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  • Research article
  • Open Access
  • Open Peer Review

Favorable mortality-to-incidence ratios of kidney Cancer are associated with advanced health care systems

  • 1, 2, 3,
  • 1, 2, 3,
  • 1, 2, 3,
  • 2, 4,
  • 5,
  • 1, 2, 3,
  • 1, 2, 3 and
  • 1, 2, 3Email author
Contributed equally
BMC Cancer201818:792

https://doi.org/10.1186/s12885-018-4698-6

  • Received: 13 November 2017
  • Accepted: 26 July 2018
  • Published:
Open Peer Review reports

Abstract

Background

The advancements in cancer therapy have improved the clinical outcomes of cancer patients in recent decades. However, advanced cancer therapy is expensive and requires good health care systems. For kidney cancer, no studies have yet established an association between clinical outcome and health care disparities.

Methods

We used the mortality-to-incidence ratio (MIR) for kidney cancer as a marker of clinical outcome to compare World Health Organization (WHO) country rankings and total expenditures on health/gross domestic product (e/GDP) using linear regression analyses.

Results

We included 57 countries based on data from the GLOBOCAN 2012 database. We found that more highly developed regions have higher crude and age-standardized rates of kidney cancer incidence and mortality, but a lower MIR, when compared to less developed regions. North America has the highest crude rates of incidence, but the lowest MIRs, whereas Africa has the highest MIRs. Furthermore, favorable MIRs are correlated with countries with good WHO rankings and high e/GDP expenditures (p < 0.001 and p = 0.013, respectively).

Conclusions

Kidney cancer MIRs are positively associated with the ranking of health care systems and health care expenditures.

Keywords

  • Kidney cancer
  • Mortality
  • Incidence
  • Mortality-to-incidence ratio

Background

Cancer is a leading cause of death worldwide, and the burden continues to increase in both developed and less developed countries due to lifestyle behaviors, such as smoking, poor diet, and physical inactivity [1, 2]. Kidney cancer currently ranks as the seventh most common cancer in men and the tenth most common in women [3]. In 2012, the worldwide estimates for kidney cancer were 338,000 new cases (incidence: 2.4%) and 143,000 deaths (mortality: 1.7%) [3]. The geographic distribution of kidney cancer is highest in the Baltic countries and in Eastern European countries, such as the Czech Republic and Slovakia, and lowest in Africa and Asia, with the exception of Israel [4]. The mortality distribution also follows incidence patterns, with the highest death rates observed in Eastern Europe [4]. Renal cell carcinoma accounts for more than 90% of kidney malignancies, with the main subtype being clear cell renal cell carcinoma (70%) [5].

The clinical outcomes of cancer treatment can be measured by the five-year survival rate, as well as partially by the mortality-to-incidence ratio (MIR) [612]. In the past 10 years, the incidence of renal cell carcinoma has increased in most countries [13]. By contrast, the mortality associated with this disease has been relatively stable worldwide, but is decreasing in Western Europe, the US, and Australia [13]. For example, the five-year relative survival rate for kidney cancer patients in the US in 2005–2011 was approximately 74%, an increase from the rate of approximately 57% in the 1980s [1, 2]. These trends suggest that health care systems and health care expenditures are affecting the screening, treatment, and prognosis of kidney cancer.

We hypothesize that the MIR should be low in countries with better health care systems. Our primary goal in the present study was to identify the roles played by the level of human development, World Health Organization (WHO) rankings, and total expenditure on health/gross domestic product (e/GDP) in kidney cancer outcomes. Our secondary goal was to clarify the correlation between MIRs and the WHO ranking and e/GDP and to determine the association between e/GDP or WHO ranking and the crude rate or age-standardized rate (ASR) of kidney cancer incidence and mortality. Our results provide a general overview of the connection between MIR and health care disparities across countries.

