Performance of multiple multi-cancer detection tests using a large independent reference set (Alliance A212102)

Marie Wood, Department of Medicine, University of Colorado Cancer Center, Aurora, CO, USA.
Paul F. Pinsky, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA.
Paul Novotny, Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, MN, USA.
Elyse Leevan, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA.
Matthias Weiss, ThedaCare, Appleton, WI, USA.
Dan C. Edelman, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA.
Mark Watson, Department of Pathology, Washington University School of Medicine, St Louis, MO, USA.
Christos Patriotis, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA.
Jason D. Merker, Department of Pathology, UNC-CH School of Medicine, Chapel Hill, NC, USA.
Philip C. Prorok, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA.
Yujia Wen, Alliance Protocol Operations Office, University of Chicago, Chicago, IL, USA.
Wendy S. Rubinstein, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA.
Konstantin Dragnev, Dartmouth Hitchcock Medical Center/Dartmouth Cancer Center, Lebanon, NH, USA.
Amanda L. Skarlupka, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA.
Hormuzd A. Katki, Division of Cancer Epidemiology and Genetics, National Cancer Institute.
Selina Chow, Alliance Protocol Operations Office, University of Chicago, Chicago, IL, USA.
Margaret Kemeny, Queens Hospital Center, Jamaica, NY, USA.
Umang Gautam, Advocate Health - MidwestFollow
Aswanth Reddy, Mercy Hospital Fort Smith, Fort Smith, AR, USA.
William Burak, Memorial Health University Medical Center, Savannah, GA, USA.
Steven Piantadosi, Brigham and Women's, Harvard Medical School, Boston, MA, USA.
Lori M. Minasian, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA.

Affiliations

Aurora BayCare Medical Center

Abstract

Background: Reference sets are needed to evaluate performance of multi-cancer detection (MCD) assays. The National Cancer Institute (NCI) funded the Alliance reference set study to assess MCDs for use in future trials.

Methods: Individuals with cancer and controls were recruited; blood specimens were collected prior to cancer treatment. A performance evaluation study was designed utilizing reference set samples. Companies (n = 6) were selected to participate based on review of performance data and ability to utilize the blood collection tube. Companies received samples from cancer types their assay was designed to detect ("targeted"), plus additional "non-targeted" and control samples. Companies reported positive/negative calls, risk scores, and tissue-of-origin (TOO) predictions. Sensitivity was computed for early (I-II) and late (III-IV) stage cases, based on positive/negative calls (SEPN) and at fixed 98% specificity (SE98). Specificity and TOO accuracy were computed.

Results: 549 cases (encompassing 13 cancer types) and 413 controls from the reference set were included in the study. Companies assessed samples from median 6 (range 5-9) targeted cancer types and median 8 (range: 7-11) overall cancer types. Median (range) specificity was 92.3% (76.5%-98.5%). Median (range) SEPN was 32% (25%-42%) for early stage 73% (48%-89%) for late stage; while median (range) SE98 was 19% (8%-35%) for early stage and 66% (13%-79%) for late stage. Median sensitivity for non-targeted types was 40% (early stage) and 52% (late stage). Median (range) TOO accuracy (primary predicted site) was 75% (64%-78%).

Conclusions: Sensitivity and specificity varied widely across assays with early-stage sensitivity substantially lower than late-stage sensitivity.

Document Type

Article

PubMed ID

41499420

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