Prognostic and Predictive biomarkers in a Mediterranean cohort (Review from Atena Project) Free

Atena project involved 5,062 women aged 30 to 69 years living in the area of Naples. The purpose of this study is to investigate the causes of those chronic diseases that have a major impact on the female population. As a part of the design (scheduled in 2002-2004). After 10 years, in 228 women, some biochemical measurements were performed.

This systematic review and meta-analysis biomarkers were evaluated in studies nested into the Atena cohort. Studies were searched using MEDLINE/PubMed. The search was performed by entering individually or in combination: Atena, Mediterranean woman, biomarkers. The preferred reporting of systematic reviews and meta-analysis (PRISMA) guidelines were used for the review. Studies selected for this review are conducted in the Atena project Cohort and reported the study of biomarkers. Disagreements on data extractions between the two investigators were solved by consensus. The extracted data were entered and analyzed using REVMAN software. The original articles were described using forest plot and table. Heterogeneity was computed by Cochran’s Q test.

The search strategy retrieved 13 potential articles, 11 were screened as full text articles and 6 were included in the pooled estimates. Among the articles included, biomarkers chosen as predictors were Lipids, Hcrp, as prognostic where predictive of IMT; and cycle length and LPa as predictive of an augmented LDL cholesterol mean. According to the comparability of data presented, for the first comparison we selected 3 of the 5 studies that assed IMT, for the second we selected 2 of the three studies that analyzed for LDL mean. Results were shown into forrest plots. The pooled estimates verified the potential of biomarkers as predictor of IMT, the significance seemed lower for prediction of LDL cholesterol.

Both results, consistent with the multifactor profile of the CV risk, identify the impact of secondary prevention according to biochemical profiles.

• Biomarkers studied in nested cohort stufies have predictive potential.

• pooled estimates may identify the impact of secondary prevention according to biochemical profiles.