Background: Obstructive sleep apnea (OSA) has been linked to tumorigenesis and tumor progression. Objectives: The Sleep Apnea in Lung Cancer (SAIL) study (NCT02764866) was designed to determine the prevalence of OSA in patients with lung cancer. Methods: Cross-sectional study including consecutive patients with newly diagnosed lung cancer. All patients were offered home sleep apnea testing (HSAT) and administered a sleep-specific questionnaire prior to initiating oncologic treatment. Sleep study-related variables, symptoms, and epidemiologic data as well as cancer related variables were recorded. Results: Eighty-three patients were enrolled in the SAIL study. Sixty-six completed HSAT. The mean age was 68 ± 11 years and 58% were male with a mean body mass index of 28.1 ± 5.4. Forty-seven percent were current smokers, 42% former smokers, and 11% never smokers with a median tobacco consumption of 51 pack-years. Fifty percent had COPD with a mean FEV1 of 83 ± 22.6% of predicted and a mean DLCO of 85.5 ± 20.1%. Adenocarcinoma was the most common histologic type (46.7%), followed by squamous cell (16.7%) and small cell (16.7%). Most patients were diagnosed at an advanced stage (65% in stages III–IV). The vast majority (80%) had OSA (apnea-hypopnea index [AHI] > 5), and 50% had moderate to severe OSA (AHI > 15) with a mean Epworth Sleepiness Score of 7.43 ± 3.85. Significant nocturnal hypoxemia was common (Median T90: 10.9% interquartile range 2.4–42.2). Conclusions: Sleep apnea and nocturnal hypoxemia are highly prevalent in patients with lung cancer.

No abstract

No abstract

In the last 2 decades, clinical genetics on hereditary colorectal syndromes has shifted from just a molecular characterization of the different syndromes to the estimation of the individual risk of cancer and appropriate risk reduction strategies. In the last years, new specific therapies for some subgroups of patients have emerged as very effective alternatives. At the same time, germline multigene panel testing by next-generation sequencing (NGS) technology has become the new gold standard for molecular genetics.