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• Reply to the letter by Camargo Jr on 27 October 2017
  Carmen SG Diniz, Alessandra CG Pellini, Adeylson G Ribeiro, Marcello V Tedardi, Marina J Miranda, Michelle M Touso, Oswaldo S Baquero, Patricia C Santos and Francisco Chiaravalloti-Neto
  Published on: 28 November 2017
• Interpreting the carcinogenicity of social and medical development - Reply to the letter by Freitas-Junior et al. on 15 October 2017
  Carmen Simone Grilo Diniz, Alessandra Cristina Guedes Pellini, Oswaldo Santos Baquero and Francisco Chiaravalloti-Neto
  Published on: 7 November 2017
• Breast cancer mortality and associated factors in São Paulo State, Brazil: two flaws need to be acknowledged
  Helio S A Jr Camargo
  Published on: 30 October 2017
• Breast cancer mortality is associated with factors linked to social and medical development in São Paulo State, Brazil
  Ruffo Freitas-Junior, Rosemar Macedo Sousa Rahal, Rosangela da Silveira Correa, Danielle Cristina Netto Rodrigues, Nilson Clementino Ferreira, Noely Vicente Ribeiro and Leonardo Ribeiro Soares
  Published on: 20 October 2017

• Published on: 28 November 2017

  Reply to the letter by Camargo Jr on 27 October 2017

  • Carmen SG Diniz, Professor Faculdade de Saúde Pública da Universidade de São Paulo
  • Other Contributors:
    • Alessandra CG Pellini, Professor
    • Adeylson G Ribeiro, PhD Candidate
    • Marcello V Tedardi, PhD Candidate
    • Marina J Miranda, Consultora
    • Michelle M Touso, Researcher
    • Oswaldo S Baquero, Professor
    • Patricia C Santos, Technical staff
    • Francisco Chiaravalloti-Neto, Professor

  Dear Editor

  We thank Prof. Helio S. A. Camargo Jr, a respected author of a handbook on breast image exams, for his letter, which presents an opportunity to make our points clearer. We agree that “having a mammogram is not the same thing as being screened with mammography”. According to Tomazelli et al (2017), based on the National Breast Cancer Control Information System (Sismama), 96.2% of the mammograms in Brazil were for screening (performed in asymptomatic women) and 3.8% were diagnostic (in patients with suspicious breast cancer signs and/or symptoms), in the period they analyzed (2010-2011) (1).
  That means that less than 1 in 25 mammograms in Brazil were diagnostic, which must be one of the lowest rates in the world. The proportion of screening over diagnostic mammography must have further increased, with the expansion in coverage of breast screening in the last five years (2). The distribution of the mammographies for reasons other than screening are, therefore, diluted in the municipalities, without forming specific clusters.
  We also agree that “death certificates in Brazil do not always reflect the actual cause of death” and we recognized this limitation in our study. But is noteworthy the Brazilian health information system has improved dramatically in last decades since the creation of SUS (Public Health System) in 1988, in terms of quality and completeness. The analysis of data quality collected by the Mortality Information System indicates t...

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  Dear Editor

  We thank Prof. Helio S. A. Camargo Jr, a respected author of a handbook on breast image exams, for his letter, which presents an opportunity to make our points clearer. We agree that “having a mammogram is not the same thing as being screened with mammography”. According to Tomazelli et al (2017), based on the National Breast Cancer Control Information System (Sismama), 96.2% of the mammograms in Brazil were for screening (performed in asymptomatic women) and 3.8% were diagnostic (in patients with suspicious breast cancer signs and/or symptoms), in the period they analyzed (2010-2011) (1).
  That means that less than 1 in 25 mammograms in Brazil were diagnostic, which must be one of the lowest rates in the world. The proportion of screening over diagnostic mammography must have further increased, with the expansion in coverage of breast screening in the last five years (2). The distribution of the mammographies for reasons other than screening are, therefore, diluted in the municipalities, without forming specific clusters.
  We also agree that “death certificates in Brazil do not always reflect the actual cause of death” and we recognized this limitation in our study. But is noteworthy the Brazilian health information system has improved dramatically in last decades since the creation of SUS (Public Health System) in 1988, in terms of quality and completeness. The analysis of data quality collected by the Mortality Information System indicates that, between 2000 and 2009, there was an improvement in coverage and the completeness of variables collected by this system. The causes of death presented a significant improvement in their definition throughout the decade (3). In 2010, the proportion of deaths due to ill-defined causes in the Southeast region of Brazil was 8.1%, decreasing to 7.1% after the investigation and reclassification proposed by the Ministry of Health (4). Additionally, the availability of large computerized databases on health turned the record linkage technique into an alternative for different study designs, particularly spatial analysis (5).
  We agree that lack of access to data of the private sector is a serious problem, in terms of transparency and accountability of processes and outcomes in Brazil. Beyond diseases with mandatory notification and vital statistics (births and deaths), information about morbidity and hospitalization in the private sector is not publicly available on a regular basis, and usually accessed only from population-based household surveys, such as Demographic and Health Surveys (6). While SUS data is publicly available in open databases (except for issues related to patient confidentiality), information of private sector is treated as a black box, which limits comparison with public sector.
  We would be glad to collaborate on joint analysis of the private sector regarding breast cancer, and other relevant public health problems.

