SciELO - Scientific Electronic Library Online

 
vol.25 issue4Chronic pelvic pain in womenConcept of management by competencies from risks, a need in the culture of medical entities author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

  • Have no cited articlesCited by SciELO

Related links

  • Have no similar articlesSimilars in SciELO

Share


Revista Archivo Médico de Camagüey

On-line version ISSN 1025-0255

Abstract

LAMBERT-MATOS, Yuber; SAGARO-DEL-CAMPO, Nelsa María  and  ZAMORA-MATAMOROS, Larisa. Identification of prognostic factors in cervical cancer by implicative statistical analysis. AMC [online]. 2021, vol.25, n.4, e7956.  Epub Aug 01, 2021. ISSN 1025-0255.

ABSTRACT

Background

: cancer is one of the leading causes of death worldwide. The identification of the prognostic factors involved in its evolution is of great interest for the secondary and tertiary prevention of this frequent entity.

Objective

: to identify the prognostic factors of cervical cancer mortality and evaluate the usefulness of implicative statistical analysis in the clinical-epidemiological investigations of causality.

Methods

: study of cases and controls in 106 women with the clinical and histological diagnosis of cervical cancer treated at the Oncology Hospital of the province Santiago de Cuba from January 2016 to January 2018. The implicative statistical analysis was applied together with the binary logistic regression, which was considered as a gold standard.

Results

: binary logistic regression identified the presence of metastases as the only poor prognostic factor (OR=2.995) and chemotherapy (OR=0.151) and event-free interval (OR=0.602) as good prognostic factors. Implicative statistical analysis detected these same factors, but also identified other poor prognostic factors such as complications, advanced stage, and relapse; all with a 99% of implication intensity.

Conclusions

: this technique reached a high sensitivity and specificity when compared with the regression and was useful for the identification of prognostic factors.

Keywords : UTERINE CERVICAL NEOPLASMS; PROGNOSIS; STATISTICAL ANALYSIS; CASE REPORTS; CAUSALITY..

        · abstract in Spanish     · text in Spanish     · Spanish ( pdf )