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PRINCIPLES OF SCREENING
SCREENING
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PRINCIPLES OF SCREENING Craig Nielsen, MD, and Richard S. Lang, MD, MPH
Physicians are asked to perform many tasks, which primarily have been directed at diagnosis, treatment, and management of disease processes. Increasingly, they have become involved in the area of preventive medicine. Conceptually, preventive medicine encompasses three tasks for the clinician: screening, counseling, and immunization or chemoprophylaxis. Although touching on all of these areas, the focus of this issue and article is on screening. The importance of preventive medicine has led to the development of major advisory groups, such as the U.S. Preventive Services Task Forcez8and the Canadian Task Force on the Periodic Health Examination.z These groups have developed guidelines for screening based on a critical appraisal of the medical literature. Other organizations, such as the American College of Physicians, have also developed preventive care guidelines.ll The basic terminology used in describing screening can be confusing. Terms such as diagnosis, screening, early detection, mass screening, routine screening, individualized screening, and case finding are often employed inter~hangeably.~ The concept of screening usually refers to laboratory tests, physical examination, or radiologic tests performed on asymptomatic patients in the hope of discovering subclinical disease. In general, a positive result of a screening intervention leads to further diagnostic workup. Early detection refers to finding a condition or disease before obvious signs or symptoms have appeared. The term diagnosis implies confirming a disease process in symptomatic patients and is therefore ideologically different from screening. The process of screening can then be further classified as mass
From the Section of Preventive Medicine (RSL), Department of General Internal Medicine, The Cleveland Clinic Foundation, Cleveland, Ohio (CN, RSL)
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screening, routine screening, or individualized screening. The term routine screening refers to automatic or repetitive testing based on age or gender.4 An example of mass screening is blood pressure or cholesterol screening done in a shopping mall. Mass screening implies a more universal approach to screening without much thought about the individual patient and his or her risk profile. Mass screening has its place, but physicians are most often involved in individualized screening (i.e., recommending screening tests to patients in private clinical settings in a oneto-one manner). Such an approach allows for individualized decision making and is the primary mode of screening that this issue of the Medical Clinics addresses. This issue looks at aspects of screening for common causes of mortality, such as cardiovascular, breast, prostate, and colon cancer as well as screening in specific patient populations, such as preemployment screening and geriatric and menopausal patient assessment. This opening article reviews the basic tenets underlying screening. This article (1)looks at the basic terminology, characteristics, and principles of screening situations; (2) reviews some barriers to screening; and (3) concludes with a call to proceed with prudence. CONCEPT OF PREVENTIVE MEDICINE
Preventive interventions have been categorized as primary, secondary, and tertiary. Primary prevention is the reduction of risk factors before a disease has occurred. Examples of primary prevention include immunizations, smoking cessation, counseling regarding the use of seatbelts and smoke detectors, dietary and exercise management, and chemoprophylaxis (e.g., hormone replacement therapy and tamoxifen in breast cancer prevention5).Secondary prevention is the detection of a condition or disease so as to reverse or slow the condition or disease and thereby improve prognosis. Examples of secondary prevention include mammograms, Papanicolaou (Pap) smears, and prostate-specific antigen testing. Tertiary prevention is the minimizing of future negative health effects of a disease or condition. An example of tertiary prevention is screening for hyperlipidemia in a person with documented coronary artery disease. EPIDEMIOLOGIC PRINCIPLES OF THE SCREENING TEST
Understanding the utility of screening tests requires knowledge of basic epidemiologic principles. The incidence is the number, of persons developing a condition or disease in a specific period of time (e.g., how many new cases of breast cancer will be found over the next year). In this example, the incidence rate excludes women who are already diagnosed with breast cancer. One cannot become a new case of breast cancer if one already has breast cancer before the start of the time period in question. The goal of primary prevention is to decrease the incidence of
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Table 1. 2 x 2 TABLE
Test Positive Test Negative Total
Disease Present
No Disease
Total
True positives (TP) False negatives (FN) All with disease
False positives (FP) True negatives (TN) All without disease
All positive All negative Total patients
Sensitivity = TP/(TP+FN); Specificity = TN/(TN+FP); Negative predictive value = TN/ (TN+FN); Positive predictive value = TP/(TP+ FP).
