Other Approaches to Assessing the Value of Imaging

Although sensitivity, specificity, and accuracy commonly are used to characterize the tumor detection process, other metrics may be of greater importance. For example, some studies have focused on how often imaging substantially changes management. This type of study is of great practical interest, but the optimal methods to assess such changes in treatment decisions are evolving. Ideally one would like to show that the use of imaging, especially a new imaging technology, when applied randomly to half of the study population, provided a reduction in the number of adverse events in the imaged population, improved survival, or had comparable outcomes at lower costs than standard treatments. As an example, a reduction in the number of “futile thoracotomies” has been used as a metric of success for PET versus CT in planning the treatment of newly diagnosed lung cancer.⁷ Ideally, randomization of patients to imaged versus not imaged groups can be shown to improve survival. Performance of randomized trials in which a portion of the patients undergo imaging and the other patients do not undergo imaging (or they obtain different types of imaging), with an end point of survival, will be of great interest. Unfortunately, such studies are complex or impossible, because management of patients after imaging may be altered markedly on the basis of imaging results. Thus it can be difficult to separate the imaging study effect from the treatment effect. Ultimately, however, for some imaging studies to be adopted, such evaluations of survival will be needed. This point is particularly relevant to screening, as will be discussed later.

Recently, registry data have been applied with substantial benefit to determine if planned or actual patient management is altered through the use of imaging tests. The National Oncologic PET Registry has provided a great deal of information on the use of FDG-PET imaging in the management of patients with a variety of cancers. The National Oncologic PET Registry collected questionnaire data from referring physicians on intended patient management before and after PET. After 1 year, the cohort included data from 22,975 studies (83.7% PET/CT) from 1178 centers. Overall, physicians changed their intended management in 36.5% (95% confidence interval [CI] 35.9-37.2) of cases after PET, supporting the usefulness of PET for cancer imaging in registry cases, which are from a wide range of sources.⁸

Screening Concepts and Challenges

Screening programs for cancer often have taken the form of laboratory tests such as the Papanicolaou (Pap) smear, or, more recently, blood tests for tumor markers. The success of the Pap smear in reducing mortality rates from cervical cancer is incontrovertible. The use of imaging in screening for cancer is an example of success and considerable interest, but also a source of considerable controversy. As discussed in detail in the chapters on breast cancer (see Chapter 91) and lung cancer (see Chapter 72), screening programs have been shown to be capable of saving lives in women older than 50 years. These programs also may save lives in women 40 to 50 years of age, but the data are less compelling.⁹

Studies have been initiated in which CT scanning is used in an attempt to detect early lung cancer.¹⁰ Screening high-risk populations with CT imaging has recently been proven to reduce lung cancer–specific mortality in the National Lung Cancer Screening Trial (NLST). This finding follows results from the Early Lung Cancer Action Project (ELCAP), a large study screening patients at increased risk of lung cancer with low-dose CT, which reported promising results in 1999.¹¹ The ELCAP showed that lung cancers are detected at a smaller size and that patients whose cancers are detected by screening live longer after diagnosis than do patients whose tumors are not detected by screening. Whether this outcome translates into longer-term survival for the screened population remains unclear. The ELCAP study further evaluated 31,567 asymptomatic persons at risk for lung cancer using low-dose CT from 1993 through 2005 and from 1994 through 2005; 27,456 repeated screenings were performed.¹² A diagnosis of lung cancer was made in 484 participants based on screening. Of particular note, 412 patients (85%) had clinical stage I lung cancer. Ten-year survival approached 90% in this group.^11,12 This study demonstrated that annual spiral CT screening can detect lung cancer that is curable.

