Ralf Pashke, MD, Ph.D

 

 

 

 

Paul Stewardson, Ph.D candidate and Dr. Pashke

Title: Classification of the Thyroid Tumours

Principal applicant: Dr. Ralf Paschke (Endocrinologist, Professor of Medicine and Endocrinology, and chair of the provincial thyroid and neuroendocrine tumour team; Calgary, Alberta)

Aims:

1. Determine the clinical impact of the recently implemented ThyroSPEC mutation panel in terms of mutation specific positive predictive value (PPV), negative predictive value (NPV), unnecessary surgeries avoided, cancers detected that would have been missed, and targeted drug regimens enabled.
2. Identify gaps or deficiencies in the current local thyroid nodule diagnostic pathway and model the improvements generated by solutions for these gaps and deficiencies. Implement the solutions that can be implemented effectively in a centralized thyroid nodule pathway and show improvement to outcomes according to clinically comprehensive models.
3. Generate a clinically applicable classifier that determines the local patient-specific risk at each step in the diagnostic pathway, revealing the statistically optimal treatment course dynamically updated at each stage.

Summary: While thyroid tumours are common, thyroid cancer is rare, and the accurate classification of these tumours as benign or malignant remains a clinical challenge. The best currently available method, fine needle aspiration cytology (FNAC), cannot distinguish between benign and cancerous nodules in 20% of FNACs, thus a “diagnostic” thyroid surgery is required to diagnose the tumour. Of these surgeries, cancer will be found only 20% of the time. The other 80% of FNAC patients will have undergone an unnecessary surgery. Detection of cancer specific mutations helps to detect most of the malignant tumors and helps to identify cancer patients who are eligible for targeted therapies, such as inhibitor drugs that work only on certain mutations. The aim of this project is to further optimize a local thyroid tumour pathway that brings patients with newly identified thyroid tumours the most accurate classification in every step of the pathway, including ultrasound detection, FNAC, mutation profiling, surgery, and post-surgical treatment. This diagnostic combination will help to select thyroid cancers for adequate surgery and could result in follow up instead of diagnostic surgery for patients with negative test outcomes, by giving physicians and patients locally validated best practices in diagnostic criteria according to local data.

Methods: This is a prospective, observational cohort study that will use the anonymized data collected in the QI project. We will compare the clinical, histopathologic, molecular diagnostic, cytologic and ultrasound results of indeterminate thyroid nodules. We will calculate the separate and added sensitivity, specificity, PPV, NPV, positive likelihood ratio, negative likelihood ratio and benign call rate of ThyroSPEC vs. standard of care.