a disease or condition-to intervene to prevent the disease or condition from occurring. Prevalence is the total number of individuals who have a condition or disease at a particular time (e.g., all women with breast cancer over the past year). The prevalence rate (and incidence rate) can vary depending on the population in question. For example, the prevalence rate of breast cancer is higher in women older than age 60 versus women younger than age 40. Similarly the prevalence of lung cancer is higher in smokers than in nonsmokers. The goal of secondary prevention is to decrease the prevalence of a disease or condition-to find a condition or disease in its early stage and cure it. The sensitivity and specificity of a particular test form the framework from which clinicians view its effectiveness. The sensitivity of a test equals the proportion of the diseased patients who have a positive test (true-positive rate). The specificity of a test equals the proportion of the nondiseased patients who have a negative test (true-negative rate). Physicians are often more interested in the predictive value of a test-not so much the ability of a test to confirm a disease, but the ability of the test to predict disease. The positive predictive value (PPV) of a test equals the proportion of patients with a positive test result who actually have the disease. The negative predictive value (NPV) of a test equals the proportion of the patients with a negative test result who do not have the disease. These principles are illustrated in a 2 X 2 table (Table 1). The 2 X 2 table is a common method for viewing the application of a screening test in a population (Table 2). The predictive value of a test is influenced by the prevalence of the disease or condition of concern. This relationship refers to Bayes' theorem. Bayes, an eighteenth century English mathematician, stated that the predictive value is proportional to prevalence. Bayes' theorem can be displayed in the following equations: PPV NPV
=
(sensitivity x prevalence) [(sensitivity x prevalence)] [(l - specificity) x (1 - prevalence)]
=
(sensitivity) x (1 - prevalence) [(specificity) x (1 - prevalence)] + [(l - sensitivity) x (prevalence)]
+
The concept is rather simple: As the prevalence of a disease or condition increases, the PPV of a test increases, and the NPV of a test decreases.
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Table 2 . 2 x 2 TABLE: HYPOTHETICAL EXAMPLE Coronary Artery Disease Present Test Y Positive Test Y Negative Total
150 pts (TP) 20 pts (FN) 170 pts
Coronary Artery Disease Absent
50 pts (FP) 180 pts (TN) 230 pts
Total
200 pts 200 pts 400 pts
Sensitivity of test Y = TP/(TP+FN) = 150/150+20 = 88%; specificity of test Y = TN/(TN+FP) = 180/180+50 = 78%; negative predictive value of test Y = TN/(TN+FN) = 180/180+20 = 90%; positive predictive value of test Y = TP/(TP+FP) = 150/150 +50 = 75%. pts = Patients; TP = true positives; FN = false negatives; FP = false positives; TN = true negatives.
