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Article

Breast Cancer Screening Programmes across the WHO European Region: Differences among Countries Based on National Income Level

by
Emma Altobelli
1,2,*,
Leonardo Rapacchietta
1,
Paolo Matteo Angeletti
1,
Luca Barbante
1,
Filippo Valerio Profeta
3 and
Roberto Fagnano
4
1
Department of Life, Health and Environmental Sciences, University of L’Aquila, 67100 L’Aquila, Italy
2
Epidemiology and Biostatistics Unit, .Local Health Unit 4, 64100 Teramo, Italy
3
Department of Community Health, Local Health Unit 4, 64100 Teramo, Italy
4
Local Health Unit 4, 64100 Teramo, Italy
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2017, 14(4), 452; https://doi.org/10.3390/ijerph14040452
Submission received: 6 February 2017 / Revised: 3 April 2017 / Accepted: 17 April 2017 / Published: 23 April 2017
(This article belongs to the Special Issue Geographical Variation in Breast Cancer Outcomes)
Browse Figures
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Abstract

:
Breast cancer (BC) is the most frequent tumour affecting women all over the world. In low- and middle-income countries, where its incidence is expected to rise further, BC seems set to become a public health emergency. The aim of the present study is to provide a systematic review of current BC screening programmes in WHO European Region to identify possible patterns. Multiple correspondence analysis was performed to evaluate the association among: measures of occurrence; GNI level; type of BC screening programme; organization of public information and awareness campaigns regarding primary prevention of modifiable risk factors; type of BC screening services; year of screening institution; screening coverage and data quality. A key difference between High Income (HI) and Low and Middle Income (LMI) States, emerging from the present data, is that in the former screening programmes are well organized, with approved screening centres, the presence of mobile units to increase coverage, the offer of screening tests free of charge; the fairly high quality of occurrence data based on high-quality sources, and the adoption of accurate methods to estimate incidence and mortality. In conclusion, the governments of LMI countries should allocate sufficient resources to increase screening participation and they should improve the accuracy of incidence and mortality rates.

1. Introduction

Breast cancer (BC) is the most frequent tumour affecting women all over the world, with an incidence rate of 43.1 (per 100,000 ASR-W), a mortality rate of 12.9 (per 100,000 ASR-W), and a 5-year prevalence of 239.9 [1]. In low- and middle-income countries, where its incidence is expected to rise further, BC seems set to become a public health emergency [2], while the highest incidence rates, reported in high-income countries, are partially to be attributed to earlier screening detection [3].
Indeed, in the WHO European Region rates are higher than global rates, incidence being 66.5 (per 100,000 ASR-W) and mortality 16.0 (per 100,000 ASR-W). In EU-28 countries the incidence rate is 80.3 (per 100,000 ASR-W) and the mortality rate 14.4 (per 100.000 ASR-W) [1]. Most EU-28 countries [4], including the UK [5,6,7,8], France [9,10], Italy [11], and Belgium [12,13,14,15], have national cancer prevention population-based (PB) screening programmes not only for BC, but also for cervical cancer (CC) [16] and, as of recently, colorectal cancer (CRC) [17,18]. Within the Council of Europe (CoE), which includes the EU-28 member States (MS) and 19 other countries [18], the right to health is enshrined in the “Right to Protection of Health” [19] and in Article 3 of the Convention on Human Rights and Biomedicine (equal conditions for access to health services) [20,21,22].
In Europe, population-based (PB) mammography screening has reduced mortality by 25%–31%, and by 38%–48% in women receiving adequate follow-up [14]. The level of evidence regarding the usefulness of mammography in reducing mortality in women aged 50 to 74 years is “sufficient” [5].
The risk of developing BC is affected by some non-modifiable factors (e.g., age, genetic and familial risk) [23] and by others that can be modified, which are related to lifestyle (e.g., alcohol abuse, tobacco use, and body mass index) [24,25]. Prevention campaigns to reduce the risk attributable to modifiable risk factors should therefore be conducted in all countries.
The aim of the present study is to provide a systematic review of current BC screening programmes in WHO European Region countries to identify possible differences among countries based on gross national income (GNI) [26].

2. Materials and Methods

The WHO European area, which is supervised by the WHO EURO office based in Copenhagen (Denmark), includes 53 countries: Albania, Andorra, Armenia, Austria, Azerbaijan, Belarus, Belgium, Bosnia, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Georgia, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Luxembourg, Malta, Monaco, Montenegro, the Netherlands, Norway, Poland, Portugal, the Republic of Moldova, the Russian Federation, Romania, San Marino, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Tajikistan, the FYR of Macedonia, Turkey, Turkmenistan, Ukraine, the UK, and Uzbekistan. For the purposes of this study, they were grouped according to GNI level referred to per capita Gross National Income (current US$), as indicated by the World Bank [26]: lower-middle income (LMI), $1,026–$4,035; upper-middle income (UMI), $4,036–$12,475; high income (HI), $12,476 or more, and HI OECD countries (Organization for Economic Co-operation and Development), whose average income is $29,016.

