Embed Size (px)
Citation preview
Analysis of cancer incidence by department in the province of Córdoba - Argentina (2004-2008): rates
of incidence and detection of spatial clusters
Authors:
Agost Lisandro, UNC ; INC. Argentina. [email protected]. Pujol Céline Jeanne. CIECS-CONICET-UNC. Argentina. [email protected]. Bertone Carola Leticia. CIECS-CONICET-UNC. [email protected] Álvarez María Franci Sussan, UNVM. Argentina. [email protected] Fantin, María Alejandra, IIGHI-CONCIET. Argentina. [email protected]
Abstract
In Argentina, cancer is the first cause of death between 35 and 74 years of age. The analysis of the
spatial distribution of cancer, using the Geographical Information Systems (GIS), makes it possible to
centralize and to give a new insight into the disease. This research analyzes the spatial distribution of
cancer incidence in the Province of Córdoba, trying to identify clusters of tumors. The information on
morbidity comes from the Registry of Tumors of the Province of Córdoba for the five year period 2004-
2008. Clusters are detected by SaTScan program. Significant clusters were obtained for different types
of malignant tumors, standing out those of the respiratory and digestive organs. This work represents a
contribution to the knowledge of the spatial distribution of tumor incidence in the province of Córdoba.
The coincidence of the spatial location of clusters found highlights the importance of further deepening
into the studies on the distribution of this disease and its influencing factors
Key words: Spatial Distribution, Neoplasms, Cluster Analysis, Morbidity
Introduction
According to the World Health Organization (WHO), the burden of the not transmissible diseases
increases steadily in all regions of the world and in all age ranges. It is estimated that in 2008, in the
world, 36 million persons died of some chronic non transmissible disease (1). Argentina is no stranger to
this reality; tumors represent the second cause of death, after circulatory diseases, and the first one if
the age group between 35 and 74 years of age is considered (2). However, little is known about cancer
morbidity.
In the frame of the lack of information about cancer incidence and prevalence of the Department of
Health of Argentina, the International Agency for Research on Cancer (IARC) estimated that in 2008, in
Argentina, there were 104,859 new cases of malignant tumors (excluding those in skin histology other
than melanoma; an incidence of 206 new cases per year every 100.000 inhabitants, for both sexes (3).
From a socio - epidemiological approach (4), it is known that cancer has a multifactorial origin;
consequently, it turns out difficult to inquire into the causes of cancer. Nevertheless, the spatial analysis
of health data is an interesting tool to centralize information and to achieve a new vision of the disease.
In effect, it is a basic approach to its potential etiologies (5). In this sense, the use of analytic tools which
allow the overlapping and interaction of varied information, with coherence and objectivity, seeking
new forms of stratification and data visualization, is fundamental.
Methodologies such as the Geographic Information Systems (GIS) can help to transfer this type of
information between different spatial and temporal units, allowing a better understanding of the
phenomenon (6). It is necessary to emphasize that, in recent years, there has been a growth in the
interest of health professionals in the use of the GIS as a tool for the analysis, management, monitoring
and decision - making in public health (5).
In the province of Córdoba the incidence of cancer was studied by using information of the Register of
Tumors of the Province for the year 2004. It was found that there exists a hierarchical structure in the
distribution of the incidence of cancer strongly conditioned by sex. It was demonstrated that the tumors
of lung, breast, prostate and colon, are grouped in the department of Córdoba Capital (7).
The present study analyzes the spatial distribution of tumor incidence in the province of Córdoba,
Argentina, for the period 2004-2008 at departmental level. More specifically it proposes to investigate
the possible existence of aggregation patterns of the disease (clusters).
Methods
This is an ecological research whose analysis unit is counties or department of the province of Córdoba.
Córdoba is one of the 23 provinces that make up the Argentine Republic. Because of its extension-
165.321 km2, Córdoba occupies the fifth place in the group of Argentine provinces. According to the
2010 census, the province of Córdoba has 3.304.825 inhabitants. This represents 8.2 % of the national
population, and makes Córdoba the second most populous province in the country, after the province of
Buenos Aires. Of the total population in Córdoba, 48.6 % are males and 51.4 % are female (8). Its
population is not homogeneously distributed in the 26 departments (legal - administrative divisions)
that make up the province, 40 % lives the capital department.