Conversely, as the prevalence of a disease or condition decreases, the PPV falls, and the NPV rises. For example, if a test with sensitivity of 90% and specificity of 90% is applied to a population in which the prevalence of a condition is lo%, the PPV of the test is only 50%, and the NPV is 98.79'0. In another population in which the prevalence of the condition is 90%0,the same test has a PPV of 98.7% and an NPV of 50%. From a practical standpoint, in the office, physicians often do not have the data concerning the sensitivity, specificity, or prevalence at their fingertips. Physicians and health care providers should nonetheless consider screening tests for common (i.e., prevalent) conditions or whether likelihood of disease (based on risk factors, such as family history) is high. GENERAL PRINCIPLES OF SCREENING
The general principles that provide the backbone for optimal use and effectiveness of screening include the following: 1. The disease or condition should be an important problem (morbidity and mortality). The optimal use of screening requires a basic understanding of the common causes of mortality. Diseases or conditions with substantial morbidity and mortality are considered reasonable to screen for. Such data can be obtained from government mortality statistics. Year to year, the leading causes of 'death for the overall population are fairly consistent-heart diseases, cancer, stroke, chronic obstructive pulmonary disease, accidents, and pneumonia and influenza. Screening measures should generally focus on these common conditions. The morbidity of conditions can also be assessed by looking at parameters such as quality-adjusted life-years and disability-adjusted lifeyears. Discussion of these topics is beyond the scope of this article. 2. The disease or condition should be common (prevalence and incidence). The prevalence of disease in the overall population should be
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high enough to justify the cost of screening. Screening all individuals in the United States for parasitic infections or screening men younger than age 30 for prostate cancer is not justifiable because the incidence and prevalence of these conditions in these populations are low. Screening for rare diseases is not usually justifiable because the cost per case detected is too high. The prevalence of a disease or condition not only depends on its frequency, but also on its duration. Diseases with long preclinical durations, such as breast, cervical, and colon cancer, are more likely to benefit from screening than diseases with short preclinical durations, such as leukemia. 3. The disease or condition should have a readily available and acceptable treatment. The goal in screening is to change the natural outcome of the disease or condition being screened for. Therefore, a disease or condition detected by screening should have appropriate treatments available that influence the ultimate course of the disease or condition. Generally, cancer screening aims to diagnose cancer at an earlier stage than might occur if the patient were to wait until becoming symptomatic because, in general, lower-stage cancers are more easily treated and cured. Screening for diseases such as Huntington’s chorea, in which treatment that can change the clinical outcome of the disease is lacking, is generally not endorsed. 4. The screening test should be accurate (sensitivity, specificity, and predictive value). A good screening test has a high sensitivity (few false-negative results) and a high specificity (few false-positive results). The sensitivity and specificity of a test are often compared to a gold standard, or definitive test. For diseases such as cancer, the gold standard is often pathologic tissue. For other diseases, the gold standard may not be as definitive. For example, a coronary angiogram is generally viewed as the gold standard for coronary artery disease, but medical literature demonstrates the many limitations of coronary a n g i ~ g r a p h y . ~ ~ 5. The screening procedure should have a reasonable cost (health and financial risk and costs). The benefits of a screening intervention should justify the financial cost.= The goal is to use the limited health care financial resources in a cost-effective manner so that most of the population benefits. The factors involved in the determination of cost-effectiveness of clinical preventive services are large and complex. These include the cost of the screening test, physician visit, follow-up diagnostic tests, and side effects and iatrogenic complications; lost work time; and potential savings from avoided illness and disability. The health effect of the intervention is also included in the overall cost and is usually expressed in terms of years of life saved. Computer modeling can help determine years of life saved and financial cost of a screening program. For example, annual Pap smears can by computer modeling be compared with Pap smears done at varying time
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intervals. Total cost and years of life saved can be estimated to help determine an optimal approach to cost-effective cervical Pap screening. Such data analysis helps to determine the appropriate frequency of screening interventions. 6 . The screening procedure should be acceptable to the patient and society. Because screening tests are performed on asymptomatic individuals, these tests should be generally safe. The risks of complications from currently accepted screening interventions are small. Some procedures may have more significant associated risks (e.g., colonic perforation during screening sigmoidoscopy or colonoscopy).21The risks of colonic perforation are smaller for sigmoidoscopy than for colonoscopy. Therefore, although colonoscopy has the advantage of surveying the whole colon, its higher risk profile and cost make colonoscopy a less viable option for screening the general population. In patients at high risk for colon cancer, however, the benefit of screening via colonoscopy may outweigh this possible harm. In addition, many of the screening tests (e.g., pap smears, mammography, digital rectal examinations, blood draws and flexible sigmoidoscopy) physicians perform are invasive and have some degree of discomfort associated with them. This is an important consideration also in the viability of a screening intervention because patient discomfort influences compliance. The ideal screening situation involves the use of an inexpensive, noninvasive test with a high level of sensitivity and specificity to detect a common problem that can be treated and that left untreated leads to significant morbidity and mortality. Medical practice and the medical literature identify few such interventions that are this ideaI.
