基于群组的轨迹模型评估HR阳性乳腺癌辅助内分泌治疗依从模式:来自里奥格兰德河谷患者的结果
Group-Based Trajectory Model to Assess Adjuvant Endocrine Therapy Adherence Pattern in HR-Positive Breast Cancer: Results from Rio Grande Valley Patients.
作者信息
Fatima Bilqees, Pruneda Phillip Shayne, Mousavi Parasto, Sheriff Rheena, Ozuna Ronnie, Trivedi Meghana V, Abughosh Susan
机构信息
Department of Pharmaceutical Health Outcomes and Policy, College of Pharmacy, University of Houston, Houston, TX 77204, USA.
Department of Pharmacy Practice and Translational Research, College of Pharmacy, University of Houston, Houston, TX 77204, USA.
出版信息
Healthcare (Basel). 2025 Jul 22;13(15):1777. doi: 10.3390/healthcare13151777.
: Adherence to oral endocrine therapy (OET) is essential to reduce recurrence but is predominantly lower among underserved patients, leading to worse health outcomes. We aimed to depict longitudinal patterns of OET adherence using group-based trajectory modeling (GBTM) and identify predictors associated with each adherence trajectory. : A single-center, retrospective study was conducted to analyze data from women 18 years or older with metastatic breast cancer who initiated with an OET and were treated from January to December 2022. Adherence was measured using a proportion of days covered (PDC > 80%) for 12 months. Binary monthly indicator of PDC was incorporated into GBTM. Four models were generated by changing the number of groups from 2 to 5, using a 2nd-order polynomial function of time. A multinomial logistic regression model was run to evaluate the predictors of non-adherence trajectories, and "adherence" was considered the reference group. : A total of 346 women had a (mean age of 60) years; 93% were Hispanic or of Mexican origin; 90% were taking aromatase inhibitors (AIs), with an endocrine therapy of 1.05 years. Three trajectories of adherence to GBTM were identified: a gradual decline in adherence ( = 88, 25.5%), improving suboptimal adherence ( = 106, 30.6%), and adherent ( = 152, 43.9%). Multinomial logistic regression analysis showed that significant predictors are diabetes (odds ratio (OR), 2.96; 95% confidence interval (CI), 1.57-5.57) and fewer years of therapy (OR, 2.96; 95% CI, 1.57-5.57). Suboptimal adherence among RGV patients receiving OET, with approximately 56% following a non-adherent trajectory. : Suboptimal adherence among RGV patients receiving OET, with approximately 56% following a non-adherent trajectory. Significant predictors should be considered when designing targeted interventions.
坚持口服内分泌治疗(OET)对于降低复发风险至关重要,但在医疗服务不足的患者中,治疗依从性普遍较低,这会导致更差的健康结果。我们旨在使用基于群体的轨迹模型(GBTM)描绘OET依从性的纵向模式,并确定与每种依从性轨迹相关的预测因素。
开展了一项单中心回顾性研究,以分析2022年1月至12月期间开始接受OET治疗的18岁及以上转移性乳腺癌女性的数据。依从性通过12个月的覆盖天数比例(PDC>80%)来衡量。PDC的二元月度指标被纳入GBTM。通过将组的数量从2组改为5组,使用时间的二阶多项式函数生成了四个模型。运行多项逻辑回归模型以评估不依从轨迹的预测因素,并将“依从性”作为参照组。
共有346名女性(平均年龄60岁);93%为西班牙裔或墨西哥裔;90%正在服用芳香化酶抑制剂(AIs),内分泌治疗时间为1.05年。确定了GBTM的三种依从性轨迹:依从性逐渐下降(n = 88,25.5%)、次优依从性改善(n = 106,30.6%)和依从(n = 152,43.9%)。多项逻辑回归分析表明,显著的预测因素是糖尿病(比值比(OR),2.96;95%置信区间(CI),1.57 - 5.57)和治疗年限较少(OR,2.96;95% CI,1.57 - 5.57)。接受OET的里奥格兰德河谷(RGV)患者中存在次优依从性,约56%遵循不依从轨迹。
接受OET的RGV患者中存在次优依从性,约56%遵循不依从轨迹。在设计针对性干预措施时应考虑显著的预测因素。
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本文引用的文献
JAMA Netw Open. 2024-5-1
Breast Cancer Res Treat. 2024-7
Cureus. 2023-12-26
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Cancers (Basel). 2023-8-21