Regarding the economic sectors of the province, the provision of services is the activity of the highest
incidence in the Gross Geographic Product (GGP) in Cordoba with a share of 59 % of the total, measured
at current prices (9). It is followed in importance by the manufacturing Industry, responsible for 18.6 %
of the aggregate value of the provincial economy among which the car industry and the manufacture of
food and beverages stand out (9). The third position is for agriculture, ranching, hunt and forestry, with
a share of 13.2 per cent. The agricultural activity is principally characterized by the cultivation of
soybeans and corn, followed by wheat, sorghum and sunflower (10). The planted zones are historically
in the south-east of the province (11). The rest of the GGP is distributed between building (7.3 %),
electricity, gas and water (1.7 %) and mining and quarrying (0.1 %) (8).
For the accomplishment of the proposed objectives we use data from the Registry of Tumors of the
Province of Córdoba. It was created by Decree N º 3450/D/1965, and depends on the Department of
Health of the province, its current headquarters being the Instituto Oncológico Dr. J. M. Urrutia (12).
Since 2003, it tracks down new cancer cases among the residents, including malignant tumors from any
location, malignant invading tumors, injuries in situ, bladder papilloma, tumors of the nervous central
system, regardless of their behavior, and malignant tumors of skin, including basal-cell carcinoma
(12)(Chapter 7, article 18).
It is a primarily hospital-based cancer registry organized as a network of Reporting Centers. It gathers
information " from both the public sector - provincial, municipal or national- as well as the private sector
and social security system that have their scope of attention within the provincial territory " (12)
(Chapter 1, article 2).
In effect, the establishments in the province, regardless of their jurisdiction or sector, have the duty to
notify every new case of tumor, such as stated by the Law N º 9769 (12).
In turn, the teams working on the tumor registry constituted in several Zonal Nodes, perform an active
search of cases and "they control, in the area of their intervention, the quality of the data collection"
(12)(Chapter 4, article 9).
The available information corresponds to the period 2004-2008. For the analysis, we considered the
number of cases of malignant tumors for all locations, and benign of the central nervous system (CNS)
registered during this five year period. This database was divided according to the International
Classification of Diseases in its tenth version (CIE-10) (13), in force since 1993 (14), which classifies
neoplasm according to their topography (C00-D48). On the contrary, the cases of in situ tumors and of
those of uncertain behavior were not taken into account given the great variability within the data
source of the cases of these types of tumor. The cases relevant to residents of provincial departments,
age or sex unknown were also excluded.
Firstly, the average number of cases and the crude rate of annual incidence of the total of tumor cases
were calculated, after that, of the large groups of tumors and subsequently of some particular tumor
types. In its preparation there were used the population data from the National Census of Population
and Housing 2001 (15), and of the Provincial Census of Housing and Homes 2008 in the Province of
Córdoba (16). These were extrapolated by the schedule AGEINT - belonging to the Population Analysis
Spreadsheets (PAS) elaborated by U. S. Census Bureau-to get the population at half of the studied
period, to 30/06/2006.
In addition, with the purpose of stating comparisons between the different departments, the rates of
annual average incidence of the five year period 2004-2008 were calculated, typified according to age.
The above mentioned rates were standardized by means of the direct method as from the " Old
Standard World Population " defined by Doll and Waterhouse (17) recommended by the WHO in order
to remove the bias that means the distribution by age of the population, strong well-known
determinant of the incidence of tumors.
After a brief description of the rates and their behavior, it was carried out the analysis of the spatial
distribution of tumor incidence in the period 2004-2008, of the residents of both sexes in the province
of Córdoba, taking as unit of analysis the political - administrative division 'department'.
For the detection and location of clusters we used an exploratory methodology. This allows us to
represent those zones with a more than expected occurrence of the disease by means of the free
software SaTScan. The latter has been developed by Kulldorf to analyze information of health events in
time and space (18). The statistics generated are used for detecting and evaluating clusters of spatial,
purely temporal and temporal-spatial cases (18). In this case only a spatial analysis was carried out due
to the short period of time for which data for morbidity is available.