BARRIERS TO SCREENING Several barriers exist that impede application of even the best preventive screening interventions. A useful classification of the barriers to implementation of clinical prevention has been devised by Frame6(Table 3). He divides barriers into issues related to the individual patient, to the health care delivery system, and to the physician or health care provider.
Patient Barriers In an individual patient, the barriers to screening interventions may include social and cultural norms, perceptions of the likelihood of getting the disease, fear of finding a disease, discomfort, cost, and the implications should a problem be found.I5 At the same time, some of these same factors, such as a patient’s perception of getting a disease,
.
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Table 3. BARRIERS TO CLINICAL PREVENTION Patient Barriers
Ignorance of benefits Doubts about the physician’s ability to detect a hidden disease Cost of procedures Discomfort Conscious or unconscious desire not to change unhealthy habits Social and cultural norms Health System Barriers
Inadequate reimbursement Lack of health insurance Population mobility Patients with multiple physicians Categoric, sporadic screening programs such as health fairs Physician Barriers
Knowledge Uncertainty about conflicting recommendations Uncertainty about the value of tests or interventions Disorganized medical records Delayed and indirect gratification from screening Lack of time Attitudes and personal characteristics Modified from Frame PS Health maintenance in clinical practice: Strategies and barriers. Am Fam Physician 45:1192-1200, 1992; with permission.
provide the impetus for patients to seek physician services. For example, Osborne et alZ found that in a sample of men from Australia, approximately 30% undergoing prostate-specific antigen testing had personally requested the test from their physicians. Patients often want to be reassured about a condition they have heard or read about or want to address a condition at an early stage to prevent an adverse outcome. Similarly, patients’ perceptions of a condition may be influenced by a friend or an acquaintance having a health outcome. The most difficult patient barrier to overcome in preventive medicine is changing patient behavior. Primary prevention focuses on preventive health-related behavior. Preventive health-related behavior includes diet, exercise, sexual practices, alcohol consumption, tobacco use, and other personal habits. Changing these behaviors can influence the success of a screening intervention. Because these habits are often difficult to change, a screening intervention may be deemed cost-inefective. The health belief model implies that behavior to prevent a disease is influenced by a person’s perception of the personal threat of the disease or ~0ndition.l~ That is, the more severe the disease and the more susceptible to it the patient perceives himself or herself to be, the more likely he or she is to change a behavior that can influence the outcome of that condition. At the same time, changing a behavior is influenced by the ease of making the change, the perceived effectiveness of making the change, and particularly the social group influence of the change.14
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Identifying the influential people of a person’s social group and, where possible, using them as allies can assist in getting a person to change a negative health-related behavior. Often these behaviors are long-standing and ingrained into the upbringing, cultural background, and social norms of the individual. No quick solutions exist to overcome these barriers. The health care cost crisis in the United States; the efforts of the media; the increased exposure of medical information via the Internet; and the emphasis of preventive services via the work of the Canadian Task Force, the U.S. Preventive Service Task Force, and other major groups have helped push the responsibility for wellness and health back onto the individual. As good preventive habits, such as not smoking, condom use, eating a lowfat diet, and exercising regularly, become ingrained in society, people should become more motivated to seek preventive advice for themselves and their families.15 Health System Barriers
The mobility of the population, leading many patients to encounter multiple physicians over their lifetime, causes difficulties for tracking and ensuring clinical preventive services. As computer technology advances and the issue of basic health insurance for all people in the United States is addressed, problems of tracking clinical preventive services should decline.lSAnother challenge for clinical preventive medicine is the provision of appropriate reimbursement to the health care providers for risk assessment and counseling. To some extent, this situation is being addressed by incentives built into systems of care. Time and priorities of patients and physicians also influence the success or failure of preventive screening interventions. Patients often come to physicians with a prioritized list of problems that need to be addressed. Preventive screening may not be high on that list. The busy practitioner may be overtaxed