Russell P. Harris, MD, MPH; Timothy J. Wilt, MD, MPH; Amir Qaseem, MD, PhD, MHA; for the High Value Care Task Force of the American College of Physicians (*)
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Disclosures: Authors followed the policy regarding conflicts of interest described at www.annals.org/article.aspx?articleid=745942. Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M14-2327. A record of conflicts of interest is kept for each High Value Care Task Force meeting and conference call and can be viewed at http://hvc.acponline.org/clinrec.html.
Requests for Single Reprints: Amir Qaseem, MD, PhD, MHA, American College of Physicians, 190 N. Independence Mall West, Philadelphia, PA 19106; e-mail, email@example.com.
Current Author Addresses: Dr. Harris: Research Center for Excellence in Clinical Preventive Services, Cecil B. Sheps Center for Health Services Research, University of North Carolina, 725 Martin Luther King Jr. Boulevard, CB 7590, Chapel Hill, NC 27599.
Dr. Wilt: Minneapolis Veterans Affairs Health Care System and the Center for Chronic Disease Outcomes Research, 1 Veterans Drive (111-0), Minneapolis, MN 55417.
Dr. Qaseem: American College of Physicians, 190 N. Independence Mall West, Philadelphia, PA 19106.
Author Contributions: Conception and design: R.P. Harris, T.J. Wilt, A. Qaseem.
Analysis and interpretation of the data: R.P. Harris, T.J. Wilt, A. Qaseem.
Drafting of the article: R.P. Harris, A. Qaseem.
Critical revision of the article for important intellectual content: R.P. Harris, T.J. Wilt, A. Qaseem.
Final approval of the article: R.P. Harris, T.J. Wilt, A. Qaseem.
Statistical expertise: R.P. Harris, A. Qaseem.
Obtaining of funding: T.J. Wilt, A. Qaseem.
Administrative, technical, or logistic support: R.P. Harris, T.J. Wilt, A. Qaseem.
Collection and assembly of data: R.P. Harris, T.J. Wilt.
Experts, professional societies, and consumer groups often recommend different strategies for cancer screening. These strategies vary in the intensity of their search for asymptomatic lesions and in their value. This article outlines a framework for thinking about the value of varying intensities of cancer screening. The authors conclude that increasing intensity beyond an optimal level leads to low-value screening and speculate about pressures that encourage overly intensive, low-value screening.
The value framework.
The value of cancer screening strategies is linked to screening intensity (population screened, frequency, and sensitivity of test used) and is determined by the balance among benefits (e.g., cancer mortality reduction), harms (e.g., anxiety from false-positive test results, harms of diagnostic procedures, labeling, and overdiagnosis leading to overtreatment), and costs. Low-value care can result from either low benefits or high harms and costs. Low-intensity strategies are initially low-value due to low benefits (left). As intensity increases, benefits increase rapidly with acceptable levels of harms and costs, and value follows an upward trend. Screening strategies provide optimal value when the informed patient or public believes that the balance between benefits and harms or costs is optimal (middle). The top of the value curve is flat because different patients or groups may view different intensities as providing the best balance. Further increases in screening intensity beyond the optimal level lead to slower increases in benefits, with disproportionately rapid increases in harms and costs. Thus, value decreases; higher-intensity screening becomes low-value screening (right).
The screening cascade.
Screening is not a single test but a cascade of events that can lead to either benefit or harm. The screening test may yield a positive result, a negative result, or an incidental finding (negative for the target condition but with some other abnormality). Patients with an incidental finding are referred for an appropriate work-up. Patients with a positive result for the target condition are referred for further diagnostic testing (work-up). This leads to a diagnosis in some patients (true-positive result), who are then referred for treatment. However, diagnosis is not the same as benefit. Depending on the need for treatment and the relative effectiveness of earlier (screening detection) versus later (clinical detection) treatment, 4 possible outcomes may occur with treatment after a true-positive result (bottom row, left to right). Earlier treatment leads to benefit, with longer or higher-quality life. The other 3 scenarios provide no benefit, for various reasons. The patient could have rapidly progressive, untreatable disease and would not benefit from earlier detection. Alternatively, the patient could have mild, easily treatable disease and could be treated just as effectively even if the cancer is clinically detected later. Finally, the patient could have either nonprogressive (or slowly progressive) cancer or severe competing mortality risk from another condition and thus would never develop clinically important symptoms from the detected cancer (also known as “overdiagnosis”). Thus, in 3 of the 4 potential outcomes after screening detection and treatment, there is no benefit. Also, every step of the cascade has potential harms, which are immediate, whereas benefits occur only after diagnosis. (Adapted from Harris and colleagues .)
Heterogeneity of cancer cases and patients.
Cases of the same type of cancer are heterogeneous in their natural history and response to treatment. Patients are also heterogeneous in their response to treatment and in the presence of serious noncancer health risks. The figure depicts the rate of disease progression for 4 hypothetical patients through 3 zones: not detectable, detectable but not symptomatic, and symptomatic. Screening episodes are represented by the vertical dashed lines, but screening detection (solid circles) occurs only in the second zone (detectable but not symptomatic). For patient 1, progression is rapid; the cancer may or may not be detected by screening because it spends little time in the detectable but not symptomatic zone. Patient 2 has cancer with an intermediate rate of progression, making it a good target for screening. This cancer has the potential to cause important clinical symptoms (top), and if treatment is more effective in the presymptomatic phase, the treatment bends the natural history curve and the patient benefits from earlier detection. Patient 3 has slowly growing cancer that will not cause symptoms during his or her lifetime. Patient 4 has serious noncancer health risks that decrease life expectancy and prevent benefit from detection of cancer. Because the cancer spends more time in the detectable but not symptomatic zone for patients 3 and 4, it is more likely to be detected by screening than patient 1's cancer; however, the earlier detection is not beneficial because these patients will die of another condition. Patients 3 and 4 are overdiagnosed and usually overtreated, both important harms of screening.
Table. Pressures to Use Low-Value Screening Strategies
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Harris RP, Wilt TJ, Qaseem A, for the High Value Care Task Force of the American College of Physicians. A Value Framework for Cancer Screening: Advice for High-Value Care From the American College of Physicians. Ann Intern Med. 2015;162:712-717. doi: 10.7326/M14-2327
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Published: Ann Intern Med. 2015;162(10):712-717.
Cancer Screening/Prevention, Guidelines, Hematology/Oncology, Prevention/Screening.
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