SatScan analyzes "spaces" or "windows", shaped like a cylinder, with its centroid and definite radius. In
the case of our study the centroids belong to the departments. This methodology is based on the
assumption that the cases may have a Poisson type distribution, which is the probability distribution
used to analyze discreet variables that represent rare events (18). The null hypothesis raised in the
analysis of SaTScan, assumes a random distribution of the observations in space.
The number of observed cases is pinned down as well as the population at risk of suffering the disease
by geographical unit of analysis.Thus, the general procedure consists in analyzing the risk that an
epidemiological event of interest may happen within every "window" (calculated from the observed and
expected cases), comparing it with the rest of the territory under study, testing the void hypothesis that
its risk of occurrence is kept constant along the space. If the void hypothesis is rejected, it means that
there exists a cluster of cases (18). For the above mentioned cluster its statistical significance is verified,
an index of the observed and expected is calculated and it attributes a relative risk of suffering the
disease, with regard to the zones not included in the cluster.
Where:
The relative risk is estimated as follows:
c = Number of cases observed within the cluster.
C = Total Number of cases.
E[c¬ = Covariate of the expected number of cases in the window generated by the program
corresponding to the null hypothesis, that is to say the found cluster.
The analysis result is presented in SatScan by a cluster map showing the department in accordance with
the significance of spatial association found. The shaded departments in the map correspond to those in
which there is evidence of significant spatial dependence.
Description of the data source
Between 2004 and 2008, in the province of Córdoba, 45,484 cases of tumors were registered (48.3 %
men and 51.7 % women), that is, an average of 9,097 annual cases. It corresponds to a crude rate of
incidence of 279.1 for every 100,000 inhabitants, according to the provincial population at half the
period on June 30/2006, estimated by the authors as 3,282,680 inhabitants.
With regard to the quality of content, there is still no official estimate of its coverage neither at
provincial nor at department level. Meanwhile, it is possible to analyze the frequency of the malignant
tumors of ill-defined secondary sites and of not specified sites which correspond to 5.3 provincial %; this
percentage varies between 3.1 % for the Sobremonte department and 9.8 % for Minas.
The average age at the moment of the diagnosis of tumor is 63 years. The registered people range from
under one year to 99 years of age. 1.8 % is between 0 and 19 years, 34.7 % between 20 and 59 years
and 63.5 % is older than 60 years of age.
The percentage distribution of cases by department (see Table 1), is similar to the percentage
distribution of the population, which tells of an approximation to the level of coverage by department. It
is necessary to emphasize that of the registered cases, the percentage of cases corresponding to
residents of unknown department is relatively low: 3.2 %.
With regard to the distribution of cases according to behavior and type of tumor, it is worth emphasizing
that 96.3 % of the tumors is of malignant behavior, 2.8 % in situ, 0.6 % of uncertain behavior and 0.3
benign %.
Results and Discussion
Description of the rates
It is necessary to remember that, for the analysis, we excluded the cases in which the department
residence, age or sex were unknown. We also excluded cases of tumors of uncertain behavior, in situ or
benign (except the benign ones of the nervous central system, included in the spatial analysis).
At the time, 42,578 cases were considered (Table 1); which corresponds to a crude annual incidence
rate of tumors of 261.3 and a typified annual incidence rate of 202.1- both rates for 100,000 inhabitants
of both sexes-. The latter turned out to be lower than the one estimated by GLOBOCAN (19) for
Argentina in 2008 (206.3 for 100,000); it is necessary to clarify that the classification was performed by
the direct method, as explained in the methodological paragraph, the same as the one adopted by
GLOBOCAN.
The rates of incidence typified at level of department vary between 127.4 for Pocho department and
236 for the Capital department, with an average of 177.8 per 100,000 inhabitants (Table 1).
