Opposite trends in the consumption of manufactured and roll-your-own cigarettes in Spain (1991–2020)

Objective: The aim of this study is to describe trends in the consumption of manufactured and roll-your-own cigarettes between 1991 and 2012 in Spain, and to project these trends up to 2020. Methods: We estimated daily consumption per capita during 1991–2012 using data on sales of manufactured cigarettes (20-packs) and rolling tobacco (kg) from the Tobacco Market Commission, and using data of the Spanish adult population from the National Statistics Institute. We considered different weights (0.5, 0.8 and 1 g) to compute the number of rolled cigarettes per capita. We computed the annual per cent of change and assessed possible changes in trends using joinpoint regression, and projected the consumption up to 2020 using Bayesian methods. Results: Daily consumption per capita of manufactured cigarettes decreased on average by 3.0% per year in 1991–2012, from 7.6 to 3.8 units, with three trend changes. However, daily consumption per capita of roll-your-own cigarettes increased on average by 14.1% per year, from 0.07 to 0.92 units of 0.5 g, with unchanged trends. Together, daily consumption per capita decreased between 2.9% and 2.5%, depending on the weight of the roll-your-own cigarettes. Projections up to 2020 indicate a decrease of manufactured cigarettes (1.75 units per capita) but an increase of roll-your-own cigarettes (1.25 units per capita). Conclusions: While the consumption per capita of manufactured cigarettes has decreased in the past years in Spain, the consumption of roll-your-own cigarettes has increased at an annual rate around 14% over the past years. Whereas a net decrease in cigarette consumption is expected in the future, use of roll-your-own cigarettes will continue to increase

Monitoring the decreasing trend of testicular cancer mortality in Spain during 2005-2019 through a Bayesian approach

Purpose : To assess time trends of testicular cancer (TC) mortality in Spain for period 1985-2019 for age groups 15-74 years old through a Bayesian age-period-cohort (APC) analysis. Methods: A Bayesian age-drift model has been fitted to describe trends. Projections for 2005-2019 have been calculated by means of an autoregressive APC model. Prior precision for these parameters has been selected through evaluation of an adaptive precision parameter and 95% credible intervals (95% CRI) have been obtained for each model parameter. Results: A decrease of -2.41% (95% CRI: -3.65%; -1.13%) per year has been found for TC mortality rates in age groups 15-74 during 1985-2004, whereas mortality showed a lower annual decrease when data was restricted to age groups 15-54 (-1.18%; 95% CRI: -2.60%; -0.31%). During 2005-2019 is expected a decrease of TC mortality of 2.30% per year for men younger than 35, whereas a leveling off for TC mortality rates is expected for men older than 35. Conclusions: A Bayesian approach should be recommended to describe and project time trends for those diseases with low number of cases. Through this model it has been assessed that management of TC and advances in therapy led to decreasing trend of TC mortality during the period 1985-2004, whereas a leveling off for these trends can be considered during 2005-2019 among men older than 35

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, REGSTATTOOLS http://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

Assessing predicted age-specific breast cancer mortality rates in 27 Europea 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. Second, making use of the base period 2006-2012, we predicted BC mortality rates by 2020. Finally, making use of the SMRs and the predicted data, we identified a clustering of countries, assessing differences in the time trends between the areas defined in this clustering. Results: The clustering approach identified two clusters of countries: the first cluster were countries where BC predicted mortality rates, in 2020, might slightly increase among women aged 69 and older compared with 2010 [Greece (SMR 1.01), Croatia (SMR 1.02), Latvia (SMR 1.15), Poland (SMR 1.14), Estonia (SMR 1.16), Bulgaria (SMR 1.13), Lithuania (SMR 1.03), Romania (SMR 1.13) and Slovakia (SMR 1.06)]. The second cluster was those countries where BC mortality rates level off or decrease in all age groups (remaining countries). However, BC mortality rates between these clusters might diminish and converge to similar figures by 2020. Conclusions: For the year 2020, our predictions have shown a converging pattern of BC mortality rates between European regions. Reducing disparities, in access to screening and treatment, could have a substantial effect in countries where a non-decreasing trend in age-specific BC mortality rates has been predicted

Five years survival of women diagnosed with breast cancer during the period 1997-1999 in Toledo-Centro and Mancha Area, Spain

Fundamentos: el cáncer de mama representa la primera causa de mortalidad prematura en las mujeres de la provincia de Toledo. El objetivo es conocer el estadío al diagnóstico para cada grupo de edad y la supervivencia relativa (SR) del cáncer de mama a los 5 años, en el Área de Toledo-Centro y Mancha de los tumores diagnosticados durante 1997-1999. Métodos: se utilizó la información del Registro Poblacional de Cáncer de Toledo. Se incluyó a 366 mujeres con tumores clasificados por estadio y grupo de edad (en función de su inclusión en el programa de detección precoz de cáncer de mama, 64). La SR e intervalo de confianza al 95% (IC) fueron calculados mediante el método de Hakulinen utilizando la aplicación WAERS. Resultados: la SR global fue 78,4% (IC: 73,6-83,6), siendo 93,3% (IC: 87,0-99,4) en 64 años. La SR fue 99,3% (IC: 94,4-104,5) para tumores localizados; 81,9% (IC: 74,0-90,8) para tumores con afectación ganglionar; y 20,1% (IC: 9,7-41,6) para tumores con metástasis. Al diagnóstico, el 52,3% de los tumores en 64 años presentaba metástasis. Conclusiones: la SR es similar a la media del estudio EUROCARE-4. Estos resultados son un punto de partida para valorar, mediante el seguimiento de estos indicadores, el impacto de las actividades de detección precoz y terapéuticas en la SR del cáncer de mama en nuestra área

