Sarcoma risk and dioxin emissions from incinerators and industrial plants: a population-based case-control study (Italy)

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Assessment of the INLA approach on gerarchic bayesian models for the spatial disease distribution: a real data application

The use of approximate methods as the INLA (Integrated Nested Laplace Approximation) approach is being widely used in Bayesian inference, especially in spatial risk model estimation where the Besag-York-Mollie (BYM) model ` has found a proper use. INLA appears time saving compared to Monte Carlo simulations based on Markov Chains (MCMC), but it produces some differences in estimates [1, 2]. Data from the Veneto Cancer Registry has been considered with the scope to compare cancer incidence estimates with INLA method and with two other procedures based on MCMC simulation, WinBUGS and CARBayes, under R environment. It is noteworthy that INLA returns estimates comparable to both MCMC procedures, but it appears sensitive to the a-priori distribution. INLA is fast and efficient in particular with samples of moderate-high size. However, care must to be paid to the choice of the parameter relating to the a-priori distribution

Renin-Angiotensin-Aldosterone System Inhibitors and Risk of Death in Patients Hospitalised with COVID-19: A Retrospective Italian Cohort Study of 43,000 Patients

Introduction The epidemic due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been spreading globally, raising increasing concerns. There are several controversial hypotheses on the potentially harmful or beneficial effects of antihypertensive drugs acting on the renin-angiotensin-aldosterone system (RAAS) in coronavirus disease 2019 (COVID-19). Furthermore, there is accumulating evidence, based on several observational studies, that angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) do not increase the risk of contracting SARS-CoV-2 infection. On the other hand, conflicting findings regarding the role of ACEIs/ARBs as prognosis modifiers in COVID-19 hospitalised patients have been reported. Objective The aim of this large-scale, retrospective cohort study was to investigate whether prior exposure to ACEIs and/or ARBs was associated with all-cause mortality among over 40,000 hospitalised COVID-19 patients compared with calcium channel blockers (CCBs), a potential therapeutic alternative. Methods This study was conducted using COVID-19 registries linked to claims databases from Lombardy, Veneto and Reggio Emilia (overall, 25% of Italian population). Overall, 42,926 patients hospitalised between 21 February and 21 April 2020 with a diagnosis of COVID-19 confirmed by real-time polymerase chain reaction tests were included in this study. All-cause mortality occurring in or out of hospital, as reported in the COVID-19 registry, was estimated. Using Cox models, adjusted hazard ratios (HRs) of all-cause mortality (along with 95% confidence intervals [CIs]) were estimated separately for ACEIs/ARBs and other antihypertensives versus CCBs and non-use. Results Overall, 11,205 in- and out-of-hospital deaths occurred over a median of 24 days of follow-up after hospital admission due to COVID-19. Compared with CCBs, adjusted analyses showed no difference in the risk of death among ACEI (HR 0.97, 95% CI 0.89-1.06) or ARB (HR 0.98, 95% CI 0.89-1.06) users. When non-use of antihypertensives was considered as a comparator, a modest statistically significant increase in mortality risk was observed for any antihypertensive use. However, when restricting to drugs with antihypertensive indications only, these marginal increases disappeared. Sensitivity and subgroup analyses confirmed our main findings. Conclusions ACEI/ARB use is not associated with either an increased or decreased risk of all-cause mortality, compared with CCB use, in the largest cohort of hospitalised COVID-19 patients exposed to these drugs studied to date. The use of these drugs therefore does not affect the prognosis of COVID-19. This finding strengthens recommendations of international regulatory agencies about not withdrawing/switching ACEI/ARB treatments to modify COVID-19 prognosis

Assessment of the INLA approach on gerarchic bayesian models for the spatial disease distribution: a real data application

The use of approximate methods as the INLA (Integrated Nested Laplace Approximation) approach is being widely used in Bayesian inference, especially in spatial risk model estimation where the Besag-York-Molli`e (BYM) model has found a proper use. INLA appears time saving compared to Monte Carlo simulations based on Markov Chains (MCMC), but it produces some differences in estimates [1, 2]. Data from the Veneto Cancer Registry has been considered with the scope to compare cancer incidence estimates with INLA method and with two other procedures based on MCMC simulation, WinBUGS and CARBayes, under R environment. It is noteworthy that INLA returns estimates comparable to both MCMC procedures, but it appears sensitive to the a-priori distribution. INLA is fast and efficient in particular with samples of moderate-high size. However, care must to be paid to the choice of the parameter relating to the a-priori distribution

Data_Sheet_1_Thirty-two-year trends of cancer incidence by sex and cancer site in the Veneto Region from 1987 to 2019.PDF

BackgroundThis observational study considers the sex-specific incidence of the most incident cancers as recorded in the population-based Veneto Regional Cancer Registry over a period of more than 30 years (1987-2019).MethodsThe Veneto Regional Cancer Registry collected data for the time interval 1987–2019. Significant changes in incidence trends calculated on age-standardized incidence rates (Annual Percent Change—APC) were identified by join point regression analysis.ResultsOverall, the incidence trend for all cancers decreased in males and remained stable in females. In nine cancer sites, the incidence trends showed consistent differences by sex (oral cavity, esophagus, colon rectum and anus, liver, larynx, lung, cutaneous malignant melanoma, bladder, and thyroid gland). Other malignancies did not show significant sex-related differences (stomach, pancreas, biliary tract, kidney/urinary tract, central nervous system, multiple myeloma, non-Hodgkin lymphoma, and leukemia).ConclusionIn the period 1987–2019, this study revealed sex-related differences in cancer incidence trends. Over time, cancer incidence remained higher in males, with a decreasing epidemiological impact, plausibly resulting from prevention campaigns against environmental cancer risk factors, as tobacco and alcohol. Conversely, a significant decrease was not observed in the incidence trend in females. These findings contribute essential insights for profiling the epidemiological map of cancer in a large Italian population, allowing comparison with other European cancer epidemiology studies and providing updated data supporting sex-related primary and secondary cancer prevention strategies.</p

Trend by year of the emission levels of the incinerators and industrial plants (I-TEQ gr/s)

<p><b>Copyright information:</b></p><p>Taken from "Sarcoma risk and dioxin emissions from incinerators and industrial plants: a population-based case-control study (Italy)"</p><p>http://www.ehjournal.net/content/6/1/19</p><p>Environmental Health 2007;6():19-19.</p><p>Published online 16 Jul 2007</p><p>PMCID:PMC1948886.</p><p></p

The coloured areas indicate the LHUs studied; (small box: Italy, Veneto Region, province of Venice)

<p><b>Copyright information:</b></p><p>Taken from "Sarcoma risk and dioxin emissions from incinerators and industrial plants: a population-based case-control study (Italy)"</p><p>http://www.ehjournal.net/content/6/1/19</p><p>Environmental Health 2007;6():19-19.</p><p>Published online 16 Jul 2007</p><p>PMCID:PMC1948886.</p><p></p