Improving Diagnosis and Care for Patients With Sarcoma: Do Real-World General Practitioners Data and Prospective Data Collections Have a Place Next to Clinical Trials?

There has been growing interest in the use of real-world data (RWD) to address clinically and policy-relevant (research) questions that cannot be answered with data from randomized controlled trials (RCTs) alone. This is, for example, the case in rare malignancies such as sarcomas as limited patient numbers pose challenges in conducting RCTs within feasible timeliness, a manageable number of collaborators, and statistical power. This narrative review explores the potential of RWD to generate real-world evidence (RWE) in sarcoma research, elucidating its application across different phases of the patient journey, from prediagnosis to the follow-up/survivorship phase.

The prediagnostic general practitioner care of sarcoma patients: A real-world data study.

Background: Limited understanding exists regarding early sarcoma symptoms presented during general practitioner (GP) consultations. The study explores GP visit patterns and recorded diagnoses in the 12 months preceding sarcoma diagnosis.

Methods: Sarcoma cases diagnosed from 2010 to 2020 were identified through the Netherlands Cancer Registry alongside general practice data.

Real-world data of HER2-low metastatic breast cancer: A population based cohort study.

Background: With the introduction of investigational human epidermal growth factor receptor 2 (HER2) targeting treatments, thorough understanding of breast cancer with different HER2 expression levels is critical. The aim of this study was to compare clinicopathologic characteristics and survival of patients with metastatic breast cancer according to the level of HER2 expression.

Methods: Women with distant metastatic breast cancer during 2008-2016 were selected from PALGA, the Dutch Pathology Registry, and linked to the PHARMO Database Network.

Risk Factor Clusters and Cardiovascular Disease in High-Risk Patients: The UCC-SMART Study.

Background: Clustering of vascular risk factors, i.e., the co-existence of two or more risk factors, has been associated with a higher risk of cardiovascular disease (CVD) in the general population.