Methods

The data were acquired as described previously [6, 12, 14]. In brief, the cancer epidemiologic data were obtained from the GLOBOCAN 2012 database, which is maintained by the International Agency for Research on Cancer (https://www.iarc.fr/) [3]. Health care expenditures and life expectancies were obtained from the WHO World Health Statistics 2015, and the WHO rankings were obtained from the WHO World’s Health Systems. We included 184 countries listed in the GLOBOCAN 2012 database. Countries that lacked WHO ranking data (22 countries) or that had little data available (a ranking of E–G for incidence or a ranking of 4–6 for mortality; 105 countries) were excluded.

The MIR is defined as the ratio of the crude rate of mortality to the disease incidence [7, 10]. The method of statistical analyses was described previously [6, 14]. We used linear regression and SPSS statistical software (SPSS, version 15.0, Inc., Chicago, IL, US) to evaluate the association between the MIRs and variants. P values < 0.05 were considered statistically significant. Scatter plots were produced using Microsoft Excel 2010.

Results

The incidence and mortality of kidney cancer are higher in more developed regions and in regions in the west

We first sought to understand the present global situation regarding kidney cancer by analyzing the crude rate and the ASR of kidney cancer incidence and mortality according to development level, WHO region, and continent (see Table 1). The crude rate of incidence and the cancer-related mortality rate worldwide are 4.8 and 2.0, respectively, for kidney cancer. Both rates tend to be higher in more developed regions (incidence: 16.1 vs. 2.4; mortality: 6.0 vs. 1.2, respectively). The analysis based on WHO regions and continents indicated that the WHO European region had the highest crude rate of incidence and mortality (13.5 and 5.9, respectively), followed by the WHO Americas region (8.9 and 2.9, respectively). North America had the highest crude rate of incidence (18.2), and Europe had the highest mortality rate (6.6). The ASR distribution showed a similar pattern, as the ASRs of incidence and mortality were 9.2 and 2.8 in more developed regions, with the highest values associated with the WHO European region (8.3 and 3.1, respectively) and the WHO Americas region (7.3 and 2.2, respectively). North America had the highest ASR of incidence (11.7), while Europe had the highest ASR of mortality (3.1), and both regions are developed.
Table 1

Summary of the number of cases, rates, and mortality-to-incidence ratios of kidney cancer according to region

Region

Number

Crude rate

Age-standardized rate

Mortality-to-incidence ratioa

Incidence

Mortality

Incidence

Mortality

Incidence

Mortality

World

337,860

143,406

4.8

2.0

4.4

1.8

0.42

Development

 More developed regions

199,991

74,948

16.1

6.0

9.2

2.8

0.37

 Less developed regions

137,869

68,458

2.4

1.2

2.6

1.3

0.50

WHO region categories

 WHO Africa region

6725

5649

0.8

0.6

1.0

0.8

0.75

 WHO Americas region

85,005

27,949

8.9

2.9

7.3

2.2

0.33

 WHO East Mediterranean region

8952

6628

1.4

1.1

1.9

1.5

0.79

 WHO Europe region

121,629

52,816

13.5

5.9

8.3

3.1

0.44

 WHO South-East Asia region

17,050

11,399

0.9

0.6

1.1

0.7

0.67

 WHO Western Pacific region

98,473

38,951

5.3

2.1

4.1

1.5

0.40

Continent

 Africa

10,033

8169

0.9

0.8

1.2

1.0

0.89

 Latin America and Caribbean

21,183

11,308

3.5

1.9

3.5

1.8

0.54

 Northern America

63,822

16,641

18.2

4.7

11.7

2.6

0.26

 Asia

123,402

57,058

2.9

1.3

2.8

1.3

0.45

 Europe

115,252

49,025

15.5

6.6

8.8

3.1

0.43

 Oceania

4168

1205

11.0

3.2

8.0

2.0

0.29

athe percentage in the ratio of the crude rate of mortalities and the crude rate of incidences

The kidney cancer mortality-to-incidence ratios are high in less developed regions

We also investigated the MIRs to determine any association between this ratio and the outcomes of kidney cancer patients. The global kidney cancer MIR is 0.42, with a higher rate in less developed regions (0.5). The WHO East Mediterranean region had the highest kidney cancer MIR (0.79), followed by the WHO Africa region (0.75). Among the continents, Africa had the highest MIR (0.89). High MIRs were therefore associated with less developed regions and with Africa.

