Yuqi Zhang

I am an epidemiologist, with research interests in cancer and diabetes epidemiology.

My primary research focus addresses critical gaps in breast cancer risk prediction, screening effectiveness, and prognosis through three complementary research streams:

1. Risk Stratification: through systematic analysis of multi-generational cohorts, we demonstrated for the first time that estrogen receptor (ER)-negative breast cancer exhibits stronger familial clustering than ER-positive subtype (JNCI, 2023). By constructing comprehensive multi-cancer etworks, this work revealed differential associations between various cancer family histories and BC subtypes, providing foundational evidence for next-generation risk prediction models that account for tumor heterogeneity.
2. Screening Optimization: leveraging the world's largest breast cancer screening study including half a million Swedish women followed over 30 years—we revealed that current mammography screening fails to detect 30% of breast cancers (interval cancers), with no improvement despite three decades of technological advances. This research identified two distinct failure mechanisms: density-related missed diagnoses (hazard ratio up to 16.52) and rapid tumor growth in genetically predisposed women (JAMA Oncol, 2025).
3. Prognostic Assessment: Through analysis of 28, 649 breast cancer patients, we uncovered nuanced relationships between family history timing and survival outcomes. Early-onset family history increases mortality risk by 41%, while late-onset family history provides survival benefit through enhanced health awareness and compliance (JAMA Netw Open, 2023).

Another research interest of mine is Diabetes Epidemiology. My PhD work encompasses:

1. assessing the disease burden of diabetes related complications and methods to reduce the future burden by understanding the risk and prognosis determinants, and the cost-effectiveness of interventions. As the leading author across a series of publications, I conducted the first Global Burden of Disease Study analysis of diabetic foot across 195 countries, which established the disease as the 10th leading cause of global disability—surpassing ischemic stroke and coronary heart disease (Diabetes Care, 2020).
2. Building on this foundation, subsequent studies using the largest prospective diabetic foot cohort identified critical risk stratification factors (Diabetes Care, 2021), which directly influenced the 2023 International Working Group on the Diabetic Foot guidelines.
3. My economic modelling further demonstrated that guideline-adherent treatment could save AUD $1.8 million per 1, 000 patients while gaining 56 quality-adjusted life years (Diabet Med, 2022).

2025.11

Teaching assistant, the Observational Studies course in master’s program in Biostatistics and Data Science, by Prof Marie Reilly, KI

2025.11

Teaching assistant, Biostat III Survival Analysis for PhD, by Prof Mark Clements, MEB, KI

2024.10

Teaching assistant, Extensions to the design and analysis of controlled epidemiological studies for PhD, by Prof Marie Reilly, MEB, KI

2024.01-2024.05

Supervisor of Master student in biomedicine, KI

2023.07-

External Supervisor of Rangi Weerasuriya at Queensland University of Technology, Australia