Yang Hannah P, Murphy Kelsey R, Pfeiffer Ruth M, George Neena, Garcia-Closas Montserrat, Lissowska Jolanta, Brinton Louise A, Wentzensen Nicolas
Am J Epidemiol. 2016 May 1;183(9):800-14. doi: 10.1093/aje/kwv308. Epub 2016 Apr 15.
Previous studies have shown that a greater number of ovulatory cycles, cumulatively summed as lifetime number of ovulatory cycles (LOC), increases ovarian cancer risk, but there is no uniform algorithm with which to compute LOC. The association between LOC and endometrial cancer is less certain. Accordingly, we identified 14 different LOC algorithms in a literature review and calculated LOCs in the Polish Cancer Study (2001-2003). We evaluated the associations of LOC with ovarian and endometrial cancer risks using unconditional logistic regression, with and without adjustment for individual risk factors used in the LOC computations. Our analysis included 302 ovarian cancer cases with 1,356 controls and 532 endometrial cancer cases with 1,286 controls. We found a high correlation between LOC values among the combined controls (r ≥ 0.88) and identified 5 groups of similar LOC algorithms. A LOC value in the highest quartile was associated with ovarian cancer risk as computed by 2 algorithms (odds ratio (OR) = 2.22 (95% confidence interval (CI): 1.07, 4.62) and OR = 2.44 (95% CI: 1.22, 4.87)) and with endometrial cancer risk as computed by 1 algorithm (OR = 1.95, 95% CI: 1.11, 3.44). LOC algorithms using a core set of variables widely available in epidemiologic studies may be independently associated with risk of gynecological cancers beyond the contribution of the individual risk factors, such as ages at menopause and menarche.
以往的研究表明,排卵周期数量越多,累计计算为一生排卵周期数(LOC),会增加卵巢癌风险,但尚无统一的算法来计算LOC。LOC与子宫内膜癌之间的关联尚不确定。因此,我们在文献综述中确定了14种不同的LOC算法,并在波兰癌症研究(2001 - 2003年)中计算了LOC。我们使用无条件逻辑回归评估了LOC与卵巢癌和子宫内膜癌风险的关联,同时对LOC计算中使用的个体风险因素进行了调整和未调整。我们的分析包括302例卵巢癌病例和1356例对照,以及532例子宫内膜癌病例和1286例对照。我们发现合并对照中LOC值之间存在高度相关性(r≥0.88),并确定了5组相似的LOC算法。最高四分位数的LOC值与2种算法计算的卵巢癌风险相关(优势比(OR)= 2.22(95%置信区间(CI):1.07,4.62)和OR = 2.44(95% CI:1.22,4.87)),与1种算法计算的子宫内膜癌风险相关(OR = 1.95,95% CI:1.11,3.44)。使用流行病学研究中广泛可用的一组核心变量的LOC算法可能独立于个体风险因素(如绝经和初潮年龄)的贡献,与妇科癌症风险相关。