Can a single tube of blood really detect dozens of cancers before symptoms appear? We dive into the science behind Galleri, a blood test that claims to detect more than 50 types of cancer from a simple blood draw. Recent headlines about the test ranged from “breakthrough” to “bust” after the release of results from a massive randomized clinical trial. In this Part 1 episode, we explore cell-free DNA, DNA methylation, machine learning, sensitivity, specificity, and positive predictive value. Along the way, we revisit the prenatal screening revolution, ask why detecting cancer earlier doesn’t always help patients, and learn how escaped DNA convicts end up swimming in a giant molecular pool party. And for the first time ever, Normal Curves ends on a cliffhanger: we’ll save the controversial results of that landmark trial for Part 2.

Statistical topics

• cancer screening
• case-control studies
• counterfactuals
• machine learning
• negative predictive value
• overdiagnosis
• positive predictive value
• randomized clinical trials
• screening tests
• sensitivity and specificity
• validation

References

• Bianchi DW, Chudova D, Sehnert AJ, et al. Noninvasive prenatal testing and incidental detection of occult maternal malignancies. JAMA. 2015; 314:162-9. 
• Liu MC, Oxnard GR, Klein EA, et al. Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA. Ann Oncol. 2020. 31:745-59. 
• Schrag D, Beer T, McDonnell C et al. Blood-based tests for multicancer early detection (PATHFINDER): a prospective cohort study.The Lancet. 402: 1251-60.
• Giridhar KV, et al. Safety and performance results from PATHFINDER 2, a registrational study of a multi-cancer early detection test in an intended-use population. Presented at the 2026 American Society of Clinical Oncology (ASCO) Annual Meeting. May 2026.

Statistic discussed in the episode

PATHFINDER 2 investigators reported that adding Galleri to routine screening increased the number of screen-detected cancers by 6.5-fold. This figure compares 31 cancers detected through USPSTF-recommended screening (for breast, cervical, lung, and colon) with 204 cancers detected when Galleri was added, counting the same 31 conventional-screening cancers in both totals. Thus, describing the increase as 6.5-fold is misleading, since the combination of Galleri plus conventional screening is, by definition, guaranteed to detect at least as many cancers as conventional screening alone. Moreover, everyone in the study received Galleri, whereas conventional screening depended on which tests participants happened to be due for and completed during the study period. The comparison therefore does not involve two equally applied screening strategies.

Kristin and Regina’s online courses: 

Demystifying Data: A Modern Approach to Statistical Understanding  

Clinical Trials: Design, Strategy, and Analysis 

Medical Statistics Certificate Program  

Writing in the Sciences 

Epidemiology and Clinical Research Graduate Certificate Program 

Programs that we teach in:

Epidemiology and Clinical Research Graduate Certificate Program 

Find us on:

Kristin –  LinkedIn & Twitter/X

Regina – LinkedIn &ReginaNuzzo.com

• (00:00) – – Introduction
• (00:44) – – The Holy Grail of Cancer Testing
• (04:31) – – Headlines: Same Data, Opposite Stories
• (07:38) – – How Cell-Free DNA Works
• (13:54) – – DNA Methylation: GRAIL’s Fingerprint
• (15:19) – – The Origin Story
• (22:18) – – The Pathfinder Studies
• (35:01) – – The Paradox: Why Earlier Detection Doesn’t Always Help
• (40:32) – – The Cliffhanger