Sweetened beverages are associated with a higher risk of differentiated thyroid cancer in the EPIC cohort: a dietary pattern approach.

BACKGROUND: Dietary pattern analysis has gained particular interest, because it reflects the complexity of dietary intake. The aim of this study was to explore the associations between a posteriori dietary patterns, derived using a data-driven approach, and the risk of differentiated thyroid cancer (TC) in Europe. METHODS: This investigation included 450,064 adults from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Dietary intake was assessed using validated country-specific dietary questionnaires. A posteriori dietary patterns were computed using principal component analyses. Cox regression was used to calculate multivariable adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: After a mean follow-up time of 14 years, 712 first differentiated TCs were diagnosed. In the fully adjusted model, a dietary pattern characterized by alcohol consumption (basically beer and wine) was negatively associated with differentiated TC risk (HRQ4vs.Q1 = 0.75; 95% CI:0.60-0.94, P-trend = 0.005), while a dietary pattern rich in sweetened beverages was positively associated with differentiated TC risk (HRQ4vs.Q1 = 1.26; 95% CI:0.99-1.61; P-trend = 0.07). The remaining 8 dietary patterns were not related to differentiated TC risk. The intake of sweetened beverages was positively associated with differentiated TC risk (HR100mL/d = 1.05; 95% CI:1.00-1.11), especially with papillary TC risk (HR100mL/d = 1.07; 95% CI:1.01-1.13). Similar results were observed with sugary and artificially sweetened beverages. CONCLUSIONS: The investigation of dietary patterns detected that the consumption of sweetened beverages was associated with a higher risk of differentiated thyroid cancer. Our results are in line with the general dietary recommendations of reducing the consumption of sweetened beverages.

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 (PBC). Stage and adherence to ET were the significant factors for predicting all-cause mortality. Compared to stage I, risk of death increased in stage II (hazard ratio [HR] 2.24, 95% confidence interval [CI]: 1.51-3.30) and stage III (HR 5.11, 95% CI 3.46-7.51), and it decreased with adherence to ET (HR 0.57, 95% CI 0.41-0.59). PBC differences were higher in non-adherent patients compared to adherent ones and increased across stages: stage I: 6.61% (95% CI 0.05-13.20); stage II: 9.77% (95% CI 0.59-19.01), and stage III: 22.31% (95% CI 6.34-38.45). The age-adjusted survival curves derived from this modeling were implemented in the web application BreCanSurvPred ( https://pdocomputation.snpstats.net/BreCanSurvPred ). Web applications like BreCanSurvPred can help oncologists discuss the consequences of non-adherence to prescribed ET with patients.

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). Since sample size is an issue for estimating age- and stage-specific survival indicators, we developed a method, ComSynSurData, for generating a large synthetic dataset (SynD) through probabilistic graphical modeling of the original cohort. We derived population-based survival indicators using a Bayesian relative survival model fitted to the SynD. Our modeling showed that hormone-receptor-positive BC patients diagnosed beyond 49 years of age at Stage I or beyond 59 years at Stage II do not have 10-year EM if they follow the prescribed ET regimen. This result calls for developing interventions to promote adherence to ET in patients with hormone receptor-positive BC and in turn improving cancer survival. The presented methodology here demonstrates the potential use of probabilistic graphical modeling for generating reliable synthetic datasets for validating population-based survival indicators when sample size is an issue.

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. Bayesian autoregressive age-period-cohort models were used to predict the burden of OC incidence and mortality rates for the 2015-2030 period. Incidence and mortality rates of ovarian cancer are expected to decline in Catalonia by 2030 in women ≥ 45 years of age. A decrease in ovarian-cancer risk was observed with increasing year of birth, with a rebound in women born in the 1980s. A decrease in mortality was observed for the period of diagnosis and period of death. Nevertheless, ovarian-cancer mortality remains higher among older women compared to other age groups. Our study summarizes the most plausible scenario for ovarian-cancer changes in terms of incidence and mortality in Catalonia by 2030, which may be of interest from a public health perspective for policy implementation.