by the activities of the day and thereby not allow time for effective, time-intensive preventive counseling. Delegating responsibility for tracking and providing preventive services to a nonphysician health care provider may be helpful. Organizational barriers for screening can be viewed as global or local. The global barriers include inadequate reimbursement to physicians for proviston of preventive services, lack of health insurance, and mobility of the population both geographically and individually from one health insurance provider to another.15A more useful view, however, is to look at the physician’s individual practice setting and to evaluate the local barriers to screening. Local barriers may include some of the same global factors, such as inadequate reimbursement and population mobility, but they also contain barriers that are more easily changeable for the individual physician. Organization of medical records, development of a health care maintenance flow sheet, and delegation of responsibility for these services to nonphysicians in the practice can allow for barriers
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to clinical preventive services to be overcome. Resources outside of the practice, such as hospital patient education programs and community and professionally sponsored programs, which can provide a variety of counseling services and education to the individual, may also be helpful.16 Physician Barriers
Are physicians a problem or a solution to providing better preventive care? This question, posed by Belcher et al,' is best answered both. Preventive services have not traditionally been a major focus of the basic medical school education curriculum. Medical education has focused on diseases after they have occurred, and the medical literature has a paucity of texts concerning the science and value of clinical prevention and its delivery. The role of the physician in providing preventive care has often been ambiguous. As Lang and Shainoff l5 state The physician trained in the curative approach to medical problems and faced with a patient with a specific problem or symptom is hard pressed to spend time on prevention of other medical issues that occur much later in a patient's life. Faced with a busy practice and time constraints, the time required for counseling and changing habits again presents itself as a barrier, particularly when reimbursement is not provided in a meaningful way. Another issue is that the practitioner does not see the "positive" health outcomes from prevention in the same patient in a mobile and ever-changing patient population. Clear consensus regarding clinical prevention screening recommendations has not existed and has led to confusion. Differences exist for recommendations regarding screening modalities, such as cholesterol screening7breast cancer screening? 9, and colorectal cancer s~reening.'~ Disagreement exists among physicians regarding recommendations made by major advisory groups, such as the U.S. Preventive Services Task Force.31Finally, physicians often do not comply, even with their own recommendation^.^^ There is no easy solution to these obstacles. The key factors for overcoming these physician barriers are (1)consensus of clinical prevention recommendations, (2) appropriate reimbursement for preventive services, (3) education about the necessity of delivering appropriate services, (4)advancement of computer applications to ease recording and tracking patients and to provide reminders about clinical preventive services, and (5) planning and organization within the practice.15 PROCEEDING WITH PRUDENCE A primary goal of screening is to improve the health of patients and the population in general. Implied in this goal is the underlying
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principle, "Do no harm." Because screening tests are generally performed in asymptomatic patients, this principle of "Do no harm" conveys added significance. A positive screening test result is often followed by a diagnostic test, which may carry more risk than the screening test itself. If the screening test was not indicated or unnecessary in the first place, it is not an ideal situation to put the patient at risk by the subsequent diagnostic testing that follows. When an individual undergoes a screening intervention, there are four possible outcomes. 1. A true-positive result. The test correctly identifies the presence of an underlying disease or condition, and the patient can go on to further diagnosis and treatment. 2. A true-negative result. The intervention correctly indicates the absence of an underlying disease or condition, and the patient can be correctly assured that they do not have the disease or condition in question. Most screening interventions result in a true-negative result. 