Classifying the diagnosis of study participants in clinical trials: a structured and efficient approach

Tjitske S.R. van Engelen*, Maadrika M.N.P. Kanglie, Inge A.H. van den Berk, Merel L.J. Bouwman, Hind J.M. Suhooli, Sascha L. Heckert, Jaap Stoker, Patrick M.M. Bossuyt, Jan M. Prins, Jouke Annema, Ludo F.M. Beenen, Shandra Bipat, Paul Bresser, Marcel Dijkgraaf, Jos Donker, Tjitske S.R. van Engelen, Betty Frankemölle, Maarten Groenink, Suzanne M.R. Hochheimer, Frits HollemanDorine Hulzebosch, Mitran Keijzers, Ivo van der Lee, Peter Leenhouts, Jan Luitse, Lilian J. Meijboom, Saskia Middeldorp, Alexander Montauban van Swijndregt, Wouter de Monyé, Jacqueline Otker, Milan Ridderikhof, Johannes A. Romijn, Antoinet J.N. Schoonderwoerd, Ralf W. Sprengers, Elizabeth M. Taal, Michiel Winter, For the OPTIMACT Study Group

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Background: A challenge in imaging research is a diagnostic classification of study participants. We hypothesised that a structured approach would be efficient and that classification by medical students, residents, and an expert panel whenever necessary would be as valid as classification of all patients by experts. Methods: OPTIMACT is a randomised trial designed to evaluate the effectiveness of replacing chest x-ray for ultra-low-dose chest computed tomography (CT) at the emergency department. We developed a handbook with diagnostic guidelines and randomly selected 240 cases from 2,418 participants enrolled in OPTIMACT. Each case was independently classified by two medical students and, if they disagreed, by the students and a resident in a consensus meeting. Cases without consensus and cases classified as complex were assessed by a panel of medical specialists. To evaluate the validity, 60 randomly selected cases not referred to the panel by the students and the residents were reassessed by the specialists. Results: Overall, the students and, if necessary, residents were able to assign a diagnosis in 183 of the 240 cases (76% concordance; 95% confidence interval [CI] 71–82%). We observed agreement between students and residents versus medical specialists in 50/60 cases (83% concordance; 95% CI 74–93%). Conclusions: A structured approach in which study participants are assigned diagnostic labels by assessors with increasing levels of medical experience was an efficient and valid classification method, limiting the workload for medical specialists. We presented a viable option for classifying study participants in large-scale imaging trials (Netherlands National Trial Register number NTR6163).

Original languageEnglish
Article number44
JournalEuropean Radiology Experimental
Issue number1
Publication statusPublished - 1 Dec 2020

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