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). The BC cohort presented a significantly higher risk of death due to endometrial and ovarian cancers than the general population. In Stage I, HR- patients showed a 1.72-fold higher probability of all-cause death and a 6.11-fold higher probability of breast cancer death than HR+ patients. In Stages II-III, the probability of CVD death (range 3.11% to 3.86%) surpassed that of other cancers (range 0.54% to 3.11%). In Stage IV patients, the probability of death from any cancer drove the mortality risk. Promoting screening and preventive measures in BC patients are warranted, since long-term control should encompass early detection of second neoplasms, ruling out the possibility of late recurrence. In patients diagnosed in Stages II-III at an older age, surveillance for preventing late cardiotoxicity is crucial.

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. In this study, we assessed the performance of a Poisson modeling approach for estimating rare cancer incidence rates, oscillating around an overall European average and using small-count data in different scenarios/computational platforms. First, we compared the performance of frequentist, empirical Bayes, and Bayesian approaches for providing 95% confidence/credible intervals for the expected rates in each country. Second, we carried out an empirical study using 190 rare cancers to assess different lower/upper bounds of a uniform prior distribution for the standard deviation of the random effects. For obtaining a reliable measure of variability for country-specific incidence rates, our results suggest the suitability of using 1 as the lower bound for that prior distribution and selecting the random-effects model through an averaged indicator derived from 2 Bayesian model selection criteria: the deviance information criterion and the Watanabe-Akaike information criterion.

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. Bayesian autoregressive age-period-cohort models were employed to predict incidence and mortality rates for 2015-2030. The incidence of endometrial cancer for women younger than 65 years was predicted to be lower in 2030 than in 2010, whereas it was predicted to be higher for women aged 65-74 years. Moreover, mortality rates for women aged ≥65 in 2030 are likely to exceed the rates in 2010. Five-year relative survival for all ages was slightly higher in the period 2005-2009 (79.3 %, 95 %CI: 75.8 %-82.9 %) compared with those in 1995-1999 (76.0 %, 95 %CI: 72.1 %-80.2 %). This plausible new scenario might be useful to plan new clinical and preventive strategies in the near future.

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). For the Missing Data Problem we assessed two scenarios: missing completely at random (MCAR) and missing not at random (MNAR). Two validated BC datasets provided by the cancer registries of Girona and Tarragona (northeastern Spain) were used. RESULTS: In both MCAR and MNAR scenarios all models showed poorer prediction performance compared to three GM models: the saturated one (GM.SAT) and two with penalty factors on the partial likelihood (GM.K1 and GM.TEST). However, GM.SAT predictions could lead to non-reliable conclusions in BC survival analysis. Simulation of a "synthetic" dataset derived from GM.SAT could be the worst strategy, but the use of the remaining GMs models could be better than oversampling. CONCLUSION: Our results suggest the use of the GM-procedure presented for one-variable imputation/prediction of missing data and for simulating "synthetic" BC survival datasets. The "synthetic" datasets derived from GMs could be also used in clinical applications of cancer survival data such as predictive risk analysis.

Exceso de mortalidad en las pacientes con cáncer de mama en estadios precoces en Tarragona y Gerona (España) / Excess mortality among breast cancer patients in early stages in Tarragona and Gerona (Spain)

OBJETIVO: Analizar la supervivencia poblacional del cáncer de mama (CM) en estadios precoces, estimando la tendencia temporal del exceso de mortalidad (EM) a largo plazo en periodos anuales y quinquenales, y determinando, si es posible, una proporción de pacientes que puedan considerarse curadas. MÉTODO: Se incluyó la cohorte de pacientes diagnosticadas de CM en estadios I y II antes de los 60 años de edad en Gerona y Tarragona (N = 2453). Se calcularon la supervivencia observada (SO) y la supervivencia relativa (SR) al CM hasta los 20 años de seguimiento. Para valorar el EM se estimó la SR a intervalos anuales (SRI) y quinquenales (SR5). Los resultados se presentan por grupos de edad (≤49 y 50-59), estadio (I/II) y periodo de diagnóstico (1985-1994 y 1995-2004). RESULTADOS: En el estadio I, la SO y la SR fueron mayores en 1995-2004 que en 1985-1994: 3,5% a los 15 años de seguimiento y 4,5% a los 20 años. La SO superó el 80% en el estadio I y se mantuvo inferior al 70% en el estadio II. Sin embargo, el EM a largo plazo no desapareció (SRI <1) independientemente del grupo de edad, el estadio y el periodo de diagnóstico. A los 15 años de seguimiento, el EM a 5 años osciló entre el 1-5% en el estadio I (SR5 ≥0,95) y el 5-10% en el estadio II. CONCLUSIONES: En nuestra cohorte, a los 15 años de seguimiento se detectó que el EM anual no desapareció y el quinquenal fue del 1-10%. Por ello, no se pudo determinar una proporción de curación del CM durante el periodo de estudio