  Warmest regards,

  Carmen Simone Grilo Diniz
  Alessandra Cristina Guedes Pellini
  Adeylston Guimarães Ribeiro
  Marcello Vannucci Tedardi
  Marina Jorge de Miranda
  Michelle Mosna Touso
  Oswaldo Santos Baquero
  Patrícia Carla dos Santos
  Francisco Chiaravalloti-Neto

  References

  1 - Tomazelli JG, Migowski A, Ribeiro CM, Assis M, Abreu DMF. Avaliação das ações de detecção precoce do câncer de mama no Brasil por meio de indicadores de processo: estudo descritivo com dados do Sismama, 2010-2011. Epidemiol Serv Saúde 2017;26(1):61-70.
  2 - Vigitel Brasil 2016: Vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico. Ministério da Saúde, Secretaria de Vigilância em Saúde, Departamento de Vigilância de Doenças e Agravos não Transmissíveis e Promoção da Saúde. Brasília: Ministério da Saúde, 2017. [cited 2017 Nov 6] Available from: http://portalarquivos.saude.gov.br/images/pdf/2017/junho/07/vigitel_2016...
  3 - Maranhão AGK, Vasconcelos AMN, Aly CMC, Rabello Neto DL, Porto DL, Oliveira H, et al. Como morrem os brasileiros: caracterização e distribuição geográfica dos óbitos no Brasil, 2000, 2005 e 2009. Ministério da Saúde, organizador. Saúde Brasil 2010: uma análise da situação de saúde e evidências selecionadas de impacto de ações de vigilância em saúde. Brasília: Ministério da Saúde; 2011. v. 1. p. 51-78. [cited 2017 Nov 21] Available from: http://www.repositorio.unb.br/bitstream/10482/12475/1/CAPITULO_ComoMorre...
  4 - França E, Teixeira R, Ishitani L, Duncan BB, Cortez-Escalante JJ, Morais Neto OL, Szwarcwald CL. Ill-defined causes of death in Brazil: a redistribution method based on the investigation of such causes. Rev Saúde Pública 2014;48(4):671-681. [cited 2017 Nov 21] Available from: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102014000....
  5 - Peres SV, Latorre MRDO, Tanaka LF, Michels FAZ, Teixeira MLP, Coeli CM, Almeida MF.. Melhora na qualidade e completitude da base de dados do Registro de Câncer de Base Populacional do município de São Paulo: uso das técnicas de linkage. Rev bras Epidemiol 2016;19(4):753-765.
  6 - Diniz CSG, d'Oliveira AFPL, Lansky S. Equity and women's health services for contraception, abortion and childbirth in Brazil. Reprod Health Matters 2012;20(40): 94-101.

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  Conflict of Interest:
  None declared.

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• Published on: 7 November 2017

  Interpreting the carcinogenicity of social and medical development - Reply to the letter by Freitas-Junior et al. on 15 October 2017

  • Carmen Simone Grilo Diniz, Professor Departamento de Saúde, Ciclos de Vida e Sociedade da Faculdade de Saúde Pública, Universidade de São Paulo, São Paulo, Brazil
  • Other Contributors:
    • Alessandra Cristina Guedes Pellini, Professor
    • Oswaldo Santos Baquero, Professor
    • Francisco Chiaravalloti-Neto, Professor

  Dear Editor:

