Analyzing Severe Mental Illness in Lung Cancer Patients

Lung cancer is the number one cause of cancer-related deaths worldwide. Patients with severe mental illness (SMI) are a group who are overrepresented in the lung cancer population. SMI refers to psychological problems, including mood disorders, major depression, schizophrenia, bipolar disorder, and substance abuse disorders, that inhibit a person’s ability to engage in functional and occupational activities.

Cancer patients diagnosed with SMI may not adhere to treatment plans and may have reduced access to healthcare. Individuals with SMI may have advanced tumor growth at diagnosis due to factors such as limited access to healthcare and healthcare systems. The aggregation of inadequate healthcare and increased risk for somatic disorders in patients with SMI can explain higher mortality rates. Many research papers have indicated that cancer represents a significant proportion of excess mortality for people with mental illness. Mental illness is typically associated with suicide, but much of the excess mortality rates associated with mental illness are due to cardiovascular or respiratory diseases and cancer.

In order to improve outcomes for lung cancer patients with SMI, it is important to study and understand the factors associated with patients who have a mental illness and whether they have a worse case fatality associated with cancer.

Allwyn performed this study in collaboration with Dr. James Baldo and Dr. Isaac Gang of the DAEN program of the Volgeneau School of Engineering at George Mason University, Fairfax VA. Several students of the DAEN program contributed to the study.

In this study, we specifically focused on lung cancer patients who have undergone lobectomy (lung cancer surgery) and analyze if any specific mental illness/psychiatric diagnoses or groups of diagnoses increase perioperative death risk. We also tried to understand the Correlation between patients who have undergone lobectomy and its effect on their length of stay in the hospital and the costs associated with it.

We will be sharing more insights from our studies on how we leveraged Data Analysis and Machine Learning to determine Correlation between Lung Cancer and Severe Mental Illness Patients. Watch this space or follow us on LinkedIn to stay tuned.