2.1. Sources of WHO European Epidemiological Data: Search Strategy

The main data source was the GLOBOCAN 2012 website of the International Agency for Research on Cancer (IARC), which provides access to several databases that enable assessing the impact of BC in 184 countries or territories in the world [1,27]. Additional sources were the WHO, IARC, EUCAN and NORDCAN, the European Network of Cancer Registries (ENCR), volume X of the CI5, and the Ministerial and Public Health Agency websites of the individual countries.
A PubMed search was conducted using Early Cancer Detection OR Cancer Screening OR Screening, Cancer OR Cancer Screening Test OR Early Diagnosis of Cancer OR Cancer Early Diagnosis AND Breast Neoplasm OR Neoplasm, Breast OR Tumours, Breast OR Breast Cancer OR Cancer, Breast OR Mammary Cancer OR Breast Carcinoma AND Europe; Early Cancer Detection OR Cancer Screening OR Screening, Cancer OR Cancer Screening Test OR Early Diagnosis of Cancer OR Cancer Early Diagnosis AND Breast Neoplasm OR Neoplasm, Breast OR Tumours, Breast OR Breast Cancer OR Cancer, Breast OR Mammary Cancer OR Breast Carcinoma AND “state name”. Only works published in English in the previous 10 years were considered. A MeSH search was conducted using ((“Breast Neoplasms”[Mesh]) AND “Early Detection of Cancer”[Mesh]) AND Europe; ((“Breast Neoplasms”[Mesh]) AND “Early Detection of Cancer”[Mesh]) AND “state name” for each country.
The EMBASE database did not provide further relevant results. The registries of some websites and the www.cochranelibrary.com, Scopus, www.clinicaltrials.gov, www.clinicaltrialsregister.eu, Research gate, and Google databases and the national sites of patients’ association were also consulted. All works reporting information considered relevant for the systematic review were examined.

2.2. Data Synthesis

The 1-, 3-, and 5-year standardized prevalence rates per 100,000 population (ASR-W) for 2012 are reported in Table 1. Incidence and mortality data and their age-standardized rates per 100,000 population (ASR-W) for 2012 are reported in Figure 1. The quality of the epidemiological data of each country, based on Data Sources and Methods according to Mathers [28], is compared in Table 4. The data concerning national primary and secondary prevention campaigns are reported in Table 2. Finally, the information regarding BC screening programmes in the WHO European region is shown in Table 3.

2.3. Correspondence Statistical Analysis

Multiple correspondence analysis was performed to evaluate the association among the following variables and identify possible patterns: measures of occurrence (BC incidence, mortality, and prevalence); GNI level (LMI, UMI, and HI); type of BC screening programme in place (national PB/non-national PB; spontaneous/organized) [1,20]; organization of public information and awareness campaigns regarding primary BC prevention (yes/no) of modifiable risk factors (tobacco use, alcohol, obesity, and sedentary lifestyle); type of BC screening services (public health services/public health services + mobile units); year of screening institution (before 2001, 2001 to 2005, after 2005); screening coverage (<50%, 50%–75%, >75%), and data quality. The latter measures included the availability of incidence data, the availability of mortality data, the method adopted to estimate incidence rates, and the method used to estimate mortality rates. As in a previous study by our group [94], these variables were coded as dummy or ordinal variables, as appropriate, and incorporated into the model. Data quality was grouped and defined according to:
  • The availability of incidence data (three categories): “high quality”, from A to C (A = national data or high-quality regional data, coverage > 50%; B = regional data, coverage between 10 and 50%); C = regional data, coverage < 10%); “medium quality”, from D to E (D = national data, rates; E = regional data, rates; and “low quality”, from F to G (F = frequency; G = no data) [28].
  • The availability of mortality data (three categories): “high/medium”, from 1 to 2 (1–2 quality complete vital registration); “low”, 3 to 4 (3 = quality complete vital registration, 4 = incomplete or sample vital registration); and “incomplete or absent”, from 5 to 6 (% = other sources: cancer registries, autopsy, etc; 6 = no data) [28].
  • The quality of the method adopted to estimate incidence rates (three categories): “high” (1). rates projected to 2012 (38 countries); “medium” (from 2 to 4): (2). Most recent rates applied to 2012 population (20 countries), (3). Estimated from national mortality by modelling, using incidence mortality ratios derived from recorded data in country-specific cancer registries (13 countries), (4). Estimated from national mortality estimates by modelling, using incidence mortality ratios derived from recorded data in local cancer registries in neighbouring countries (nine European countries); “low” (from 5 to 9): (5). Estimated from national mortality estimates using modelled survival (32 countries), (6). Estimated as the weighted average of the local rates (16 countries), (7). One cancer registry covering part of a country is used as representative of the country profile (11 countries), (8). Age/sex specific rates for "all cancers" were partitioned using data on relative frequency of different cancers (by age and sex) (12 countries), (9). The rates are those of neighbouring countries or registries in the same area (33 countries) [28].
  • The quality of the method used to estimate mortality rates (three categories): “high” (1). rates projected to 2012 (69 countries); “medium” (from 2 to 4): (2). Most recent rates applied to 2012 population (26 countries), (3). Estimated as the weighted average of regional rates (1 country), (4). Estimated from national incidence estimates by modelling, using country-specific survival (two countries); “low” (from 5 to 6): (5). Estimated from national incidence estimates using modelled survival (83 countries). (6). The rates are those of neighbouring countries or registries in the same area (3 countries) [28].
Finally, incidence, 5-year prevalence, and mortality data were grouped into the following classes, respectively: ≤10/100,000/population, from 10.1 to 20/100,000, from 20.1 to 30/100,000, >30/100,000), ≤100/100,000, 101–150/100,000, 151–200/100,000, 201–250/100,000, >250/100,000), ≤5/100,000, from 5.1 to 10, from 10.1 to 15 and >15/100,000. SAS/STAT software (SAS Institute, Cary, NC, USA) was used for statistical analysis.

