Survival Analysis in Oral Cancer Patients: A Reliable Statistical Analysis Tool

Nihar Ranjan Panda; Devipriya  Gouda; Sanat Kumar Bhuyan; Ruchi Bhuyan

doi:10.55489/njcm.141120233384

Authors

Nihar Ranjan Panda IMS & SUM Hospital, SOA Deemed to be University, Bhubaneswar, India
Devipriya Gouda Institute of dental science, SOA Deemed to be University, Bhubaneswar, India
Sanat Kumar Bhuyan Institute of dental science, SOA Deemed to be University, Bhubaneswar, India
Ruchi Bhuyan IMS & SUM Hospital, SOA Deemed to be University, Bhubaneswar, India

DOI:

https://doi.org/10.55489/njcm.141120233384

Keywords:

Oral cancer, Survival analysis, Survival Rate, Cox Regression, Hazard Ratio

Abstract

Clinical trials or follow-up studies sometimes necessitate the long-term monitoring of patients, with an emphasis on crucial events such as mortality, recurrence, severe medication responses, or the advent of new illnesses. These studies cover a range of follow-up times, from a few weeks to several years. Analyzing such data necessitates the use of specialized statistical approaches such as time-to-event analysis and survival analysis. This method is extremely useful in clinical research, providing crucial insights into therapies. The three basic purposes of survival analysis are to determine and analyze survival/hazard functions using survival data, compare these functions, and evaluate how explanatory factors relate to survival time. This methodology is useful for investigating event timing in a variety of situations, notably in clinical studies where event-based data is common. This paper is intended to serve as a primer for researchers, exposing them to the wide range of methods accessible in the discipline of survival analysis. Researchers have the ability to traverse the complex terrain of clinical trial data distinguished by variable follow-up durations, by diving into this approach. The key to survival analysis is its capacity to provide subtle insights into the temporal elements of patient reactions, providing a full view of intervention success. We have taken the cases of oral cancer survival analysis studies and put a light on methods and association used there.

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