Ten-Year Probabilities of Death Due to Cancer and Cardiovascular Disease among Breast Cancer Patients Diagnosed in North-Eastern Spain.

Mortality from cardiovascular disease (CVD), second tumours, and other causes is of clinical interest in the long-term follow-up of breast cancer (BC) patients. Using a cohort of BC patients (N = 6758) from the cancer registries of Girona and Tarragona (north-eastern Spain), we studied the 10-year probabilities of death due to BC, other cancers, and CVD according to stage at diagnosis and hormone receptor (HR) status. Among the non-BC causes of death (N = 720), CVD (N = 218) surpassed other cancers (N = 196).

Using population-based data to evaluate the impact of adherence to endocrine therapy on survival in breast cancer through the web-application BreCanSurvPred.

We show how the use and interpretation of population-based cancer survival indicators can help oncologists talk with breast cancer (BC) patients about the relationship between their prognosis and their adherence to endocrine therapy (ET). The study population comprised a population-based cohort of estrogen receptor positive BC patients (N = 1268) diagnosed in Girona and Tarragona (Northeastern Spain) and classified according to HER2 status (+ / -), stage at diagnosis (I/II/III) and five-year cumulative adherence rate (adherent > 80%; non-adherent ≤ 80%). Cox regression analysis was performed to identify significant prognostic factors for overall survival, whereas relative survival (RS) was used to estimate the crude probability of death due to BC (P).

No Excess Mortality up to 10 Years in Early Stages of Breast Cancer in Women Adherent to Oral Endocrine Therapy: A Probabilistic Graphical Modeling Approach.

Breast cancer (BC) is globally the most frequent cancer in women. Adherence to endocrine therapy (ET) in hormone-receptor-positive BC patients is active and voluntary for the first five years after diagnosis. This study examines the impact of adherence to ET on 10-year excess mortality (EM) in patients diagnosed with Stages I to III BC (N = 2297).

Predicting Ovarian-Cancer Burden in Catalonia by 2030: An Age-Period-Cohort Modelling.

Ovarian cancer is the most lethal gynaecological cancer in very-high-human-development-index regions. Ovarian cancer incidence and mortality rates are estimated to globally rise by 2035, although incidence and mortality rates depend on the region and prevalence of the associated risk factors. The aim of this study is to assess changes in incidence and mortality of ovarian cancer in Catalonia by 2030.

Estimating Country-Specific Incidence Rates of Rare Cancers: Comparative Performance Analysis of Modeling Approaches Using European Cancer Registry Data.

Estimating incidence of rare cancers is challenging for exceptionally rare entities and in small populations. In a previous study, investigators in the Information Network on Rare Cancers (RARECARENet) provided Bayesian estimates of expected numbers of rare cancers and 95% credible intervals for 27 European countries, using data collected by population-based cancer registries. In that study, slightly different results were found by implementing a Poisson model in integrated nested Laplace approximation/WinBUGS platforms.

Predicting the rising incidence and mortality of endometrial cancers among women aged 65-74 years in Catalonia.

Endometrial cancer is currently one of the most common gynecological cancers. Reported incidence rates vary in Spain depending on the region. We estimated what the incidence and mortality of endometrial cancers in Catalonia will be by 2030 and compared the predictions with data from 2010.

Missing data imputation and synthetic data simulation through modeling graphical probabilistic dependencies between variables (ModGraProDep): An application to breast cancer survival.

Background: Two common issues may arise in certain population-based breast cancer (BC) survival studies: I) missing values in a survivals' predictive variable, such as "Stage" at diagnosis, and II) small sample size due to "imbalance class problem" in certain subsets of patients, demanding data modeling/simulation methods.

Methods: We present a procedure, ModGraProDep, based on graphical modeling (GM) of a dataset to overcome these two issues. The performance of the models derived from ModGraProDep is compared with a set of frequently used classification and machine learning algorithms (Missing Data Problem) and with oversampling algorithms (Synthetic Data Simulation).

Epidemiology of human papillomavirus-related oropharyngeal cancer in a classically low-burden region of southern Europe.

