RESUMEN
BACKGROUND: The number and projections of cancer survivors are necessary to meet the healthcare needs of patients, while data on cure prevalence, that is, the percentage of patients who will not die of cancer by time since diagnosis, are lacking. MATERIALS AND METHODS: Data from Italian cancer registries (duration of registration ranged from 9 to 40 years, with a median of 22 years) covering 47% of the population were used to calculate the limited-duration prevalence, the complete prevalence in 2018, projections to 2030, and cure prevalence, by cancer type, sex, age, and time since diagnosis. RESULTS: A total of 3 347 809 people were alive in Italy in 2018 after a cancer diagnosis, corresponding to 5.6% of the resident population. They will increase by 1.5% per year to 4 012 376 in 2030, corresponding to 6.9% of the resident population, 7.6% of women and â¼22% after age 75 years. In 2030, more than one-half of all prevalent cases (2 million) will have been diagnosed by ≥10 years. Those with breast (1.05 million), prostate (0.56 million), or colorectal cancers (0.47 million) will be 52% of all prevalent patients. Cure prevalence was 86% for all patients alive in 2018 (87% for patients with breast cancer and 99% for patients with thyroid or testicular cancer), increasing with time since diagnosis to 93% for patients alive after 5 years and 96% after 10 years. Among patients who survived at least 5 years, the excess risk of death (1 - cure prevalence) was <5% for patients with most cancer types except for those with cancers of the breast (8.3%), lung (11.1%), kidney (13.2%), and bladder (15.5%). CONCLUSIONS: Study findings encourage the implementation of evidence-based policies aimed at improving long-term clinical follow-up and rehabilitation of people living after cancer diagnosis throughout the course of the disease. Updated estimates of complete prevalence are important to enhance data-driven cancer control planning.
RESUMEN
In order to investigate the extent of stress reaction during driving, this study was carried out on truck drivers engaged in long distance work. For each driver, epinephrine, norepinephrine, and cortisol were measured in urine, and dynamic ECG and blood pressure were monitored. The excretion rates of catecholamines showed great individual differences in the size of variations related to driving conditions. Epinephrine excretion rates were particularly high when weather and traffic conditions were more stressful. A relationship was found between epinephrine urinary levels and state-anxiety scores. Urinary excretion of norepinephrine was generally increased at the end of the working day and while driving in fog. The pattern of cortisol was not affected by the stress related to driving. The highest mean heart rates were monitored during difficult traffic and bad weather conditions.