The most frequent tumor in term of morbidity, as expected according to GLOBOCAN, is that of breast
(C50) with a typified incidence rate of 33.7 per 100,000 inhabitants, lower than the one estimated
GLOBOCAN for Argentina in 2008 (Table 3) (19). The most frequent second tumor is that of bronchus
and lungs (C34), with a typified rate of incidence of 18.7 per 100.000 inhabitants, lower than that
estimated by GLOBOCAN (19) for Argentina 2008 (20.5 for 100.000). According to the same GLOBOCAN,
they occupy a third position, after the tumors of prostate. The intestinal tumors (C17-C21) have a
typified incidence rate of 18 cases per 100.000 inhabitants. In the next position are the tumors of
prostate with a rate of 13.7 per 100.000, lower than that by GLOBOCAN (19) for Argentina in 2008 (58.8
for 100.000).
In conducting the analysis of the distribution of the incidence of tumors, without discriminating on
tumor type or sex of the affected person, we found the presence of a statistically significant cluster (p =
0.004) constituted only by the Capital department, to which corresponds a Relative Risk of 1.09 (Table
4).
Then, the procedure was performed using the incidence for each cancer group (according to the
classification CIE-10). In this case a significant cluster was constituted for the digestive tumors (C15-C26)
(p = 0.01), the malignant tumors of the respiratory and intrathoracic organs (C30-C39) (p <0.001). All
these clusters are composed of the departments of the South and South - East (Figure 1) - Marcos
Juárez, Union, General San Martín, Juárez Celman, Tercero Arriba, Río Segundo, Presidente Roque Sáenz
Peña, San Justo, Río Cuarto , Calamuchita-, and associated with a Relative Risk of 1.19 and 1.55,
respectively (Table 4).
Malignant tumors of the thyroid and other endocrine glands (C73-C75) formed a cluster consisting of
departments Colon and Capital with a RR of 1.69, while a cluster of malignant tumors of lymphatic tissue
and of the hematopoietic organs and related tissue was identified (C81-C96) in the department Río
Segundo and Capital with a RR of 1.34.
Meanwhile, using the incidence of each tumor type, the same above cluster was defined for malignant
neoplasm of bronchus and lung (C34) (p <0.001) and pancreatic tumors (C25) (p = 0.042) excluding the
department Calamuchita (Figure 1 and Table 4). The relative risks were 1.66, and 1.44 respectively
(Table 4). In addition we a cluster was situated in the department Capital when studying breast tumors
(C50) with a RR of 1.35.
It should be noted that the determination of cluster technique applied in this study is widespread and
has been used in investigations of this kind worldwide (20; 21; 22; 23; 24). It is an excellent tool
although it has some limitations, which must be corroborated by other methods of spatiotemporal
analysis; it is useful as an exploratory method.
Key results highlight that there is a pattern of spatial distribution of tumor cases in the province of
Cordoba between 2004 and 2008. That coincides with the conclusion of the work of Diaz and others in
2010 (7).
The clusters defined by the department Capital, have a possible explanation related to its degree of
urbanization. Some previous studies discuss this relationship, not only with the incidence (7) but also
with cancer mortality (25). So it was expected, being the most urbanized city in the province that this
would happen. However, this does not happen to other tumors of high incidence, which formed a
cluster in the southeast of the province, made up of the same departments, as in the case of malignant
neoplasms, respiratory system and intrathoracic organs (C30-C39) and digestive organs (C15-C26),
particularly the malignant neoplasm of bronchus and lung (C34) and pancreatic ones (C25).
Notably Rio Segundo department is included in three of the identified significant clusters.
These results make it clear that further research is important to elucidate the possible causes of such
distribution.
This work represents a contribution to the knowledge of the spatial distribution of the incidence of
tumors in the province of Cordoba on having demonstrated the presence of significant clusters of cases
It is important to emphasize that it is exploratory, and does not try to infer causality
The fact of finding clusters for different types of tumors in the same region shows that the studies must
be deepened. Particularly, research is needed to provide information on the factors that influence their
impact on the territory.
Considering health as a fundamental human right (26), and being cancer the second leading cause of
death in the country, it is essential from the State and the scientific community to respond to the
questions raised about this disease.
Bibliography
1. Organización Mundial de la Salud. Cánceres de origen ambiental y ocupacional. Nota descriptiva N°
350. [Online] Jule, 2011. [Cited : 10 de novenber de 2011.]
www.who.int/mediacentre/factsheets/fs350/es/index.html.
