A federated approach to identify women with early-stage cervical cancer at low risk of lymph node metastases

An Overview of Real-World Data Infrastructure for Cancer Research

AIMS

There is increasing interest in the opportunities offered by Real World Data (RWD) to provide evidence where clinical trial data does not exist, but access to appropriate data sources is frequently cited as a barrier to RWD research. This paper discusses current RWD resources and how they can be accessed for cancer research.

MATERIALS AND METHODS

There has been significant progress on facilitating RWD access in the last few years across a range of scales, from local hospital research databases, through regional care records and national repositories, to the impact of federated learning approaches on internationally collaborative studies. We use a series of case studies, principally from the UK, to illustrate how RWD can be accessed for research and healthcare improvement at each of these scales.

RESULTS

For each example we discuss infrastructure and governance requirements with the aim of encouraging further work in this space that will help to fill evidence gaps in oncology.

CONCLUSION

There are challenges, but real-world data research across a range of scales is already a reality. Taking advantage of the current generation of data sources requires researchers to carefully define their research question and the scale at which it would be best addressed.

Clinicopathological and radiological stratification within FIGO 2018 stages improves risk-prediction in cervical cancer

OBJECTIVE

Assess the added prognostic value of the updated International Federation of Gynecology and Obstetrics (FIGO) 2018 staging system, and to identify clinicopathological and radiological biomarkers for improved FIGO 2018 prognostication.

METHODS

Patient data were retrieved from a prospectively collected patient cohort including all consenting patients with cervical cancer diagnosed and treated at Haukeland University Hospital during 2001-2022 (n = 948). All patients were staged according to the FIGO 2009 and FIGO 2018 guidelines based on available data for individual patients. MRI-assessed maximum tumor diameter and stromal tumor invasion, as well as histopathologically assessed lymphovascular space invasion were applied to categorize patients according to the Sedlis criteria.

RESULTS

FIGO 2018 stage yielded the highest area under the receiver operating characteristic (ROC) curve (AUC) (0.86 versus 0.81 for FIGO 2009) for predicting disease-specific survival. The most common stage migration in FIGO 2018 versus FIGO 2009 was upstaging from stages IB/II to stage IIIC due to suspicious lymph nodes identified by PET/CT and/or MRI. In FIGO 2018 stage III patients, extent and size of primary tumor (p = 0.04), as well as its histological type (p = 0.003) were highly prognostic. Sedlis criteria were prognostic within FIGO 2018 IB patients (p = 0.04).

CONCLUSIONS

Incorporation of cross-sectional imaging increases prognostic precision, as suggested by the FIGO 2018 guidelines. The 2018 FIGO IIIC stage could be refined by including the size and extent of primary tumor and histological type. The FIGO IB risk prediction could be improved by applying MRI-assessed tumor size and stromal invasion.

Peptidylarginine Deiminase Type 2 Predicts Tumor Progression and Poor Prognosis in Patients with Curatively Resected Biliary Tract Cancer

(1) Background: PADI2 is a post-translational modification (PTM) enzyme that catalyzes citrullination, which then triggers autoimmune disease and cancer. This study aimed to evaluate the prognostic value of peptidylarginine deiminase 2 (PADI2) protein expression in biliary tract cancer (BTC) patients. (2) Methods: Using immunohistochemistry, the PADI2 protein expression in BTC tissues was analyzed. The correlations between PADI2 protein expression and clinicopathologic characteristics were analyzed using Chi-square tests. The Kaplan-Meier procedure was used for comparing survival distributions. We used Cox proportional hazards regression for univariate and multivariate analyses. From 2014 to 2020, 30 resected BTC patients were enrolled in this study. (3) Results: Patients with high PADI2 protein expression were associated with shorter progress-free survival (PFS; p = 0.041), disease-specific survival (DSS; p = 0.025), and overall survival (OS; p = 0.017) than patients with low PADI2 protein expression. (4) Conclusions: The results indicated that PADI2 protein expression was an independent poor prognostic factor for BTC patients regarding PFS, DSS, and OS.