch Dermatol. 2010;146(3):283–7.CrossRefPubMedGoogle Scholar
  5. 5.
    Staples MP, Elwood M, Burton RC, William JL, Marks R, Giles GG. Non-melanoma skin cancer in Australia: the 2002 national survey and trends since 1985. MJA. 2006;184:6–10.PubMedGoogle Scholar
  6. 6.
    Australian Bureau of Statistics. Causes of death Cat. No. 3303.0. Canberra: ABS; 2013.Google Scholar
  7. 7.
    International Agency for Research on Cancer. World Cancer Report 2014. Geneva: WHO; 2014.Google Scholar
  8. 8.
    Cancer Council Australia. Australian Cancer Network Melanoma Guidelines Revision Working Party, Clinical Practice Guidelines for the Management of Melanoma in Australia and New Zealand. Wellington Cancer Council Australia and Australian Cancer Network, Sydney and New Zealand Guidelines Group; 2008.Google Scholar
  9. 9.
    National Cancer Control Initiative. The 2002 National Non-Melanoma Skin Cancer Survey. A report by the NCCI Non-melanoma skin cancer working groups. Melbourne: NCCI; 2003.Google Scholar
  10. 10.
    Cancer Council Australia. Basal cell carcinoma, squamous cell carcinoma (and related lesions) - a guide to clinical management in Australia. Sydney: Cancer Council Australia and Australian Cancer Network; 2008.Google Scholar
  11. 11.
    Stern RS. Prevalence of a history of skin cancer in 2007: results of an incidence-based model. Arch Dermatol. 2010;146(3):279–82.CrossRefPubMedGoogle Scholar
  12. 12.
    Australian Institute of Health and Welfare. Cancer incidence projections: Australia, 2011 to 2020, vol. Cancer Series no. 66. Cat. No. CAN 62. Canberra: AIHW; 2012.Google Scholar
  13. 13.
    Aitken R, Morrell S, Barraclough H, Baker D, Clements M, Jelfs P, et al. Cancer incidence and mortality projections in New South Wales, 2007 to 2011. Sydney: Cancer Institute NSW; 2008.Google Scholar
  14. 14.
    Baade P, Coory M. Trends in melanoma mortality in Australia: 1950–2002 and their implications for melanoma control. ANZJPH. 2005;29(4):383–6.Google Scholar
  15. 15.
    Clegg LX, Reichman ME, Miller BA, Hankey BF, Singh GK, Lin YD, et al. Impact of socioeconomic status on cancer incidence and stage at diagnosis: selected findings from the surveillance, epidemiology, and end results: National Longitudinal Mortality Study. Cancer Causes Control. 2009;20(4):417–35.CrossRefPubMedGoogle Scholar
  16. 16.
    Davis KL, Mitra D, Kotapati S, Ibrahim R, Wolchok JD. Direct economic burden of high-risk and metastatic melanoma in the elderly: evidence from the SEER-Medicare linked database. Appl Health Econ Health Policy. 2009;7(1):31–41.CrossRefPubMedGoogle Scholar
  17. 17.
    Ekwueme DU, Guy GP, Li C, Rim SH, Parelkar P, Chen SC. The health burden and economic costs of cutaneous melanoma mortality by race/ethnicity-United States, 2000 to 2006. J Am Acad Dermatol. 2011;65(5 Suppl 1):S133–43.PubMedGoogle Scholar
  18. 18.
    Seidler AM, Pennie ML, Veledar E, Culler SD, Chen SC. Economic burden of melanoma in the elderly population: population-based analysis of the Surveillance, Epidemiology, and End Results (SEER)--Medicare data. Arch Dermatol. 2010;146(3):249–56.CrossRefPubMedGoogle Scholar
  19. 19.
    Pereira de Souza RJ, Mattedi AP, Correa MP, Rezende ML, Ferreira AC. An estimate of the cost of treating non-melanoma skin cancer in the state of Sao Paulo, Brazil. An Bras Dermatol. 2011;86(4):657–62.CrossRefGoogle Scholar
  20. 20.
    Augustin M, Blome C, Rustenbach SJ, Reusch M, Radtke M. Routine skin cancer screening in Germany: First data on the impact on health care in dermatology. J Dtsch Dermatol Ges. 2010;8(9):674–80.PubMedGoogle Scholar
  21. 21.