3. Results

3.1. Systematic Review

3.1.1. High-Income OECD Countries

The group of HI OECD countries includes 25 States, 21 EU MS (Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Luxembourg, the Netherlands, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, and UK), three CoE MS (Iceland, Norway, Switzerland), and a country with observer status in the CoE (Israel).
The highest BC incidence rates are found in Belgium (111.9), the Netherlands (99), and the UK (95) (vs. 80.3 in EU-28 and 66.5 in the WHO European region) and the lowest in Greece (43.9), Estonia (51.6), Poland (51.9), and Hungary (54.5). Mortality rates are highest in Belgium (20.3), Norway (20.2), Italy (19.1), and Denmark (18.8), and lowest in Spain (11.8), Slovakia (13.1), Portugal (13.1), and Sweden (13.4) (Figure 1).
The 1-year prevalence of BC is > 200 in Denmark and Belgium; its 3-year prevalence is >500 in Denmark, Belgium, the Netherlands, and Finland; and its 5-year prevalence is >800 in Belgium, Denmark, the Netherlands, and Finland. The lowest 1-year and 5-year prevalence rates are found in Greece and Estonia, respectively (Table 1).
In 22 of these 25 countries, data quality is high (A–C) as regards the availability of incidence data, medium/high (1–3) for the mortality data, and medium/high (1–3) for the quality of the method adopted to estimate incidence and mortality rates (Table 4).
Public information and awareness campaigns for primary cancer prevention seem to be more common in the States with a universal health service and in Mediterranean countries (Table 2). Organized BC screening programmes are active in all HI OECD countries except Greece, Czech Republic, Slovakia, and some Swiss cantons, with some differences in the target population (Table 3). In the Czech Republic, a campaign directed at women of screening age who had failed to screen was organized in 2014; nonetheless, screening remains spontaneous, meaning that mammography is prescribed by a specialist (senologist or gynaecologist). In Slovakia and Greece there is no mention of organized screening programmes. In Austria, a national screening programme adopted in 2014 (Brustkrebs-Früherkennungs programm) involves rounds at 2-year intervals. Its target population are 45–69 year olds, who are given an e-card offering a mammogram at an approved public or private centre free of charge. Women aged 40–44 years and those aged 70 years or older can also obtain BC screening free of charge, again through activation of an e-card.

3.1.2. High-Income non-OECD Countries

This group includes nine countries, five EU-28 MS (Croatia, Cyprus, Latvia, Lithuania, and Malta) and four CoE MS (Andorra, Monaco, San Marino, and Russian Federation). BC incidence and mortality rates are highest in Malta (85.9; 18.1); incidence is lowest in the Russian Federation (45.6), and mortality is lowest in Cyprus (14.9) (Figure 1). The highest 1-, 3-, and 5-year prevalence rates are found in Malta and the lowest in the Russian Federation.
Public information and awareness campaigns for primary cancer prevention are carried out in nearly all of these States. All have organized BC screening programmes except the Russian Federation, where screening is spontaneous.
In five of these nine countries, data quality is high (A-C) as regards the availability of incidence data, medium/high (1–3) for mortality data, and medium/high (1–3) for the quality of the method applied to estimate incidence and mortality (Table 4). Three countries are not evaluable.

3.1.3. Upper/Middle-Income Countries

This group includes 12 States: Albania (CoE), Azerbaijan (CoE), Belarus, the Federation of Bosnia and Herzegovina (CoE), Bulgaria (EU-28), Kazakhstan, Montenegro (CoE), Romania (EU-28), Republika Srpska (CoE), the FYR of Macedonia (CoE), Turkey (CoE), and Turkmenistan. The FYR of Macedonia has the highest incidence (76.2), mortality (25.5), and prevalence rates as well as 1-, 3-, and 5-year BC prevalence. Incidence and mortality are lowest in Azerbaijan (respectively 25.4 and 8.6), whereas the lowest 1-, 3-, and 5-year prevalence rate is found in Turkmenistan (Figure 1 and Table 1 respectively).
BC screening is PB and nationwide in Kazakhstan, Serbia, the FYR of Macedonia, and Turkey (Table 3); it is PB but local/regional in Belarus and Bosnia and Herzegovina; and is spontaneous in Albania, Bulgaria, and Romania. There is no evidence of BC screening in Azerbaijan or Turkmenistan (Table 3).
Data quality is high (A–C) as regards the availability of incidence data in three countries; medium/high (1–3) for mortality data in four countries; and medium/high (1–3) for the quality of the method used to estimate incidence in three countries. In all but two countries the quality of the method used to estimate mortality is high (Table 4).

3.1.4. Lower/Middle-Income Countries

This group includes seven countries: Armenia, Georgia, Republic of Moldova, and Ukraine (all CoE MS), Kyrgyzstan, Tajikistan, and Uzbekistan. BC incidence is highest in Armenia (74.1) and mortality in Georgia (25.5); 1-, 3-, and 5-year prevalence peaks in Armenia and is lowest in Tajikistan. PB screening programmes are active in Georgia, Kyrgyzstan, and Uzbekistan; they are also reported in Ukraine in 2002–2006, but they are no longer mentioned. In the other countries there is no evidence of BC screening.
In two of these seven countries data quality is medium/high (A–C) for data source incidence, medium/high (1–3) for data source mortality; the quality of the method used to estimate mortality is medium/high (1–3) (Table 4).