Another large randomized trial of lung cancer screening, the NLST, was reported in 2011.¹³ In this trial, 53,454 persons at high risk for lung cancer were enrolled from more than 30 U.S. sites. Study participants were randomly assigned to undergo three annual screenings with either low-dose CT (26,722 participants) or single-view posteroanterior chest radiography (26,732). In the CT-screened and chest radiograph–screened groups, 24.2% and 6.9%, respectively, had positive screening studies at some point. A high false-positive screening rate occurred; 96.4% of the positive screening results in the low-dose CT group and 94.5% in the radiography group were false positives. The incidence of lung cancer was significantly higher (1060 vs. 941 cancers) in the low-dose CT group compared with the chest radiograph group. There were 247 deaths from lung cancer per 100,000 person-years in the low-dose CT group and 309 deaths per 100,000 person-years in the radiography group, representing a relative reduction in mortality from lung cancer with low-dose CT screening of 20.0% (95% CI 6.8-26.7; P = .004). The rate of death from any cause was reduced in the low-dose CT group compared with the radiography group by 6.7% (95% CI 1.2-13.6; P = .02).

This exciting trial has raised some controversies, because the vast majority of small pulmonary nodules identified are not malignant, the costs of the trial and of the medical care for incidentally detected lesions are substantial, and a substantial radiation burden, which, in principle, could be carcinogenic, is delivered to patients who undergo the screening. However, there is considerable hope that screening programs can achieve a reduction in lung cancer mortality because the radiation is given to patients later in their lives when the risks of radiation-induced cancers are reduced.

Based on the findings of the NLST, many centers have offered lung cancer screening clinics for high-risk patients. However, a risk for lower risk patients is that screening may have an unacceptably high false-positive rate. It is important to note that the promising results of the NLST are for a higher risk population and extrapolations of benefit to lower risk populations may be highly problematic.

As discussed later in this chapter, CT colonography holds excellent promise as a screening method for colon cancer as an alternative to optical colonoscopy and is increasingly paid for by health insurers based on its good accuracy.

Screening with noninvasive imaging has also been performed for colorectal cancer, for which virtual colonoscopy can be used to look for early colon cancers, and in the pelvis in women who are at risk for ovarian cancer. More recently, screening CT centers offering a virtual evaluation of the entire body have become available, and even more recently, magnetic resonance imaging (MRI) and PET screening have been offered in some locales. The growth of these centers has been driven by emotional and economic factors; these tests are not yet well founded scientifically in the screening setting. In some cultures, screening imaging is done more commonly than in others. The risk of false-positive results in patients at low risk for cancer is substantial.

Screening carries challenges, risks, and costs that are beyond the scope of this overview chapter. However, several key points apply to all screening approaches, including those using noninvasive imaging. These points include (1) whether a screening program is reasonable to consider; (2) lead time bias; (3) length bias; (4) the overall economic cost implications of screening, especially the costs of investigating false-positive results; and (5) the risk that radiation used in screening may include subsequent cancers.

The requirements that a screening program must meet to be considered “reasonable” may differ substantially based on the specific society’s values and a specific individual’s perception of risk. However, in general, the following characteristics are important for cancer screening:

Further, the imaging test itself must be acceptable to patients (in terms of level of discomfort and cost), and it must be sufficiently sensitive to identify cancer often and sufficiently specific to minimize false-positive results. Finally, the costs of the screening process—and attendant costs related to false-positive examinations—must be compatible with the economic resources of the society or individual, and the screening procedure must pose little or no risk to the patient.⁴

Another important consideration in screening programs is lead time bias. This concept, simply stated, indicates that if the natural history of a disease is unchanged, but the diagnosis is made earlier in the course of the illness, the apparent survival will be improved. For example, let us assume that tumor X has a 6-year natural history from its beginning until the death of the patient, and that treatment is ineffective. The disease might become clinically detectable after 4 years and lead to death in 6 years, with a 2-year survival after diagnosis. With screening, if the tumor is detected 3 years after the onset of disease and no improvement in treatment occurs, then the survival in the screened population would appear to increase from 2 to 3 years after diagnosis. This illusion of improved survival in the screened population is a considerable concern and can lead to inappropriate enthusiasm for screening programs.⁴

Another important consideration in screening is the possibility of length bias, which is a more complex concept, but it may be related to the types of cancer that can be detected by screening programs. A possibility is that very rapidly growing and presumably highly lethal cancers are less likely to be detected by annual screening programs, whereas more slowly growing cancers, which have an intrinsically better prognosis, may be detected more frequently by screening. In fact, some of the early cancers discovered by screening may not be biologically relevant at all. If so, the patients with cancers identified in the screened population could appear to have a better survival than the patients with cancers identified in the unscreened population, as is the case for prostate cancer screening by prostate-specific antigen (PSA), for example, for which major concerns exist regarding overdiagnosis of slow-growing cancers that are presumed to be indolent and might not require surgery.¹⁴

