The relationship between vitamin D and breast cancer is still controversial. The present meta-analysis examines the effects of the 25(OH)D, 1,25(OH)2D and vitamin D intake on breast cancer risk. For this purpose, a PubMed, Scopus and Web of Science-databases search was conducted including all papers published with the keywords “breast cancer” and “vitamin D” with at least one reported relative risk (RR) or odds ratio (OR). In total sixty eight studies published between 1998 and 2018 were analyzed. Information about type of study, hormonal receptors and menopausal status was retrieved. Pooled OR or RR were estimated by weighting individual OR/RR by the inverse of their variance Our study showed a protective effect between 25 (OH) D and breast cancer in both cohort studies (RR = 0.85, 95%CI:0.74–0.98) and case-control studies (OR = 0.65, 95%CI: 0.56–0.76). However, analyzing by menopausal status, the protective vitamin D – breast cancer association persisted only in the premenopausal group (OR = 0.67, 95%CI: 0.49–0.92) when restricting the analysis to nested case-control studies. No significant association was found for vitamin D intake or 1,25(OH)2D. Conclusion: This systematic review suggests a protective relationship between circulating vitamin D (measured as 25(OH) D) and breast cancer development in premenopausal women.

Colorectal cancer (CRC) screening of the average risk population is only indicated according to age. We aim to elaborate a model to stratify the risk of CRC by incorporating environmental data and single nucleotide polymorphisms (SNP). The MCC-Spain case-control study included 1336 CRC cases and 2744 controls. Subjects were interviewed on lifestyle factors, family and medical history. Twenty-one CRC susceptibility SNPs were genotyped. The environmental risk model, which included alcohol consumption, obesity, physical activity, red meat and vegetable consumption, and nonsteroidal anti-inflammatory drug use, contributed to CRC with an average per factor OR of 1.36 (95% CI 1.27 to 1.45). Family history of CRC contributed an OR of 2.25 (95% CI 1.87 to 2.72), and each additional SNP contributed an OR of 1.07 (95% CI 1.04 to 1.10). The risk of subjects with more than 25 risk alleles (5th quintile) was 82% higher (OR 1.82, 95% CI 1.11 to 2.98) than subjects with less than 19 alleles (1st quintile). This risk model, with an AUROC curve of 0.63 (95% CI 0.60 to 0.66), could be useful to stratify individuals. Environmental factors had more weight than the genetic score, which should be considered to encourage patients to achieve a healthier lifestyle.

IntroductionThe evidence on the relationship between breast cancer and different types of antihypertensive drugs taken for at least 5 years is limited and inconsistent. Furthermore, the debate has recently been fueled again with new data reporting an increased risk of breast cancer among women with a long history of use of antihypertensive drugs compared with nonusers.MethodsIn this case-control study, we report the antihypertensive drugs–breast cancer relationship in 1,736 breast cancer cases and 1,895 healthy controls; results are reported stratifying by the women’s characteristics (i.e., menopausal status or body mass index category) tumor characteristics and length of use of antihypertensive drugs.ResultsThe relationship among breast cancer and use of calcium channel blockers (CCB) for 5 or more years had odds ratio (OR) = 1.77 (95% CI, 0.99 to 3.17). Stratifying by BMI, the OR increased significantly in the group with BMI ≥ 25 (OR 2.54, 95% CI, 1.24 to 5.22). CCBs were even more strongly associated with more aggressive tumors, (OR for invasive tumors = 1.96, 95% CI = 1.09 to 3.53; OR for non ductal cancers = 3.97, 95% CI = 1.73 to 9.05; OR for Erbb2+ cancer = 2.97, 95% CI: 1.20 to 7.32). On the other hand, premenopausal women were the only group in which angiotensin II receptor blockers may be associated with breast cancer (OR = 4.27, 95% CI = 1.32 to 13.84) but this could not be identified with any type or stage. Use of angiotensin-converting-enzyme inhibitors, beta blockers and diuretics were not associated with risk.ConclusionsIn this large population-based study we found that long term use of calcium channel blockers is associated with some subtypes of breast cancer (and with breast cancer in overweight women).

Prostate cancer (PCa) is the second most common cancer among men worldwide. Its etiology remains largely unknown compared to other common cancers. We have developed a risk stratification model combining environmental factors with family history and genetic susceptibility. 818 PCa cases and 1,006 healthy controls were compared. Subjects were interviewed on major lifestyle factors and family history. Fifty-six PCa susceptibility SNPs were genotyped. Risk models based on logistic regression were developed to combine environmental factors, family history and a genetic risk score. In the whole model, compared with subjects with low risk (reference category, decile 1), those carrying an intermediate risk (decile 5) had a 265% increase in PCa risk (OR = 3.65, 95% CI 2.26 to 5.91). The genetic risk score had an area under the ROC curve (AUROC) of 0.66 (95% CI 0.63 to 0.68). When adding the environmental score and family history to the genetic risk score, the AUROC increased by 0.05, reaching 0.71 (95% CI 0.69 to 0.74). Genetic susceptibility has a stronger risk value of the prediction that modifiable risk factors. While the added value of each SNP is small, the combination of 56 SNPs adds to the predictive ability of the risk model.