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. RS was also estimated at annual (RSI) and in five-year intervals (RS5) to graphically assess the EM. The results are presented by age groups (≤49 and 50-59), stage (I/II) and diagnostic period (1985-1994 and 1995-2004). RESULTS: In stage I, OS and RS were higher during 1995-2004 compared to 1985-1994: 3.5% at 15 years of follow-up and 4.5% at 20-years of follow-up. In 1995-2004, the OS surpassed 80% in stage I patients whereas in stage II it remained below 70%. During 1995-2004, the long-term EM did not level off towards 0 (RSI <1) independently of age group, stage and period of diagnosis. After 15 years of follow-up, the 5-year EM oscillated between 1 and 5% in stage I (RS5 ≥0.95) and between 5 and 10% in stage II. CONCLUSIONS: In our cohort, after 15 years of follow-up, it was detected that the annual EM did not disappear and the five-year EM remained between 1 and 10%. Therefore, it was not possible to determine a cure rate of BC during the study period

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. Relative survival and Cox and parametric regression models were used to assess changes in survival. RESULTS: The lung cancer 5-year survival probability decreased with increasing stage, from 50-65% in patients with stage I disease to 2-3% in those with stage IV disease. Comparing patients diagnosed from 2011-2014 and 2003-2006, we found that survival improved: (a) the risk of death (hazard ratio) in 2003-2006 was 1.66 for stage I, 1.51 for stage II, 1.21 for stage III, and 1.10 for stage IV; (b) the 5-year relative survival increased from 11.0% to 17.8% in the period 2011-2014; and (c) the years of life lost decreased significantly from 2003-2006 to 2011-2014, varying between 6.16 (stage I) and 16.21 (stage IV). CONCLUSIONS: Survival from lung cancer by stage in the Basque Country has lengthened significantly across all disease stages. Nonetheless, since we estimated that lung cancer patients still have significantly lower mean survival times than the general population, there is a need for more research to improve these outcomes.

[Excess mortality among breast cancer patients in early stages in Tarragona and Gerona (Spain)]. / Exceso de mortalidad en las pacientes con cáncer de mama en estadios precoces en Tarragona y Gerona (España).

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. RS was also estimated at annual (RSI) and in five-year intervals (RS5) to graphically assess the EM. The results are presented by age groups (≤49 and 50-59), stage (I/II) and diagnostic period (1985-1994 and 1995-2004). RESULTS: In stage I, OS and RS were higher during 1995-2004 compared to 1985-1994: 3.5% at 15 years of follow-up and 4.5% at 20-years of follow-up. In 1995-2004, the OS surpassed 80% in stage I patients whereas in stage II it remained below 70%. During 1995-2004, the long-term EM did not level off towards 0 (RSI <1) independently of age group, stage and period of diagnosis. After 15 years of follow-up, the 5-year EM oscillated between 1 and 5% in stage I (RS5 ≥0.95) and between 5 and 10% in stage II. CONCLUSIONS: In our cohort, after 15 years of follow-up, it was detected that the annual EM did not disappear and the five-year EM remained between 1 and 10%. Therefore, it was not possible to determine a cure rate of BC during the study period.

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. Faecal immunological haemoglobin test (3 samples; positive> 4 µg Hb/g), and a survey to register clinical variables of interest were performed. Colorectal cancer and advanced adenoma were considered as advanced colonic neoplasia. A sample size of 600 and 500 individuals were calculated for each phase 1 and phase 2 of the study, respectively (Phase 1, derivation and Phase 2, validation cohort). A Bayesian logistic regression analysis was used to derive a predictive score. RESULTS: 1495 patients were included. Age (OR, 21), maximum faecal-Hb value (OR, 2.3), and number of positive samples (OR, 28) presented the highest ORs predictive of advanced colonic neoplasia. The additional significant predictive variables adjusted for age and faecal-Hb variables in Phase 1 were previous colonoscopy (last 5 years) and smoking (no, ex/active). With these variables a predictive score of advanced colonic neoplasia was derived. Applied to Phase 2, patients with a Score > 20 had an advanced colonic neoplasia probability of 66% (colorectal cancer, 32%), while those with a Score ≤ 10, a probability of 10% (colorectal cancer, 1%). Prioritizing patients with Score > 10, 49.4% of patients would be referred for fast-track colonoscopy, diagnosing 98.3% of colorectal cancers and 77% of advanced adenomas. CONCLUSIONS: A scoring system was derived and validated to prioritize fast-track colonoscopies according to risk, which was efficient, simple, and robust.