2. Dirección de Estadísticas e Información en Salud (DEIS). Estadísticas Vitales, anuario estadístico.
Dirección de Estadísticas e Información en Salud (DEIS). [Online] [Cited : june, 24, 2010.]
http://www.deis.gov.ar/.
3. Ministerio de salud-Presidencia de la Nación-Argentina. Instituto Nacional del Cáncer. [Online] [Cited
: 2012 de 01 de 25.] http://www.msal.gov.ar/inc/equipos_analisis.php.
4. Sabulsky, Jacobo. Investigacion científica en salud-enfermedad. [ed.] Kosmos editorial medica.
Tercera edición. April 2000. pag. 83. Vol. 3 . ISBN 987-99342-2-6.
5. Organización Panamericana de la Salud (OPS). Boletín Epidemiológico. Análisis Espacial en
Epidemiología y Salud Pública. [Online] Vol. 25: No. 4, 2004. [Cited : january , 12, 2012.]
http://www.paho.org/spanish/dd/ais/EB_v25n4.pdf.
6. Unidades y Escalas en los Análisis Espaciales en Salud. Barcellos, Christovam. [ed.] Sociedad Cubana
de Administración de Salud. 004, La Habana, Cuba : s.n., october - december, 2003, Revista Cubana de
Salud Pública, Vol. 29, págs. 307-313.
7. Modeling Spatial Distribution of Cancer Incidence in Cordoba, Argentina. Díaz, M.P., y otros, y otros.
2, 2010, Applied Cancer Research, Vol. 30, págs. 245-252.
8. Cámara de Comercio de Argentina. Informe económico: Provincia de Córdoba. Observatorio de
Comercio y Servicios, Cámara de Comercio de Argentina. 2011.
9. Ministerio de Economía. Panorama económico provincial. Secretaria de Política Económica. 2006.
10. Secretaria de Ambiente y desarrollo sustentable de la Nación. Secretaria de Ambiente y desarrollo
sustentable de la Nación. [Online] [Cited : november, 09, 2011.]
http://www2.medioambiente.gov.ar/acuerdos/convenciones/cdb/images/regnat1.gif.
11. Ministerio de la Agricultura, Ganadería y Pesca, Argentina. [Online] [Cited : novenber, 07, 2011.]
/www.siia.gov.ar/.
12. Gobierno de la provincia de Córdoba. Ley 9769: Registro Provincial de Tumores de la Provincia de
Córdoba. Boletin oficial, Publicaciones de gobierno. [Online] N°74, 20 de 04 de 2010. [Cited : march, 24,
2012.] www.boletinoficialcba.gov.ar.
13. Ministerio de la salud Argentina. Clasificación Internacional de Enfermedades 10°. CIE 10° REVISION.
[Online] http://www.sssalud.gov.ar/hospitales/archivos/cie_10_revi.pdf.
14. Organización Mundial de la Salud (OMS), Organización Panamericana de la salud (OPS). Boletín
Epidemiológico, Vol. 23, No. 4. [Online] Vol.23 , No. december, 4, 2002.
http://www.paho.org/spanish/dd/ais/be_v23n4-cover.htm.
15. Instituto Nacional de Estadística e Censo (INDEC). Censo Nacional de Población 2001. [Online]
[Cited : september, 17, 2011.] http://www.indec.gov.ar/.
16. Dirección General de Estadística y Censos de la Provincia de Córdoba. Censo provincial de vivienda
y hogares 2008. Dirección General de Estadística y Censos de la Provincia de Córdoba (DGEyC). [Online]
2008. [Cited : february, 21, 2011.]
http://estadistica.cba.gov.ar/Poblaci%C3%B3n/Censo2008/tabid/462/language/es-AR/Default.aspx.
17. Doll, Richard, Payne, Peter y Waterhouse, John. Cancer Incidence in Five Continents. [ed.] Springer-
Verlag. Geneva : Union Internationale Contre le Cancer, 1966. Vol. I.