3. A false-positive result. The intervention falsely indicates that a disease or condition is present. The patient usually undergoes further testing, with its attendant risks, inconveniences, and costs. A false-positive result may also cause unnecessary anxiety and label a patient with a disease or condition that the patient does not actually have. Patients falsely labeled with a diagnosis of hypertension have been shown to have adverse outcomes (e.g., decreased work productivity and altered behavior pattems).17 4. A false-negative result. The screening intervention falsely indicates that a disease or condition is absent. In such a case, the patient may develop a mistaken sense of security and ignore symptoms when they occur. More importantly, diagnostic and therapeutic interventions may be delayed. Physicians should generally look to screening tests with good track records (e.g., screening tests that are both effective, the performance characteristics of the test, and efjicacious, the intervention results in more good than harm). The literature provides examples of obstetric and gynecologic tests, such as ovarian cancer screening with CA-125 and home uterine activity monitoring, that have been put into clinical practice before true demonstration of their clinical effectiveness has occurred.s The performance characteristics of a test (predictive value) depend on. the prevalence of the disease or condition in question. Even highly accurate screening tests generate a large number of false-positive results when applied to an uncommon disease or condition. For example, a test with a sensitivity and specificity of !%%, when applied to a population of 1 million with a disease X prevalence of 0.05% produces the following test results (Table 4): True positives (TP)-4750 individuals True negatives (TN)-945,250 individuals False negatives (FN)-250 individuals False positives (FP)-49,750 individuals
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Table 4. EFFECT OF PREVALENCE ON TEST CHARACTERISTICS
Test Positive Test Negative Total
Disease X Present
Disease X Absent
Total
4750 pts (TI') 250 pts (FN) 5000 pts
49,750 pts (FP) 945,250 pts (TN) 995,000 pts
54,500 pts 945,500 pts 1,000,000 pts
Testing conditions: population size = 1,000,000; disease X prevalence = 0.05%; sensitivity of test = 95%; specificity of test = 95%. pts = Patients; TP = true positives; FN = false negatives; FP = false positives; TN = true negatives.
The positive predictive value of the test in this population is thereby only 8.7%. In this hypothetical example, 49,750 individuals would be labeled as false-positives and could thereby suffer increased risks from follow-up testing. In this situation, the benefits (early detection) may not outweigh the risks (high number of false positives). The quest for doing more good than harm is an underlying concept of what today is commonly referred to as evidence-based medicine. Evidence-based medicine is important in the arena of preventive medicine to help determine preventive screening interventions of greatest utility to the population. Evidence-based medicine can be viewed as "the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients."25This concept generally implies having scientific backing from well-conceived, randomized, controlled clinical trials or other well-designed clinical trials, such as cohort studies. These clinical trials provide the scientific evidence and base of preventive medicine to integrate with the clinical judgment of the individual physician. Sackett et alZ5state, "External clinical evidence can inform, but can never replace, individual clinical expertise, and it is expertise that decides whether external evidence applies to the individual patient at all and, if so, how it should be integrated into a clinical decision." This is not, however, a call to disregard clinical evidence in regard for personal preference. To do so would be a disservice to patients. Clinical judgment and external evidence should go hand in hand. Major advisory groups have different recommendations for screening based on their different integrations of the external evidence and clinical judgment. The articles in this issue also present recommendations for screening in light of this integration. The U.S. Preventive Services Task Force and the Canadian Task Force on the Periodic Health Examination are prominent examples of evidence-based 'medicine at work. They attempt to make screening recommendations based on scientific evidence rather than relying on expert opinion. The underlying theme is that the benefits of an intervention should be clearly shown to outweigh possible harms before an intervention is used routinely on an asymptomatic population. The quality of
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the evidence is believed to be as important as the results of the study itself. The hierarchy of evidence, in decreasing order of importance, is randomized, controlled trials; nonrandomized, controlled trials; cohort studies; case-control studies; uncontrolled experiments; descriptive studies; and expert opinion. The U.S. Preventive Services Task Force quality of evidence criteria and strength of recommendations are outlined in Table 5. Such a hierarchial approach is valid because all clinical trials have inherent weaknesses and biases. The main biases affecting the internal validity of the randomized, controlled trials are diIution and cont~minution.~ Dilution implies that some patients who are offered screening may not actually receive it, and contamination implies that some of the patients who were not randomized to the screening arm may receive the test anyway. Also, the patient population of the randomized, controlled trials may not mirror the general population secondary to the imposed exclusion criteria that most randomized clinical trials use. Additionally, individual clinicians in the community may not perform the screening test in the same manner as the investigator who usually has special expertise and a standardized Cohort studies, which are prospective in design, and case-control studies, which are retrospective in design, are also prone to bias. Both study designs can be affected by patient-selection bias and confounding variables (i.e., related factors that may be more directly responsible for the outcome of the study than the intervention itself). Uncontrolled