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. After a mean of 18 years of follow-up, 3,561 deaths were recorded, of which 1,694 were from cancer, 761 from CVD, and 870 from other causes. Data on egg consumption was collected using a validated diet history at recruitment. Cox proportional hazards models, adjusted for confounders, were used in the analyses. RESULTS: The mean (standard deviation) egg consumption was 22.0 g/day (15.8) and 30.9 g/day (23.1) in women and men, respectively. No association was observed between egg consumption and all-cause mortality for the highest vs the lowest quartile (HR 1.01; 95% CI 0.91-1.11; P trend = 0.96). Likewise, no association was observed with cancer and cardiovascular diseases mortality. However, an inverse association was found between egg consumption and deaths for other causes (HR 0.76; 95% CI 0.63-0.93; P trend = 0.003), particularly for deaths from the nervous system (HR 0.59; 95% CI 0.35-1.00; P trend = 0.036). No interaction was detected with the adherence to Mediterranean diet. CONCLUSIONS: This study shows no association between moderate egg consumption, up to 1 egg per day, and main causes of mortality in a large free-living Mediterranean population.

WebSurvCa: estimación vía web de las probabilidades de fallecimiento y de supervivencia de una cohorte / WebSurvCa: web-based estimation of death and survival probabilities in a cohort

La supervivencia relativa se ha utilizado habitualmente como medida de la evolución temporal del exceso de riesgo de mortalidad en cohortes de pacientes diagnosticados de cáncer, teniendo en cuenta la mortalidad de una población de referencia. Una vez estimado el exceso de riesgo de mortalidad pueden calcularse tres probabilidades acumuladas a un tiempo T: 1) la probabilidad de fallecer asociada a la causa de diagnóstico inicial (enfermedad en estudio), 2) la probabilidad de fallecer asociada a otras causas, y 3) la probabilidad de supervivencia absoluta en la cohorte a un tiempo T. Este trabajo presenta la aplicación WebSurvCa (https://shiny.snpstats.net/WebSurvCa/), mediante la cual los registros de cáncer de base hospitalaria y poblacional, y los registros de otras enfermedades, estiman dichas probabilidades en sus cohortes seleccionando como población de referencia la mortalidad de la comunidad autónoma que consideren

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.snpstats.net/WebSurvCa/), whereby hospital-based and population-based cancer registries and registries of other diseases can estimate such probabilities in their cohorts by selecting the mortality of the relevant region (reference population)

Sentinel Amenable Mortality: 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. We introduce a new approach by identifying a subgroup of causes for which there are available treatments with a high level of efficacy. These causes should be considered sentinel events to help identify limitations in the effectiveness and quality of health provision. METHODS: We conducted an extensive literature review using a list of amenable causes of death compiled by Spanish researchers. We complemented this approach by assessing the time trends of amenable mortality in two high-income countries that have a similar quality of healthcare but very different systems of provision, namely, Spain and the United States. This enabled us to identify different levels of efficacy of medical interventions (high, medium, and low). We consulted a group of medical experts and combined this information to help make the final classification of sentinel amenable causes of death. RESULTS: Sentinel amenable mortality includes causes such as surgical conditions, thyroid diseases, and asthma. The remaining amenable causes of death either have a higher complexity in terms of the disease or need more effective medical interventions or preventative measures to guarantee early detection and adherence to treatment. These included cardiovascular diseases, diabetes, hypertension, all amenable cancers, and some infectious diseases such as pneumonia, influenza, and tuberculosis. CONCLUSIONS: Sentinel amenable mortality could act as a good sentinel indicator to identify major deficiencies in healthcare quality and provision and detect inequalities across populations.