3.2. Correspondence Analysis

The results of multiple correspondence analysis are represented in Figure 2 (object scores plot). The data provided two dimensions with eigenvalues that explain 65% of the variance: dimension 1 = 0.40 and dimension 2 = 0.25. The first dimension is related to GNI level, year of BC screening institution, type of screening programme in place, and occurrence data; the second dimension relates to the quality of the availability of mortality data, the quality of the method applied to estimate incidence and mortality, and the organization of public information and awareness campaigns for primary prevention of risk factors (tobacco use, alcohol abuse, obesity, and sedentary lifestyle). Multiple correspondence analysis produced clear and interesting patterns, which are represented in the four quadrants of Figure 2. The right upper quadrant is characterized by medium/low GNI, absence of public information and awareness campaigns for primary prevention, low/medium quality of data availability, low quality of the method applied to estimate occurrence rates, low/medium quality of occurrence data, and institution of non-PB organized screening after 2005. The variables found in the left lower quadrant include: HI GNI OECD countries, organized PB screening, 50%–75% and >75% coverage, access to organized PB screening centres, institution of screening programmes before 2001, use of primary prevention public information and awareness campaigns, high/medium-high quality of occurrence data, high quality of the method applied to estimate data, and high quality data availability. The right lower quadrant shows the categories relating to the absence of public information and awareness campaigns for the primary prevention of the risk factors considered in the study (alcohol abuse, tobacco use, obesity, and sedentary lifestyle). Finally, the variables found in the upper left quadrant include HI GNI non-OECD countries, organization of public information and awareness campaigns for the primary prevention of the risk factors considered, institution of screening programmes since 2001–2005, screening coverage <50%, access to approved screening centres, use of mobile units to increase participation, and low-quality data availability.

4. Discussion

Over the past three decades, the number of new BC cases has more than doubled worldwide. European incidence and mortality rates vary widely, the highest being found in Belgium (HI; respectively 111.9 and 20.3) and the lowest in Tajikistan (LMI; 20.4 and 8.7). The incidence of BC in developing countries has been increasing by an annual rate of 4.4%. An encouraging finding is that in the countries that have enacted BC screening programmes (all HI States) mortality rates are declining [4]. It has been estimated that 68,000 women aged 15 to 49 years died from BC in LMIs in 2010 as opposed to only 26,000 in HI States [95]. In fact, outcomes in HI countries have improved due to a combination of early screening detection and better treatment [3]. In 1980, 37 women in every 100 new cases died in developing countries; in 2010 the figure was 26 [96]. In contrast, a reduction in the age at BC onset in developing countries is a matter for concern, since these patients account for 44.1% of all cases, while in HI countries BC has become less frequent among women of reproductive age [32]. Mortality would thus appear to correlate inversely with GNI. Mortality rates are a valuable measure of the problem and burden of BC in a country and of the effectiveness of secondary prevention through early detection. Moreover, cancer-specific mortality rates are useful to evaluate the impact of cancer management and treatment. In fact, in developed countries the combination of cancer prevention, early detection, and better treatment has reduced the incidence and mortality of the most common tumours [97,98]. Incidence rates may provide a valuable indicator to investigate risk factors and plan the adoption of prevention programmes. However, their estimation must be accurate if the phenomenon is not to be underestimated, and the absence of a PB or hospital-based cancer registry may be the cause of suboptimal accuracy of data sources. As demonstrated by the data reported above, a very different data quality is found in HI and LMI States, both in terms of the available data sources and of the methods applied to estimate incidence and mortality. This should prompt governments to invest in data source upgrading, to achieve an assessment of the tumour burden as accurate as possible, also with a view to optimising the demand and supply of diagnostic and treatment services. It should also be stressed that high rates of BC detected in advanced phases should prompt the organization of prevention campaigns.
According to the present study, not all HI countries employ awareness campaigns to prevent important risk factors such as tobacco use and alcohol abuse. HI States lacking them include Austria, Denmark, France, Iceland, and the Netherlands, a UMI country like Bulgaria, and LMI States like Georgia, and Ukraine. The same is true of the prevention of overweight and the promotion of exercise. As regards the enhancement of screening participation, HI States harness multiple means of communication that are sometimes provided in different languages, whereas awareness campaigns in LMI are organized only in Macedonia, Republika Srpska, and Turkey. It is worth stressing that with the exception of Kyrgyzstan, none of the LMI States use mobile units to reach the fraction of the target population who do not respond to the screening invitation. A key difference between HI and LMI States, emerging from the present data, is that in the former screening programmes are well organized, with approved screening centres, the presence of mobile units to increase coverage, the offer of screening tests free of charge; the fairly high quality of occurrence data based on high- quality sources, and the adoption of accurate methods to estimate incidence and mortality, whose accuracy is supported by cancer registries and PB screening.

5. Conclusions

The study suggests the following considerations: first of all, HI Countries like Slovakia, some Swiss cantons, the Russian Federation, and Greece, lack population-based (PB) screening; countries such as Austria, Denmark, France, Iceland, and the Netherlands lack prevention campaigns for the risk factors; countries such as Greece, Hungary, Luxemburg, and Russia lack high-quality data either in terms of data source and of the quality of the method used to estimate incidence and mortality rates. The governments of HI countries should allocate sufficient resources to increase screening participation by harnessing mobile units as well as devising campaigns to enhance women’s awareness of the importance of early BC diagnosis, a goal that would also ensure a more rational utilization of existing approved centres; secondly, they should improve the accuracy of incidence and mortality rates by upgrading the quality of data sources, to avoid being faced with large numbers of BC patients (also) with advanced disease in the near future. High-quality occurrence data are essential to understand cancer trends and devise control strategies. As regards low-middle income countries, they have a less efficient general organization, and the proportion of organized programmes is low in low-income countries while programmes are often absent in middle-income countries. It should however be stressed that for a screening programme to be effective the country should also have suitable facilities to manage all the new cases resulting from early diagnosis, as well as resources to ensure their follow-up. Therefore, small communities lacking specialized medical staff or economic resources to set up screening programmes could rely on nearby centres or regions having the resources and facilities for quality screening.

