Investigating the relationship between breast cancer and the postmenopausal period: a systematic meta-analysis

Abstract

One possible explanation for the ongoing debate surrounding breast cancer risk factors is that differences in assessment methodologies lead to conflicting results. One way to address methodological differences in assessment between studies is to use a single standardized assessment to calibrate cancer studies. To achieve this goal, we conducted a meta-analysis, integrating findings from various studies that utilized menopause risk factors in the evaluation of breast cancer cases. We conducted a systematic literature review from 2010 to 2023 and included studies that examined the association between the postmenopausal period and breast cancer. Among the results, we found statistically significant evidence that the postmenopausal period has a positive association with breast cancer. We identified and carefully reviewed 49 articles considered relevant in the literature review and 12 met all of our inclusion and exclusion criteria. The intercept value was 0.768 (positive), indicating a significant degree of heterogeneity between the studies. The standard error (0.209) suggests that the effect size estimation is more precise and reliable across studies. The observed log odds ratios ranged from -0.1716 to 2.0202, with the majority of estimates being positive (92%). The estimated average log odds ratio based on the random-effects model was 0.7679 (95% Confidence Interval (CI): 0.3590 to 1.1768). Therefore, the average outcome significantly differed from zero (z = 3.6809, p < 0.001). Kendall's Tau value was 0.455, and the p-value was 0.045, indicating a positive, statistically significant and moderate relationship between breast cancer and the postmenopausal period. The results obtained in this study carry significant implications for shaping public health policies and breast cancer screening programs. Understanding breast cancer cases in the postmenopausal period holds substantial importance in devising tailored treatment strategies. These findings can provide valuable insights for the enhancement of clinical practice, allowing for more effective and individualized treatment approaches.