Open Access
Estimating LOCP cancer mortality rates in small domains in Spain using its relationship with lung cancer
(Nature Research, 2021) Retegui Goñi, Garazi; Etxeberria Andueza, Jaione; Ugarte Martínez, María Dolores; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2; Estadística, Informática y Matemáticas; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
The distribution of lip, oral cavity, and pharynx (LOCP) cancer mortality rates in small domains (defined as the combination of province, age group, and gender) remains unknown in Spain. As many of the LOCP risk factors are preventable, specific prevention programmes could be implemented but this requires a clear specification of the target population. This paper provides an in-depth description of LOCP mortality rates by province, age group and gender, giving a complete overview of the disease. This study also presents a methodological challenge. As the number of LOCP cancer cases in small domains (province, age groups and gender) is scarce, univariate spatial models do not provide reliable results or are even impossible to fit. In view of the close link between LOCP and lung cancer, we consider analyzing them jointly by using shared component models. These models allow information-borrowing among diseases, ultimately providing the analysis of cancer sites with few cases at a very disaggregated level. Results show that males have higher mortality rates than females and these rates increase with age. Regions located in the north of Spain show the highest LOCP cancer mortality rates.
Open Access
Multivariate Bayesian models with flexible shared interactions for analyzing spatio-temporal patterns of rare cancers
(Springer, 2024) Retegui Goñi, Garazi; Etxeberria Andueza, Jaione; Ugarte Martínez, María Dolores; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2; Universidad Pública de Navarra - Nafarroako Unibertsitate Publikoa
Rare cancers afect millions of people worldwide each year. However, estimating incidence or mortality rates associated with rare cancers presents important difculties and poses new statistical methodological challenges. In this paper, we expand the collection of multivariate spatio-temporal models by introducing adaptable shared spatio-temporal components to enable a comprehensive analysis of both incidence and cancer mortality in rare cancer cases. These models allow the modulation of spatio-temporal efects between incidence and mortality, allowing for changes in their relationship over time. The new models have been implemented in INLA using r-generic constructions. We conduct a simulation study to evaluate the performance of the new spatio-temporal models. Our results show that multivariate spatio-temporal models incorporating a fexible shared spatio-temporal term outperform conventional multivariate spatio-temporal models that include specifc spatio-temporal efects for each health outcome. We use these models to analyze incidence and mortality data for pancreatic cancer and leukaemia among males across 142 administrative health care districts of Great Britain over a span of nine biennial periods (2002-2019)
Open Access
La estadística en la investigación en ciencias de la salud
(Sociedad de Estadística e Investigación Operativa, 2020) Martínez Baz, Iván; Alejos Ferreras, Belén; Ramis Prieto, Rebeca; Arostegui Madariaga, Inmaculada; Arrospide Elgarresta, Arantzazu; Belzunegui Otano, Tomás; Cadarso Suárez, Carmen María; Navarrete Muñoz, Eva María; Ugarte Martínez, María Dolores; Etxeberria Andueza, Jaione; Pijoan Zubizarreta, José Ignacio; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
Statistics and health research are closely related. Statistical methods and analysis are essential components in any research field and have acquired a relevant role in recent decades. In this context, the Universidad Pública de Navarra offered a summer course entitled ‘Statistics in Health Sciences. A look from research’ in order to divulge the role of statistics in health sciences research. To this end, health research professionals with extensive experience, with different backgrounds and areas of profesional interest (academic, health, epidemiological or statistical) were convened to present their vision of the topic. All participants agreed on the need of setting multidisciplinary teams, including health and statistician professionals, and greater synergy between the health and academic fields.The statistical profile is becoming more relevant role within health research teams, especially after the acquisition of complementary skills in epidemiology and public health.
