How to Avoid Pitfalls in Study Design

A strong research question can still fail if the study design cannot answer it. Michael Soulen, MD, and Shudaveep Ganguly, MD, DM, speak with host Amit Gupta, MD, about selecting meaningful outcomes, matching design to the question, avoiding pitfalls of diagnostic accuracy studies, involving statisticians early, and building multidisciplinary trials. Listen to their discussion in episode 3 of The Early Career Researcher's Playbook, an AJR Podcast Series. *Key Takeaways Meaningful Outcomes vs. Surrogates: Technical success and progression-free survival are only surrogate endpoints. Patients and clinicians ultimately care about overall survival and quality of life. Imaging surrogates are notoriously poor predictors of true clinical benefit. Flaws in Diagnostic Accuracy: Relying purely on sensitivity and specificity is problematic if the study population doesn't reflect real-world conditions. Likelihood ratios may provide a realistic indication of a test's clinical impact. Early Statistical Integration: Never treat a statistician as a data calculator at the end of a study. Engaging them during the brainstorming phase ensures feasibility and helps to properly structures your protocol and database. *Chapters 0:00 - Welcome 2:23 - Choosing Meaningful Outcomes 9:28 - RCTs and Real World Limits 18:36 - Diagnostic Study Pitfalls 25:58 - From Accuracy to Impact 28:55 - Statistics Starts Early 37:45 - Making Collaboration Work 47:01 - Quick Fire Playbook 51:04 - Final Advice Follow AJR on Social Media LinkedIn: https://www.linkedin.com/showcase/ajr-radiology/ YouTube: https://www.youtube.com/channel/UCfFAYezkLMxJGMgIJLN0Dpg Instagram: https://www.instagram.com/ajr_radiology/ TikTok: https://www.tiktok.com/@ajr_radiology X: https://x.com/AJR_Radiology BlueSky: https://bsky.app/profile/ajrradiology.bsky.social Threads: https://www.threads.com/@ajr_radiology *These sections were generated using artificial intelligence (Descript and Google Gemini) and then reviewed for accuracy.