  We thank Freitas-Junior et al. for their detailed letter, which we read with great consideration, specially coming from leaders of the Brazilian Mastology Society.
  We will reply starting from the points that we believe that we all agree. First, that breast cancer mortality is linked to “social and medical developments”. Better health and higher life expectancy are associated with indicators of social development, such as Human development index (IDH), higher income and education. But better health is not necessarily associated to more health care (1). People of higher income may have more cancer not because of their wealth (which was expected to protect them), but because they are subjected to higher “observational intensity”, the combined effect of factors such as the frequency of screening and diagnostic exams, the ability of the exams to detect small irregularities, and the threshhold used to label results as abnormal, which can be an undesirable consequence (overdiagnosis) of medical development. As pointed by Welch and Fisher (2017), “Excessive testing of low-risk people produces real harm, leading to treatments that have no benefit (because there is nothing to fix) but can nonetheless result in medication side effects, surgical complications, and occasionally even death” (1).
  We also agree that radioprotection and radioinduced breast cancer are important issues to be addressed in a benefit-harm rationale, but we believe that the harm...

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  Dear Editor:

  We thank Freitas-Junior et al. for their detailed letter, which we read with great consideration, specially coming from leaders of the Brazilian Mastology Society.
  We will reply starting from the points that we believe that we all agree. First, that breast cancer mortality is linked to “social and medical developments”. Better health and higher life expectancy are associated with indicators of social development, such as Human development index (IDH), higher income and education. But better health is not necessarily associated to more health care (1). People of higher income may have more cancer not because of their wealth (which was expected to protect them), but because they are subjected to higher “observational intensity”, the combined effect of factors such as the frequency of screening and diagnostic exams, the ability of the exams to detect small irregularities, and the threshhold used to label results as abnormal, which can be an undesirable consequence (overdiagnosis) of medical development. As pointed by Welch and Fisher (2017), “Excessive testing of low-risk people produces real harm, leading to treatments that have no benefit (because there is nothing to fix) but can nonetheless result in medication side effects, surgical complications, and occasionally even death” (1).
  We also agree that radioprotection and radioinduced breast cancer are important issues to be addressed in a benefit-harm rationale, but we believe that the harms may have been underestimated. With outcomes similar to international studies, the careful research conduced by Corrêa et al. (2) estimated that for 100.000 women screened biannually in the State of Goiás, the number of radioinduced cancers ranged from 14.9 (50-70 years, conventional mammography) to 64.1 (40-70 years, digital mammography). In this setting, they found that the risk of radioinduced cancer incidence and mortality was higher in the private sector, and that 12% of the conventional mammography equipment and 50% of the digital ones (more common in private sector) used radiation doses above the recommendations, possibly indicating, as pointed out by the authors (2), on page 126, an “increased risk of cancer induction resulting from the introduction of digital technology in mammography”. Estimates of radioinduced cancers could be higher if considered the additional exposure of increased frequency (in 2010-2011, 44.6% women in Brazil reported an interval of one year or less since last mammography), and age range (48.8% of screened women were out of the recommended age 50-70y) (3). Both annual screening and digital mammography are more common in the private sector, leading to higher radiation exposure and higher observational intensity, which reinforces our hypothesis of underestimation of harms of intensive screening.
  We also agree, as stated several times in our paper, that ecological analysis are not appropriate to affirm causality; the best research design would be randomized controlled trials, and their systematic reviews - the gold standard for causal links. In sharp contrast with public perception and Pink October campaigns, the Cochrane systematic review of clinical trials of mammographic screening shows no reduction in overall cancer mortality (4), which reinforces our hypothesis of overestimation of benefits. The ratio of lives saved and lives losts owing to mammography depends on the belief that mammography saves lives, and how many, which is controversial (6). As debated by other authors (5-9), mortality-to-incidence, survival time, and proportion of advanced lesions can be inappropriate measures to assess mortality reduction, since screening substantially increases incidence, and these measures can coexist with an increased mortality. In our paper, we dialogue with publications with results similar to ours, in Brazil and abroad, with different methodologies (ecological, spatial analysis, individual level, aggregate level, systematic reviews), reinforcing our hypothesis. Unfortunately, some of the post-graduation studies with similar findings in Brazil (2, 10, 11), are found only in university repositories and in Portuguese, contributing to publication bias.
