Cahir Caitriona, Barron Thomas I, Sharp Linda, Bennett Kathleen
Division of Population Health Sciences, Royal College of Surgeons in Ireland, Beaux Lane House, Mercer Street Lower, Dublin 2, Ireland.
Trinity College Dublin, Ireland and Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Cancer Causes Control. 2017 Mar;28(3):215-225. doi: 10.1007/s10552-017-0851-9. Epub 2017 Feb 16.
To investigate whether demographic, clinical and treatment-related risk factors known at treatment initiation can be used to reliably predict future hormonal therapy non-persistence in women with breast cancer, and to inform intervention development.
Women with stage I-III breast cancer diagnosed 2000-2012 and prescribed hormonal therapy were identified from the National Cancer Registry Ireland (NCRI) and linked to pharmacy claims data from Ireland's Primary Care Reimbursement Services (PCRS). Non-persistence was defined as a treatment gap of ≥180 days within 5 years of initiation. Seventeen demographic, clinical and treatment-related risk factors, identified from a systematic review, were abstracted from the NCRI-PCRS dataset. Multivariate binomial models were used to estimate relative risks (RR) and risk differences (RD) for associations between risk factors and non-persistence. Calibration and discriminative performance of the models were assessed. The analysis was repeated for early non-persistence (<1 year of initiation).
Within 5 years of treatment initiation 680 women (19.9%) were non-persistent. Women aged <50 years (adjusted RR 1.41, 95% CI 1.16-1.70) and those prescribed antidepressants (RR 1.22, 95% CI 1.04-1.45) had increased risk of non-persistence. Married women (RR 0.82 95% CI 0.71-0.94) and those with prior medication use (RR 0.62 95% CI 0.51-0.75) had reduced risk of non-persistence. The area under the receiver-operating characteristic (ROC) curve for non-persistence was 0.61. Findings were similar for early non-persistence.
The risk prediction model did not discriminate well between women at higher and lower risk of non-persistence at treatment initiation. Future studies should consider other factors, such as psychological characteristics and experience of side-effects.
探讨在开始治疗时已知的人口统计学、临床和治疗相关风险因素是否可用于可靠预测乳腺癌女性未来激素治疗的不持续性，并为干预措施的制定提供依据。
从爱尔兰国家癌症登记处（NCRI）识别出2000年至2012年诊断为I - III期乳腺癌并接受激素治疗的女性，并将其与爱尔兰初级医疗报销服务（PCRS）的药房报销数据相关联。不持续性定义为开始治疗后5年内治疗间隔≥180天。从NCRI - PCRS数据集中提取了从系统评价中确定的17个人口统计学、临床和治疗相关风险因素。使用多变量二项式模型估计风险因素与不持续性之间关联的相对风险（RR）和风险差异（RD）。评估模型的校准和判别性能。对早期不持续性（开始治疗<1年）重复进行分析。
在开始治疗的5年内，680名女性（19.9%）出现不持续性。年龄<50岁的女性（调整后RR 1.41，95%CI 1.16 - 1.70）和开具抗抑郁药的女性（RR 1.22，95%CI 1.04 - 1.45）不持续性风险增加。已婚女性（RR 0.82，95%CI 0.71 - 0.94）和既往有用药史的女性（RR 0.62，95%CI 0.51 - 0.75）不持续性风险降低。不持续性的受试者工作特征（ROC）曲线下面积为0.61。早期不持续性的结果相似。
风险预测模型在开始治疗时对不持续性风险较高和较低的女性区分效果不佳。未来研究应考虑其他因素，如心理特征和副作用经历。
