Skip to main content
main-content

01.12.2018 | Research article | Ausgabe 1/2018 Open Access

BMC Cancer 1/2018

Using Resistin, glucose, age and BMI to predict the presence of breast cancer

Zeitschrift:
BMC Cancer > Ausgabe 1/2018
Autoren:
Miguel Patrício, José Pereira, Joana Crisóstomo, Paulo Matafome, Manuel Gomes, Raquel Seiça, Francisco Caramelo
Wichtige Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s12885-017-3877-1) contains supplementary material, which is available to authorized users.

Abstract

Background

The goal of this exploratory study was to develop and assess a prediction model which can potentially be used as a biomarker of breast cancer, based on anthropometric data and parameters which can be gathered in routine blood analysis.

Methods

For each of the 166 participants several clinical features were observed or measured, including age, BMI, Glucose, Insulin, HOMA, Leptin, Adiponectin, Resistin and MCP-1. Machine learning algorithms (logistic regression, random forests, support vector machines) were implemented taking in as predictors different numbers of variables. The resulting models were assessed with a Monte Carlo Cross-Validation approach to determine 95% confidence intervals for the sensitivity, specificity and AUC of the models.

Results

Support vector machines models using Glucose, Resistin, Age and BMI as predictors allowed predicting the presence of breast cancer in women with sensitivity ranging between 82 and 88% and specificity ranging between 85 and 90%. The 95% confidence interval for the AUC was [0.87, 0.91].

Conclusions

These findings provide promising evidence that models combining age, BMI and metabolic parameters may be a powerful tool for a cheap and effective biomarker of breast cancer.
Zusatzmaterial
Additional file 1: R script with the algorithm implementation. (ZIP 330 kb)
12885_2017_3877_MOESM1_ESM.zip
Literatur
Über diesen Artikel

Weitere Artikel der Ausgabe 1/2018

BMC Cancer 1/2018 Zur Ausgabe

Neu im Fachgebiet Onkologie

Mail Icon II Newsletter

Bestellen Sie unseren kostenlosen Newsletter Update Onkologie und bleiben Sie gut informiert – ganz bequem per eMail.

Bildnachweise