  We disagree that we need to increase mammography coverage or capacity. The authors say that the coverage of mammography is just 24% in the public system, not reaching the 70% necessary to produce an impact on mortality. But according to the Vigitel (national surveillance system of risk factors and protection for chronic diseases by telefone survey) with data from 2016, the coverage for the eligible women (aged 50-69y) in all Brazilian capitals was 78,2% for screening in the last two years (90,5% for more educated women) (12). This is higher than in the USA (71.6%) (13), Germany (52.7%), France (52,3%), the average in Europe (49.2%) (14), and Japan (36,4%) (15). In terms of mammography infraestructure, to fully atend the populational need for bianual screening, in 2012 there was already an excess of 196 mammography equipments in Brazil (irregularly distributed), and the State of São Paulo, the focus of our research, had 89 excedent equipments.(16) Annual screening is in disagreement with the Ministry of Health's recommendations and “may compromise its effectiveness and entail greater risk to women” (3).
  We disagree that our analysis ignored the gross domestic product, human development index and income: as clearly described in our article, we tested models with these variables (V_68, V_69 and V_41, respectively), but they did not fit the data better than our final model. We agree with the fact that the final model is not necessarily perfect. However, this is the model, among all tested ones, with the highest probability of minimizing the estimated information loss.
  Linear regression results are valid as long as model assumption are not violated. To ensure this, firstly we performed an exploratory analysis before modeling to, among other things, evaluate the presence of outliers and collinearity between the covariates and make the required adjustments (in this case, covariate transformation and elimination of highly correlated covariates). After modeling, we evaluate the behavior of the residuals, which is the way indicated to ensure that the assumptions of a linear regression model are not violated. Thus, we evaluated the normality and the mean of the residuals, their relationship with the dependent and independent variables, to ensure homoscedasticity, and finally, that the residuals were spatially independent, since we worked with a design with spatially aggregated data (municipalities).
  For doing this last evaluation, we used the Moran Global Index to assess the existence of spatial autocorrelation of the residuals. Since we did not identify spatial dependency in the residuals, it was not necessary to consider more complex models, such as Simultaneous or Conditional Autorregressive models, Geographically Weighted regression, among other possibilities (16). According to the criterion of parsimony, if the model meets the basic assumptions of regression modeling, there is no reason to look for more complex models. We agree with Freitas-Jr et al. in their observation about the existence of spatial autocorrelation of the dependent variable (breast cancer mortality rates), however, this dependence was explained by the covariates considered, resulting in non-spatially autocorrelated residuals. When we work with spatially aggregate data, we have a wide range of spatial statistical tools available, but we need to be careful to choose the most appropriate ones so that our goals can be achieved. In this way, it would only make sense to use Moran Local index if we were interested in identifying clusters of municipalities with high (or low) mortality rates, which was not the case in our study.
  We want to insist that the conclusion of our work is not that there is “a possible association” between increased mortality and those three variables (mammography, nulliparity and use of private sector); the association exists and is very robust, in all our models, as in the studies we present. The question is if there are causal links, and we present evidence of plausibility for this argument, from recent studies of different research designs. Our conclusion is that there is a possible overestimation of benefits and underestimation of harms in mammographic screening as a public health strategy.
  This can be an outstanding opportunity to study real time outcomes of screening mammography, using randomization for informed decision and individualized risk assessment, evaluating differences in incidence, morbidity and mortality. We believe that we have enough uncertainty, and equipoise, to justify such a trial, and we would be glad to collaborate in this direction.