18. Kulldorf, M. SaTScan TM User Guide for version 9.0. [Online] 2010. [Cited : february, 27, 2012.]
http://www.SaTScan.org/cgi-bin/SaTScan/register.pl/SaTScan_Users_
Guide.pdf?todo=process_userguide_download.
19. Organización Mundial de la Salud (OMS), International Agency for Research on Cancer (IARC).
GLOBOCAN 2008. Cancer Incidence, Mortality and Prevalence Worldwide in 2008. [Online] 2008.
Instituto Nacional de Estadística y Censos.
20. Santamaría Ulloa, Carolina. Análisis para la determinación de conglomerados espacio – temporales
en la incidencia de cáncer. Costa Rica, 1990-1997. [ed.] UNIVERSIDAD DE COSTA RICA. 2002. Trabajo
final de graduación presentado a la Escuela de Estadística, para optar por el grado de Máster en
Población y Salud.
21. A geographical information system-based analysis of cancer mortality and population exposure to
coal mining activities in West Virginia, United States of America. Hendryx, Michael, Fedorko, Evan y
Anesetti-Rothermel, Andrew. 2, 2010, Geospatial Health, Vol. 4, págs. 243-256.
22. Institut de Veille Sanitaire. Étude de mortalité et d'incidence par cancer autour du Centre de
stockage de déchets radioactifs de faible et moyenne activité de l'Aube. Institut de Veille Sanitaire.
[Online]
23. Spatio-temporal evolution of female lung cancer mortality in a region of Spain, is it worth taking
migration into account? Zurriaga, Oscar, y otros, y otros. 2008, BMC Cancer, pag. 8:35.
24. Detección de cluster espaciales de cáncer pediátrico en los municipios de la Región de Murcia. López
Hernández, Fernando. 1, s.l. : XVI Jornadas ASEPUMA – IV Encuentro Internacional, Journal Economic
Literature, Vol. 16, pag. 303.
25. Cancer mortality in Córdoba, Argentina, 1986-2006: an age-period-cohort análisis. Pou, S.A., y otros,
y otros. 2010, Tumori, Vol. 96, págs. 202-212.
26. Naciones Unidas. Declaración Universal de Derechos Humanos. [Online] 1948. [Cited : march, 18 ,
2010.] http://www.un.org/es/documents/udhr/index.shtml.
Table 1- Registered cases and studied cases of neoplasias of the province of Córdoba for department.
2004-2008
Departament
Population a
Registered cases Studied cases b
Inhabitants %
Total of
cases %
Total of
cases %
Annual
average
Raw rate of
annual
incident c
Rate
typified of
annual
incident c
Calamuchita 53817 1,65 665 1,46 654 1,50 131 242 178,9
Capital 1333809 40,92 19871 43,69 19018 44,70 3803 285,2 236
Colon 211008 6,47 2358 5,18 2300 5,40 460 218 200,4
Cruz del Eje 56104 1,72 689 1,51 674 1,60 135 240,3 189,9
General Roca 35871 1,10 390 0,86 388 0,90 78 216,3 160,2
General San Martín 123987 3,80 1477 3,25 1437 3,40 287 231,8 174,7
Ischilín 31553 0,97 319 0,70 313 0,70 63 198,4 150,2
Juárez Celman 58952 1,81 632 1,39 623 1,50 125 211,4 153,6
Marcos Juárez 104737 3,21 1420 3,12 1404 3,30 281 268,1 161,5
Minas 5343 0,16 61 0,13 58 0,10 12 217,1 168,2
Pocho 5091 0,16 47 0,10 46 0,10 9 180,7 127,4
Presidente Roque Sáenz
Peña
36364 1,12 584 1,28 574 1,30 115 315,7 211,1
Punilla 163455 5,01 2168 4,77 2120 5,00 424 259,4 178,8
Río Cuarto 245698 7,54 3063 6,73 2973 7,00 595 242 171,8
Río Primero 46083 1,41 549 1,21 533 1,30 107 231,1 199,6
Río Seco 13128 0,40 126 0,28 123 0,30 25 187,4 177,3
Río Segundo 99566 3,05 1302 2,86 1259 3,00 252 252,9 190,1
San Alberto 37405 1,15 314 0,69 304 0,70 61 162,5 140,7
San Javier 51456 1,58 596 1,31 575 1,30 115 223,5 178,1
San Justo 202612 6,22 2819 6,20 2763 6,50 553 272,7 188
Santa María 94836 2,91 1090 2,40 1055 2,50 211 222,5 184,3
Sobremonte 5031 0,15 64 0,14 63 0,10 13 250,4 184,7
Tercero Arriba 108551 3,33 1529 3,36 1492 3,50 298 274,9 188,4
Totoral 18023 0,55 181 0,40 177 0,40 35 196,4 171,8
Tulumba 13704 0,42 155 0,34 149 0,30 30 217,4 161,7
Unión 103164 3,17 1535 3,37 1503 3,50 301 291,4 195,4
Zona Rural - 4 0,01 - - - - -
Desconocido - 1388 3,05 - - - - -
Total 3259350 100 45484 100 42578 100 8516 261,3 202,1
a Population on June 30, 2006. Own estimation.