A third factor is the selection bias that is difficult to control for in retrospective observational studies—that is, how the patients and their referring physicians determined that a scan should be performed. Selection bias occurs when unintended differences exist between the groups observed that—while associated with the variable used to sort the groups (for example, exposure in case-control studies and outcome in cohort studies)—affect measurement of the study variable.¹⁵ For instance, in a case-control design on the effects on disease-specific mortality of a particular screening program, investigators would examine records from patients who have died from the disease in question versus those who have not died, and then determine the rates of the screening intervention in these two populations.

It is possible that the persons likeliest to have sought screening were the ones at highest risk for the disease. Results for the effect of the screening on mortality could be underestimated in such a scenario. Selection bias also can work in the opposite direction, when the persons with a high risk/poor prognosis are less likely to seek screening. With the relative absence of large randomized prospective trials, as is commonly the case when evaluating imaging as a screening tool, we may be tempted to base our conclusions on cohort or case-control studies. However, the most accurate conclusions would be drawn from a prospective randomized study design.

Collectively, lead time bias and length bias and, at times, selection bias can make screening programs appear to improve the survival of patients with cancer. Because of these major biases intrinsic in screening, very large, randomized studies are required to show that overall cancer-specific mortality (and ideally mortality from all causes) declines as a result of screening programs.

All-cause mortality is a critical parameter. If the treatment of a presumed tumor discovered by a screening imaging test carries with it a risk of death or morbidity, the screening program could lower cancer-specific mortality but not all-cause mortality. If the screened population is very young, late adverse effects of screening may be difficult to detect, such as slightly increased risks of cancer due to radiation.

The advent of imaging and other screening tools that uncover a tumor long before it is symptomatic also brings up the need for biomarker discovery to help physicians determine whether to treat what has been discovered through screening. The experience with PSA screening in prostate cancer serves to illustrate the point that not all cancers identified by screening eventually lead to death. Discovering and validating biomarkers that can help to distinguish reliably between lethal and nonlethal tumor types will be of great help in reducing unnecessary treatment in patients with less active disease. Identifying and phenotyping tumors of the greatest risk for progression is of great importance because it is clear that not all cancers carry the same risk of mortality if left untreated.

Screening Costs

The determination of whether a screening program is valuable to society is often, in part, based on its cost and benefit. The concept of quality-adjusted life-years (QALYs) often is applied. This concept is defined as the economic cost to society required to result in 1 additional year of quality life for a member of the society. In many Western countries, a figure of $50,000 has been considered a useful guide, with QALYs costing less than this amount considered cost-effective. Such a guideline, however, does not necessarily apply when individuals make their own determinations about whether to pay for a screening test. For example, it is reasonable to expect that persons with greater disposable income would be willing to pay more per QALY than would persons with less disposable income. Thus it can be difficult to generalize about the cost efficacy of screening procedures.¹⁶

Even when people choose to undergo a screening test at their own expense, considerable costs can be transferred to society as a result of the screening program. For example, if a screening test has a high rate of false-positive results, a substantial number of follow-up biopsies or procedures will occur and can cost a great deal of money. Such costs can dramatically raise the total cost per QALY. Invasive procedures also can increase the likelihood of morbidity or death as a result of additional investigations. To determine the true cost per QALY associated with screening, these additional costs and risks must be considered. Thus screening remains an area of great promise but also of considerable controversy.

Screening beyond breast imaging must overcome major hurdles before it is likely to be accepted. Overcoming such hurdles appears to be occurring for virtual colonoscopy and increasingly so for CT scanning of the lungs in persons at high risk for lung cancer. However, it is quite possible that in high-risk patient groups (such as those with a family history of cancer or major carcinogen exposure, with a high penetrance or early onset), screening may prove of greater value than in the general population. For example, MRI screening in patients at high risk for breast cancer is increasingly accepted as appropriate.