A compartmental model for smoking dynamics in Italy: a pipeline for inference, validation, and forecasting under hypothetical scenarios

We propose a compartmental model for investigating smoking dynamics in an Italian region (Tuscany). Calibrating the model on local data from 1993 to 2019, we estimate the probabilities of starting and quitting smoking and the probability of smoking relapse. Then, we forecast the evolution of smoking prevalence until 2043 and assess the impact on mortality in terms of attributable deaths. We introduce elements of novelty with respect to previous studies in this field, including a formal definition of the equations governing the model dynamics and a flexible modelling of smoking probabilities based on cubic regression splines. We estimate model parameters by defining a two-step procedure and quantify the sampling variability via a parametric bootstrap. We propose the implementation of cross-validation on a rolling basis and variance-based Global Sensitivity Analysis to check the robustness of the results and support our findings. Our results suggest a decrease in smoking prevalence among males and stability among females, over the next two decades. We estimate that, in 2023, 18% of deaths among males and 8% among females are due to smoking. We test the use of the model in assessing the impact on smoking prevalence and mortality of different tobacco control policies, including the tobacco-free generation ban recently introduced in New Zealand

Bayesian probabilistic sensitivity analysis of Markov models for natural history of a disease: an application for cervical cancer

Background: parameter uncertainty in the Markov model’s description of a disease course was addressed. Probabilistic sensitivity analysis (PSA) is now considered the only tool that properly permits parameter uncertainty’s examination. This consists in sampling values from the parameter’s probability distributions. Methods: Markov models fitted with microsimulation were considered and methods for carrying out a PSA on transition probabilities were studied. Two Bayesian solutions were developed: for each row of the modeled transition matrix the prior distribution was assumed as a product of Beta or a Dirichlet. The two solutions differ in the source of information: several different sources for each transition in the Beta approach and a single source for each transition from a given health state in the Dirichlet. The two methods were applied to a simple cervical cancer’s model. Results : differences between posterior estimates from the two methods were negligible. Results showed that the prior variability highly influence the posterior distribution. Conclusions: the novelty of this work is the Bayesian approach that integrates the two distributions with a product of Binomial distributions likelihood. Such methods could be also applied to cohort data and their application to more complex models could be useful and unique in the cervical cancer context, as well as in other disease modeling

Comparison of multi-state Markov models for cancer progression with different procedures for parameters estimation. An application to breast cancer

Background: the knowledge of sojourn time (the duration of the preclinical screen-detectable period) and screening test sensitivity is crucial for understanding the disease progression and the effectiveness of screening programmes. For this purpose a model of the natural history of the disease is needed. The aim of this work is to provide an illustration of the application of multistate Markov models for breast cancer progression to the data of the Florentine screening programme, in order to estimate the sojourn time and sensitivity for breast cancer screening. Methods: three different multi-state Markov models of increasing complexity were used with three different estimation procedures based on non-linear least squares, maximum likelihood, and on a Bayesian approach. All the models produced estimates for screening sensitivity and mean sojourn time. The data used in our application seem to lead to a non-identifiability problem, since the estimation procedures for both the Maximum Likelihood and Non-Linear Least Squares gave estimates that changed with the parameters’ initial values or difficultly converged. In order to take this problem into account we used the Bayesian Approach by incorporating prior information on all the parameters. Results: the mean sojourn time varied between 2-7 years and 3-5 years for women aged 50-59 and 60-69, respectively. When the model complexity was increased a higher variability in estimates was observed among the estimation procedures. The results of the screening sensitivity estimates were highly variable, both among estimation techniques and models - varying between 63% and 100%, and between 77% and 100% for women aged 50-59 and 60-69, respectively. Conclusions: results are in accord with the literature; those obtained through the Bayesian Approach seem to be more reliable.&nbsp

The confidence in the results of physiotherapy systematic reviews in the musculoskeletal field is not increasing over time: a meta-epidemiological study using AMSTAR 2 tool

Objectives: To assess the confidence in the results of systematic reviews on the effectiveness of physiotherapy for musculoskeletal conditions in the past ten years and to analyze trends and factors associated. Design: This is a meta-epidemiological study on systematic reviews with meta-analysis (SRs) of randomized controlled trials (RCT). Methods: MEDLINE, Cochrane Database of Systematic Reviews, CINAHL, and PEDro were searched for SRs of RCT on physiotherapy interventions for musculoskeletal disorders from December 2012 to December 2022. Two researchers independently screened the records based on the inclusion criteria; a random sample of 100 studies was selected, and each journal, author, and study variable was extracted. The methodological quality of SRs was independently assessed with the AMSTAR 2 tool. Any disagreement was solved by consensus. Results: The confidence in SRs results was critically low in 90% of the studies, and it did not increase over time. Cochrane reviews are predominantly represented in the higher AMSTAR 2 confidence levels, with a statistically significant difference compared to non-Cochrane reviews. The last author's H-index is the only predictor of higher confidence among the variables analyzed (OR 1.04; 95% CI 1.01 - 1.06). Conclusion: The confidence in SRs results is unacceptably low. Given the relevance of musculoskeletal disorders and the impact of evidence synthesis on the clinical decision-making process, there is an urgent need to improve the quality of secondary research by adopting more rigorous methods

