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.

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.

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.

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.

Genotypic classification of patients with Wolfram syndrome: insights into the natural history of the disease and correlation with phenotype.

PURPOSE: Wolfram syndrome is a degenerative, recessive rare disease with an onset in childhood. It is caused by mutations in WFS1 or CISD2 genes. More than 200 different variations in WFS1 have been described in patients with Wolfram syndrome, which complicates the establishment of clear genotype-phenotype correlation. The purpose of this study was to elucidate the role of WFS1 mutations and update the natural history of the disease. METHODS: This study analyzed clinical and genetic data of 412 patients with Wolfram syndrome published in the last 15 years. RESULTS: (i) 15% of published patients do not fulfill the current -inclusion criterion; (ii) genotypic prevalence differences may exist among countries; (iii) diabetes mellitus and optic atrophy might not be the first two clinical features in some patients; (iv) mutations are nonuniformly distributed in WFS1; (v) age at onset of diabetes mellitus, hearing defects, and diabetes insipidus may depend on the patient's genotypic class; and (vi) disease progression rate might depend on genotypic class. CONCLUSION: New genotype-phenotype correlations were established, disease progression rate for the general population and for the genotypic classes has been calculated, and new diagnostic criteria have been proposed. The conclusions raised could be important for patient management and counseling as well as for the development of treatments for Wolfram syndrome.

Predicting the change in breast cancer deaths in Spain by 2019: a Bayesian approach.

BACKGROUND: Breast cancer mortality rates have been decreasing in Spain since 1992. Recent changes in demography, breast cancer therapy, and early detection of breast cancer may change this trend. METHODS: Using breast cancer mortality data from years 1990 to 2009, we sought to predict the changes in the burden of breast cancer mortality during the years 2005-2019 through a Bayesian age-period-cohort model. The net change in the number of breast cancer deaths between the periods of 2015-2019 and 2005-2009 was separated into changes in population demographics and changes in the risk of death from breast cancer. RESULTS: During the period 1990-2009, breast cancer mortality rates decreased (age-standardized rates per 100,000 women-years 50.6 in 1990-1994 vs. 41.1 in 2005-2009), whereas the number of breast cancer deaths increased (28,149 in 1990-1994; 29,926 in 2005-2009). There was a decrease in the number of cases among women 45-64 years of age (10,942 in 1990-1994; 8,647 in 2005-2009). Changes in population demographics contribute to a total increase of 12.5-12.8% comparing periods 2005-2009 versus 2015-2019, whereas changes in the risk of death from breast cancer contribute to a reduction of 12.9-13.7%. We predict a net decline of 0.1-1.2% in the absolute number of breast cancer deaths comparing these time periods. CONCLUSIONS: The decrease in the risk of death from breast cancer may exceed the projected increase in deaths from growing population size and aging in Spain. These changes may also explain the decrease in the absolute number of breast cancer deaths in Spain since 2005.

Dietary flavonoid and lignan intake and mortality in a Spanish cohort.

BACKGROUND: Dietary flavonoids and lignans may protect against several chronic diseases, but there is little evidence on the relationship between flavonoid and lignan intake and mortality. We investigated the association between both all-cause and specific-cause mortality and intake of flavonoids and lignans in the Spanish European Prospective Investigation into Cancer and Nutrition (EPIC-Spain) cohort. METHODS: The EPIC-Spain study follows 40,622 participants (38% men) aged 29-69 years. A validated diet history questionnaire was administered at recruitment. A food composition database was compiled based on US Department of Agriculture and Phenol-Explorer databases. Cox proportional hazards models, adjusted for confounders, were used in the analyses. RESULTS: During a mean follow-up of 13.6 years, 1915 deaths were reported, with 416 from cardiovascular diseases (CVDs) and 956 from cancer. After adjustment for several potential confounders, the hazard ratios (HRs) for the highest versus the lowest quintile of dietary flavanone and flavonol intakes were 0.60 (95% confidence interval = 0.38-0.94) and 0.59 (0.40-0.88). Total flavonoid intake was also associated with a decrease in all-cause mortality (0.71 [0.49-1.03]). Lignan intake was not associated with all-cause mortality. In cause-specific mortality analyses, using competing risk regressions, doubling total flavonoid intake was inversely related to mortality from CVD (HR for log2 0.87 [0.77-0.98]), but not to mortality from either cancer (HR for log2 0.96 [0.89-1.04]) or other causes (HR for log2 0.97 [0.87-1.09]). CONCLUSIONS: A diet high in flavonoids, particularly in flavanones and flavonols, is associated with a reduction in all-cause mortality, mainly of mortality from CVD.