World Health Organization ranking and total expenditure on health/GDP are significantly associated with kidney cancer mortality-to-incidence ratios

We sought to understand the observed differences between nations by including countries based on national data, WHO rankings, total expenditure on health/GDP (e/GDP), crude rate of incidence and mortality, the ASR of incidence and mortality, and life expectancy (Table 2). France was the highest WHO ranked country, whereas the US had the highest e/GDP (17.0%). Among all the countries, the Czech Republic had the highest crude rate of incidence (22.7), and Estonia had the highest mortality rate (10.6). Of the 57 countries compared, Luxembourg had the lowest MIR (0.17). We further examined the correlation between the kidney cancer MIR and the WHO ranking and e/GDP (Table 2; Fig. 1). The WHO ranking and e/GDP showed a significant positive correlation with kidney cancer MIRs (R2 = 0.232, p < 0.001; R2 = 0.107, p = 0.013, respectively; Fig. 1).
Table 2

Summary of World Health Organization country rankings; total expenditure on health/GDP; life expectancy; and the kidney cancer incidence, mortality, and mortality-to-incidence ratios of selected countries

Country

Ranking

Total expenditure on health/GDP (%)

Life expectancy

Number

Crude rate

Age-standardized rate

Mortality-to-incidence ratioa

Incidence

Mortality

Incidence

Mortality

Incidence

Mortality

France

1

11.6

82

11,023

4186

17.4

6.6

9.7

2.8

0.38

Italy

2

9.2

83

11,300

4203

18.5

6.9

8.7

2.5

0.37

Malta

5

8.7

81

57

27

13.6

6.4

8.0

3.0

0.47

Singapore

6

4.2

83

401

175

7.6

3.3

5.2

2.2

0.43

Spain

7

9.3

83

6474

2295

13.8

4.9

7.9

2.2

0.36

Oman

8

2.7

76

36

21

1.2

0.7

2.1

1.4

0.58

Austria

9

11.1

81

1322

536

15.7

6.4

8.0

2.5

0.41

Japan

10

10.3

84

16,830

8124

13.3

6.4

5.3

1.9

0.48

Norway

11

9.3

82

798

263

16.1

5.3

9.3

2.5

0.33

Portugal

12

9.9

81

1004

368

9.4

3.4

5.0

1.4

0.36

Iceland

15

9.0

82

45

19

13.7

5.8

8.8

3.2

0.42

Luxembourg

16

7.2

82

70

12

13.4

2.3

8.3

0.9

0.17

Netherlands

17

12.7

81

2679

1463

16.0

8.8

8.8

4.0

0.55

United Kingdom

18

9.3

81

9714

4150

15.5

6.6

8.2

3.0

0.43

Ireland

19

8.9

81

571

230

12.5

5.0

8.4

3.0

0.40

Switzerland

20

11.4

83

948

448

12.3

5.8

6.5

2.4

0.47

Belgium

21

10.9

80

1763

728

16.3

6.7

8.7

2.7

0.41

Colombia

22

6.8

78

1048

483

2.2

1.0

2.4

1.1

0.45

Sweden

23

9.6

82

1125

635

11.8

6.7

6.4

2.6

0.57

Cyprus

24

7.3

82

46

17

4.1

1.5

3.0

1.0

0.37

Germany

25

11.3

81

18,615

7540

22.7

9.2

10.6

3.3

0.41

Israel

28

7.4

82

1002

217

13.0

2.8

10.0

1.8

0.22

Canada

30

10.9

82

5579

1739

16.1

5.0

9.3

2.5

0.31

Finland

31

9.1

81

882

333

16.3

6.2

7.9

2.4

0.38

Australia

32

8.9

83

3501

960

15.3

4.2

9.5

