Week 6: Completion of Study Screening and Transition to a Systematic Review

Over the past few weeks, I have been developing my search strategy to complete the two rounds of screening for the studies I have collected. After refining my database searches and establishing clear inclusion and exclusion criteria, I applied these standards to evaluate each article based on its title and abstract. This process allowed me to significantly narrow the initial pool of studies and identify the ones most relevant to my research question.

Through this screening phase, I began to notice an important issue with my dataset. While I was able to find studies related to pluripotent stem cell–derived tissues, gene editing, and immune response, very few papers addressed all components of my research question simultaneously. In particular, there was a lack of consistency in how immune rejection was measured and reported across studies. Some papers focused on molecular markers such as HLA expression, while others examined immune cell activation or general inflammatory responses. Additionally, many studies were conducted in different experimental systems, including organoids, animal models, or in vitro assays, making direct comparison difficult.

As I continued the full-text screening of the remaining articles, it became clear that this variability posed a significant challenge to conducting a meta-analysis. A meta-analysis requires a relatively consistent set of quantitative outcomes across studies to combine and statistically analyze the results. However, the studies I identified used different methodologies, measured different outcomes, and often lacked comparable data formats. Because of this, combining their results into a single statistical analysis would be neither reliable nor meaningful.

Based on these observations, I realized that continuing with a meta-analysis would not be the most appropriate method for my research. For now, I am converting my project into a systematic review, in which I will qualitatively synthesize how different studies approach hypoimmunogenic gene editing and evaluate their effectiveness in reducing immune rejection across various models.