b They include only malignant tumors of all locations and benign of the Nervous Central System
c For 100.000 inhabitants.
Source: own estimation from information of the Record of Tumors of the Province of Córdoba and National Census
of Population and Housing 2001 (15) and provincial census of housing and homes 2008 (16).
Table 2- Malignant tumors according to big groups used in the analysis. Province of Córdoba.2004-2008
Big groups of malignant tumors as CIE-10 Studied cases
Annual
average Porcent
Raw rate of
annual
incident a
Rate
typified of
annual
incident a
Malignant neoplasms, lip, oral cavity and
pharynx (C00-C14) 712 142 1,7 4,4 3,6
Malignant neoplasms, digestive organs
(C15-C26) 9946 1989 23,4 61 43,5
Malignant neoplasms, respiratory system
and intrathoracic organs (C30-C39) 4886 977 11,5 30 23,1
Malignant neoplasms, bone and articular
cartilage (C40-C41) 240 48 0,6 1,5 1,3
Malignant neoplasms, skin (C43-C44) 3073 615 7,2 18,9 14,4
Malignant neoplasms, connective and
soft tissue (C45-C49) 611 122 1,4 3,7 3,1
Malignant neoplasms of genital organs
(C51-C63) 6885 1377 16,2 42,2 32,5
Malignant neoplasms, urinary organs
(C64-C68) 2746 549 6,4 16,8 12,8
Malignant neoplasms of eye and adnexa
(C69) 54 11 0,1 0,3 0,3
Malignant and benign neoplasms of brain
and central nervous system (C70-C72)
and (D32-D33) 1191 238 2,8 6,8 5,8
Malignant neoplasms of thyroid gland,
endocrine glands and related structures
(C73-C75) 733 147 1,7 4,5 4,1
Neoplasms of uncertain or unknown
behavior (D37-D48) 2381 476 5,6 14,6 10,4
Malignant neoplasms, stated or
presumed to be primary, of lymphoid,
hematopoietic and related tissue (C81-
C96) 2437 487 5,7 15 12,9
Total 42578 8498,2 100 260,74 201,59
a For 100.000 inhabitants.
Source: own estimation from information of the Record of Tumors of the Province of Córdoba and National
Census of Population and Housing 2001 (15) and provincial census of housing and homes 2008 (16).
