Personalized Risk Assessment in Never, Light, and Heavy Smokers in a prospective cohort in Taiwan.

The objective of this study was to develop markedly improved risk prediction models for lung cancer using a prospective cohort of 395,875 participants in Taiwan. Discriminatory accuracy was measured by generation of receiver operator curves and estimation of area under the curve (AUC). In multivariate Cox regression analysis, age, gender, smoking pack-years, family history of lung cancer, personal cancer history, BMI, lung function test, and serum biomarkers such as carcinoembryonic antigen (CEA), bilirubin, alpha fetoprotein (AFP), and c-reactive protein (CRP) were identified and included in an integrative risk prediction model. The AUC in overall population was 0.851 (95% CI = 0.840-0.862), with never smokers 0.806 (95% CI = 0.790-0.819), light smokers 0.847 (95% CI = 0.824-0.871), and heavy smokers 0.732 (95% CI = 0.708-0.752). By integrating risk factors such as family history of lung cancer, CEA and AFP for light smokers, and lung function test (Maximum Mid-Expiratory Flow, MMEF25-75%), AFP and CEA for never smokers, light and never smokers with cancer risks as high as those within heavy smokers could be identified. The risk model for heavy smokers can allow us to stratify heavy smokers into subgroups with distinct risks, which, if applied to low-dose computed tomography (LDCT) screening, may greatly reduce false positives

Development of Risk Prediction Equations for Incident Chronic Kidney Disease

IMPORTANCE ‐ Early identification of individuals at elevated risk of developing chronic kidney disease  could improve clinical care through enhanced surveillance and better management of underlying health  conditions.  OBJECTIVE – To develop assessment tools to identify individuals at increased risk of chronic kidney  disease, defined by reduced estimated glomerular filtration rate (eGFR).  DESIGN, SETTING, AND PARTICIPANTS – Individual level data analysis of 34 multinational cohorts from  the CKD Prognosis Consortium including 5,222,711 individuals from 28 countries. Data were collected  from April, 1970 through January, 2017. A two‐stage analysis was performed, with each study first  analyzed individually and summarized overall using a weighted average. Since clinical variables were  often differentially available by diabetes status, models were developed separately within participants  with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external  cohorts (N=2,253,540). EXPOSURE Demographic and clinical factors.  MAIN OUTCOMES AND MEASURES – Incident eGFR <60 ml/min/1.73 m2.  RESULTS – In 4,441,084 participants without diabetes (mean age, 54 years, 38% female), there were  660,856 incident cases of reduced eGFR during a mean follow‐up of 4.2 years. In 781,627 participants  with diabetes (mean age, 62 years, 13% female), there were 313,646 incident cases during a mean follow‐up of 3.9 years. Equations for the 5‐year risk of reduced eGFR included age, sex, ethnicity, eGFR, history of cardiovascular disease, ever smoker, hypertension, BMI, and albuminuria. For participants  with diabetes, the models also included diabetes medications, hemoglobin A1c, and the interaction  between the two. The risk equations had a median C statistic for the 5‐year predicted probability of  0.845 (25th – 75th percentile, 0.789‐0.890) in the cohorts without diabetes and 0.801 (25th – 75th percentile, 0.750‐0.819) in the cohorts with diabetes. Calibration analysis showed that 9 out of 13 (69%) study populations had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was  similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 out of 18 (89%) had a slope of observed to predicted risk between 0.80 and 1.25. CONCLUSIONS AND RELEVANCE – Equations for predicting risk of incident chronic kidney disease developed in over 5 million people from 34 multinational cohorts demonstrated high discrimination and  variable calibration in diverse populations

Serum potassium and adverse outcomes across the range of kidney function: a CKD Prognosis Consortium meta-analysis.