The incidence of human papillomavirus (HPV)-related oropharyngeal cancer is increasing in some regions. Nevertheless, the epidemiology of this disease has not been extensively investigated in southern Europe. We conducted a retrospective cohort study of patients diagnosed with primary oropharyngeal cancer from 1991 to 2016.

Changes in lung cancer survival by TNM stage in the Basque country from 2003 to 2014 according to period of diagnosis.

Introduction: The objective of this study was to analyze the survival of patients with lung cancer by TNM stage in the 4-year periods 2003-2006, 2007-2010 and 2011-2014, treated in the Basque Health Service, and to compare this with survival in an equivalent sample of the general population.

Methods: A retrospective observational design was applied to cases from the Hospital Cancer Registry of Euskadi. A cohort of 11,635 patients had complete data for the following variables: TNM stage, age, sex, histology, date of diagnosis, vital status and date of death.

Detection of incident breast and colorectal cancer cases from an administrative healthcare database in Catalonia, Spain.

Objective: To validate the Catalan minimum basic data set (MBDS) of hospital discharges as an information source for detecting incident breast (BC) and colorectal cancer (CRC), against the Hospital del Mar Cancer Registry (RTHMar) in Barcelona (Spain) as the gold standard.

Methods: Using ASEDAT software (Analysis, Selection and Extraction of Tumour Data), we identified Catalan public hospital discharge abstracts in patients with a first-time diagnosis of BC and CRC in the years 2005, 2008, and 2011, aggregated by unique patient identifiers and sorted by date. Once merged with the RTHMar database and anonymized, tumour-specific algorithms were validated to extract data on incident cases, tumour stage, surgical treatment, and date of incidence.

Prediction of advanced colonic neoplasm in symptomatic patients: a scoring system to prioritize colonoscopy (COLONOFIT study).

Background: Fast-track colonoscopy to detect patients with colorectal cancer based on high-risk symptoms is associated with low sensitivity and specificity. The aim was to derive a predictive score of advanced colonic neoplasia in symptomatic patients in fast-track programs.

Methods: All patients referred for fast-track colonoscopy were evaluated.

Cause-specific mortality after a breast cancer diagnosis: a cohort study of 10,195 women in Girona and Tarragona.

Introduction: Evidence suggests an excess of long-term mortality due to cardiovascular diseases, second tumours and other causes in patients diagnosed with invasive breast cancer (BC). Our aim was to assess this risk of death in a cohort of patients diagnosed with BC in Girona and Tarragona, northeastern Spain.

Materials And Methods: Using data from the cancer registries in these areas, a population-based cohort study was carried out including all the women diagnosed with BC during 1985-2004 and followed up until December 31st 2014 (N = 10,195).

[Excess mortality among breast cancer patients in early stages in Tarragona and Gerona (Spain)].

Objective: To analyze the population-based survival of breast cancer (CM) diagnosed in early stages estimating the time trends of excess mortality (EM) in the long term in annual and five-year time intervals, and to determine, if possible, a proportion of patients who can be considered cured.

Method: We included women diagnosed with BC under the age of 60 years in stages I and II in Girona and Tarragona (N = 2453). The observed (OS) and relative survival (RS) were calculated up to 20 years of follow-up.

: A New Way to Assess the Quality of Healthcare by Examining Causes of Premature Death for Which Highly Efficacious Medical Interventions Are Available.

Background: Amenable mortality, or premature deaths that could be prevented with medical care, is a proven indicator for assessing healthcare quality when adapted to a country or region's specific healthcare context. This concept is currently used to evaluate the performance of national and international healthcare systems. However, the levels of efficacy and effectiveness determined using this indicator can vary greatly depending on the causes of death that are included.

Projections in Breast and Lung Cancer Mortality among Women: A Bayesian Analysis of 52 Countries Worldwide.

Among women, lung cancer mortality rates have surpassed those for breast cancer in several countries. This reflects the breast cancer mortality declines due to access to screening and effective treatment alongside the entrance of certain countries in stages of the tobacco epidemic in which smoking becomes more prevalent in women. In this study, we project lung and breast cancer mortality until 2030 in 52 countries.