2.1

0.27

Chile

33

7.3

80

1353

737

7.8

4.2

6.0

3.1

0.54

Denmark

34

11.0

80

754

352

13.5

6.3

7.2

2.9

0.47

Costa Rica

36

10.1

79

179

69

3.7

1.4

3.7

1.4

0.38

United States of America

37

17.0

79

58,222

14,900

18.4

4.7

12.0

2.6

0.26

Slovenia

38

9.4

80

400

171

19.6

8.4

11.1

3.9

0.43

Cuba

39

8.6

78

517

271

4.6

2.4

3.1

1.5

0.52

New Zealand

41

10.2

82

586

198

13.1

4.4

8.2

2.4

0.34

Bahrain

46

4.4

77

23

7

1.7

0.5

2.6

1.0

0.29

Thailand

47

4.5

75

1017

632

1.5

0.9

1.2

0.7

0.60

Czech Republic

48

7.5

78

3313

1095

31.4

10.4

16.7

4.8

0.33

Malaysia

49

4.0

74

611

255

2.1

0.9

2.4

1.0

0.43

Poland

50

6.8

77

5244

2721

13.7

7.1

8.1

3.7

0.52

Jamaica

53

5.6

74

31

20

1.1

0.7

1.1

0.7

0.64

Korea, Republic of

58

7.6

82

5651

1264

11.6

2.6

8.0

1.6

0.22

Philippines

60

4.4

69

1008

600

1.0

0.6

1.4

0.9

0.60

Slovakia

62

8.1

76

1063

388

19.4

7.1

12.5

4.2

0.37

Egypt

63

4.9

71

1740

1275

2.1

1.5

2.4

1.8

0.71

Uruguay

65

8.6

77

465

243

13.7

7.2

9.4

4.4

0.53

Trinidad and Tobago

67

5.5

71

32

18

2.4

1.3

2.3

1.1

0.54

Belarus

72

5.0

72

1575

637

16.5

6.7

11.1

4.1

0.41

Lithuania

73

6.7

74

773

309

23.5

9.4

13.2

4.9

0.40

Argentina

75

6.8

76

4068

1998

9.9

4.9

8.0

3.6

0.49

Estonia

77

5.9

77

284

142

21.2

10.6

11.7

4.6

0.50

Ukraine

79

7.5

71

5240

2542

11.7

5.7

7.5

3.4

0.49

Mauritius

84

4.8

74

53

25

4.0

1.9

4.2

2.2

0.48

Fiji

96

4.0

70

4

3

0.5

0.3

0.4

0.4

0.60

Bulgaria

102

7.4

75

881

470

11.9

6.4

6.9

3.3

0.54

Latvia

105

5.9

74

449

225

20.1

10.1

10.9

4.7

0.50

Ecuador

111

6.4

76

403

216

2.7

1.5

2.9

1.5

0.56

Brazil

125

9.5

75

6255

3291

3.2

1.7

3.0

1.5

0.53

Russian Federation

130

6.5

69

19,313

9025

13.5

6.3

8.9

3.8

0.47

South African Republic

175

8.9

60

506

420

1.0

0.8

1.2

1.1

0.80

athe percentage in the ratio of the crude rate of mortalities and the crude rate of incidences

Fig. 1
Fig. 1

The (a) World Health Organization country rankings and (b) total expenditures on health/GDP are significantly associated with the mortality-to-incidence ratio of kidney cancer

No significant correlation is evident between the World Health Organization ranking, crude rate, and age-standardized rate of incidence and mortality for kidney cancer

Unexpectedly, we found no significant correlation between WHO ranking and the crude rate of incidence and mortality for kidney cancer (R2 = 0.058, p = 0.071; R2 = 0.018, p = 0.317, respectively; Additional file 1: Figure S1A and B). Countries with a higher WHO ranking also showed no higher incidence or greater mortality rate in age-standardized groups (R2 = 0.032, p = 0.185; R2 = 0.004, p = 0.629, respectively; Additional file 1: Figure S1C and D).

