Abstract

TERRAZAS MATA, Luz Elena et al. Statistical Risk Management Analysis in Patients With CaCu on Cd. Juárez Chihuahua. RIDE. Rev. Iberoam. Investig. Desarro. Educ [online]. 2021, vol.11, n.22, e061.  Epub Sep 20, 2021. ISSN 2007-7467.  https://doi.org/10.23913/ride.v11i22.930.

In recent years, the rapid development of probabilistic models and statistical analysis applied to survival data has increased. The Cox proportional hazards model has become one of the most widely used methods, mainly in health-related issues, it is particularly useful for comparing groups in which the time elapsed until the occurrence of an event is studied, being able to jointly analyze the effect of several variables.

The objective of this study is to present the validation parameters of the assumptions of the Cox proportional hazards model as a tool for decision-making, regarding the time of occurrence of the phenomenon, comparison of groups, effects of different factors on the event of outcome or failure, as well as highlighting characteristics that identify groups at risk; in order to provide health professionals with statistical information that helps them inform decisions regarding diagnosis, prognosis and treatment; thus also highlighting these strengths in different fields of study that seek to identify these behaviors.

This is an exploratory cross-sectional investigation where the results obtained from a statistical analysis performed on the data derived from records and interviews with a group of 127 patients diagnosed with cervical cancer are reported during the period from 2013 to 2017 in the colposcopy clinic of the Jurisdicción Sanitaria II in Cd. Juárez Chihuahua.

Age, diabetes, education, marital status and number of partners were analyzed in order to determine their risk rate using the Cox proportional hazards model. The study identified that the factors that have the greatest effect on patient survival are age and diabetes.

The Cox model allows the using information from subjects who are lost to follow-up, as in survival analyzes, in addition to taking into account all the risk factors that may intervene in a given result, it helps to substantiate clinical judgment.

Keywords : application validation parameters; Cox model; hazard ratio; survival.

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