William E. Barlow, Cancer Research and Biostatistics, Seattle, WA
Elisabeth F. Beaber, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
Berta M. Geller, Departments of Family Medicine, and the University of Vermont Cancer Center, University of Vermont, Burlington, VT
Aruna Kamineni, Kaiser Permanente Washington Health Research Institute, Seattle, WA
Yingye Zheng, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
Jennifer S. Haas, Division of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Dana Farber, Harvard Cancer Institute, Harvard School of Public Health, Boston, MA
Chun R. Chao, Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA
Carolyn M. Rutter, RAND Corporation, Santa Monica, CA
Ann G. Zauber, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY
Brian L. Sprague, Departments of Surgery and Radiology, University of Vermont, Burlington, VT
Ethan A. Halm, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX Simmons Comprehensive Cancer Center, Dallas, TX
Donald L. Weaver, Department of Pathology and the UVM Cancer Center, University of Vermont, Burlington, VT
Jessica Chubak, Kaiser Permanente Washington Health Research Institute, Seattle, WA
V Paul Doria-Rose, Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, Healthcare Delivery Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD
Sarah Kobrin, Healthcare Delivery Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD
Tracy Onega, Departments of Biomedical Data Science, Epidemiology, and the Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH
Virginia P. Quinn, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, and CMC VA Medical Center, Philadelphia, PA
Marilyn M. Schapira, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, and CMC VA Medical Center, Philadelphia, PA
Anna N A Tosteson, The Dartmouth Institute for Health Policy and Clinical Practice and Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH
Douglas A. Corley, Division of Research, Kaiser Permanente Northern California, Oakland, CA
Celette Sugg Skinner, Simmons Comprehensive Cancer Center, Dallas, TX, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX
Mitchell D. Schnall, Department of Radiology, University of Pennsylvania, Perelman School of Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA
Katrina Armstrong, General Medicine Division, MA General Hospital, Harvard Medical School, Boston, MA
Cosette M. Wheeler, Departments of Pathology and Obstetrics and Gynecology, University of New Mexico Health Science Center, Albuquerque, NMUniversity of New Mexico Comprehensive Cancer Center, Albuquerque, NM
Michael J. Silverberg, Division of Research, Kaiser Permanente Northern California, Oakland, CA
Bijal A. Balasubramanian, Simmons Comprehensive Cancer Center, Dallas, TX UTHealth School of Public Health, Dallas, TX
Chyke A. Doubeni, Department of Family Medicine and Community Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
Dale McLerran, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
Jasmin A. Tiro, Simmons Comprehensive Cancer Center, Dallas, TX, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX

Document Type

Article

Publication Date

3-1-2020

Abstract

BACKGROUND: Cancer screening is a complex process encompassing risk assessment, the initial screening examination, diagnostic evaluation, and treatment of cancer precursors or early cancers. Metrics that enable comparisons across different screening targets are needed. We present population-based screening metrics for breast, cervical, and colorectal cancers for nine sites participating in the Population-based Research Optimizing Screening through Personalized Regimens consortium.

METHODS: We describe how selected metrics map to a trans-organ conceptual model of the screening process. For each cancer type, we calculated calendar year 2013 metrics for the screen-eligible target population (breast: ages 40-74 years; cervical: ages 21-64 years; colorectal: ages 50-75 years). Metrics for screening participation, timely diagnostic evaluation, and diagnosed cancers in the screened and total populations are presented for the total eligible population and stratified by age group and cancer type.

RESULTS: The overall screening-eligible populations in 2013 were 305 568 participants for breast, 3 160 128 for cervical, and 2 363 922 for colorectal cancer screening. Being up-to-date for testing was common for all three cancer types: breast (63.5%), cervical (84.6%), and colorectal (77.5%). The percentage of abnormal screens ranged from 10.7% for breast, 4.4% for cervical, and 4.5% for colorectal cancer screening. Abnormal breast screens were followed up diagnostically in almost all (96.8%) cases, and cervical and colorectal were similar (76.2% and 76.3%, respectively). Cancer rates per 1000 screens were 5.66, 0.17, and 1.46 for breast, cervical, and colorectal cancer, respectively.

CONCLUSIONS: Comprehensive assessment of metrics by the Population-based Research Optimizing Screening through Personalized Regimens consortium enabled systematic identification of screening process steps in need of improvement. We encourage widespread use of common metrics to allow interventions to be tested across cancer types and health-care settings.

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