Author Contributions

Emma Altobelli contributed to this paper with conception and design of the study, literature review, developed statistical analysis, drafting and critical revision and editing. Leonardo Rapacchietta participated to literature search, participated to build database. Paolo Matteo Angeletti participated to literature search, acquired the data and participated in writing the paper. Luca Barbante, Filippo Valerio Profeta and Roberto Fagnano participated to acquire the data. All authors have approved the final version of manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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Ijerph 14 00452 g001 550
Figure 1. Breast Cancer Incidence and Mortality data and their age standardized rates per 100,000 population (ASR-W), in WHO European Region Countries and in the World, according to GLOBOCAN 2012 (Andorra, Monaco and San Marino not reported).
Figure 1. Breast Cancer Incidence and Mortality data and their age standardized rates per 100,000 population (ASR-W), in WHO European Region Countries and in the World, according to GLOBOCAN 2012 (Andorra, Monaco and San Marino not reported).
Ijerph 14 00452 g001
Ijerph 14 00452 g002 550
Figure 2. Results of multiple correspondence analysis.
Figure 2. Results of multiple correspondence analysis.
Ijerph 14 00452 g002
Table
Table 1. Breast Cancer prevalence for each country of WHO European Region by gross income levels according to World Bank.
Table 1. Breast Cancer prevalence for each country of WHO European Region by gross income levels according to World Bank.
High Income
OECD Countries		Prevalence Rate *High Income
OECD Countries		Prevalence RateUpper Middle Income CountriesPrevalence Rate
1 Year3 Years5 Years 1 Year3 Years5 Years1 Year3 Years5 Years
Austria122.9348.0551.4Slovakia96.4259.0388.8Albania73.7212.1338.1
Belgium202.1571.4899.4Slovenia125.2348.8540.1Azerbaijan31.383.5127.0
Czech Rep132.1360.2547.2Spain113.4325.1516.2Belarus76.8211.5324.2
Denmark205.0571.6887.4Sweden151.5434.0687.4Bosnia63.2181.2287.7
Estonia93.2254.6388.3Switzerland156.6446.4705.6Kazakhstan79.5210.3319.0
Finland180.8513.8809.2The Netherlands183.1521.3821.4FRY of Macedonia123.2354.4564.5
France168.3484.1771.0United Kingdom174.1485.2755.1Montenegro90.7260.8414.7
Germany173.8488.6765.7High Income non OECD CountriesPrevalence rateRomania84.2231.0353.7
Greece87.4251.4400.71 year3 years5 yearsSerbia120.8344.8545.9
Hungary98.8271.2415.5AndorraNRNRNRTurkey45.8122.4187.0
Iceland158.9464.5745.3Croatia121.7347.3549.4Turkmenistan29.578.6119.9
Ireland145.2403.9625.9Cyprus121.5347.9553.0Lower Middle Income CountriesPrevalence rate
Israel123.1341.6532.9Malta156.8437.4678.41 year3 years5 years
Italy169.0486.5775.6MonacoNRNRNRArmenia101.8270.2411.2
Luxembourg159.4456.2727.4Latvia96.0262.7401.4Kyrgyzstan28.375.4114.6
Norway131.9374.2588.5Lithuania85.4234.5358.6Georgia63.5170.0260.3
Poland92.4256.3397.0Russia78.5215.0328.3Moldova63.7174.1265.0
Portugal114.7324.6512.2San MarinoNRNRNRTajikistan18.850.476.9
Ukraine69.7191.0292.0
Uzbekistan28.074.5113.3
* 100,000 ASR-W (GLOBOCAN 2012).
Table
Table 2. Campaigns of primary prevention and screening promotion in 53 WHO European Countries.
Table 2. Campaigns of primary prevention and screening promotion in 53 WHO European Countries.
CountryCampaign
Control of Cancer Risk FactorsScreening PromotionType of BC Screening Services (Public Health Services/Public Health Services + Mobile Units)
TobaccoAlcoholPhisical ActivityOverweightMediaLanguages
HIGH INCOME COUNTRIES: OECD
Austria [29,30]NONONOYESInternet; TV; Radio; Brochures; postersEnglish; Turkish; Bosniac; Croatian; Serbian; Slovenian; MagyarAccredited centers
Belgium [12,13,14,15]YESYESYESYESInternet; Brochures; PostersFrench; NetherlandsAccredited centers
Czech Rep [31,32,33]YESYESYESYESInternet; Česky; EnglishAccredited centers
Denmark [34,35,36,37]NONOYESYESInternetDanes; English; Turkish; Somali; Bosnian; Arabic; Farsi; Urdu; KalaallisutAccredited centers
Estonia [4,38]YESYESYESYESInternetEstonia; EnglishAccredited centers, mobile mammography units
Finland [4,39]YESYESYESYESInternetFinnish; Swedish; EnglishAccredited centers
France [9,10]NONOYESYESInternet; TV; Radio; Brochures; PostersFrench, EnglishAccredited centers
Germany[40,41]YESYESYESYESInternetGerman; EnglishAccredited centers