Open Access
Using mortality to predict incidence for rare and lethal cancers in very small areas
(VCH Publishers, 2022) Etxeberria Andueza, Jaione; Goicoa Mangado, Tomás; Ugarte Martínez, María Dolores; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2
Incidence and mortality figures are needed to get a comprehensive overview of cancer burden. In many countries, cancer mortality figures are routinely recorded by statistical offices, whereas incidence depends on regional cancer registries. However, due to the complexity of updating cancer registries, incidence numbers become available 3 or 4 years later than mortality figures. It is, therefore, necessary to develop reliable procedures to predict cancer incidence at least until the period when mortality data are available. Most of the methods proposed in the literature are designed to predict total cancer (except nonmelanoma skin cancer) or major cancer sites. However, less frequent lethal cancers, such as brain cancer, are generally excluded from predictions because the scarce number of cases makes it difficult to use univariate models. Our proposal comes to fill this gap and consists of modeling jointly incidence and mortality data using spatio-temporal models with spatial and age shared components. This approach allows for predicting lethal cancers improving the performance of individual models when data are scarce by taking advantage of the high correlation between incidence and mortality. A fully Bayesian approach based on integrated nested Laplace approximations is considered for model fitting and inference. A validation process is also conducted to assess the performance of alternative models. We use the new proposals to predict brain cancer incidence rates by gender and age groups in the health units of Navarre and Basque Country (Spain) during the period 2005-2008.
Open Access
Predicting cancer incidence in regions without population-based cancer registries using mortality
(Oxford University Press, 2023) Retegui Goñi, Garazi; Etxeberria Andueza, Jaione; Riebler, Andrea; Ugarte Martínez, María Dolores; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, PJUPNA2018-11
Cancer incidence numbers are routinely recorded by national or regional population-based cancer registries (PBCRs). However, in most southern European countries, the local PBCRs cover only a fraction of the country. Therefore, national cancer incidence can be only obtained through estimation methods. In this paper, we predict incidence rates in areas without cancer registry using multivariate spatial models modelling jointly cancer incidence and mortality. To evaluate the proposal, we use cancer incidence and mortality data from all the German states. We also conduct a simulation study by mimicking the real case of Spain considering different scenarios depending on the similarity of spatial patterns between incidence and mortality, the levels of lethality, and varying the amount of incidence data available. The new proposal provides good interval estimates in regions without PBCRs and reduces the relative error in estimating national incidence compared to one of the most widely used methodologies.
Open Access
Projections of lung cancer incidence by 2035 in 40 countries worldwide: population-based study
(JMIR Public Health and Surveillance, 2023) Luo, Ganfeng; Zhang, Yanting; Etxeberria Andueza, Jaione; Arnold, Melina; Cai, Xiuyu; Hao, Yuantao; Zou, Huachun; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2
Background: The global burden of lung cancer (LC) is increasing. Quantitative projections of the future LC burden in different world regions could help optimize the allocation of resources and provide a benchmark for evaluating LC prevention and control interventions. Objective: We aimed to predict the future incidence of LC in 40 countries by 2035, with an emphasis on country- and sex-specific disparities. Methods: Data on LC incidence from 1978 to 2012 were extracted from 126 cancer registries of 40 countries in Cancer Incidence in Five Continents Volumes V-XI and used for the projection. Age-standardized incidence rates (ASRs) per 100,000 person-years and the number of incident cases were predicted through 2035, using the NORDPRED age-period-cohort model. Results: Global ASRs of the 40 studied countries were predicted to decrease by 23% (8.2/35.8) among males, from 35.8 per 100,000 person-years in 2010 to 27.6 in 2035, and increase by 2% (0.3/16.8) among females, from 16.8 in 2010 to 17.1 in 2035. The ASRs of LC among females are projected to continue increasing dramatically in most countries by 2035, with peaks after the 2020s in most European, Eastern Asian, and Oceanian countries, whereas the ASRs among males will continue to decline in almost all countries. The ASRs among females are predicted to almost reach those among males in Ireland, Norway, the United Kingdom, the Netherlands, Canada, the United States, and New Zealand in 2025 and in Slovenia in 2035 and even surpass those among males in Denmark in 2020 and in Brazil and Colombia in 2025. In 2035, the highest ASRs are projected to occur among males in Belarus (49.3) and among females in Denmark (36.8). The number of new cases in 40 countries is predicted to increase by 65.32% (858,000/1,314,000), from 1.31 million in 2010 to 2.17 million in 2035. China will have the largest number of new cases. Conclusions: LC incidence is expected to continue to increase through 2035 in most countries, making LC a major public health challenge worldwide. The ongoing transition in the epidemiology of LC highlights the need for resource redistribution and improved LC control measures to reduce future LC burden worldwide.