Fernández L, Buch M L, Molina A, Carabelloso M, Gausioso R, Lage A
Neoplasma. 1986;33(4):535-41.
The evolution of mammography has provided possibilities for mass screening programs. Early diagnosis is considered the most important factor in reducing the breast cancer mortality but the mass screening is very expensive if we include all female population. In this paper we show the results of an early diagnosis pilot study with a multivariate data analysis. Data concerning risk factors (age, age at menarche, menopause, parity, age at first childbirth, lactation, abortions and previous benign breast disease) were recorded in 438 patients with breast carcinoma and 1750 patients with benign breast diseases diagnosed in the Early Diagnosis Pilot Program at the National Institute of Oncology and Radiobiology in Cuba. A group of 449 healthy women living in Havana City was also studied. Age and age at first childbirth were the major factor considered. Multivariate data analysis allowed to build stratification trees identifying subgroups with different breast cancer incidence. The usefulness of these stratifications for screening with optimal coverage, sufficiency and efficacy, is discussed.
乳腺钼靶摄影术的发展为大规模筛查计划提供了可能性。早期诊断被认为是降低乳腺癌死亡率的最重要因素,但如果将所有女性人群都纳入,大规模筛查的成本非常高。在本文中,我们展示了一项采用多变量数据分析的早期诊断试点研究的结果。在古巴国家肿瘤与放射生物学研究所的早期诊断试点项目中,记录了438例乳腺癌患者和1750例乳腺良性疾病患者的风险因素(年龄、初潮年龄、绝经、产次、首次生育年龄、哺乳、流产及既往乳腺良性疾病)。还对居住在哈瓦那市的449名健康女性进行了研究。主要考虑的因素是年龄和首次生育年龄。多变量数据分析有助于构建分层树,识别出具有不同乳腺癌发病率的亚组。讨论了这些分层对于以最佳覆盖率、充分性和有效性进行筛查的实用性。