No abstract

Full funding sources listed at the end of the paper (see Acknowledgments).

Population Health Research Institute, the Canadian Institutes of Health Research, Heart and Stroke Foundation of Ontario, Canadian Institutes of Health Research Strategy for Patient Oriented Research through the Ontario SPOR Support Unit, the Ontario Ministry of Health and Long-Term Care, pharmaceutical companies (with major contributions from AstraZeneca [Canada], Sanofi Aventis [France and Canada], Boehringer Ingelheim [Germany amd Canada], Servier, and GlaxoSmithKline), Novartis and King Pharma, and national or local organisations in participating countries.

Full funding sources listed at the end of the paper (see Acknowledgments).

ObjectiveTo evaluate the performance of the non-laboratory INTERHEART risk score (NL-IHRS) to predict incident cardiovascular disease (CVD) across seven major geographic regions of the world. The secondary objective was to evaluate the performance of the fasting cholesterol-based IHRS (FC-IHRS).MethodsUsing measures of discrimination and calibration, we tested the performance of the NL-IHRS (n=100 475) and FC-IHRS (n=107 863) for predicting incident CVD in a community-based, prospective study across seven geographic regions: South Asia, China, Southeast Asia, Middle East, Europe/North America, South America and Africa. CVD was defined as the composite of cardiovascular death, myocardial infarction, stroke, heart failure or coronary revascularisation.ResultsMean age of the study population was 50.53 (SD 9.79) years and mean follow-up was 4.89 (SD 2.24) years. The NL-IHRS had moderate to good discrimination for incident CVD across geographic regions (concordance statistic (C-statistic) ranging from 0.64 to 0.74), although recalibration was necessary in all regions, which improved its performance in the overall cohort (increase in C-statistic from 0.69 to 0.72, p<0.001). Regional recalibration was also necessary for the FC-IHRS, which also improved its overall discrimination (increase in C-statistic from 0.71 to 0.74, p<0.001). In 85 078 participants with complete data for both scores, discrimination was only modestly better with the FC-IHRS compared with the NL-IHRS (0.74 vs 0.73, p<0.001).ConclusionsExternal validations of the NL-IHRS and FC-IHRS suggest that regionally recalibrated versions of both can be useful for estimating CVD risk across a diverse range of community-based populations. CVD prediction using a non-laboratory score can provide similar accuracy to laboratory-based methods.

EORTC criteria and PERCIST 1.0 are more sensitive and accurate than RECIST 1.1 for the detection of an early therapeutic response to chemotherapy in patients with NSCLC. Although EORTC criteria and PERCIST 1.0 showed similar results, PERCIST 1.0 is preferred because detailed and unambiguous definitions are given. We also found that response evaluations with PERCIST 1.0 using a single lesion and multiple lesions gave similar response classifications.

Few studies have shown comparison data between calcaneus stiffness index (SI) calculated by quantitative ultrasound (QUS) and bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA) in the Chinese population. This study was aimed to examine the correlations between calcaneus SI calculated by QUS and total body BMD and bone mineral content (BMC) measured by DXA in Chinese children and adolescents. We measured the total body BMD and BMC using Lunar Prodigy (GE Healthcare), and speed of sound (SOS), broadband ultrasound attenuation (BUA), and a calculated SI of the left os calcis using Lunar Achilles Express (GE Healthcare) in 392 healthy Chinese schoolchildren and adolescents aged 5-19 years. The short-term precision for DXA was 0.5 % for total body BMD. The precision for QUS was 1.8 % for SI, 2.9 % for BUA, and 0.4 % for SOS. Pearson's correlation coefficients (r) were calculated to assess the possible correlations between the total body BMC by DXA and SI calculated by QUS. There were significantly positive correlations between SI of the left os calcis and total body BMD (r = 0.693, p < 0.001, n = 392) and BMC (r = 0.690, p < 0.001, n = 392). For all the subjects, significant positive correlations were observed between the calcaneal SI and the age, weight, height, BMI, total body BMD, total body BMC, total body lean mass, and total body fat mass, with r ranging from 0.310 (total body fat mass) to 0.693 (total body BMD) (p < 0.001, n = 392). In conclusion, QUS bone densitometry is a useful measuring method showing the physiological bone development in childhood and adolescence.

This study aimed to analyze the relationships between the lean mass index (LMI) and bone outcomes in Chinese children and adolescents using dual-energy X-ray absorptiometry (DXA) and to establish sex-specific reference percentile curves for the assessment of muscle status. A total of 1541 Chinese children and adolescents between the ages of 5 and 19 years were recruited from southern China. Body composition was measured by DXA (Lunar Prodigy) to acquire total body and total body less head (TBLH) measures. LMI was calculated as the LM (kg) divided by the height in meters squared. Strong sex gaps were observed after age 14 in total body LMI and appendicular LMI (p < 0.001). LM and LMI values continued to increase for boys up to age 14 compared to girls who plateaued after age 12. For each sex group, total body bone mineral content (BMC) and TBLH BMC were highly correlated with total body LMI and appendicular LMI (r = 0.856-0.916 in boys, and r = 0.651-0.804 in girls, p < 0.001). The appendicular LMI was more strongly associated with total body BMC and TBLH BMC than was total body LMI. The correlations between the BMC values and the LM measures were stronger than the fat mass results. We also present sex-specific percentile curves for LM-age and LMI-age relationships, which could be useful for identifying the LM deficits in this population.