Publications by authors named "M Di Maso"

Cancer burden can be reduced by controlling modifiable risk factors, including diet. We provided an evidence-based assessment of cancer cases and deaths attributable to diet in Italy in 2020. We considered dietary factor-cancer type pairs for which the World Cancer Research Fund/American Institute for Cancer Research - Continuous Update Project reported either 'convincing' or 'probable' evidence of causal association.

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Objective: We aimed to retrospectively evaluate obstetric and neonatal outcomes in patients who underwent ultrasound-indicated and rescue cervical cerclage and to identify predictors for cerclage failure and consequent preterm birth (PTB).

Materials And Methods: We conducted a retrospective analysis on singleton pregnancies between 16 and 27 weeks of gestation who presented with a transvaginal sonographic cervical length (TVS-CL) <25 mm and a previous PTB/second-trimester miscarriage or prolapsed amniotic membranes and/or a TVS-CL <15 mm and underwent cervical cerclage at Mangiagalli Center, Milan, between September 2011 and December 2021. Univariate and multivariate logistic regression analyses were used to identify possible predictive factors of cerclage failure.

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Background: Pancreatic cancer risk has been associated with increased serum cholesterol level, which is in turn partially influenced by diet. This study aimed at evaluating the association between pancreatic cancer risk and the adherence to a plant-based cholesterol-lowering diet.

Methods: Data were derived from an Italian case-control study including 258 pancreatic cancer patients and 551 controls.

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Objective: Endogenous and exogenous hormonal factors have been associated with female breast, genital, and colorectal cancer risk. The aim of the present study is to conduct an evidence-based evaluation of the fraction of cancers attributable to and prevented by exogenous hormonal (i.e.

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Background: Tobacco smoking is still frequent in Italy and a major cause of cancer globally. We estimated the burden of smoking-related cancer in Italy.

Methods: To calculate the population attributable fraction (PAF), we adopted a counterfactual scenario for which all individuals never smoked.

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