Zhijun Yin1, Morgan Harrell2, Jeremy L Warner1,3, Qingxia Chen1,4, Daniel Fabbri1,5, Bradley A Malin1,4,5. 1. Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 2. Roam Analytics, San Mateo, California, USA. 3. Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 4. Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 5. Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA.
Abstract
Objective: Online platforms have created a variety of opportunities for breast patients to discuss their hormonal therapy, a long-term adjuvant treatment to reduce the chance of breast cancer occurrence and mortality. The goal of this investigation is to ascertain the extent to which the messages breast cancer patients communicated through an online portal can indicate their potential for discontinuing hormonal therapy. Materials and Methods: We studied the de-identified electronic medical records of 1106 breast cancer patients who were prescribed hormonal therapy at Vanderbilt University Medical Center over a 12-year period. We designed a data-driven approach to investigate patients' patterns of messaging with healthcare providers, the topics they communicated, and the extent to which these messaging behaviors associate with the likelihood that a patient will discontinue a prescribed 5-year regimen of therapy. Results: The results indicates that messaging rate over time [hazard ratio (HR) = 1.373, P = 0.002], mentions of side effects (HR = 1.214, P = 0.006), and surgery-related topics (HR = 1.170, P = 0.034) were associated with increased risk of early medication discontinuation. In contrast, seeking professional suggestions (HR = 0.766, P = 0.002), expressing gratitude to healthcare providers (HR = 0.872, P = 0.044), and mentions of drugs used to treat side effects (HR = 0.807, P = 0.013) were associated with decreased risk of medication discontinuation. Discussion and Conclusion: This investigation suggests that patient-generated content can inform the study of health-related behaviors. Given that approximately 50% of breast cancer patients do not complete a course of hormonal therapy as described, the identification of factors associated with medication discontinuation can facilitate real-time interventions to prevent early discontinuation.
Objective: Online platforms have created a variety of opportunities for breast patients to discuss their hormonal therapy, a long-term adjuvant treatment to reduce the chance of breast cancer occurrence and mortality. The goal of this investigation is to ascertain the extent to which the messages breast cancerpatients communicated through an online portal can indicate their potential for discontinuing hormonal therapy. Materials and Methods: We studied the de-identified electronic medical records of 1106 breast cancerpatients who were prescribed hormonal therapy at Vanderbilt University Medical Center over a 12-year period. We designed a data-driven approach to investigate patients' patterns of messaging with healthcare providers, the topics they communicated, and the extent to which these messaging behaviors associate with the likelihood that a patient will discontinue a prescribed 5-year regimen of therapy. Results: The results indicates that messaging rate over time [hazard ratio (HR) = 1.373, P = 0.002], mentions of side effects (HR = 1.214, P = 0.006), and surgery-related topics (HR = 1.170, P = 0.034) were associated with increased risk of early medication discontinuation. In contrast, seeking professional suggestions (HR = 0.766, P = 0.002), expressing gratitude to healthcare providers (HR = 0.872, P = 0.044), and mentions of drugs used to treat side effects (HR = 0.807, P = 0.013) were associated with decreased risk of medication discontinuation. Discussion and Conclusion: This investigation suggests that patient-generated content can inform the study of health-related behaviors. Given that approximately 50% of breast cancerpatients do not complete a course of hormonal therapy as described, the identification of factors associated with medication discontinuation can facilitate real-time interventions to prevent early discontinuation.
Authors: Guergana K Savova; Ioana Danciu; Folami Alamudun; Timothy Miller; Chen Lin; Danielle S Bitterman; Georgia Tourassi; Jeremy L Warner Journal: Cancer Res Date: 2019-08-08 Impact factor: 12.701
Authors: Davy Weissenbacher; Suyu Ge; Ari Klein; Karen O'Connor; Robert Gross; Sean Hennessy; Graciela Gonzalez-Hernandez Journal: J Am Med Inform Assoc Date: 2021-11-25 Impact factor: 4.497
Authors: Slavica Janeva; Toshima Z Parris; Salmir Nasic; Shahin De Lara; Karolina Larsson; Riccardo A Audisio; Roger Olofsson Bagge; Anikó Kovács Journal: BMC Cancer Date: 2021-04-21 Impact factor: 4.430