6 citations · 7 across the 5 of their papers we have counts for
6 papers
Increasing power and robustness in screening trials by testing stored specimens in the control arm
Hormuzd A. Katki, Li C. Cheung
Background: Screening trials require large sample sizes and long time-horizons to demonstrate mortality reductions. We recently proposed increasing statistical power by testing sto…
Data-integration with pseudoweights and survey-calibration: application to developing US-representative lung cancer risk models for use in screening
Lingxiao Wang, Yan Li, Barry Graubard +1
Accurate cancer risk estimation is crucial to clinical decision-making, such as identifying high-risk people for screening. However, most existing cancer risk models incorporate da…
Representative Pure Risk Estimation by Using Data from Epidemiologic Studies, Surveys, and Registries: Estimating Risks for Minority Subgroups
Lingxiao Wang, Yan Li, Barry I. Graubard +1
Representative risk estimation is fundamental to clinical decision-making. However, risks are often estimated from non-representative epidemiologic studies, which usually underrepr…
Efficient and Robust Propensity-Score-Based Methods for Population Inference using Epidemiologic Cohorts
Lingxiao Wang, Barry I. Graubard, Hormuzd A. Katki +1
Most epidemiologic cohorts are composed of volunteers who do not represent the general population. To enable population inference from cohorts, we and others have proposed utilizin…
Statistical approaches using longitudinal biomarkers for disease early detection: A comparison of methodologies
Yongli Han, Paul S. Albert, Christine D. Berg +3
Early detection of clinical outcomes such as cancer may be predicted based on longitudinal biomarker measurements. Tracking longitudinal biomarkers as a way to identify early disea…
Novel decision-theoretic and risk-stratification metrics of predictive performance: Application to deciding who should undergo genetic testing
Hormuzd A. Katki
Currently, women are referred for BRCA1/2 mutation-testing only if their family-history of breast/ovarian cancer implies that their risk of carrying a mutation exceeds 10\%. Howeve…