As the term implies, survival analysis studies are concerned with estimating the lifespan of a specific group under investigation. In cancer research, such studies address diverse questions, including the proportion of patients with specific cancer stages and disease sites whose life expectancy after the diagnosis exceeds five or ten years (Raman et al., 2018). Focusing on survival rates, these studies shed light on the risks of death and the chances of recovery and remission for various cancers, thus increasing the accuracy of available data used in cancer prognosis prediction. Therefore, survival analysis contributes to the fight against cancer by improving the healthcare system’s understanding of the most likely disease outcomes and survival expectations. All of this enables healthcare providers to avoid overly optimistic prognoses when treating patients.
Aside from informing disease prognosis, survival analysis research in cancer patients might support the fight against disease by identifying possible gaps in healthcare provision and disparities affecting particular demographic groups. For instance, there are SEER (surveillance, epidemiology, and end results) studies, a type of survival analysis research, that reveal significant racial disparities in ovarian carcinoma patients’ 5-year survival rates (Tercek et al., 2021). The knowledge pertaining to such disparities might be indicative of diverse barriers to accessing the required cancer services, including socioeconomic constraints, risks of being discriminated against, limited access to health insurance, and similar factors. An adequate understanding of race-specific factors that influence disease prognosis and survival rates can give rise to interventions and programs targeted at particular population groups that seem to be underserved. Possible actions to address cancer more effectively could include revising cancer screening and treatment guidelines to eliminate disparities, racial minority cancer awareness events, and other strategies. Therefore, survival analysis studies can facilitate the identification of barriers to fighting cancer effectively.
References
Raman, P., Maddipati, R., Lim, K. H., & Tozeren, A. (2018). Pancreatic cancer survival analysis defines a signature that predicts outcome. PloS One, 13(8), 1-18. Web.
Tercek, A., Galbo, A., Makhani, S., Bouz, A., & Chung-Bridges, K. (2021). Racial disparities in women with serous epithelial ovarian cancer: A surveillance, epidemiology, and end results (SEER) survival analysis. Gynecologic Oncology, 162(1), S251-S252. Web.
Texas Cancer Registry. (2021). Age-adjusted invasive cancer incidence rates in Texas: Specify your criteria. Web.
Texas Health and Human Services. (2021). Cancer incidence and mortality in Texas. Web.