Vaidya Shrutangi, Atal Shubham, Joshi Rajnish
MBBS Student, All India Institute of Medical Sciences (AIIMS), Bhopal, Madhya Pradesh, India.
Department of Pharmacology, College Building, All India Institute of Medical Sciences (AIIMS), Bhopal, Madhya Pradesh, India.
J Family Med Prim Care. 2024 Nov;13(11):5090-5100. doi: 10.4103/jfmpc.jfmpc_605_24. Epub 2024 Nov 18.
Uncontrolled diabetes persists despite guideline-based treatment, partly attributed to inadequate patient involvement. This research addresses shared decision-making by eliciting patient preferences in Type 2 Diabetes Mellitus (T2DM) treatment based on certain key attributes and explores their correlation with socio-demographic-clinical profiles.
A discrete choice experiment (DCE) was conducted among T2DM outpatients in an Indian tertiary care center. A choice card was developed using the contextual choice framework, having six second-line antidiabetic drugs (ADs) from different classes incorporating seven attributes. Face-to-face interviews were conducted with patients, and elicited preferences were analyzed using descriptive statistics, Chi-square analysis, and multinomial logistic regression.
Out of the 87 evaluated participant choices, the most preferred drug was Glimepiride (51.7%), followed by Dapagliflozin (22.9%) and Teneligliptin (17.2%). Overall, the most important attributes were the effect on weight (29%), followed by route of administration (24%), and additional benefits offered by the drug (18%). Significant associations were found between participants' drug preferences and their age ( = 0.002), socioeconomic status ( = 0.04), occupation ( = 0.004), and monthly income ( = 0.03). Age was not a significant predictor of drug choice for any of the drugs. Multinomial logistic regression showed that the overall model was statistically significant ( = 0.025), and it correctly predicted drug choice for 58.6% of the participants.
Glimepiride was the most preferred option overall while the effect on weight was the most important attribute for patients in determining their preference. The study highlighted the importance of shared decisions and can guide practitioners in considering patient preferences when prescribing antidiabetic drugs.
尽管采用了基于指南的治疗方法，但糖尿病仍未得到有效控制，部分原因是患者参与度不足。本研究通过在2型糖尿病（T2DM）治疗中基于某些关键属性引出患者偏好来解决共同决策问题，并探讨其与社会人口统计学 - 临床特征的相关性。
在印度一家三级护理中心对T2DM门诊患者进行了离散选择实验（DCE）。使用情境选择框架开发了一张选择卡，其中包含六种来自不同类别的二线抗糖尿病药物（ADs），涵盖七个属性。对患者进行面对面访谈，并使用描述性统计、卡方分析和多项逻辑回归分析引出的偏好。
在87个评估的参与者选择中，最受欢迎的药物是格列美脲（51.7%），其次是达格列净（22.9%）和替格列汀（17.2%）。总体而言，最重要的属性是对体重的影响（29%），其次是给药途径（24%）和药物提供的额外益处（18%）。发现参与者的药物偏好与其年龄（= 0.002）、社会经济地位（= 0.04）、职业（= 0.004）和月收入（= 0.03）之间存在显著关联。年龄不是任何一种药物选择的显著预测因素。多项逻辑回归表明，总体模型具有统计学意义（= 0.025），并且它正确预测了58.6%参与者的药物选择。
总体而言，格列美脲是最受欢迎的选择，而对体重的影响是患者确定偏好时最重要的属性。该研究强调了共同决策的重要性，并可指导从业者在开具抗糖尿病药物时考虑患者偏好。