Greece [42]YESYESYESNOInternetGreek; EnglishAccredited centers
Hungary [43,44,45]YESNONONOInternetTurkishAccredited centers
Iceland [46]NONONONOInternetIcelandic; English; PolishAccredited centers
Ireland [47]YESYESYESYESInternet, Smartphones appEnglish, Irish Accredited centers, mobile mammography units
Israel [48]YESNOYESYESInternetIsraeli; Arabic, EnglishAccredited centers, mobile mammography units
Italy [11,49,50]YESYESYESYESInternet; TV; Radio; BrochuresItalianAccredited centers, mobile mammography units
Luxembourg [51,52,53]YESNOYESYESInternet; BrochuresFrench, GermanAccredited centers
Norway [54,55,56,57]YESYESYESNOInternet; BrochuresNorwegian; EnglishAccredited centers
Poland [4,58,59]YESYESYESNOInternetPolish (mi sembra che lo screening sia iniziato di recente. Non ho trovato un sito ufficiale …)Accredited centers
Portugal [60,61,62]YESYESYESNONRPortugueseAccredited centers, mobile mammography units
Slovakia [4]YESYESYESYESNRNRNR
Slovenia [4,63]YESYESYESNOInternetSlovenian; EnglishAccredited centers; mobile mammography units
Spain [64,65]YESYESYESYESInternetSpanishAccredited centers mammography centers
Sweden [66]YESYESYESYESInternetSwedish; EnglishAccredited centers
Switzerland [67,68]YESYESYESYESInternet; TV; Radio, Brochures;English; Turkish; Bosniac; Croatian; Serbian; German; French; Italian; Spanish; Portuguese; AlbanianAccredited centers
The Netherlands [56,57,58,59]NONONOYESInternet Nederlands; English; Turkish; ArabicAccredited centers; mobile mammography units
United Kingdom [5,6,7,8]YESYESYESYESInternetEnglishAccredited centers
HIGH INCOME NON OECD
Andorra [69]YESYESYESYESInternetCatalan; Spanish; French; Portuguese; EnglishAccredited centers
Croatia [70]YESYESYESNOInternet; BrochuresCroatian Accredited centers
Cyprus [71,72,73]YESYESNRNRNR NRAccredited centers
Malta [4,74]YESYESYESYESInternetEnglishAccredited centers
Monaco [75]YESYESYESYESInternet; TV; Radio; Brochures; PostersFrench; EnglishAccredited centers
Latvia [4]YESYESYESNOInternetLatvianAccredited centers
Lithuania [4]YESYESYESYESInternetLithuanian; EnglishNR
Russian Fed [76]YESYESYESYESNRNRNR
San Marino [77]YESYESYESYESInternetItalianAccredited centers
UPPER MIDDLE INCOME
Albania [78]NOYESNONONRNRAccredited centers
AzerbaijanNONONONONRNRNR
Belarus [79]NRNRNRNRNRNRNR
Bosnia [80]NRNRNRNRUnrealisedUnrealisedUnrealised
Bulgaria [4]NONONONOInternetItalianoAccredited centers
Kazakhstan [81]NRNRNRNRNRNRNR
FRY of Macedonia [82]YESYESYESYESInternet, StampaMacedonian Accredited centers
Montenegro [83,84]YESYESYESYESNRNRNR
Romania [4]YESNONONONRNRNR
Serbia [85,86]YESNONONOInternetSerbian; EnglishAccredited centers
Turkey [87]YESNOYESYESInternetTurkish; EnglishAccredited centers
TurkmenistanYESYESYESYESNRNRNR
LOWER MIDDLE INCOME
ArmeniaYESYESYESYESNRNRNR
Georgia [88]NONONONOInternetGeorgian; EnglishAccredited centers
Kyrgyzstan [89]YESYESYESYESBrochures; Conferences; seminarsKyrgyz; RussianAccredited centers; mobile mammography units
MoldovaYESYESNONONRNRNR
TajikistanYESYESYESYESNRNRNR
Ukraine [90]NONONONONRNRNR
Uzbekistan [91]NONONONOInternetUzbekNR
Health Expenditure: data available from World Bank website. Referred to 2014; Cancer policy: data available from WHO web site. All data are referred to a survey (2014); NR: not reported.
Table
Table 3. Distribution of Breast Cancer screening programmes in 53 WHO European Countries as of July 2016.
Table 3. Distribution of Breast Cancer screening programmes in 53 WHO European Countries as of July 2016.
CountryEURO Area TypeRegionsStart ProgramNatw CoverageTestAge TargetViewsDouble ReadingScreening IntervalRecall %Level of Participation %Payment Policy
HIGH income: OECD countries
Austria [35,36]EU28PBAll nation2014-DM,US45–692Yes2--
NPBAll nation2014-DM, US40–44; >702----Free of charge
Tyrol (Innsbruck and hinterland) 2007–2008-DM, US40–592No1 year 40–59
2 years 60–69		3.155.5Free of charge
Belgium [12,13,14,15]EU28PBWallonie-Bruxelles2000-DM, US50–692Yes: if necessary 32--Free of charge
PBFlanders2001-DM, US50–69 -2-32.7-
Czech Rep [36,37,38]EU28NPBAll nation20022007MM45–692Yes2-70.0NA
PBAll nationJan–Dec 2014 MM45–702Yes2--
Denmark [39,40,41,42]EU28 All nation20012008–2010DM50–692Yes2Initial: 4.3
Later: 1.8		73.0 *Free of charge
Estonia [4,43]EU28 All nation20022007DM50–652Yes23.153.0Free of charge
Finland [4,44]EU28PBAll Nation19871992DM,US 50–692Yes22.784.0Free of charge