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. Cancer mortality data were obtained from the WHO Mortality Database. Age-standardized mortality rates (ASMR), per 100,000, were calculated (direct method) for 2008 to 2014 and projected for the years 2015, 2020, 2025, and 2030 using a Bayesian log-linear Poisson model. In 52 countries studied around the world, between 2015 and 2030, the median ASMR are projected to increase for lung cancer, from 11.2 to 16.0, whereas declines are expected for breast cancer, from 16.1 to 14.7. In the same period, the ASMR will decrease in 36 countries for breast cancer and in 15 countries for lung cancer. In half of the countries analyzed, and in nearly three quarters of those classified as high-income countries, the ASMR for lung cancer has already surpassed or will surpass the breast cancer ASMR before 2030. The mortality for lung and breast cancer is higher in high-income countries than in middle-income countries; lung cancer mortality is lower in the latter because the tobacco epidemic is not yet widespread. Due to these observed characteristics of lung cancer, primary prevention should still be a key factor to decrease lung cancer mortality.Significance: The mortality for lung and breast cancer is projected to be higher in high-income countries than in middle-income countries, where lung cancer mortality is expected to surpass breast cancer mortality before 2030. Cancer Res; 78(15); 4436-42. ©2018 AACR.

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. We considered European incidence rates (IRs), calculated over all the data available in RARECAREnet, as a valid a priori to merge with country-specific observed data. Therefore we provided (1) Bayesian estimates of IRs and the yearly numbers of cases of rare cancers in each country; (2) the expected time (T) in years needed to observe one new case; and (3) practical criteria to decide when to use the Bayesian approach. RESULTS: Bayesian and classical estimates did not differ much; substantial differences (>10%) ranged from 77 rare cancers in Iceland to 14 in England. The smaller the population the larger the number of rare cancers needing a Bayesian approach. Bayesian estimates were useful for cancers with fewer than 150 observed cases in a country during the study period; this occurred mostly when the population of the country is small. CONCLUSION: For the first time the Bayesian estimates of IRs and the yearly expected numbers of cases for each rare cancer in each individual European country were calculated. Moreover, the indicator T is useful to convey incidence estimates for exceptionally rare cancers and in small countries; it far exceeds the professional lifespan of a medical doctor.

[WebSurvCa: web-based estimation of death and survival probabilities in a cohort]. / WebSurvCa: estimación vía web de las probabilidades de fallecimiento y de supervivencia de una cohorte.

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.snpstats.net/WebSurvCa/), whereby hospital-based and population-based cancer registries and registries of other diseases can estimate such probabilities in their cohorts by selecting the mortality of the relevant region (reference population).

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. The prevalence were projected for the period 2012-2025 using a Bayesian logistic binomial model and estimated the probability to achieve the 30% relative reduction endorsed by the WHO. We calculated the 95% credible interval (CrI) of the posterior distribution, which includes a 95% of the distribution of potential smoking prevalences. Results: In men, the projections show a decline for crude (-2.64% annually, 95% CrI: -3.32; -1.97) and adjusted (-2.50%, 95% CrI:-3.14; -1.87) prevalence. In women, the projections show a decline for crude prevalence (-0.36%, 95% CrI: -1.02; -0.30)) and the age-adjusted prevalence (-1.02%, 95% CrI: -1.61, -0.47). By age groups, the decline is greater among women aged 15-39 years (-3.92%, 95% CrI: -4.92; -2.96)) while for women aged 40-64 years an increase (1.84%, 95% CrI: 1.06; 2.58) is expected. In men, the probability to achieve the WHO target is 0.728 and in women is less than 0.001. The age group 15-39 shows the highest probability to achieve the target. Conclusions: The results suggest smoking prevalence will decrease during 2012-2025 in all age groups for both sexes except for women aged 40-64. We found that the WHO target of a 30% reduction in prevalence is likely to be achieved overall and in the 15-39 years age groups for both sexes, but not achieved for older women and it is uncertain whether it will be achieved for older men. These results highlight the need to strengthen public health interventions that focus on reducing tobacco use in adult women aged 40-64 years old. Implications: We project a decrease in smoking prevalence in during 2012-2025 except for women aged 40-64. The WHO Target of a 30% relative reduction could be achieved in the population aged 15-39; but not in women and the results are inconclusive in men. These results highlight the need to strengthen public health interventions that focus on reducing tobacco use in adult women aged 40-64 years old.