  Best regards,

  Carmen Simone Grilo Diniz
  Alessandra Cristina Guedes Pellini
  Francisco Chiaravalloti-Neto

  References

  1 - Welch HG and Elliott SF. Income and Cancer Overdiagnosis—When Too Much Care Is Harmful. N Eng J Med 2017;376.23:2208-2209.
  2 – Corrêa RS, Peixoto JE, Ferreira RS, Tanaka R, Freitas-Junior R. Estimativa do risco de cancer radioinduzido em rastreamento mamográfico. In: Corrêa RS. Mamografia: infraestrutura, cobertura, qualidade e risco de cancer radioinduzido em rastreamento oportunístico no Estado de Goiás. PhD Thesis, UFG. 2012 (unpublished). Available at: https://repositorio.bc.ufg.br/tede/bitstream/tde/1534/1/Tese%20Rosangela.... Accessed on November 6, 2017.
  3 - Tomazelli JG, Migowski A, Ribeiro CM, Assis M, Abreu DMF. Avaliação das ações de detecção precoce do câncer de mama no Brasil por meio de indicadores de processo: estudo descritivo com dados do Sismama, 2010-2011. Epidemiol Serv Saúde 2017;26.1:61-70.
  4 - Gøtzsche PC and Karsten JJ. Screening for breast cancer with mammography. Cochrane Database of Systematic Reviews 2013;6:CD001877.
  5 - Gigerenzer G. Full disclosure about cancer screening. BMJ 2016;352: h6967–2.
  6 - Prasad V, Lenzer J, Newman DH. Why cancer screening has never been shown to "save lives"--and what we can do about it. BMJ 2016;352:h6080.
  7 - Narod SA, Iqbal J, Miller AB. Why have breast cancer mortality rates declined? J Cancer Policy 2015;5:8–17.
  8 - Welch HG, Black WC. Overdiagnosis in cancer. J Natl Cancer Inst 2010;102:605–13.
  9 - Carter JL, Coletti RJ, Harris RP. Quantifying and monitoring overdiagnosis in cancer screening: a systematic review of methods. BMJ 2015;350:g7773.
  10 - Bello MA. Análise estatística espacial da mortalidade por câncer de mama feminina no estado do Rio de Janeiro, 2001 a 2006. Dissertação. Rio de Janeiro: Escola Nacional de Saúde Pública Sergio Arouca, 2010. Available at: https://bvssp.icict.fiocruz.br/lildbi/docsonline/get.php?id=2331. Accessed on November 5, 2017.
  11 - Silveira DP. Perfil Da incidência e da sobrevida de câncer de mama: análise a partir dos registros de câncer de base populacional e cobertura de planos privados de saúde no município de São Paulo. Escola Nacional de Saúde Pública Sergio Arouca. 2011. Available at: http:// bvssp.icict. fiocruz. br/ lildbi/ docsonline/ get. php? id= 2739. Accessed on November 6, 2017.
  12 - Vigitel Brasil 2016: Vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico. Ministério da Saúde, Secretaria de Vigilância em Saúde, Departamento de Vigilância de Doenças e Agravos não Transmissíveis e Promoção da Saúde. Brasília: Ministério da Saúde, 2017. Available at: http://portalarquivos.saude.gov.br/images/pdf/2017/junho/07/vigitel_2016.... Accessed on November 6, 2017.
  13 – National Cancer Institute. Cancer Trends Progress Report. Breast Cancer Screening. 2017. USA: NIH. Available at: https://progressreport.cancer.gov/detection/breast_cancer. Accessed on November 6, 2017.
  14 - International Agency for Research on Cancer. Cancer screening in the Europe Union. Lyon: IARC, 2017. Available at: https://ec.europa.eu/health/sites/health/files/major_chronic_diseases/do.... Accessed on November 6, 2017.
  15 - Sano, Hiroshi, Rei Goto, and Chisato Hamashima. "Does lack of resources impair access to breast and cervical cancer screening in Japan?." PloS one 12.7 (2017): e0180819.
  16 - Xavier DR, De Oliveira RAD, De Matos VP, Viacava F, Carvalho CC. Mammograms coverage, allocation and use of equipment in the Health Regions. Saúde Debate, Rio de Janeiro. 2016;40(110):20-35. Available at: http://www.scielo.br/pdf/sdeb/v40n110/0103-1104-sdeb-40-110-0020.pdf. Accessed on November 6, 2017.
  17 - Bivand RS, Pebesma E, Gómez-Rubio V. Applied spatial data analysis with R. New York: Second Springer editor, 2013:405.

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  Conflict of Interest:
  None declared.

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• Published on: 30 October 2017

  Breast cancer mortality and associated factors in São Paulo State, Brazil: two flaws need to be acknowledged

  • Helio S A Jr Camargo, Radiologist CDE Diagnostic Imaging, Febrasgo, Brazil

  Dear Editor:
  On reading the study conducted by Diniz et al. on the possible association between mammography and breast cancer-related mortality in the state of São Paulo, Brazil, I found two weaknesses that cannot go unnoticed. The authors have gathered information on mammography ratio and discussed the presumable effect on mortality of mammographic screening. These are two different situations. Having a mammogram is not the same thing as being screened with mammography. There are other reasons for having a mammogram, as having a palpable lump, being prepared for breast cancer surgery or systemic treatment, following up patients treated for breast cancer, orienting breast biopsies. When studying a population comprised of people who have actually died of breast cancer, one should expect to find a cluster of mammograms performed for non-screening purposes. And one should expect a higher mortality rate from breast cancer in this population.
  The other weakness is perhaps easier to understand for those familiar with health care in Brazil. It is very well known that death certificates in Brazil do not always reflect the actual cause of death. It is to be expected a serious under notification in the public health sector as compared to the private health sector. I do acknowledge that the mortality information system in Sao Paulo state is extensive in its coverage and that could be perceived as a strength of the article. However, one has to make sure that the rate of ad...

