Visit-to-visit fasting blood glucose variability and lifetime risk of cardiovascular disease: a prospective study

Aims Previous studies suggested an adverse association between higher fasting blood glucose (FBG) variability and cardiovascular disease (CVD). Lifetime risk provides an absolute risk assessment during the remainder of an individual’s life. However, the association between FBG variability and the lifetime risk of CVD is uncertain. Objective We aimed to investigate the effect of the visit-to-visit FBG variability on the lifetime risk of CVD. Methods This study included participants from the Kailuan Study who did not have CVD at index ages 35, 45, and 55 years. The FBG variability was defined as the coefficient of variation (CV) of three FBG values that were measured during the examination periods of 2006–2007, 2008–2009, and 2010–2011. We used a modified Kaplan-Merrier method to estimate lifetime risk of CVD according to tertiles of FBG variability. Results At index age 35 years, the study sample comprised 46,018 participants. During a median follow-up of 7.0 years, 1889 participants developed CVD events. For index age 35 years, participants with high FBG variability had higher lifetime risk of CVD (32.5%; 95% confidence interval [CI]: 28.9–36.1%), compared with intermediate (28.3%; 95% CI: 25.5 –31.1%) and low (26.3%; 95% CI: 23.0–29.5%) FBG variability. We found that higher FBG variability was associated with increased lifetime risk of CVD in men but not women. Similar patterns were observed at index ages 45 and 55 years. Conclusions Higher FBG variability was associated with increased lifetime risk of CVD at each index age. Focusing on the FBG variability may provide an insight to the clinical utility for reducing the lifetime risk of CVD.

Lifetime risk of knee and hip replacement following a diagnosis of RA: findings from a cohort of 13 961 patients from England

Objective To estimate the lifetime risk of knee and hip replacement following a diagnosis of RA. Methods The analysis was undertaken using routinely collected data from the English NHS. Diagnosis of RA was identified using primary care records, with knee and hip replacement observed in linked hospital records. Parametric survival models were fitted for up to 15 years of follow-up, with age, sex, Charlson comorbidity score, socioeconomic status, BMI and smoking status included as explanatory variables. A decision model was used to combine and extrapolate survival models to estimate lifetime risk. Results The number of individuals with a diagnosis of RA and included in the study was 13 961. Lifetime risk of knee replacement and hip replacement was estimated to be 22% (95% CI: 16, 29%) and 17% (95% CI: 11, 26%) following a diagnosis of RA for the average patient profile (non-smoking women aged 64 with no other comorbidities, BMI of 27 and in the top socioeconomic quintile). Risks were higher for younger patients. Conclusion The lifetime risk of knee and hip replacement for individuals with a diagnosis of RA is approximately double that of the general population. These findings allow for a better understanding of long-term prognosis and healthcare resource use, and highlight the importance of timely diagnosis and effective treatment.

A Method for Using Life Tables to Estimate Lifetime Risk for Prostate Cancer Death

Prostate cancer can have a long and indolent course, and management without curative therapy should be considered in select patients. When counseling patients, a useful way to convey the risk for death from competing causes is to estimate their lifetime risk for dying from prostate cancer. Double-decrement life tables were constructed to calculate age-specific death rates using the death probabilities from the Social Security Administration life tables and Gleason score–specific mortality rates reported from pre-PSA cohort study. The lifetime risk for prostate cancer death was calculated. Life tables provided life expectancy and risk for prostate cancer death based on age at diagnosis. For example, 60-year-old patient with a Gleason score 6, 7, or 8 tumor had an overall life expectancy of 14.4, 10.2, or 6.6 years, respectively. The risk for prostate cancer death during the expected years of life was 33%, 49%, or 57%, respectively. If a 10-year lead-time bias was assumed for PSA detection, the risks for death from prostate cancer decreased to 16%, 26%, or 37%, respectively. If the patient was in the bottom quartile for overall health and disease was detected by prostate examination, the risk for death from prostate cancer was 21%, 32%, or 40%, respectively. A Web-based tool for performing these calculations is available at http://www.roswellpark.org/Patient_Care/Specialized_Services/Prostate_Cancer_Estimator.html. Life tables can be created to estimate overall life expectancy and risk for prostate cancer death, and to assist with decision-making when considering management without curative therapy.