    Leiter U, Marghoob AA, Lasithiotakis K, Eigentler TK, Meier F, Meisner C, et al. Costs of the detection of metastases and follow-up examinations in cutaneous melanoma. Melanoma Res. 2009;19(1):50–7.CrossRefPubMedGoogle Scholar
  22. 22.
    Alexandrescu DT. Melanoma costs: a dynamic model comparing estimated overall costs of various clinical stages. Dermatol Online J. 2009;15(11):1.Google Scholar
  23. 23.
    Stang A, Stausberg J, Boedeker W, Kerek-Bodden H, Jockel KH. Nationwide hospitalization costs of skin melanoma and non-melanoma skin cancer in Germany. J Eur Acad Dermatol Venereol. 2008;22(1):65–72.PubMedGoogle Scholar
  24. 24.
    Chevalier J, Bonastre J, Avril M-F. The economic burden of melanoma in France: assessing healthcare use in a hospital setting. Melanoma Res. 2008;18(1):40–6.CrossRefPubMedGoogle Scholar
  25. 25.
    Chen JG, Fleischer AB, Smith ED, Kancler C, Goldman ND, Williford PM, et al. Cost of nonmelanoma skin cancer treatment in the United States. Dermatol Surg. 2001;27(12):1035–8.PubMedGoogle Scholar
  26. 26.
    Guy G, Ekwueme D, Tangka F, Richardson L. Melanoma treatment costs: a systematic review of the literature, 1990–2011. Am J Prev Med. 2012;43(5):537–45.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Guy G, Ekwueme D. Years of potential life lost and indirect costs of melanoma and non-melanoma skin cancer: a systematic review of the literature. Pharmacoeconomics. 2011;29(10):863–74.CrossRefPubMedGoogle Scholar
  28. 28.
    Bradley CJ, Yabroff KR, Dahman B, Feuer EJ, Mariotto A, Brown ML. Productivity Costs of Cancer Mortality in the United States: 2000–2020. J Natl Cancer Inst. 2008;100(24):1763–70. doi: 10.1093/jnci/djn384.CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Tinghog G, Carlsson P, Synnerstad I, Rosdahl I. Societal cost of skin cancer in Sweden in 2005. Acta Derm-Venereol. 2008;88(5):467–73.CrossRefPubMedGoogle Scholar
  30. 30.
    O’Dea D. The costs of skin cancer to New Zealand. Cancer Society of New Zealand: Wellington; 2009.Google Scholar
  31. 31.
    Morris S, Cox B, Bosanquet N. Cost of skin cancer in England. Eur J Health Econ. 2009;10(3):267–73.CrossRefPubMedGoogle Scholar
  32. 32.
    Eriksson T, Tinghög G. Societal cost of skin cancer in Sweden in 2011. Acta Derm Venereol. 2015;95(3):347–8.CrossRefPubMedGoogle Scholar
  33. 33.
    Cancer Institute New South Wales. NSW skin cancer prevention strategy 2012–15. Sydney: Cancer Institute NSW; 2012.Google Scholar
  34. 34.
    Drummond M, Torrance G, O Brien B, Stoddart G. Methods for the economic evaluation of health care programmes. New York: Oxford University Press; 2005.Google Scholar
  35. 35.
    Cancer Institute New South Wales. NSW Central Cancer Registry Data Access. Sydney: CINSW; 2013. http://www.cancerinstitute.org.au/data-and-statistics/cancer-registries/nsw-central-cancer-registry-data-access.
  36. 36.
    Australian Bureau of Statistics. Estimated resident population, by age and sex. Catalogue no. 3201.0. Canberra: ABS; 2013.Google Scholar
  37. 37.
    Marks R, Staples MP, Giles GG. Trends in non-melanocytic skin cancer treated in Australia: the second national survey. Int J Cancer. 1993;53:585–90.CrossRefPubMedGoogle Scholar
  38. 38.
    Australian Institute of Health and Welfare. Non-melanoma skin cancer, General practice consultations, hospitalisation and mortality. Cat. No. 39. Canberra: AIHW; 2008.Google Scholar
  39. 39.