France [9,10]EU28PBAll nation19892004MM,DM,CBE50–742Yes21.352.7Free of charge
Germany [45,46]EU28PBAll Nation20022009DM50–692Yes2North Westphalia (2005–2009)
Initial: 6.1
Subsequent: 3.4		54.1Free of charge
Greece [47]EU28NPBPilot2004–2009-MM40–692-1-2--
Hungary [48,49,50]EU28PBAll nation1995 (PILOT)2002DM45–652Yes27.2 56.3Free of charge
Iceland [52]EU19PBAll nation19871989DM40–692Yes24.162.0Free of charge
Ireland [53]EU28PBAll nation20002007DM50–642Yes2Initial: 8.4
Subsequent: 2.8		74.2Free of charge
Israel [54]EU19PBAll nation19972005MM,DM50–74--2-72.0Free of charge
Italy [11,54,55]EU28PBAll nation1990 DM,US50–692Yes25.4North: 61.0
Centrale: 56.0
South and Islands: 40.0
Emilia Romagna2010 DM45–742Yes45–49 (1 yr)
50–74 (2 yrs)		 Free of charge
NPBPiedmont2006 DM45–49
70–75		2Yes1 year2 years Free of charge
PBLombardy2012 2 years 70.0Free of charge
Luxembourg [56,57,58]EU28PBAll nation19921992DM50–692Yes25.464.0Free of charge
Norway [59,60,61,62]EU19PBAll nation19952005DM50–692Yes2Initial: 46.0
Subsequent: 2.6		76.0
Poland [4,63,64]EU28PBAll nation20062007MM,DM50–692Yes22.440.0Free of charge
Portugal [65,66,67]EU28PBAll nation DM45–692Yes2 60.0
Region Centro19902014 63.0Free of charge
Lisboa and Vale do
Vale do Tejo		1991 50.0
Alentejo19972014 66.0
Algarve20052014 66.0
Region Norte2009 58.0
Slovakia [4]EU28NPB----40+--2--Free of charge
Slovenia [4,68]EU28PBAll nation2008-DM50–692Yes2Initial: 4.8
Subsequent: 2.3		77.3
Spain [69,70]EU28PBAndalucia, Castile-La Mancha, Valencian Community, Navarra La Rioja, City of Ceuta, City of Melilla1990–20011992–2005DM45–692Yes2 67.0Free of charge
PBAragon, Asturias, Balearic Islands, Cantabria, Castile-Leon, Catalonia, Extremadura, Galicia, Madrid, Murcia, Basque Country1991–19981996–2009DM50–692Yes2
Sweden [71]EU28PBSakaraborg, Stockholm Kronoberg Vrmland Vasterbotten Jamtland 1997MM,DM50–692Yes2–1.5-72.0–91.0Free of charge
Dalarna1977 40–70 88.0
Vastmanland, Gotland1986 40–69 87.0
89.0
Malmo1977 46–69 66.0
Angelholm, Kristianstand, Bohus Halland1986–1989 50–74 70.0–90.0
Gavelborg, Ostergotland, Kalmar, Jonkoping, Malmohus, Alvsborg North, Alvborg South g, Orebro, Uppsala, Sodermanland, norbotten Vasternorrland1974–1989 40–74 80.0–86.0
Switzerland [72,73]EU19PBBasilea, Berna, Friburgo, Ginevra, Giura, Grigioni-Neuchatel, San Gallo, Turgovia, Vaud, Vallese19991999MM,DM50–702Yes2N/A48.2Free of charge
NPBOther cantons
The Netherlands [92]EU28PBAll nation19891997MM, DM50–752(1)Yes2-80.0Free of charge
United Kingdom [5,6,7,8]EU28PBAll nation1988, 2004 (ext 50–70)1995DM50–702-3Initial: 7.4
Subsequent: 3.6		76.0Free of charge
Northern Ireland1990 50–70
Scotland 50–70
Wales1989 50–70
HIGH INCOME NON OECD COUNTRIES
Andorra [75] PBAll nationNa MA50–69NANA2NaNaFree of charge
Croatia [76]EU28PB Oct 2006 DM50–692Yes2 years 60.0
Cyprus [77,78,79]EU28PBAll nation20032007DM50–692-2-50.0
Malta [4,80]EU28PBAll nation20072009DM50–6022 (+1)317.158.1Free of charge
Monaco [81,82] PBAll nation1994 DM, US50–802-2--
Latvia [4]EU28PBAll nation20082009DM, US50–692 2N/A34.2Free of charge
Lithuania [4]EU28PBAll nation2005-DM50–692 2
Russian Fed [83]EU19NPBKhanty-Mansiysky autonomous Region Yugra2007–2012 DM>402No2 67.5
San Marino [84]EU19PBAll nation19931993DM,US35–742N/A2N/A76.0Free of charge
UPPER MIDDLE INCOME COUNTRIES
Albania [85]EU 19NPBTirana2007–2008 -
AzerbaijanEU 19N/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A
Belarus [86]OEINPBN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A
Bosnia and Herzegovina [4,87]EU 19PBSarajevo2000–2006 M45–55-N/AN/AN/A53.5Free of charge
Bulgaria [4]EU28NPBAll nation2000 FM45–69N/AN/AN/AN/AN/AN/A
Kazakhstan [88]OEIPBAll nation2008 DM N/AYes2 N/A
FRY of Macedonia [89]EU 19PBAll nation2007 M ,US50–692N/A2N/AN/AN/A
Montenegro [90]EU 19PBPodgorica, Danilovgrad, Cetinje and Kolašin. DM50–6940–69 Yes2N/A70%Free of charge
Romania [4]EU28NPBAll nationN/AN/AN/AN/AN/AN/AN/AN/AN/AFree of charge
Serbia [91,92]EU 19PBAll nation20132014M50–69-Yes2-75.0Free of charge
Republika Srpska N/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A
Turkey [93,94]EU 19PBAll nation20092009DM, US50–692Yes2N/A20.0N/A
TurkmenistanOEIN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A
LOWER MIDDLE INCOME COUNTRIES
ArmeniaEU 19N/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A
Georgia [95]EU 19PBAll nationNA MA40–70 22YES75.0Free of charge