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  Dear Editor:
  On reading the study conducted by Diniz et al. on the possible association between mammography and breast cancer-related mortality in the state of São Paulo, Brazil, I found two weaknesses that cannot go unnoticed. The authors have gathered information on mammography ratio and discussed the presumable effect on mortality of mammographic screening. These are two different situations. Having a mammogram is not the same thing as being screened with mammography. There are other reasons for having a mammogram, as having a palpable lump, being prepared for breast cancer surgery or systemic treatment, following up patients treated for breast cancer, orienting breast biopsies. When studying a population comprised of people who have actually died of breast cancer, one should expect to find a cluster of mammograms performed for non-screening purposes. And one should expect a higher mortality rate from breast cancer in this population.
  The other weakness is perhaps easier to understand for those familiar with health care in Brazil. It is very well known that death certificates in Brazil do not always reflect the actual cause of death. It is to be expected a serious under notification in the public health sector as compared to the private health sector. I do acknowledge that the mortality information system in Sao Paulo state is extensive in its coverage and that could be perceived as a strength of the article. However, one has to make sure that the rate of adequate notification is similar in the private and public sectors before being able to adequately make this comparison. Without this certitude, the reliance on the death certificates becomes a weakness.

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  Conflict of Interest:
  None declared.

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• Published on: 20 October 2017

  Breast cancer mortality is associated with factors linked to social and medical development in São Paulo State, Brazil

  • Ruffo Freitas-Junior, Professor & physician Rede Brasileira de Pesquisa em Mastologia. Faculdade de Medicina da Universidade Federal de Goiás - Goiânia, GO, Brasil.
  • Other Contributors:
    • Rosemar Macedo Sousa Rahal, Professor & physician
    • Rosangela da Silveira Correa, Researcher
    • Danielle Cristina Netto Rodrigues, Researcher
    • Nilson Clementino Ferreira, Professor & researcher
    • Noely Vicente Ribeiro, Professor & researcher
    • Leonardo Ribeiro Soares, Researcher & physician

  Dear Editor:
  We have read the study conducted by Diniz et al. on the possible association between mammography and breast cancer-related mortality in the state of São Paulo, Brazil with the greatest of care. Despite the detailed statistical analysis, the ecological study design implies limitations to the hypothesis generated, as pointed out by the authors themselves (1). In our opinion, both the authors’ main conclusion and the assumed association of cause and effect are inappropriate.

  The factors associated with the incidence of breast cancer in Brazil and its resulting mortality have recently been evaluated in different studies (2-4). Mortality rates have been found to vary as a function of geospatial location (rural areas versus urban centers)(4). In addition, the reduction encountered in mortality was associated with the regions in which the human development index (HDI) was higher. On the other hand, the highest mortality rates have been found to occur in the states with the highest HDI (5). Diniz et al. and many other investigators have mentioned that a higher incidence of breast cancer occurs among more affluent women living in urban areas and in large cities (1,5). In this respect, we are certain that mortality is also related to the incidence of the disease; hence, the higher the incidence, the greater the resulting mortality will be. Conversely, women who do not have breast cancer will obviously not die from the disease.

  Therefore, we believe t...

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  Dear Editor:
  We have read the study conducted by Diniz et al. on the possible association between mammography and breast cancer-related mortality in the state of São Paulo, Brazil with the greatest of care. Despite the detailed statistical analysis, the ecological study design implies limitations to the hypothesis generated, as pointed out by the authors themselves (1). In our opinion, both the authors’ main conclusion and the assumed association of cause and effect are inappropriate.

  The factors associated with the incidence of breast cancer in Brazil and its resulting mortality have recently been evaluated in different studies (2-4). Mortality rates have been found to vary as a function of geospatial location (rural areas versus urban centers)(4). In addition, the reduction encountered in mortality was associated with the regions in which the human development index (HDI) was higher. On the other hand, the highest mortality rates have been found to occur in the states with the highest HDI (5). Diniz et al. and many other investigators have mentioned that a higher incidence of breast cancer occurs among more affluent women living in urban areas and in large cities (1,5). In this respect, we are certain that mortality is also related to the incidence of the disease; hence, the higher the incidence, the greater the resulting mortality will be. Conversely, women who do not have breast cancer will obviously not die from the disease.