REGSTATTOOLS: freeware statistical tools for the analysis of disease population databases used in health and social studies.

BACKGROUND: The repertoire of statistical methods dealing with the descriptive analysis of the burden of a disease has been expanded and implemented in statistical software packages during the last years. The purpose of this paper is to present a web-based tool, REGSTATTOOLShttp://regstattools.net intended to provide analysis for the burden of cancer, or other group of disease registry data. Three software applications are included in REGSTATTOOLS: SART (analysis of disease's rates and its time trends), RiskDiff (analysis of percent changes in the rates due to demographic factors and risk of developing or dying from a disease) and WAERS (relative survival analysis). RESULTS: We show a real-data application through the assessment of the burden of tobacco-related cancer incidence in two Spanish regions in the period 1995-2004. Making use of SART we show that lung cancer is the most common cancer among those cancers, with rising trends in incidence among women. We compared 2000-2004 data with that of 1995-1999 to assess percent changes in the number of cases as well as relative survival using RiskDiff and WAERS, respectively. We show that the net change increase in lung cancer cases among women was mainly attributable to an increased risk of developing lung cancer, whereas in men it is attributable to the increase in population size. Among men, lung cancer relative survival was higher in 2000-2004 than in 1995-1999, whereas it was similar among women when these time periods were compared. CONCLUSIONS: Unlike other similar applications, REGSTATTOOLS does not require local software installation and it is simple to use, fast and easy to interpret. It is a set of web-based statistical tools intended for automated calculation of population indicators that any professional in health or social sciences may require.

Bayesian approach to predicting cancer incidence for an area without cancer registration by using cancer incidence data from nearby areas.

This paper compares three different methods for performing cancer incidence prediction in an area without a cancer registry under a Bayesian framework, using linear and log-linear age-period models with either age-specific slopes or a common slope across age groups. The three methods assume that a nearby area with a cancer registration has similar incidence and mortality patterns as the area of interest without a cancer registry where the cancer incidence prediction is carried out. The three methods differ in modeling strategies: (i) modeling the incidence rate directly; (ii) modeling the ratio of the number of incident cases to that of mortality cases; and (iii) modeling the difference between the incidence rate and the mortality rate. Strategy (iii) is a new approach in this type of projection. Empirical assessment is made using real data from the cancer registry of Tarragona, Spain, to predict cancer incidence in Girona, Spain, and vice versa. Predictions of short-term (3-4 years) incidence were made for 2001 in Tarragona using observed cancer incidence and mortality data for 1994-1998 from Girona. Short-term predictions were made for 2002 in Girona using Tarragona's 1994-1998 data. Additionally, long-term (10 years) incidence rate predictions were made for 2002 in Girona using data from Tarragona for the period 1985-1992. Our results suggest that extrapolating time-trends of incidence rates minus mortality rates may have the best predictive performance overall. These methods of population-level disease-incidence prediction are highly relevant to health care planning and policy decisions.

Occupational health impact of the 2009 H1N1 flu pandemic: surveillance of sickness absence.

OBJECTIVES: Workplace absences due to illness can disrupt usual operations and increase costs for businesses. This study of sickness absence due to influenza and influenza-related illness presents a unique opportunity to characterise and measure the impact of the 2009 (H1N1) pandemic, by comparing trends during the pandemic to those of previous years, and adding this information to that obtained by traditional epidemiological surveillance systems. METHODS: We compared the numbers of cases of sickness absence due to illness caused by influenza and influenza-related illness in 2007-2009, and in the first 3 months of 2010 in Catalonia (n=811 940) using a time series approach. Trends were examined by economic activity, age and gender. The weekly endemic-epidemic index (EEI) was calculated and its 95% CI obtained with the delta method, with observed and expected cases considered as independent random variables. RESULTS: Influenza activity peaked earlier in 2009 and yielded more cases than in previous years. Week 46 (in November 2009) had the highest number of new cases resulting in sickness absence (EEI 20.99; 95% CI 9.44 to 46.69). Women and the 'education, health and other social activities' sector were the most affected. CONCLUSIONS: Results indicate that the new H1N1 pandemic had a significant impact on business, with shifts in the timing of peak incidence, a doubling in the number of cases, and changes in the distribution of cases by economic activity sector and gender. Traditional epidemiological surveillance systems could benefit from the addition of information based on sickness absence data.

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.

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.

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.

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.

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.

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.