Treatment patterns and outcomes in breast cancer patients: real world evidence
Yanin Chavarri-Guerra1, Siddhartha Kar2 and Tanja Cufer3
1Department of Hemato-Oncology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubiran, Mexico City, Mexico
2Department of Oncology, University of Cambridge, Cambridge, UK
3Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
Corresponding author: Yanin Chavarri-Guerra Email: yanin.chavarrig@incmnsz.mx
Breast cancer is the leading cause of cancer death worldwide. In 2020, 2,621,419 new cases were diagnosed, and 684,996 deaths from breast cancer occurred [1]. The global burden of breast cancer is expected to increase, especially in low- and middle-income countries where the economic cost of cancer treatment limits the access to high quality care. By 2040 the number of new breast cancer cases is expected to increase 47.4% in Latin America and 80.7% in Africa [1]. Therefore, the need for highly effective evidence regarding breast cancer treatment is a priority.
Clinical trials are considered gold standard for assessing efficacy, they provide precise measures of efficacy and toxicity outcomes and have a high internal validity. However, the cost of developing a clinical trial is high. The number and characteristics of patients that are included in a clinical trial is restricted; resulting in a highly selected population. Therefore, external validity of underrepresented groups such as older and vulnerable patients is reduced and do not necessarily represent routine clinical practice. In addition, clinical trials’ capacity to detect long term or rare side effects is limited [2].
On the other hand, real world data (RWD) includes a significant number of patients in routine clinical practice with a high external validity. It provides new evidence of effectiveness in the general population. The cost of RWD is low and can be collected relatively quickly allowing for the detection of new and long-term adverse events. RWD limitations include selection bias, variability of data quality and a significant proportion of missing data [2]. RWD is defined by the US FDA as “the data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources” [3]. RWD sources include electronic health records, health claims datasets surveys and population registries. In addition, the wide use of internet social media, wearable devices and health-related mobile applications have increased the diversity of sources of RWD [4].
Due to the limitations of clinical trial evidence, regulatory and health technology assessment agencies are increasingly considering real world evidence to address questions related to effectiveness, cost effectiveness and safety of treatments as well as to support the approval of new indications of approved drugs, to satisfy post-approval study requirements and to use it in the process of reimbursement decision making [3].
In the last few decades, breast cancer treatment has progressed enormously and the number of treatments that are available and approved by regulatory agencies is very large. Even in the frame of the clinical trials some of those treatments showed limited clinical benefit, while their value for patients treated in everyday clinical practice remains unknown. The value of RWD has become very important to understand treatment patterns and outcomes of these new treatments among patients with frequent cancers, such as breast cancer [5]. This Special Issue is dedicated to RWD in patients with breast cancer, including BRCA mutated breast cancer, triple negative breast cancer, treatment with poly ADP-ribose polymerase inhibitors, and CDK4/6 inhibitors in patients with advanced stage hormone receptor positive breast cancer as well as a very interesting and novel strategy to downstage breast cancer at diagnosis with a telephone counselling helpline.
References
[1] Ferlay J, Ervik M, Lam F, Colombet M, Mery L, Piñeros M, Znaor A, Soerjomataram I, Bray F (2020). Global Cancer Observatory: Cancer Today. Lyon, France: International Agency for Research on Cancer. Available from: https://gco.iarc.fr/today, accessed [10 November 2023].
[2] US Food and Drug Administration, et al. Real-World Evidence. 2022. https://www.fda.gov/science-research/science-and-research-specialtopics/real- world-evidence. Accessed on November 8, 2023.
[3] Tang M, Pearson SA, Simes RJ, Chua BH. Harnessing Real-World Evidence to Advance Caner Research. Curr Oncol 2023; 30:1844-1859
[4] Liu F, Panagiotakos D. Real-world data: a brief review of the methods, applications, challenges and opportunities. BMC Medical Research Methodology 2022; 22: 287
[5] Cottu P, Ramsey SD, Solà-Morales O, et al. The emerging role of real-world data in advanced breast cancer therapy: Recommendations for collaborative decision-making. The Breast 2022;61:118-122