  Therefore, we believe that the study conducted by Diniz et al. should be interpreted in another manner. According to their report, breast cancer-related mortality was associated with three characteristics of the more affluent female population in Brazil: healthcare within the private healthcare system, nulliparity, and access to mammography (1). Nevertheless, the women with greatest access to mammography are those with better socioeconomic conditions living in urban areas and for this reason are more likely to develop breast cancer and, consequently, to die from this disease.

  The authors take advantage of the results obtained to criticize mammography screening. In fact, screening programs must reach at least 70% of the target population to be considered effective. In 2016, the coverage provided by mammography screening within the Brazilian National Health Service (Sístema Único de Saúde - SUS) reached only 24% of the female population of 50 to 69 years of age. This percentage almost doubles within the supplementary healthcare system (6,7), and that fact also permits a critical analysis to be made in relation to the results obtained by Diniz et al. (1). In other population-based studies, improved access to healthcare and an increase in the number of mammograms performed was found to be associated with a considerable reduction in cases of breast cancer diagnosed at an advanced stage in some regions (7-9). When well conducted, mammography screening can reduce mortality by approximately 30% (10).

  In terms of radiological protection, mammography screening is justifiable if the imaging procedures performed are of excellent quality and conducted using the lowest possible dose of radiation (11,12). Diniz et al. concluded that the number of cases of radiation-induced cancer caused by the ionizing radiation from imaging could be increasing the mortality rate (1). This association is wrong, since it would be necessary to take the dose at which the imaging procedure is performed into consideration, together with other factors, to enable the number of cases of radiation-induced cancer in a population to be calculated (13). Corrêa et al. found that the number of imaging procedures performed was not associated with the number of breast cancer deaths induced by women’s exposure to radiation and concluded that the final magnitude of the risk was exclusively determined by the dose of radiation emitted by the mammography equipment (13).

  In the study conducted by Corrêa et al., the likelihood of developing a radiation-induced cancer as a result of mammography was found to be 0.2 per 100,000 women. Furthermore, the probability of death at 85 years of age as a result of the accumulated radiation dose to which a woman would be exposed at imaging procedures conducted every two years was estimated at 0.18 per 100,000 women annually. Therefore, the risk of dying from radiation-induced cancer is much lower than the risk associated with other factors that could result in death, including not undergoing imaging for the early detection of breast cancer and thus being diagnosed at an advanced stage (13,14). In a recent study, women receiving care within the private healthcare system were found to be half as likely to have advanced lesions at diagnosis, reflected in an increase in survival of approximately 10% in relation to the women treated within the Brazilian National Healthcare Service (SUS) (15). These data also conflict with those reported by Diniz et al. (1).

  In the statistical analysis, Diniz et al. selected and analyzed an expressive set of explanatory variables. They also performed multiple regression analyses and applied the Akaike Information Criterion (AIC), which estimates the model with the best fit, to the set of resulting models (1). Nevertheless, application of the AIC does not judge whether the best-fit model found is actually satisfactory, bearing in mind that all the models could be inadequate. The final fitted model used by the authors contains the following variables: the mammography ratio, the percentage of women with private healthcare and the proportion of women of childbearing age who did not have children. Therefore, many important variables were largely ignored in the analysis, including the gross domestic product, human development index, and income, among others.

  Figure 1 in the paper merits further scrutiny, together with charts on the human development index, gross domestic product and income. Despite the availability of computer software programs such as Geographically Weighted Regression (GWR) (16), the authors elected to use the Global Moran’s Index, even in the presence of spatial clusters from the municipalities with higher and lower mortality rates as shown in Figure 1. Apparently, these clusters occur in metropolitan regions where socioeconomic factors are high but whose population is larger and exposed to greater levels of pollution, stress and anxiety. Therefore, the Local Moran’s Index rather than the Global Moran’s Index should be applied to this map (17). In this respect, we believe that the analysis of the results was inadequate, since the study’s findings were not discussed in relation to the social, economic and environmental factors associated with the occurrence of mortality in the state of São Paulo, Brazil. Finally, a critical analysis should be conducted with respect to the data collection and registry of mammograms performed within the Brazilian National Health Service (SUS). Individuals who have to travel to another municipality to undergo mammography (18), sometimes within the private healthcare system, and the bias in the mammography registries caused by discrepancies in the public funding of the exams should be emphasized.

