Erikas Simonavičius

Erikas holds a BA in Psychology (2008) and MA in Clinical Psychology (2010) from Vilnius University in Lithuania, MSc in Addictions studies (2017) and PhD in Addiction Sciences (2020) from King’s College London, where he explored how smokers in general population perceive tobacco harm reduction. After PhD, Erikas continued working as a Research Associate at the Addictions Department, King’s College London, where, together with colleagues at the Nicotine Research group, prepared the most comprehensive to date vaping evidence review (to be published in 2022). Jointly supported by the SSA post-doctoral transitional development award and the NIHR Maudsley Biomedical Research Centre, Erikas explored the feasibility of electronic primary healthcare data for identifying smokers who might be at heightened risk of developing smoking-related diseases.

Detecting at-risk tobacco smokers through the history of their past treatment events

In the UK, nearly a fifth of cancer cases per year and many other, including fatal diseases, can be attributed to tobacco use. However, the role that smoking plays in the development of patients’ conditions is often overlooked in primary care services, where practitioners are mostly limited to opportunistic brief smoking cessation interventions that are often only offered to the heaviest smokers. This oversight is evident from scarce and unstandardised information on patients’ smoking on electronic health records and complicates the prediction of longer-term smoking-related health outcomes.

Research into temporal disease trajectories demonstrates how non-communicable diseases can be predicted by temporal patterns of treatment events and diseases diagnosed in the past. Within temporal disease trajectories, smoking can be a significant but overlooked risk factor responsible for transition from specific treatment events towards more serious preventable diseases. Therefore, identifying treatment events that can act as early markers of smoking-related diseases would enable early intervention. This study explored how patients’ smoking is associated with temporal disease trajectories leading to smoking-related cancers within electronic health data at the South London and Maudsley NHS Foundation Trust clinical records system.