The association between total expenditure on health/GDP and the kidney cancer crude rate and age-standardized rate of incidence and mortality

We also analyzed the correlation between e/GDP and crude rate and the ASR of incidence and mortality for kidney cancer (Additional file 2: Figure S2). The crude rate of incidence and mortality in these countries increased with increasing e/GDP (R2 = 0.237, p < 0.001; R2 = 0.169, p = 0.001, respectively; Additional file 2: Figure S2A and B), and the same trend was seen for the association between e/GDP and the ASR of incidence (R2 = 0.187, p = 0.001; Additional file 2: Figure S2C). However, no significant correlation was noted between e/GDP and the ASR of mortality (R2 = 0.053, p = 0.084; Additional file 2: Figure S2D). In summary, the e/GDP had a significant correlation with the incidence and mortality crude rate of kidney cancer, while the ASR of mortality was not significantly correlated with e/GDP.

Discussion

To the best of our knowledge, this is the first article to explore the relationship between the MIRs of kidney cancer and WHO rankings, life expectancy, and e/GDP. Negative correlations between the WHO ranking and life expectancy and e/GDP (%) would be understandable, as disability-adjusted life expectancy and fair financial contribution were two of the index factors on which the WHO ranking is based. High MIRs are observed in less developed countries for genitourinary malignancies [15]. In the present study, we found a positive correlation between WHO rankings and MIRs, in agreement with a previous study on colorectal cancer that showed similar results among the Organisation for Economic Co-operation and Development countries [10]. Sunkara et al. attributed this correlation to the better screening programs provided by countries with better WHO rankings for certain cancer such as colorectal cancer. However, there is no screen program for kidney cancer, the improved MIR might relate to the availability of medical service and health examination.

As with colorectal cancer, kidney cancer outcomes depend on early detection and proper intervention. The increased demand for abdominal imaging has led to an increase in the incidental detection of kidney masses, usually as small indolent cancers [16]. As a result, in the US, 63% of kidney cancers are diagnosed at a localized stage [17], and this directly affects outcome as the five-year survival rates show substantial differences among stages. The localized stage has the best prognosis, with a 92% five-year survival rate, while the distant stage has only a 12% five-year survival rate [17]. These numbers point to the importance of early detection of this disease. In general, this means that countries with better health care programs would be expected to have lower MIRs due to the availability of image survey such as sonography or computed tomography scan. This increases the incidental finding of renal mass and might relate to early diagnosis and good prognosis. This could then explain the observed association between WHO rankings and MIRs.

We also found negative correlations between WHO rankings and crude mortality and incidence rates, indicating higher rates in countries with better WHO rankings. One possible explanation is the inconsistency of access to medical care among different countries, as nations with worse WHO rankings are less likely to have good health care access. This means less abdominal imaging and less detection of early signs and symptoms of kidney cancer, so the incidence and mortality rates increase. Another explanation is the age distribution of this disease. Most cases are diagnosed between the ages of 60 and 70, with the median age being 65 [18, 19]. Therefore, the populations of countries with longer life expectancy would have a greater risk of developing kidney cancer. As life expectancy correlates positively with WHO rankings and WHO rankings correlate negatively with mortality, the crude rates of incidence are understandable.

The impact of high health care expenditure on good MIRs for kidney cancer is multifactorial, as noted for other types of cancer [6, 11, 12, 14]. Patients in countries with higher health care expenditure would have a greater chance of early malignancy detection and prompt curative treatment or less invasive surgery. From the perspective of surgical intervention for kidney cancer, patients with early T stage cancer would have a larger volume of healthy renal parenchyma for renal preservation, which might result in a better clinical outcome [20]. For partial nephrectomy, outcomes are more favorable for robotic surgery than for laparoscopic surgery in terms of a lower conversion rate to radical nephrectomy, favorable retention of renal function, and shorter warm ischemia time [2123]. These features could partially explain the role of health expenditure in the MIR of kidney cancer.