  Based on the aforementioned considerations, we conclude that the study conducted by Diniz et al., although contributing with a fairly important analysis, fails to reach an adequate conclusion (1). According to our analysis, breast cancer-related mortality is associated with factors linked to social and medical development in the state of São Paulo.

  Best regards,

  Ruffo Freitas-Junior
  Rosemar Macedo Sousa Rahal
  Rosangela da Silveira Corrêa
  Danielle Cristina Netto Rodrigues
  Nilson Clementino Ferreira
  Noley Vicente Ribeiro
  Leonardo Ribeiro Soares

  References
  1. Diniz CSG, Pellini ACG, Ribeiro AG, et al. Breast cancer mortality and associated factors in São Paulo State, Brazil: an ecological analysis. BMJ Open 2017;7(8):e016395.
  2. Cecilio AP, Takakura ET, Jumes JJ, et al. Breast cancer in Brazil: epidemiology and treatment challenges. Breast Cancer (Dove Med Press) 2015;7:43-9.
  3. Gonzaga CM, Freitas-Junior R, Curado MP, et al. Temporal trends in female breast cancer mortality in Brazil and correlations with social inequalities: ecological time-series study. BMC Public Health 2015;15:96.
  4. Gonzaga CM, Freitas-Junior R, Souza MR, et al. Disparities in female breast cancer mortality rates between urban centers and rural areas of Brazil: ecological time-series study. Breast 2014;23(2):180-7.
  5. Liedke PER, Finkelstein DM, Szymonifka J, et al. Outcomes of Breast Cancer in Brazil Related to Health Care Coverage: A Retrospective Cohort Study. Cancer Epidemiol Biomarkers Prev 2014; 23:126-33.
  6. Freitas-Junior R, Rodrigues DCN, Corrêa RS, et al. Contribution of the Unified Health Care System to mammography screening in Brazil, 2013. Radiol Bras 2016; 49(5): 305-10.
  7. Smith RA, Duffy SW, Gabe R, et al. The randomized trails of breast cancer screening: what have we learned? Radiol Clin North Am 2004; 42:793-806.
  8. Martins E, Freitas-Junior R, Curado MP, et al. [Temporal evolution of breast cancer stages in a population-based cancer registry in the Brazilian central region]. Rev Bras Ginecol Obstet 2009;31(5):219-23.
  9. Nunes RD, Martins E, Freitas-Junior R, et al. Descriptive study of breast cancer cases in Goiânia between 1989 and 2003. Rev Col Bras Cir 2011;38(4):212-6.
  10. Corrêa R. da S, Freitas-Júnior R, Peixoto JE, et al. [Estimated mammogram coverage in Goiás State, Brazil]. Cad Saude Publica 2011;27(9):1757-67.
  11. Berrington de González A, Reeves G. Mammographic screening before age 50 years in the UK: comparison of the radiation risks with the mortality benefits. Br J Cancer 2005;93:590-6.
  12. Corrêa R da S, Peixoto JE, Ferreira RDS, et al. Risco de câncer radioinduzido em rastreamento mamográfico. Rio de Janeiro, RJ, Brazil: IX Latin American IRPA Regional Congress on Radiation Protection and Safety - IRPA 2013, 2013. http://www.iaea.org/inis/collection/NCLCollectionStore/_Public/45/071/45...
  13. Yaffe MJ, Mainprize JG. Risk of radiation-induced breast cancer from mammographic screening. Radiology 2011;258:98-105.
  14. Young KC, Faulkner K, Wall B, et al. UK National Health Service Breast Screening Programme (NHSBSP). Review of radiation risk in breast screening. NHSBSP Publication no. 54, 2003.
  15. Anselin L. Exploring Spatial Data with GeoDATM: A Workbook. Center for Spatially Integrated Social Science, 2005.
  16. Wheeler D, Tiefelsdorf M. Multicollinearity and correlation among local regression coefficients in geographically weighted regression. J Geog Syst 2005;7:161-87.
  17. Henley SJ, Anderson RN, Thomas CC, Massetti GM, Peaker B, Richardson LC. Invasive Cancer Incidence, 2004-2013, and Deaths, 2006-2015, in Nonmetropolitan and Metropolitan Counties - United States. MMWR Surveill Summ 2017;66(14):1-13.
  18. Vieira RADC, Formenton A, Bertolini SR. Breast cancer screening in Brazil. Barriers related to the health system. Rev Assoc Med Bras (1992). 2017;63:466-74.

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  Conflict of Interest:
  None declared.

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