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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
From exclusion to inclusion: Analysis of patterns of follow-up in breast cancer
N Hariharan1, T S Rao1, S J Rajappa2
1Department of Surgical Oncology, Basavatarakam Indo American Cancer Hospital & Research Institute, Hyderabad, India.
Introduction:
Follow-up data in breast cancer is essential and forms the basis for survival metrics and key statistical measures related to morbidity and mortality. Standard practice classifies any woman who does not engage in reviews/follow-up as "lost to follow-up (LTFU)," effectively excluding her from further analysis and disregarding her data. This study aims to evaluate patterns and predictors of LTFU among women with non-metastatic breast cancer.
Design:
This is a single-center prospective cohort study involving women diagnosed with non-metastatic breast cancer between 2017 and 2018. The study will follow a three-phase approach. In Phase I, 5-year follow-up data will be collected retrospectively through hospital records and electronic medical records (EMRs) up to 2024. In Phase II, patients identified as LTFU will be contacted using phone, SMS, or email to assess health status and update follow-up data. Informed consent will be obtained during outreach. In Phase III, patients who respond will be asked about reasons for missed follow-up visits, including barriers related to logistics, finance, awareness, or physician advice. Data will be analyzed using descriptive statistics, logistic regression, and thematic analysis.
Objectives:
To determine the proportion of patients who are lost-to-follow-up at 5 years, identify factors associated with LTFU, and explore patient-reported barriers to follow-up in a public sector cancer care setting.
Discussion:
This study uses a mixed-methods approach, combining quantitative tracking with qualitative insights, with the aim of understanding patient retention and long-term oncology care. This study will provide real-world evidence on follow-up adherence and its determinants in a high-volume, resource-constrained oncology setting. The study is registered with ClinicalTrials.gov (Trial identifier: NCT06927102).
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