Moderate egg consumption and all-cause and specific-cause mortality in the Spanish European Prospective into Cancer and Nutrition (EPIC-Spain) study.

Purpose: Dietary guidelines for egg consumption for general population differ among public health agencies. Our aim was to investigate the association between egg intake and both all-cause and specific-cause of mortality in a Mediterranean population.

Methods: The European Prospective Investigation into Cancer and Nutrition (EPIC)-Spain cohort included 40,621 men and women aged 29-69 years old in the nineties from 5 Spanish regions.

Bayesian estimates of the incidence of rare cancers in Europe.

Background: The RARECAREnet project has updated the estimates of the burden of the 198 rare cancers in each European country. Suspecting that scant data could affect the reliability of statistical analysis, we employed a Bayesian approach to estimate the incidence of these cancers.

Methods: We analyzed about 2,000,000 rare cancers diagnosed in 2000-2007 provided by 83 population-based cancer registries from 27 European countries.

Long-term crude probabilities of death among breast cancer patients by age and stage: a population-based survival study in Northeastern Spain (Girona-Tarragona 1985-2004).

Background: We provide population-based long-term survival indicators of breast cancer patients by quantifying the observed survival, and the probabilities of death due to breast cancer and to other causes by age and tumor stage at diagnosis.

Methods: We included a total of 10,195 female patients diagnosed before 85 years with invasive primary breast cancer in Girona and Tarragona during the periods 1985-1994 and 1995-2004 and followed-up until December 31st 2014. The survival indicators were estimated at 5, 10, 15 and 20 years of follow-up comparing diagnostic periods.

[WebSurvCa: web-based estimation of death and survival probabilities in a cohort].

Relative survival has been used as a measure of the temporal evolution of the excess risk of death of a cohort of patients diagnosed with cancer, taking into account the mortality of a reference population. Once the excess risk of death has been estimated, three probabilities can be computed at time T: 1) the crude probability of death associated with the cause of initial diagnosis (disease under study), 2) the crude probability of death associated with other causes, and 3) the probability of absolute survival in the cohort at time T. This paper presents the WebSurvCa application (https://shiny.

Predicting the cancer burden in Catalonia between 2015 and 2025: the challenge of cancer management in the elderly.

Background: Developing effective cancer control programmes requires information on the future cancer burden in an ageing population. In our study we predicted the burden of cancer in Catalonia from 2015 to 2025.

Methods: Bayesian age-period-cohort models were used to predict the burden of cancer from 2015 to 2025 using incidence data from the Girona and Tarragona cancer registries and cancer mortality data from the Catalan mortality registry.

Assessing predicted age-specific breast cancer mortality rates in 27 European countries by 2020.

Background: We assessed differences in predicted breast cancer (BC) mortality rates, across Europe, by 2020, taking into account changes in the time trends of BC mortality rates during the period 2000-2010.

Methods: BC mortality data, for 27 European Union (EU) countries, were extracted from the World Health Organization mortality database. First, we compared BC mortality data between time periods 2000-2004 and 2006-2010 through standardized mortality ratios (SMRs) and carrying out a graphical assessment of the age-specific rates.

Sex and Age Specific Projections of Smoking Prevalence in Spain: A Bayesian Approach.

Objectives: To project future smoking prevalence rates in Spain by sex and age groups using Bayesian methods and to estimate the probability of a 30% relative reduction between 2010 and 2025.

Methods: We used the data from the Spanish National Health Surveys (2003, 2006, and 2011) to obtain information about current and former smoking. We reconstructed annual smoking rates from 1989 through 2011 by sex and 5-year age groups.

Modelling lung cancer mortality rates from smoking prevalence: Fill in the gap.

Background: The objective of this study is to estimate the gap between smoking prevalence and lung cancer mortality and provide predictions of lung cancer mortality based on previous smoking prevalence.

Materials And Methods: We used data from the Spanish National Health Surveys (2003, 2006 and 2011) to obtain information about tobacco use and data from the Spanish National Statistics Institute to obtain cancer mortality rates from 1980 to 2013. We calculated the cross-correlation among the historical series of smoking prevalence and lung cancer mortality rate (LCMR) to estimate the most likely time gap between both series.