Randomized Controlled Trial of a Computer-Based, Tailored Intervention to Increase Smoking Cessation Counseling by Primary Care Physicians

OBJECTIVE: The primary care visit represents an important venue for intervening with a large population of smokers. However, physician adherence to the Smoking Cessation Clinical Guideline (5As) remains low. We evaluated the effectiveness of a computer-tailored intervention designed to increase smoking cessation counseling by primary care physicians. METHODS: Physicians and their patients were randomized to either intervention or control conditions. In addition to brief smoking cessation training, intervention physicians and patients received a one-page report that characterized the patients’ smoking habit and history and offered tailored recommendations. Physician performance of the 5As was assessed via patient exit interviews. Quit rates and smoking behaviors were assessed 6 months postintervention via patient phone interviews. Intervention effects were tested in a sample of 70 physicians and 518 of their patients. Results were analyzed via generalized and mixed linear modeling controlling for clustering. MEASUREMENTS AND MAIN RESULTS: Intervention physicians exceeded controls on “Assess” (OR 5.06; 95% CI 3.22, 7.95), “Advise” (OR 2.79; 95% CI 1.70, 4.59), “Assist–set goals” (OR 4.31; 95% CI 2.59, 7.16), “Assist–provide written materials” (OR 5.14; 95% CI 2.60, 10.14), “Assist–provide referral” (OR 6.48; 95% CI 3.11, 13.49), “Assist–discuss medication” (OR 4.72;95% CI 2.90, 7.68), and “Arrange” (OR 8.14; 95% CI 3.98, 16.68), all p values being < 0.0001. Intervention patients were 1.77 (CI 0.94, 3.34,p = 0.078) times more likely than controls to be abstinent (12 versus 8%), a difference that approached, but did not reach statistical significance, and surpassed controls on number of days quit (18.4 versus 12.2, p < .05) but not on number of quit attempts. CONCLUSIONS: The use of a brief computer-tailored report improved physicians’ implementation of the 5As and had a modest effect on patients’ smoking behaviors 6 months postintervention

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe