Implicative Statistical Analysis to Identify Prognostic Factors for Mortality from Lymphomas in Children and Adolescents - Mayelyn Rodríguez Estenger; Nelsa María Sagaró del Campo; Larisa Zamora Matamoros; Evelyn Yolanda Fundichely Vázquez (Revista Finlay)
Background: the implicative statistical analysis arose in the 80s to solve problems in the didactics of mathematics. Its use in the Medical Sciences to identify risk factors and prognoses was recently founded. Objective: to evaluate the usefulness of the implicative statistical analysis in the identification of the prognostic factors that most affect mortality from lymphomas in children and adolescents. Method: a case-control study was carried out in children and adolescents diagnosed with Hodgkin and non-Hodgkin lymphoma treated at the Dr. Antonio María Béguez César Sur Pediatric Teaching Hospital in Santiago de Cuba from January 2008 to January 2021. The state of the deceased or alive patient at the time of the study was analyzed as the dependent variable and the following were taken as covariates: poor prognosis stage, presence of B symptoms, histological subtype, presence of three or more extranodal sites, metastasis, age and presence of tumor mass. Two statistical techniques were applied: binary logistic regression and implicative statistical analysis. Results: non-Hodgkin's lymphoma was more frequent in the cases, while Hodgkin's lymphoma predominated in the controls. Both techniques recognized the histological subtype and extranodal involvement as unfavorable prognostic factors. The implicative statistical analysis also recognized the stage and the presence of metastases. Conclusion: the implicative statistical analysis is a technique that complements the binary logistic regression in the identification of prognostic factors, which allows a better understanding of causality.