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Zhou, Shouhao

0000-0002-8124-5047

Mayo Clinic

Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania, USA.

Citations 3

Bayesian sparse modeling to identify high‐risk subgroups in meta‐analysis of safety data
Qi, Xinyue , Wang, Yucai , Peterson, Christine B. , Zhou, Shouhao , Wang, Yucai , Peterson, Christine , Zhou, Shouhao

Research Synthesis Methods | August 11, 2022 | Volume: 13 | Issue: 6 | Pages: 807-820

10.1002/jrsm.1597 Get It

AbstractMeta‐analysis allows researchers to combine evidence from multiple studies, making it a powerful tool for synthesizing information on the safety profiles of new medical interventions. There is a critical need to identify subgroups at high risk of experiencing treatment‐related toxicities. However, this remains quite challenging from a statistical perspective as there are a variety of clinical risk factors that may be relevant for different types of adverse events, and adverse events of interest may be rare or incompletely reported. We frame this challenge as a variable selection problem and propose a Bayesian hierarchical model which incorporates a horseshoe prior on the interaction terms to identify high‐risk groups. Our proposed model is motivated by a meta‐analysis of adverse events in cancer immunotherapy, and our results uncover key factors driving the risk of specific types of treatment‐related adverse events.
A population-based study of cardiovascular disease mortality risk in US cancer patients
Sturgeon, Kathleen M. , Deng, Lei , Bluethmann, Shirley M. , Zhou, Shouhao , Jiang, Changchuan , Kelly, Scott P. , Zhou, Shouhao , Deng, Lei , Trifiletti, Daniel M. , Zaorsky, Nicholas G.

European Heart Journal | October 9, 2019 | Volume: 40 | Issue: 48 | Pages: 3889-3897

10.1093/eurheartj/ehz766 Get It

Abstract Aims This observational study characterized cardiovascular disease (CVD) mortality risk for multiple cancer sites, with respect to the following: (i) continuous calendar year, (ii) age at diagnosis, and (iii) follow-up time after diagnosis. Methods and results The Surveillance, Epidemiology, and End Results program was used to compare the US general population to 3 234 256 US cancer survivors (1973–2012). Standardized mortality ratios (SMRs) were calculated using coded cause of death from CVDs (heart disease, hypertension, cerebrovascular disease, atherosclerosis, and aortic aneurysm/dissection). Analyses were adjusted by age, race, and sex. Among 28 cancer types, 1 228 328 patients (38.0%) died from cancer and 365 689 patients (11.3%) died from CVDs. Among CVDs, 76.3% of deaths were due to heart disease. In eight cancer sites, CVD mortality risk surpassed index-cancer mortality risk in at least one calendar year. Cardiovascular disease mortality risk was highest in survivors diagnosed at <35 years of age. Further, CVD mortality risk is highest (SMR 3.93, 95% confidence interval 3.89–3.97) within the first year after cancer diagnosis, and CVD mortality risk remains elevated throughout follow-up compared to the general population. Conclusion The majority of deaths from CVD occur in patients diagnosed with breast, prostate, or bladder cancer. We observed that from the point of cancer diagnosis forward into survivorship cancer patients (all sites) are at elevated risk of dying from CVDs compared to the general US population. In endometrial cancer, the first year after diagnosis poses a very high risk of dying from CVDs, supporting early involvement of cardiologists in such patients.