Table 3-Some types of tumors used in the analysis. Province of Córdoba.2004-2008
Some tumors of interest
Studied
cases
Annual
average Porcent
Raw
rate of
annual
incident
a
Rate
typified of
annual
incident a
Malignant neoplasm of Esophagus (C15) 941 188,2 2,2 5,77 4,03
Malignant neoplasm of Stomach (C16) 1442 288,4 3,4 8,85 6,40
Malignant neoplasms of small intestine,
colon, rectosigmoid junction, rectum, anus
and anal canal (C17-C21)
4047 809,4 9,5 24,83 17,96
Malignant neoplasms of liver, intrahepatic
bile ducts and biliary tract (C22-C24) 1498 299,6 3,5 9,19 6,46
Malignant neoplasm of pancreas (C25) 1587 317,4 3,7 9,74 6,73
Malignant neoplasm of larynx (C32) 593 118,6 1,4 3,64 2,97
Malignant neoplasm of trachea (C33) 12 2,4 0,0 0,07 0,06
Malignant neoplasm of bronchus and lung
(C34) 4020 804,0 9,5 24,67 18,73
Malignant neoplasm of breast (C50) 6683 1337 15,7 41 33,7
Malignant neoplasm of cervix uteri (C53) 1133 226,6 2,7 6,95 6,42
Malignant neoplasm of corpus uteri (C54) 590 118,0 1,4 3,62 2,92
Malignant neoplasm of uterus, part
unspecified (C55) 295 59,0 0,7 1,81 1,37
Malignant neoplasm of ovary (C56) 849 169,8 2,0 5,21 4,29
Malignant neoplasm of prostate (C61) 3308 661,6 7,8 20,30 13,71
Malignant neoplasm of testis (C62) 399 79,8 0,9 2,45 2,34
Malignant neoplasm of bladder (C67) 1372 274,4 3,2 8,42 6,05
Benign neoplasm of brain and other parts
of central nervous system (D33) 87 17,4 0,2 0,53 0,48
Subtotal 22173 4434,6 52,2 - -
Total of studied cases 42578 8498 100,0 - -
a For 100.000 inhabitants.
Source: own estimation from information of the Record of Tumors of the Province of Córdoba and National Census
of Population and Housing 2001 (15) and provincial census of housing and homes 2008 (16).
Figure 1
Principal spatial significant clusters detected by SaTScan for the province of Córdoba, 2004-2008.
Source: own estimation from information of the Record of Tumors of the Province of Córdoba and National Census of Population and Housing 2001 (15) and provincial census of housing and homes 2008 (16).
20
Table 4-Description of the significant clusters of cases of tumors found in the province of Córdoba.
2004-2006
Cluster defined for Department included inside
the cluster
Observe
d cases a
Awaited
cases b
Observed
/
Awaited
RR
Raw
rate of
incident
2006c
Total tumors (C00-C97 to
D33) Capital
3803
3628
1,05
1,09
271,4
Big groups of tumors
Malignant neoplasms,
digestive organs (C15-
C26)
Marco Juárez, Unión, General
San Martín, Juárez Celman,
Tercero Arriba, Río Segundo,
Presidente Roque Sáenz Peña,
San Justo, Río Cuarto,
Calamuchita.
759 681 1,12
1,19 67,5
Malignant neoplasms,
respiratory system and
intrathoracic organs
(C30-C39)
Marco Juárez, Unión, General
San Martín, Juárez Celman,
Tercero Arriba, Río Segundo,
Presidente Roque Sáenz Peña,
San Justo, Río Cuarto,
Calamuchita.
436 335 1,30 1,55 38,8
Malignant neoplasms of
thyroid gland, endocrine
glands and related
structures (C73-C75)
Colon, Capital 89 70 1,27 1,69 5,6
Malignant neoplasms, Rio Segundo, Capital 258 222 1,16 1,34 17,2
21
stated or presumed to
be primary, of lymphoid,
hematopoietic and
related tissue (C81-C96)
Simple tumors
Malignant neoplasm of
breast (C50) Capital 670 569 1,18 1,35 47,8
Malignant neoplasm of
bronchus and lung (C34)
Marco Juárez, Unión, General
San Martín, Juárez Celman,
Tercero Arriba, Río Segundo,
Presidente Roque Sáenz Peña,
San Justo, Río Cuarto,
Calamuchita.
371 274 1,35 1,66 33,0
Malignant neoplasm of
pancreas (C25)
Marco Juárez, Unión, General
San Martín, Juárez Celman,
Tercero Arriba, Río Segundo,
Presidente Roque Sáenz Peña,
San Justo, Río Cuarto.
130 103 1,26 1,44 12,1
a Cases observed according to the database inside the cluster.
b Cases waited inside the cluster calculated by SaTScan.
c For 100.000 inhabitants, inside the cluster calculated by SaTScan.
Source: own estimation from information of the Record of Tumors of the Province of Córdoba and National
Census of Population and Housing 2001 (15) and provincial census of housing and homes 2008 (16).