Life gain in Italian smokers who quit

This study aims to estimate the number of life years gained with quitting smoking in Italian smokers of both sexes, by number of cigarettes smoked per day (cig/day) and age at cessation. All-cause mortality tables by age, sex and smoking status were computed, based on Italian smoking data, and the survival curves of former and current smokers were compared. The more cig/day a man/woman smokes, and the younger his/her age of quitting smoking, the more years of life he/she gains with cessation. In fact, cessation at age 30, 40, 50, or 60 years gained, respectively, about 7, 7, 6, or 5, and 5, 5, 4, or 3 years of life, respectively, for men and women that smoked 10-19 cig/day. The gain in life years was higher for heavy smokers (9 years for >20 cig/day) and lower for light smokers (4 years for 1-9 cig/day). Consistently with prospective studies conducted worldwide, quitting smoking increases life expectancy regardless of age, gender and number of cig/day. The estimates of the number of years of life that could be gained by quitting smoking, when computed specifically for a single smoker, could be used by physicians and health professionals to promote a quit attempt. © 2014 by the authors; licensee MDPI, Basel, Switzerland

Italians are still loyal to traditional cigarettes, despite novel tobacco products

Introduction: Over the last few decades in Italy we observed a substantial reduction in conventional tobacco cigarette consumption, the introduction of electronic cigarettes (e-cigarette) in 2010, and the launch of heated tobacco products (HTP) in 2015. Methods: We investigated novel products, i.e., e-cigarettes and HTP, use in Italy in 2018-2020 using data from the cross-sectional annual PASSI survey conducted in representative samples of adults aged 18-69 (overall n=79,529). We compared characteristics of conventional cigarette smokers with those of novel product users. Results: A stall in e-cigarette use at around 2.5% and a three-fold increase in HTP use from 0.5% in 2018 to 1.5% in 2020 were recorded, with around 60% of e-cigarette or HTP users who kept on smoking conventional cigarettes. Around 90% of smokers did not use novel products at all. Novel products use among former smokers was more likely in younger e-cigarette users, whereas older users of both novel products were less able to completely shift to an exclusive use. Conclusions: After 10 years from the introduction of e-cigarettes and 5 years from that of HTP, the majority of smokers in Italy were still loyal to conventional tobacco cigarettes, and more than half of novel product users kept on smoking conventional cigarettes

Effects of a prevention program on multiple health-compromising behaviours in adolescence: A cluster randomized controlled trial.

We aimed to assess the effectiveness of 'Paesaggi di Prevenzione', a school-based prevention program delivered by trained teachers and designed to tackle smoking, alcohol misuse, dietary risks, and physical inactivity in adolescence. We evaluated the program between 2010 and 2013 with a two-arm, parallel-group, multicentre cluster randomized controlled trial in which schools were the units of randomization. We collected data on health-compromising behaviours using self-reported measurements of behaviour frequency administered before and after program implementation. We used multivariable mixed-effects logistic regression models to estimate program effects on health-compromising behaviours. The analysis sample included 3410 middle school students and 1651 high school students. Among middle school students, mean age at baseline was 12 years (standard deviation [SD] 0.5 years), 51% were boys, and 41% had high socioeconomic status [SES] (defined as having at least one parent/guardian with university level education). In high school students, mean age at baseline was 14 years (SD 0.7 years), 56% were boys, and 31% had high SES. The program did not have effects on smoking, alcohol misuse, and physical activity. The program had iatrogenic effects in regard to some eating behaviours, resulting in (i) lower odds of fruit consumption among middle-school students (odds ratio [OR] 0.82; 95% confidence interval [CI] 0.68-0.99) and (ii) lower odds of having breakfast every day in high-school students at the post-intervention measurement (OR 0.76; 95%CI 0.58-0.99) but not at one-year follow-up (OR 0.94; 95%CI 0.69-1.28). Due to the possibility of unintended effects, we advise against disseminating 'Paesaggi di Prevenzione' in its present form. TRIAL REGISTRATION: ISRCTN00953701