    Sax Instittute. 45 and Up Study. Sydney: Sax Instittute; 2013. https://www.saxinstitute.org.au/our-work/45-up-study/. Accessed June 2012.
  40. 40.
    Australian Bureau of Statistics. NSW Health Department, admitted patient data collection. Cat. No. 1368.1. Canberra: ABS; 2013.Google Scholar
  41. 41.
    Australian Government Department of Human Services. Pharmaceutical Benefits Scheme (PBS). Canberra: Australian Government; 2013. http://www.pbs.gov.au/pbs/home. Accessed June 2012.
  42. 42.
    Australian Government Department of Human Services. Medicare Benefits Schedule. Canberra: Australian Government; 2013. http://www.mbsonline.gov.au/. Accessed June 2012.
  43. 43.
    Government of New South Wales. Registry of Births, Deaths and Marriages (RBDM). Sydney: NSW Government; 2013. http://www.bdm.nsw.gov.au/. Accessed June 2012.
  44. 44.
    World Health Organisation. International Statistical Classification of Diseases and Related Health Problems 10th Revision. Geneva: WHO; 2013. http://apps.who.int/classifications/icd10/browse/2010/en. Accessed June 2012.
  45. 45.
    Australian Institute of Health and Welfare. Health expenditure Australia 2010–11. Health and welfare expenditure series no. 47. Cat. No. HWE 56. Canberra: AIHW; 2012.Google Scholar
  46. 46.
    Begg S, Vos T, Barker B, Stevenson C, Stanley L, Lopez AD. The burden of disease and injury in Australia 2003. PHE 82. Canberra: AIHW; 2007.Google Scholar
  47. 47.
    Single E, Collns D, Easton B, Harwood HJ, Lapsley H, Kopp P, et al. International guidelines for estimating the costs of substance abuse. Geneva: World Health Organisation; 2003.Google Scholar
  48. 48.
    Australian Bureau of Statistics. Average weekly earnings. Cat. No. 6302.0. Canberra: ABS; 2013.Google Scholar
  49. 49.
    Australian Bureau of Statistics. Labour force. Cat. No. 6202.0. Canberra: ABS; 2013.Google Scholar
  50. 50.
    Safe Work Australia. National hazard exposure worker surveillance: exposure to direct sunlight and the provision of sun exposure controls in Australian workplaces. Canberra: Commonwealth of Australia; 2010.Google Scholar
  51. 51.
    Economics A. The economic value of informal care in 2010: Report for Carers Australia. Access Economics: Canberra; 2010.Google Scholar
  52. 52.
    Barzilai DA, Koroukian SM, Neuhauser D, Cooper KD, Rimm AA, Cooper GS. The sensitivity of Medicare data for identifying incident cases of invasive melanoma (United States). Cancer Causes Control. 2004;15(2):179–84.CrossRefPubMedGoogle Scholar
  53. 53.
    Styperek A, Kimball AB. Malignant melanoma: The implications of cost for stakeholder innovation. Am J Pharm Ben. 2012;4(2):66–76.Google Scholar
  54. 54.
    Australian Institute of Health and Welfare. Health system expenditures on cancer and other neoplasms in Australia, 2000–2001, in Health and Welfare Expenditure Series no. 22. Canberra: AIHW; 2005.Google Scholar
  55. 55.
    Mathers C, Penm R, Sanson-Fisher R, Carter R, Campbell E. Health system costs of cancer in Australia 1993–94. AIHW Cat. No. HWE 4. Canberra: AIHW and National Cancer Countrol Intitiative; 1998.Google Scholar

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© Doran et al. 2015

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  • Christopher M. Doran
    • 1
  • Rod Ling
    • 1
  • Joshua Byrnes
    • 2
  • Melanie Crane
    • 3
    • 4
  • Andrew Searles
    • 1
  • Donna Perez
    • 3
  • Anthony Shakeshaft
    • 5
  1. 1.Hunter Medical Research Institute, University of NewcastleNew LambtonAustralia
  2. 2.Centre for Applied Health Economics, Griffith UniversityMeadowbrookAustralia
  3. 3.Cancer Institute NSWAlexandriaAustralia
  4. 4.School of Public Health, University of SydneySydneyAustralia
  5. 5.National Drug and Alcohol Research Centre, University of New South Wales SydneySydneyAustralia

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