A 2019/2020 Summer Studentship research project
We anticipate that our study will provide useful information for clinicians as to the sensitivity of pleural fluid cytology in the New Zealand context and allow comparison with international standards. In addition, if cancer is not proven on the first procedure in a substantial proportion of patients with pleural malignancy it provides a clear rationale for improving diagnostic pathways.
Student: Lorna Pairman
Supervisors: Dr Michael Maze, Professor Lutz Beckert, Department of Medicine, UOC; Dr Mark Dagger, Department of Pathology, CDHB
Sponsor: Cancer Society Cheviot, Westport and Ellesmere Groups
Pleural fluid cytology has imperfect sensitivity for the diagnosis of pleural malignancy but remains the recommended first diagnostic test for pleural effusions that are suspected to be malignant. Novel strategies for the management pleural effusion and the advent of pleural ultrasound provide an opportunity to improve diagnostic pathways for pleural malignancy.
We aim to establish a local estimate of the sensitivity of pleural fluid cytology.
We will audit the 150 patients who presented with an undiagnosed malignant pleural effusion prior to 31 October 2019. We will identify these patients through the pleural procedure logbook on the Respiratory Ward, which captures patient identifiers for every patient undergoing a pleural procedure. We will collect basic demographic data, as well as relevant radiographic and pathologic data from the patient information system (Health Connect South).
Information would be collected on to a standardized case report form and entered into a database. Patient details will be de-identified when entered onto the case report form, and will remain de-identified in the database. The database will be backed up onto the password protected University server. Sensitivity will be estimated by calculating the proportion of patients with proven pleural malignancy whose pleural cancer was diagnosed on their pleural fluid cytology from their first pleural procedure.
Student researcher’s component of the study
The student will perform data collection, and a supervised data analysis. They will write a first draft of a manuscript for publication in a peer reviewed journal.
Medical student with reasonable IT skills. Some statistics knowledge is an advantage.
How to apply