Aims: Both hypo- and hyperkalaemia can have immediate deleterious physiological effects, and less is known about long-term risks. The objective was to determine the risks of all-cause mortality, cardiovascular mortality, and end-stage renal disease associated with potassium levels across the range of kidney function and evaluate for consistency across cohorts in a global consortium. Methods and results: We performed an individual-level data meta-analysis of 27 international cohorts [10 general population, 7 high cardiovascular risk, and 10 chronic kidney disease (CKD)] in the CKD Prognosis Consortium. We used Cox regression followed by random-effects meta-analysis to assess the relationship between baseline potassium and adverse outcomes, adjusted for demographic and clinical characteristics, overall and across strata of estimated glomerular filtration rate (eGFR) and albuminuria. We included 1 217 986 participants followed up for a mean of 6.9 years. The average age was 55 ± 16 years, average eGFR was 83 ± 23 mL/min/1.73 m2, and 17% had moderate- to-severe increased albuminuria levels. The mean baseline potassium was 4.2 ± 0.4 mmol/L. The risk of serum potassium of >5.5 mmol/L was related to lower eGFR and higher albuminuria. The risk relationship between potassium levels and adverse outcomes was U-shaped, with the lowest risk at serum potassium of 4-4.5 mmol/L. Compared with a reference of 4.2 mmol/L, the adjusted hazard ratio for all-cause mortality was 1.22 [95% confidence interval (CI) 1.15-1.29] at 5.5 mmol/L and 1.49 (95% CI 1.26-1.76) at 3.0 mmol/L. Risks were similar by eGFR, albuminuria, renin-angiotensin-aldosterone system inhibitor use, and across cohorts. Conclusions: Outpatient potassium levels both above and below the normal range are consistently associated with adverse outcomes, with similar risk relationships across eGFR and albuminuria

Predicting the risk of osteopenia for women aged 40–55 years

Osteoporosis has been linked to an increased fracture risk and subsequent mortality in the later life. Previous prediction models have focused on osteoporosis in postmenopausal women; however, a prediction tool for osteopenia is needed. Our objective was to establish a prediction model for osteopenia risk in women aged 40–55 years. Methods: This was a cross-sectional study. A total of 1350 Taiwanese women aged 40–55 years were recruited from a health checkup center from 2009 to 2010. The main outcome measure was osteopenia (−1≥bone mineral density T-score > −2.5). Results: The Osteoporosis Preclinical Assessment Tool (OPAT) developed in this study was based on variables with biological importance to osteopenia and variables that remained significant (p<0.05) in the multivariable analysis, which include age, menopausal status, weight, and alkaline phosphatase level. The OPAT has a total score that ranges from 0 to 7, and categorizes women into high-, moderate-, and low-risk groups. The predictive ability of the OPAT (area under the receiver operating characteristic curve=0.77) was significantly better than that of the Osteoporosis Self-assessment Tool for Asians (area under the receiver operating characteristic curve=0.69). The inclusion of serum total alkaline phosphatase level in the model, which is easy to obtain from routine health checkups, significantly enhanced the sensitivity (McNemar test, p=0.004) for detecting osteopenia in women aged 40–55 years. Conclusion: Our findings provide an important tool for identifying women at risk of osteoporosis at the preclinical phase

Characteristics of the study population.

<p><b>Abbreviations:</b> BMD, bone mineral density; BMI, body mass index; hypertension, systolic blood pressure >140 mmHg or diastolic blood pressure >90 mmHg or had medication for controlling blood pressure; diabetes, fasting glucose ≥126 mg/dl or using medication for diabetes; regular exercise: walking or hiking ≥30 mins/2 to 3 days.</p><p>Numbers in bold indicate significant findings (<i>p</i><0.05).</p

Association of <i>SPP1</i> common htSNPs and haplotypes with low BMD.

