Estimating the Lifetime Risk of Dementia in the Canadian Elderly Population Using Cross-Sectional Cohort Survival Data

Carone, Marco; Asgharian, Masoud; Jewell, Nicholas P.

doi:10.1080/01621459.2013.859076

Cited by 29 publications

(23 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This information is needed to facilitate communication between physicians and patients, 10 to educate the public, 11 and to inform policy-makers, as has been accomplished for other diseases including breast cancer, 12 hypertension, 13 diabetes, 14 and dementia. 15 …”

mentioning

confidence: 99%

Risk of ESRD in the United States

Albertus

Morgenstern

Robinson

et al. 2016

American Journal of Kidney Diseases

View full text Add to dashboard Cite

Background Although incidence rates of end-stage renal disease (ESRD) in the United States are reported routinely by the US Renal Data System (USRDS), risks (probabilities) are not reported. Short- and long-term risk estimates need to be updated and expanded to minority populations, including Native Americans, Asian/Pacific Islanders, and Hispanics. Study Design Risk estimation from surveillance data in large populations using life-table methods. A competing-risks framework was applied by constructing a hypothetical cohort followed up from birth to death. Setting & Participants Total US population. Incidence and mortality rates of ESRD were obtained from the USRDS; all-cause mortality rates were obtained from CDC WONDER. Predictors Age, sex, race/ethnicity, and year. Outcomes 10-year to lifetime risks (cumulative incidence) of ESRD. Results Among males, the lifetime risks of ESRD from birth using 2013 data were 3.1% (95% CI, 3.0%-3.1%) for non-Hispanic (NH) whites, 8.0% (95% CI, 7.9%-8.2%) for NH blacks, 3.8% (95% CI, 3.4%-4.9%) for NH Native Americans, 5.1% (95% CI, 4.8%-5.4%) for NH Asians/Pacific Islanders, and 6.2% (95% CI, 6.1%-6.4%) for Hispanics. Among females, the lifetime risks were 2.0% (95% CI, 2.0%-2.1%) for NH whites, 6.8% (95% CI, 6.7%-6.9%) for NH blacks, 3.6% (95% CI, 3.3%-4.2%) for NH Native Americans, 3.8% (95% CI, 3.6%-4.0%) for NH Asian/Pacific Islanders, and 4.3% (95% CI, 4.2%-4.5%) for Hispanics. The lifetime risk of ESRD from birth increased from 3.5% in 2000 to 4.0% in 2013 in males and decreased from 3.0% to 2.8% in females. Limitations Standard life-time assumption of fixed age-specific rates over time; and possible ESRD misclassification. To be useful in clinical practice, this application will require additional predictors (e.g., comorbidities, chronic kidney disease stage). Conclusions ESRD risk in the United States varies more than 2-fold among racial/ethnic groups for both sexes.

show abstract

mentioning

confidence: 99%

Risk of ESRD in the United States

Albertus

Morgenstern

Robinson

et al. 2016

American Journal of Kidney Diseases

View full text Add to dashboard Cite

show abstract

“…On the other hand, as noted, the onset of dementia after recruitment was not observed. Figure A1 of Carone et al . schematically describes this complex sampling method.…”

Section: Schematic For Disease Initiation and Progressionmentioning

confidence: 99%

“…On the other hand, as noted, the onset of dementia after recruitment was not observed. Figure A1 of Carone et al 69 schematically describes this complex sampling method. In addition, as might be expected, the sample was based on stratification factors, including age, and these effects also needed to be accommodated.…”

Section: Hybrid Studiesmentioning

confidence: 99%

Natural history of diseases: Statistical designs and issues

Jewell

2016

Clin Pharma and Therapeutics

Self Cite

View full text Add to dashboard Cite

Understanding the natural history of a disease is an important prerequisite for designing studies that assess the impact of interventions, both chemotherapeutic and environmental, on the initiation and expression of the condition. Identification of biomarkers that mark disease progression may provide important indicators for drug targets and surrogate outcomes for clinical trials. However, collecting and visualizing data on natural history is challenging in part because disease processes are complex and evolve in different chronological periods for different subjects. Various epidemiological designs are used to elucidate components of the natural history process. We briefly discuss statistical issues, limitations and challenges associated with various epidemiological designs.

show abstract

“…Statistical methods for estimating absolute risks have been extensively reviewed . Specific issues in lifetime risk estimation for dementia based on cohort and cross‐sectional studies have been considered …”

Section: Introductionmentioning

confidence: 99%

“…3 Specific issues in lifetime risk estimation for dementia based on cohort and cross-sectional studies have been considered. [4][5][6] In this paper, motivated by recent developments in Alzheimer's research, we discuss lifetime risk estimation using biomarkers for preclinical disease based on multistate models for the disease process using a discrete nonhomogeneous Markov multistate model. We focus on nonhomogeneous models because of the importance of accounting for age and calendar year in the application to AD.…”

Section: Introductionmentioning

confidence: 99%

Multistate models and lifetime risk estimation: Application to Alzheimer's disease

Brookmeyer

Abdalla

2018

Statistics in Medicine

View full text Add to dashboard Cite

The lifetime risk of a clinical condition is the probability of onset of the condition during one's lifespan. Recent advances in Alzheimer's disease (AD) research have identified screening tests for biomarkers that can identify persons who are in the earliest stages of the AD process but who do not yet have any clinical signs or symptoms. A critical question asked by patients and clinicians is, what is the probability an individual will develop AD dementia during his or her lifetime? Here, we discuss estimation of lifetime risks using biomarkers for preclinical disease based on a discrete nonhomogeneous Markov multistate model for the disease process. We allow the transition probabilities to depend on chronological age. In addition, we allow the probabilities to depend on calendar time to account for possible calendar trends in death rates and to evaluate the impact on lifetime risks of future interventions designed to slow disease progression. We develop estimating equations for calculating the lifetime risks from the nonhomogeneous multistate Markov model. Estimates of lifetime risks for AD dementia based on biomarkers for preclinical disease are presented.

show abstract

Estimating the Lifetime Risk of Dementia in the Canadian Elderly Population Using Cross-Sectional Cohort Survival Data

Cited by 29 publications

References 21 publications

Risk of ESRD in the United States

Risk of ESRD in the United States

Natural history of diseases: Statistical designs and issues

Multistate models and lifetime risk estimation: Application to Alzheimer's disease

Contact Info

Product

Resources

About