Kyrgyzstan [96]EU 19PBAll nation20072007DM40–69--3--
Republic of Moldova EU 19N/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A
TajikistanOEIN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A
Ukraine [97]EU 19N/AAll nation2002–2006N/AN/AN/AN/AN/AN/AN/AN/AN/A
Uzbekistan [93]OEIPBAll nation20092013N/AN/AN/AN/AN/AN/AN/AN/A
DM: Digital Mammografy, MA: Mammography Us: Ultrasounds; EU 28: Country of European Union EU 19: Country of European Council outside of EU 28 OEI: outside of European institutions; N/A: not available; PB: population-based; NPB: non-population-based.
Table
Table 4. Epidemiological data quality for the 53 WHO European area nations.
Table 4. Epidemiological data quality for the 53 WHO European area nations.
Quality of Data
CountryData SourceMethods
IncidenceMortalityCancer Registry *Incidence (a)Mortality (b)
HIGH INCOME OECD COUNTRIES
AustriaA2Austria, Tyrol, Vorarlberg11
BelgiumA2National22
Czech RepA2National11
DenmarkA2National11
EstoniaA1National11
FinlandA1National11
France (metropolitan)B2Bas−Rhin, Calvados, Doubs, Haut−Rhin, Hérault, Isère, Loire−Atlantique, Manche Somme, Tarn, Vendée31
GreeceG3-41
GermanyB2Brandenburg, Bremen, Free State of Saxony, Hamburg, Mecklenburg−Western Pomerania, Munich, North Rhine−Westphalia; Saarland, Schleswig−Holstein11
HungaryG1-41
IcelandA1National11
IrelandA1National11
IsraelA2National 11
ItalyB2Biella, Brescia, Catania and Messina, Catanzaro, Como, Ferrara, Florence and Prato, Friuli-Venezia Giulia, Genoa, Latina, Lecco, Lombardy South, Mantua, Milan, Modena, Naples, Nuoro, Palermo, Parma, Ragusa, Reggio Emilia, Romagna, Salerno, Sassari, Sondrio, South Tyrol, Syracuse, Trapani, Trento, Turin, Umbria, Varese, Veneto31
LuxembourgD2-41
NetherlandsA2National, Eindhoven11
NorwayA2National11
PolandC3Cracow, Kielch, Lower Sileisa, Podkarpackie31
PortugalC3Azores41
Slovak RepA1National11
SloveniaA1National11
SpainB2Albacete, Asturias, Basque Country, Canary Islands, Ciudad Real Cuenca, Girona, Granada, La Rioja, Mallorca, Murcia, Navarra, Tarragona31
SwedenA2National31
SwitzerlandB2Basel, Geneva, Graubünden and Glarus, Neuchâtel, St Gall−Appenzell, Ticino, Valais, Vaud, Zurich31
UKA1England, East of England Region; North Western, Northern and Yorkshire, Oxford Region; England, South and Western Regions, Thames, Trent West Midlands, Northern Ireland; Scotland Wales11
HIGH INCOME NON OECD COUNTRIES
Andorra--Hospital based (National)--
CroatiaA2National11
CyprusA3National22
Malta A1National11
Monaco--Hospital based (National)--
LatviaA1National11
LithuaniaA1National11
Russian FedD2Saint Pethersburg 11
San Marino--National (Activeted 2013)--
UPPER MIDDLE INCOME COUNTRIES
AlbaniaG3Tirana and 36 districts41
AzerbaijanG2Activated in 201552
BelarusA2National12
BosniaD5-22
BulgariaA2National11
KazakhstanG2National52
MacedoniaG3National 41
MontenegroG6-96
RomaniaE1Timisoara, Cluj 41
SerbiaB2Subnational (Serbia, Central)41
TurkeyC6Antalya, Edirne, Izmir, Trabzon 65
TurkmenistanG2-51
LOWER MIDDLE INCOME COUNTRIES
ArmeniaG3-52
KyrgyzstanG2-51
GeorgiaG2-52
MoldovaA2-11
TajikistanG3-52
UkraineA2National 22
UzbekistanG2-52
* Cancer registry according to IARC.

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MDPI and ACS Style

Altobelli, E.; Rapacchietta, L.; Angeletti, P.M.; Barbante, L.; Profeta, F.V.; Fagnano, R. Breast Cancer Screening Programmes across the WHO European Region: Differences among Countries Based on National Income Level. Int. J. Environ. Res. Public Health 2017, 14, 452. https://doi.org/10.3390/ijerph14040452

AMA Style

Altobelli E, Rapacchietta L, Angeletti PM, Barbante L, Profeta FV, Fagnano R. Breast Cancer Screening Programmes across the WHO European Region: Differences among Countries Based on National Income Level. International Journal of Environmental Research and Public Health. 2017; 14(4):452. https://doi.org/10.3390/ijerph14040452

Chicago/Turabian Style

Altobelli, Emma, Leonardo Rapacchietta, Paolo Matteo Angeletti, Luca Barbante, Filippo Valerio Profeta, and Roberto Fagnano. 2017. "Breast Cancer Screening Programmes across the WHO European Region: Differences among Countries Based on National Income Level" International Journal of Environmental Research and Public Health 14, no. 4: 452. https://doi.org/10.3390/ijerph14040452

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