<p><b>Abbreviations:</b> SNP, single nucleotide polymorphism; Freq., haplotype frequency; BMD, bone mineral density; AOR, adjusted odds ratio; CI, confidence interval; L, low BMD; H, high BMD.</p><p>All models were adjusted for age, menopausal status, BMI (kg/m²), serum ALP (IU/L), UA (mg/dL), LDL (mg/dL), and exercise (frequency × duration × intensity).</p><p>The SNPs with underscore indicate variant allele.</p><p>Numbers in bold indicated significant findings (<i>p</i><0.05).</p

Cardiometabolic disorder reduces survival prospects more than suboptimal body mass index irrespective of age or gender: a longitudinal study of 377,929 adults in Taiwan

Abstract Background The effect of cardio-metabolic profile on the relationship of body mass index (BMI) with mortality is unclear. The aim of this study was to explore association between BMI and mortality at all ages, taking account of cardio-metabolic disorders. Methods We followed 377,929 individuals (≥ 20 years), who registered for health checkups in 1996–2007, until 2008 and found 9490 deaths. From multivariable Cox proportional hazards models we estimated mortality hazard ratios (HR) for those in high blood pressure, hyperglycemia, high waist circumference, dyslipidemia, and different BMIs categories (the underweight [< 18.5 kg/m2], low normal weight [18.5–21.9 kg/m2], normal weight [22–23.9 kg/m2, the referent], overweight [24–26.9 kg/m2], obese1 [27–29.9 kg/m2], and obese2 [≥ 30 kg/m2]). Population attributable risk (PAR) provided estimates of the population mortality burden attributable to high blood pressure, hyperglycemia, high waist circumference, dyslipidemia, and deviant BMIs. Results Higher blood pressure, hyperglycemia, high waist circumference, and dyslipidemia were significantly predictive of higher mortality for nearly all ages. Compared with the referent BMI, underweight (HR = 1.69, 95% confidence interval = 1.51–1.90) and low normal weight (HR = 1.19, 1.11–1.28) were significant mortality risks, while overweight (HR = 0.82, 0.76–0.89) and obese1 (HR = 0.88, 0.79–0.97) were protective against premature death. The mortality impact of obesity was largely attributable to cardio-metabolic profile and attenuated by age. The population mortality burden with high blood pressure (PAR = 7.29%), hyperglycemia (PAR = 5.15%), high waist circumference (PAR = 4.24%), and dyslipidemia (PAR = 5.66%) was similar to that in the underweight (PAR = 5.50%) or low normal weight (PAR = 6.04%) groups. Findings for non-smokers and by gender were similar. Conclusions The effect of BMI on mortality varies with age and is affected by cardio-metabolic status. Compared to any deviant BMI, abnormal cardio-metabolic status has a similar or even greater health impact at both the individual and population levels

The Role of Physical Activity in Harm Reduction among Betel Quid Chewers from a Prospective Cohort of 419,378 Individuals.

OBJECTIVE:To assess the benefits of regular exercise in reducing harms associated with betel quid (BQ) chewing. METHODS:The study cohort, 419,378 individuals, participated in a medical screening program between 1994 and 2008, with 38,324 male and 1,495 female chewers, who consumed 5-15 quids of BQ a day. Physical activity of each individual, based on "MET-hour/week", was classified as "inactive" or "active", where activity started from a daily 15 minutes/day or more of brisk walking (≥3.75 MET-hour/week). Hazard ratios for mortality and remaining years in life expectancy were calculated. RESULTS:Nearly one fifth (18.7%) of men, but only 0.7% of women were chewers. Chewers had a 10-fold increase in oral cancer risk; and a 2-3-fold increase in mortality from lung, esophagus and liver cancer, cardiovascular disease, and diabetes, with doubling of all-cause mortality. More than half of chewers were physically inactive (59%). Physical activity was beneficial for chewers, with a reduction of all-cause mortality by 19%. Inactive chewers had their lifespan shortened by 6.3 years, compared to non-chewers, but being active, chewers improved their health by gaining 2.5 years. The improvement, however, fell short of offsetting the harms from chewing. CONCLUSIONS:Chewers had serious health consequences, but being physically active, chewers could mitigate some of these adverse effects, and extend life expectancy by 2.5 years and reduce mortality by one fifth. Encouraging exercise, in addition to quitting chewing, remains the best advice for 1.5 million chewers in Taiwan