RESUMEN
BACKGROUND: Tobacco-related illnesses are leading causes of death and healthcare use. Our objective was to determine whether implementation of a hospital-initiated smoking cessation intervention would reduce mortality and downstream healthcare usage. METHODS: A 2-group effectiveness study was completed comparing patients who received the 'Ottawa Model' for Smoking Cessation intervention (n=726) to usual care controls (n=641). Participants were current smokers, >17â years old, and recruited during admission to 1 of 14 participating hospitals in Ontario, Canada. Baseline data were linked to healthcare administrative data. Competing-risks regression analysis was used to compare outcomes between groups. RESULTS: The intervention group experienced significantly lower rates of all-cause readmissions, smoking-related readmissions, and all-cause emergency department (ED) visits at all time points. The largest absolute risk reductions (ARR) were observed for all-cause readmissions at 30â days (13.3% vs 7.1%; ARR, 6.1% (2.9% to 9.3%); p<0.001), 1â year (38.4% vs 26.7%; ARR, 11.7% (6.7% to 16.6%); p<0.001), and 2â years (45.2% vs 33.6%; ARR, 11.6% (6.5% to 16.8%); p<0.001). The greatest reduction in risk of all-cause ED visits was at 30â days (20.9% vs 16.4%; ARR, 4.5% (0.4% to 8.7%); p=0.03). Reduction in mortality was not evident at 30â days, but significant reductions were observed by year 1 (11.4% vs 5.4%; ARR 6.0% (3.1% to 9.0%); p<0.001) and year 2 (15.1% vs 7.9%; ARR, 7.3% (3.9% to 10.7%); p<0.001). CONCLUSIONS: Considering the relatively low cost, greater adoption of hospital-initiated tobacco cessation interventions should be considered to improve patient outcomes and decrease subsequent healthcare usage.
Asunto(s)
Hospitalización , Readmisión del Paciente/estadística & datos numéricos , Cese del Hábito de Fumar/métodos , Prevención del Hábito de Fumar , Adulto , Anciano , Servicio de Urgencia en Hospital/estadística & datos numéricos , Femenino , Humanos , Masculino , Persona de Mediana Edad , Ontario , Desarrollo de Programa , Evaluación de Programas y Proyectos de Salud , Análisis de Regresión , Conducta de Reducción del Riesgo , Fumar/mortalidad , Factores de Tiempo , Resultado del TratamientoRESUMEN
Despite the fact that colorectal cancer (CRC) is a highly treatable form of cancer if detected early, a very low proportion of the eligible population undergoes screening for this form of cancer. Integrating a genomic screening profile as a component of existing screening programs for CRC could potentially improve the effectiveness of population screening by allowing the assignment of individuals to different types and intensities of screening and also by potentially increasing the uptake of existing screening programs. We evaluated the utility and predictive value of genomic profiling as applied to CRC, and as a potential component of a population-based cancer screening program. We generated simulated data representing a typical North American population including a variety of genetic profiles, with a range of relative risks and prevalences for individual risk genes. We then used these data to estimate parameters characterizing the predictive value of a logistic regression model built on genetic markers for CRC. Meta-analyses of genetic associations with CRC were used in building science to inform the simulation work, and to select genetic variants to include in logistic regression model-building using data from the ARCTIC study in Ontario, which included 1,200 CRC cases and a similar number of cancer-free population-based controls. Our simulations demonstrate that for reasonable assumptions involving modest relative risks for individual genetic variants, that substantial predictive power can be achieved when risk variants are common (e.g., prevalence > 20%) and data for enough risk variants are available (e.g., approximately 140-160). Pilot work in population data shows modest, but statistically significant predictive utility for a small collection of risk variants, smaller in effect than age and gender alone in predicting an individual's CRC risk. Further genotyping and many more samples will be required, and indeed the discovery of many more risk loci associated with CRC before the question of the potential utility of germline genomic profiling can be definitively answered.