Our study has some limitations. Since the GLOBCAN database provides national statistics information worldwide, the data quality should be further validated. Countries with low data quality or unknown data quality were excluded to avoid misleading effects of over diagnosis or other influences. Due to concerns about generating misleading MIRs, we did not include all the countries listed in the database. This resulted in incomplete data, which makes our results unreliable in the global context. Furthermore, we did not document the diagnosed stage and risk factors among countries, such as smoking, obesity, and hypertension rates. These risk factors may play crucial roles in explaining the incidence and mortality rates among countries and regions. In addition, we only examined cross-sectional data for a single year, so the actual disease trend may not be accurately presented. Another limitation is the use of WHO rankings. This grading system was established in 2000, so it may not precisely reflect the current situation for health care systems in different countries, although the correlations with life expectancy and e/GDP speak to its credibility.

Despite these limitations, our study shows higher kidney cancer incidence and mortality rates in more developed regions and in countries with better WHO rankings. Moreover, the MIRs for these countries are negatively correlated with their WHO rankings for both genders. Based on the results, we suspect that the kidney cancer MIR might be an appropriate indicator for evaluating health care systems. The massive discrepancies in kidney cancer MIRs between countries and regions suggest a role for early detection and proper screening facilities in countries with higher MIR values.

Conclusions

Kidney cancer MIRs are associated with the ranking of health care systems and health care expenditures and therefore might be an indicator of health care disparities.

Notes

Abbreviations

ASR: 

Age-standardized rate

e/GDP: 

Total expenditures on health/gross domestic product

MIR: 

Mortality-to-incidence ratio

WHO: 

World Health Organization

Declarations

Funding

There is no funding or grant support for this work.

Availability of data and materials

All the data were obtain from the global statistics of GLOBOCAN (http://globocan.iarc.fr/Default.aspx).

Research involving human participants

All the data were obtained from the global statistics of GLOBOCAN (http://globocan.iarc.fr/Default.aspx). This is a study of analytic epidemiology, and we did not perform any intervention on human participants.

Informed consent

All the data were obtain from the global statistics of GLOBOCAN (http://globocan.iarc.fr/Default.aspx). This is a study of analytic epidemiology that involved no intervention on human participants, so no informed consent was required.

Authors’ contributions

Conception and design: WWS, TYH, SCW; acquisition of data: TYH; analysis and interpretation of data: WWS, WJC, CJH, CYH; drafting of the manuscript: CJH, CYH; critical revision of the manuscript: WWS, YLK, SLC; statistical analysis: WWS, TYH; supervision: WWS, SCW, SLC. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Not applicable. All the data were obtained from the global statistics of GLOBOCAN (http://globocan.iarc.fr/Default.aspx). This is a study of analytic epidemiology, and we did not perform any intervention on human participants. We confirm that this study complies with national guidelines (http://law.moj.gov.tw/LawClass/LawAll.aspx?PCode=L0020162).

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Authors’ Affiliations

(1)
Department of Urology, Chung Shan Medical University Hospital, No.110, Sec. 1, Jianguo N. Rd., South Dist, Taichung City, 402, Taiwan
(2)
School of Medicine, Chung Shan Medical University, No.110, Sec. 1, Jianguo N. Rd., South Dist, Taichung City, 402, Taiwan
(3)
Institute of Medicine, Chung Shan Medical University, No.110, Sec. 1, Jianguo N. Rd., South Dist, Taichung City, 402, Taiwan
(4)
Department of Medical Education, Chung Shan Medical University Hospital, No.110, Sec. 1, Jianguo N. Rd., South Dist, Taichung City, 402, Taiwan
(5)
Department of Urology, National Taiwan University Hospital, No.95, Wenchang Rd., Shilin Dist, Taipei City, 111, Taiwan

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