Contingency chart: class predictions by sample at various marker levels in the Kentucky screening cohort.

<p>Specificity is presented by case series (all negative measures) and by individual sample (time of negative radiograph). Bolded data are predictions using predetermined cutoff value (640 FU). Absolute fluorescence is the additive sum of six markers in the panel.</p

Characteristics of cancers associated with the KY screening cohort.

*<p>Exclusion criteria included: (1) Current or prior personal history of lung cancer (2) Prior malignancy except adequately treated non-melanomatous skin cancer or in-situ cervical cancer.</p><p>The table includes class prediction and temporal relationship of sample draw to cancer diagnosis. Binomial prediction is based on additive measures from the six-marker panel. Up to three individual sample measures from each subject are designated either positive (+) or negative (–) based on levels relative to a predetermined cutoff value of 640 FU (fluorescent units). Assay results at time-of-diagnosis (radiographic detection) of five screening detected lung cancers (three prevalence and two incidence cancers) are designated as “0” months. Two samples designated “+3” and “+15” were drawn 3 and 15 months respectively following a diagnosis of a stage I head and neck cancer in one participant of the lung cancer screening study.</p

Strong, steady and straight: UK consensus statement on physical activity and exercise for osteoporosis

Exercise and physical activity can improve bone strength and the risk of falls, which may offer benefits in the prevention and management of osteoporosis. However, uncertainty about the types of exercise that are safe and effective instigates lack of confidence in people with osteoporosis and health professionals. Existing guidelines leave some questions unresolved. This consensus statement aimed to determine the physical activity and exercise needed to optimise bone strength, reduce fall and fracture risk, improve posture and manage vertebral fracture symptoms, while minimising potential risks in people with osteoporosis. The scope of this statement was developed following stakeholder consultation. Meta-analyses were reviewed and where evidence was lacking, individual studies or expert opinion were used to develop recommendations. A multidisciplinary expert group reviewed evidence to make recommendations, by consensus when evidence was not available. Key recommendations are that people with osteoporosis should undertake (1) resistance and impact exercise to maximise bone strength; (2) activities to improve strength and balance to reduce falls; (3) spinal extension exercise to improve posture and potentially reduce risk of falls and vertebral fractures. For safety, we recommend avoiding postures involving a high degree of spinal flexion during exercise or daily life. People with vertebral fracture or multiple low trauma fractures should usually exercise only up to an impact equivalent to brisk walking. Those at risk of falls should start with targeted strength and balance training. Vertebral fracture symptoms may benefit from exercise to reduce pain, improve mobility and quality of life, ideally with specialist advice to encourage return to normal activities. Everyone with osteoporosis may benefit from guidance on adapting postures and movements. There is little evidence that physical activity is associated with significant harm, and the benefits, in general, outweigh the risks

Partial correlations between pack-years of smoking and BMI-GRS.

<p>Partial correlations between pack-years of smoking and BMI-GRS.</p

Adjusted means of the BMI-GRS (95% CIs) by BMI category after adjustment for age, sex, study sites, genetic principal components, smoking status, and pack-years of smoking.

<p>Bar represents mean±s.d.</p

Partial correlations between BMI and pack-years of smoking by smoking status.

<p>Partial correlations between BMI and pack-years of smoking by smoking status.</p

The Z statistics for associations of 241 SNPs with BMI, pack-years of smoking, and smoking.

<p>The vertical axis represents Z scores for associations of SNPs with pack-years of smoking or smoking. The horizontal axis represents Z scores for associations of SNPs with BMI. All Z scores were adjusted by age, sex, study sites, genetic principal components and lung cancer disease status. The blue dots were SNPs that were determined to be pleiotropic with further validation in TAG.</p

Twelve possbile directed acyclic graphs (DAGs) of one SNP, BMI and pack-years (PY) of smoking.

<p>Possible DAGs between one SNP, BMI and PY. The DAGs are categorized into 4 groups. SNPs in Category 1 (DAGs of 1, 2, and 3) do not have effects on either BMI or pack-years. SNPs in Category 2 (DAGs of 4, 5, and 6) have direct effects on BMI, but not PY. SNPs in Category 3 (DAGs of 7, 8, and 9) have direct effects on PY, but not BMI. SNPs in Category 4 (DAGs of 10, 11, and 12) have pleiotropic effects on BMI and PY. ≡ represents models that are not differentiable.</p

Adjusted means of BMI (95% CIs) for never-smokers, ex-smokers, and current smokers with adjustment for age, sex, and study sites.

<p>Bar represents mean±s.d.</p

Characteristics of 17,037 European-descent subjects in the OncoArray Project and epidemiologic data.

<p>Characteristics of 17,037 European-descent subjects in the OncoArray Project and epidemiologic data.</p