As the field of immunotherapy continues to revolutionize cancer treatment, it is essential to comprehensively understand the potential links between immunotherapy and the onset or exacerbation of autoimmune conditions. This research project seeks to investigate the occurrence, mechanisms, and clinical implications of autoimmune diseases in patients undergoing immunotherapy for cancer presenting as emergent, urgent, or non-urgent conditions. The main objective is to assess the incidence of autoimmune diseases among patients with cancer treatment with immunotherapy, compare the emergent, urgent, or non-urgent presentations of these conditions and investigate the long-term consequences of autoimmune diseases in the context of cancer immunotherapy, including their influence on treatment response, survival rates, and quality of life.

LEARNING OBJECTIVES

Data collection and management: To gain practical experience in collecting, organizing, and managing research data, ensuring accuracy, reliability, and adherence to ethical guidelines.

Data analysis skills: To learn and apply different statistical analysis techniques to the collected data.

Statistical software use: To develop/improve practical skills in using different statistical software including R and STATA.

Literature Review and Synthesis: To effectively conduct a comprehensive literature review, synthesizing existing knowledge and critically analyzing previous studies to support the project and the final manuscript.

Manuscript/abstract writing: To develop skills in writing a scientific paper and scientific abstract.

ELIGIBILITY REQUIREMENTS

Knowledgeable about conducting literature reviews and familiar with different databases including PubMed, and Embase.

Familiar with statistical software such as STATA or R.

Familiar with quantitative data analysis including descriptive statistics and basic inferential statistics including hypothesis testing (T-test, ANOVA test, Mann-Whitney U test), different regression analyses (linear and logistic regressions), survival analyses, and basic machine learning analyses.

Understanding and adherence to ethical guidelines governing human subjects' research.

Can collaborate effectively with a multidisciplinary research team and have communication and coordination skills to ensure seamless teamwork.

FACULTY MENTOR

Sai-Ching Yeung