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The potential protective effect of Renin-angiotensin system (RAS) inhibitors is a subject of increasing interest due to their possible role as chemopreventive agents against colorectal cancer (CRC). To evaluate this association, we conducted a case-control study with 2,165 cases of colorectal cancer, diagnosed between 2007 and 2012, and 3,912 population controls frequency matched (by age, sex and region) from the Spanish multicenter case-control study MCC-Spain. We found a significant protective effect of the Angiotensin-converting enzyme Inhibitors (ACEIs) against CRC, limited to the under-65 years group (OR=0.65 95%CI (0.48-0.89)) and to a lesser degree to men (OR=0.81 95%CI (0.66-0.99). In contrast, the angiotensin receptor blockers (ARBs) did not show a significant effect. Regarding the duration of use, a greater protection was observed in men as the length of consumption increases. In contrast, in the under-65 stratum, the strongest association was found in short-term treatments. Finally, by analyzing ACEIs effect by colon subsite, we found no differences, except for under 65 years old, where the maximum protection was seen in the proximal intestine, descending in the distal and rectum (without statistical significance). In conclusion, our study shows a protective effect on CRC of the ACEis limited to males and people under 65 years old, which increases in proximal colon in the latter. If confirmed, these results may suggest a novel approach to proximal CRC prevention, given the shortcomings of colonoscopy screening in this location.

This study evaluates several feature ranking techniques together with some classifiers based on machine learning to identify relevant factors regarding the probability of contracting breast cancer and improve the performance of risk prediction models for breast cancer in a healthy population. The dataset with 919 cases and 946 controls comes from the MCC-Spain study and includes only environmental and genetic features. Breast cancer is a major public health problem. Our aim is to analyze which factors in the cancer risk prediction model are the most important for breast cancer prediction. Likewise, quantifying the stability of feature selection methods becomes essential before trying to gain insight into the data. This paper assesses several feature selection algorithms in terms of performance for a set of predictive models. Furthermore, their robustness is quantified to analyze both the similarity between the feature selection rankings and their own stability. The ranking provided by the SVM-RFE approach leads to the best performance in terms of the area under the ROC curve (AUC) metric. Top-47 ranked features obtained with this approach fed to the Logistic Regression classifier achieve an AUC = 0.616. This means an improvement of 5.8% in comparison with the full feature set. Furthermore, the SVM-RFE ranking technique turned out to be highly stable (as well as Random Forest), whereas relief and the wrapper approaches are quite unstable. This study demonstrates that the stability and performance of the model should be studied together as Random Forest and SVM-RFE turned out to be the most stable algorithms, but in terms of model performance SVM-RFE outperforms Random Forest.

Introduction Systemic lupus erythematosus (SLE) has been described as an independent risk factor for the development of cardiovascular (CV) disease. Recently, the QRESEARCH risk estimator version 3 (QRISK3) calculator has been launched for CV risk assessment in the general population. QRISK3 now includes the presence of SLE as one of its variables for calculating CV risk. Our objective was to compare the predictive capacity between QRISK3 and the Systematic Coronary Risk Assessment (SCORE) for the presence of subclinical carotid atherosclerosis in patients with SLE. Methods 296 patients with SLE were recruited. The presence of subclinical atherosclerosis was evaluated by carotid ultrasound to identify carotid plaque and the thickness of the carotid intima media (cIMT). QRISK3 and SCORE were calculated. The relationship of QRISK3 and SCORE with each other and with the presence of subclinical carotid atherosclerosis (both carotid plaque and cIMT) was studied. Results There was no correlation between SCORE and QRISK3 in patients with SLE (Rho Spearman r= -0.008, p= 0.90). Although QRISK3 showed a statistically significant correlation with cIMT (Rho Spearman r = 0.420, p= 0.000), this relationship was not found between SCORE and cIMT (Rho Spearman r= -0.005, p= 0.93). The discrimination capacity of QRISK3 for the presence of carotid plaque was statistically significant and superior to that of SCORE (AUC 0.765 [95% CI 0.711–0.820] vs 0.561 [95% CI 0.494–0.629], p= 0.000). Conclusion QRISK3 discrimination for subclinical atherosclerosis is higher than that of SCORE. QRISK3, and not SCORE, should be used for the calculation of CV risk in patients with SLE.