Justin J. Badal, MD

Justin J. Badal, MD

Baylor College of Medicine

Houston, Texas

Justin J. Badal, MD, is a urologic surgeon and the Assistant Professor of Urology at Baylor College of Medicine in Houston, Texas. Dr. Badal has clinical interests in managing prostate and kidney cancers with minimally invasive techniques. His research interests focus on the cross-section of medicine and emerging technologies, including the development of advanced robotic skills to remain at the forefront of medical education and oncologic care for genitourinary malignancies.

Dr. Badal earned his medical degree from Baylor College of Medicine, working closely with the medical school's leadership and serving as President of the Medical Student Council and the Director of the medical school's student mentorship network. Dr. Badal completed an internship and residency in General Surgery and served as Chief Resident for Urologic Surgery at the University of California, Davis, and subsequently completed a fellowship in Robotic Surgery and Urologic Oncology at the City of Hope Cancer Center in Duarte, California. Dr. Badal has authored numerous peer-reviewed publications in urology and robotic surgery, with his work widely cited in the field.

Dr. Badal is also interested in cognitive behavioral education and how to amplify compassionate, empathetic approaches in medical education. He was awarded the Lehmann Outstanding Medical Student Award in 2015 for his leadership contributions to the Medical School. Throughout his medical education, Dr. Badal volunteered time at Houston Outreach Medicine, Education, and Social Services Clinic (HOMES), a student-run Federally Qualified Healthcare Center (FQHC) located in downtown Houston, Texas,  serving people experiencing homelessness.

Talks by Justin J. Badal, MD

Key Principles from the 2024 AUA Guidelines Updates on Salvage Prostate Cancer Therapy

Key Principles from the 2024 AUA Guidelines Updates on Salvage Prostate Cancer Therapy

| Jan 2025

Justin J. Badal, MD, reviews the updated 2024 guidelines for advanced prostate cancer, reflecting substantial advancements since the last revision in 2013. The revision synthesizes evidence from numerous trials to reshape recommendations, focusing particularly on treatment strategies for biochemical recurrence (BCR) following radical prostatectomy.

In this 18-minute presentation, Badal shares guidelines emphasizing utilizing prognostic factors, such as PSA doubling time and Gleason grade, to stratify patient risk and guide treatment timing. He notes that ultra-sensitive PSA testing for high-risk individuals and PET imaging, particularly PSMA PET scans, is recognized as valuable tools for detecting biochemical recurrence.

The integration of androgen deprivation therapy (ADT) with SRT is advised for patients showing high-risk features, while, for those without high-risk markers, radiation monotherapy remains an option. For recurrent or node-positive cases post-primary therapy, combined modality approaches, including the use of expanded radiation fields and intensified androgen receptor suppression, are encouraged within a clinical trial setting.

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Diagnosing Renal Masses: Do Advanced Imaging Techniques and Biomarkers Play an Important Role?

Diagnosing Renal Masses: Do Advanced Imaging Techniques and Biomarkers Play an Important Role?

| Aug 2024

Justin J. Badal, MD, explores the prognostic and predictive value of biomarkers and imaging in the diagnosis of renal conditions. He begins by reviewing the history of biomarkers and their use in the diagnosis and treatment of renal conditions.

Dr. Badal then addresses potential predictive uses of renal condition biomarkers. He presents data from the Checkmate 025 and INmotion150 studies which did not support the predictive value of certain prognostic biomarkers, and future directions for identifying predictive biomarkers.

Dr. Badal concludes with an overview of the effectiveness of combining biomarker detection with imaging technologies to improve prognostic and predictive accuracy. He presents data from the ZIRCON study, and discusses the potential integration of AI in biomarker detection.

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Cognitive Bias in Practice and Training

Cognitive Bias in Practice and Training

| Jul 2024

Justin J. Badal, MD, examines the impact of cognitive bias in medical training and practice on clinical decision-making, diagnostic accuracy, and patient outcomes. He begins by defining cognitive bias, and analyzing common biases, including:

Representativeness Bias
Misconception of Regression Bias
Availability Bias
Adjustment and Anchoring Bias

Dr. Badal demonstrates examples of the impact of each bias in diagnostic testing, clinical decision-making, and patient outcomes. He concludes by making recommendations for counteracting cognitive bias in practice with evidence that bias training improves overall clinician performance.

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Diagnosing Renal Masses: Do Advanced Imaging Techniques and Biomarkers Play an Important Role?

Diagnosing Renal Masses: Do Advanced Imaging Techniques and Biomarkers Play an Important Role?

| Dec 2023

Justin J. Badal, MD, explores how advancements in imaging techniques and biomarkers enhance diagnostic accuracy, inform treatment decisions, and potentially improve patient outcomes. He acknowledges the limitations of traditional imaging modalities, such as ultrasound and computed tomography (CT), and emphasizes the need for more precise tools.
Multiparametric MRI (mpMRI), positron emission tomography (PET) combined with CT or MRI, and the use of biomarkers are all analyzed. These advanced diagnostic tools have the potential to enhance diagnostic accuracy, guide treatment decisions, and ultimately improve patient outcomes. They are a significant step forward in the personalized management of renal cancer.

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Cognitive Bias in Training and Practice

Cognitive Bias in Training and Practice

| Dec 2023

Justin J. Badal, MD, examines the impact of cognitive bias in medical training and practice on clinical decision-making, diagnostic accuracy, and patient outcomes. He begins by defining cognitive bias, and analyzing common biases, including:

Representativeness Bias
Misconception of Regression Bias
Availability Bias
Adjustment and Anchoring Bias

Dr. Badal demonstrates examples of the impact of each bias in diagnostic testing, clinical decision-making, and patient outcomes. He concludes by making recommendations for counteracting cognitive bias in practice with evidence that bias training improves overall clinician performance.

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