Data Harmonization for Collaborative Research Among Australian and US Registries: A Case Study in Medullary Thyroid...

Area of Science:

• Oncology
• Endocrinology
• Data Science

Background:

• Medullary thyroid cancer (MTC) is a rare neuroendocrine tumor, accounting for 1-2% of thyroid malignancies.
• Its aggressive nature and rarity necessitate large datasets for comprehensive understanding.
• Data harmonization is crucial for standardizing diverse information from multiple sources.

Purpose of the Study:

• To assess the feasibility of international collaboration, data mapping, and harmonization for medullary thyroid cancer (MTC) research.
• To establish a unified dataset for analyzing MTC characteristics.
• To identify pre-operative factors associated with cervical lymph node metastases in MTC.

Main Methods:

• Retrospective data harmonization using Maelstrom guidelines across three clinical networks in Australia and the US (2018-2021).
• Categorization of data into exact, close, or low matches, with exact and close matches forming the harmonized dataset.
• Logistic regression analysis to determine pre-operative factors linked to cervical lymph node metastases.

Main Results:

• Data from 114 MTC patients across 17 hospitals were harmonized, with 80.8% of data points deemed suitable.
• Prevalence of palpable lymph node involvement was 15.8% in the harmonized dataset.
• Younger age (<55 years) and abnormal ultrasound findings were associated with metastases; incidental MTC diagnosis showed lower metastasis odds.

Conclusions:

• International data mapping and harmonization are feasible, enabling meaningful analyses not possible with isolated datasets.
• The Maelstrom guidelines offer an efficient framework for achieving data harmonization.
• This study serves as a white paper for rare disease researchers on sharing heterogeneous data and fostering collaboration.