Estimating country-specific incidence rates of rare cancers: comparative perfomance 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

Opposite trends in the consumption of manufactured and roll-your-own cigarettes in Spain (1991-2020)

Objective: the aim of this study is to describe trends in the consumption of manufactured and roll-your-own cigarettes between 1991 and 2012 in Spain, and to project these trends up to 2020. Methods: we estimated daily consumption per capita during 1991-2012 using data on sales of manufactured cigarettes (20-packs) and rolling tobacco (kg) from the Tobacco Market Commission, and using data of the Spanish adult population from the National Statistics Institute. We considered different weights (0.5, 0.8 and 1 g) to compute the number of rolled cigarettes per capita. We computed the annual per cent of change and assessed possible changes in trends using joinpoint regression, and projected the consumption up to 2020 using Bayesian methods. Results: daily consumption per capita of manufactured cigarettes decreased on average by 3.0% per year in 1991-2012, from 7.6 to 3.8 units, with three trend changes. However, daily consumption per capita of roll-your-own cigarettes increased on average by 14.1% per year, from 0.07 to 0.92 units of 0.5 g, with unchanged trends. Together, daily consumption per capita decreased between 2.9% and 2.5%, depending on the weight of the roll-your-own cigarettes. Projections up to 2020 indicate a decrease of manufactured cigarettes (1.75 units per capita) but an increase of roll-your-own cigarettes (1.25 units per capita). Conclusions: while the consumption per capita of manufactured cigarettes has decreased in the past years in Spain, the consumption of roll-your-own cigarettes has increased at an annual rate around 14% over the past years. Whereas a net decrease in cigarette consumption is expected in the future, use of roll-your-own cigarettes will continue to increase

Cálculo automatizado de la supervivencia relativa vía web. El proyecto WAERS del Instituto Catalán de Oncología

The most commonly used measure to estimate cancer survival is relative survival, defined as the ratio between observed and expected survival. Expected survival is computed on the basis of the mortality of a reference population. Mortality tables for the general population are not always available and their calculation requires specific software. For that purpose, the Catalan Institute of Oncology developed WAERS (Web-Assisted Estimation of Relative Survival), a web-based application that estimates the relative survival for a cohort of patients. The user prepares data in a specific format and sends them to a remote server located at the Catalan Institute of Oncology. This server computes relative survival and returns a file with the results to the electronic address supplied by the user. By means of this application, hospital- and population-based Spanish cancer registries and registries of other diseases can estimate relative survival of their cohorts using their reference population (province or autonomous community). This application could also be useful for cohort mortality studies

Automatización de un registro hospitalario de tumores

La medida utilizada habitualmente para estimar la supervivencia del cáncer es la supervivencia relativa, definida como el cociente entre la supervivencia observada y la esperada. La supervivencia esperada se calcula a partir de la mortalidad de una población de referencia. La disponibilidad y la preparación de tablas de mortalidad de la población general no es siempre posible y requiere software específico para su cálculo. A tal efecto, el Instituto Catalán de Oncología (ICO) ha desarrollado la aplicación WAERS, una aplicación web que proporciona la estimación de la supervivencia relativa para una cohorte de pacientes. El usuario debe preparar los datos en un formato específico y enviarlos a un servidor remoto que se encuentra en el ICO. Este servidor calcula la supervivencia relativa y devuelve los resultados en un fichero a una dirección que ha indicado el usuario. Mediante esta aplicación, los registros de cáncer de base hospitalaria y poblacional y los registros de otras enfermedades pueden estimar la supervivencia relativa de sus cohortes seleccionando a la población de referencia que consideren (provincia o comunidad autónoma). También puede ser útil para estudios de mortalidad en cohortes

Microsurgery influences breast reconstruction and its timing in patients with breast cancer: A population-based multilevel analysis

Background: The number of post-mastectomy breast reconstructions performed in patients with breast cancer varies widely. This study aimed to assess geographic and temporal variability and associated factors from 2018 to 2020, including the effect of the COVID-19 pandemic. Methods: This population-based cohort study was conducted in women who underwent mastectomy for invasive breast cancer from 2018 to 2020 in the Catalan public healthcare system, with follow-up until November 2022. Data were drawn from the Catalan hospital discharge registry. Random-effects logistic regression was performed to identify individual, temporal, and center-based variables influencing breast reconstruction and to assess the associations with immediate versus delayed reconstruction. Results: Among the 4315 included patients, 2173 (50.4%) underwent breast reconstruction (range by center 0% to 79%); 1750 (80.5%) surgeries were immediate and 423 (19.5%) were delayed. Significant, negative associations were older age, heart disease, kidney disease, and metastasis. Microsurgery and the R2 health region showed positive associations (odds ratio [OR] 4.67, 95% credible intervals [CrI] 1.73-13.63). Surgeries were immediate in 0% to 99% of the cases, according to center. Age was unrelated; however, microsurgery (OR 7.15, 95% CrI 1.92-29.34) and belonging to health region R5 (OR 47.88, 95% CrI 1.67-99.0) were related. Compared to 2018, rates of reconstructive surgery were similar to those in 2019 (OR 0.98, 95% CrI 0.81-1.18) and 2020 (OR 0.94, 95% CrI 0.77-1.14), whereas immediate reconstruction was more common (2019: OR 1.72, 95% CrI 1.30-2.27; 2020: OR 4.85, 95% CrI 3.44-6.84). Conclusions: Age, comorbidities, and microsurgery help explain between-center variability in breast reconstruction, while its timing appeared to be influenced by microsurgery alone. The pandemic may have accelerated the trend toward immediate surgery