Table 5. QUALITY OF EVIDENCE AND STRENGTH OF RECOMMENDATIONS Quality of Evidence I Evidence obtained from at least one properly designed randomized, controlled trial 11-1 Evidence obtained from well-designed controlled trials without randomization II-2 Evidence obtained from well-designed cohort or case-control analytic studies, preferably from more than one center or research group 11-3 Evidence obtained from multiple time series with or without the intervention or dramatic results in uncontrolled experiments (such as the results of the introduction of penicillin treatment in the 1940s) 111 Opinions of respected authorities, based on clinical experience, descriptive studies, or reports of expert committees Strength of Recommendations A There is good evidence to support the recommendation that the condition be specifically considered in a periodic health examination B There is fair evidence to support the recommendation that the condition be specifically considered in a periodic health examination There is poor evidence regarding the inclusion of the condition in a periodic health C examination, but recommendations may be made on other grounds D There is fair evidence to support the recommendation that the condition be excluded from consideration in a periodic health examination E There is good evidence to support the recommendation that the condition be excluded from consideration in a periodic health examination From US. Preventive Services Task Force: Task Force Ratings: Guide to Clinical Preventive Services. Washington, DC, U.S. Department of Health and Human Services, 1996, p 862.
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studies can also be affected by patient-selection bias and confounding variables but are subject to lead-time bias and length bias as well. In lead-time bias, the Zead-time is the time between the screening diagnosis and the clinical diagnosis. This lead-time often overestimates the effectiveness of screening. For example, suppose disease X is diagnosed through a screening intervention in 1990, and despite treatment the patient dies in 1995. Suppose a similar patient has the same-stage disease in 1990 but is not screened and is not diagnosed until he or she develops clinical symptoms in 1992. This patient undergoes treatment as well and dies in 1995. Studies may report a 2-year survival benefit for screening when in reality no clinical benefit is gained. The observed increase in survival time is related to the earlier diagnosis and not to any true prolongation of life. This is an inherent difficulty when comparing screened and unscreened populations. Length term bias also overestimates the effectiveness of screening. Screening tests are more likely to detect chronic, slowly progressive conditions than fast, aggressive conditions or diseases. Fast, aggressive conditions are usually present in the population only for short periods of time. Length term bias refers to the overrepresentation of slowly growing conditions in the screened population. These chronic conditions carry a longer survival time that is unrelated to the screening intervention itself. Interpretation of a clinical trial should consider the type of trial used and the biases that may be affecting it. A secondary goal of screening is the cost-efficient use of the medical resources available. The resources to screen for all diseases simply do not exist. The actual cost-effectiveness and economic consequences of prevention can be difficult to clarify.Is Although some economic models have demonstrated the cost-effectiveness of screening tests using a population-based model,1z it is difficult to obtain hard evidence for such conclusions. For example, if colorectal cancer in a 65-year-old woman is prevented through appropriate screening, she may develop coronary artery disease or breast cancer at a later date, and the ultimate monetary cost is higher than the original treatment of colon cancer. Alternatively, if it were possible to prevent most diseases, such as cancer, would a burgeoning nursing home population and the high costs associated with nursing home care result? These are difficult questions. It is generally agreed on that the use of screening tests without demonstrated clinical effectiveness in place of tests that have demonstrated effectiveness would not be in the best interest of society and are probably not in the best interest of patients either. Physicians are best to endorse screening tests with established track records. CONCLUSION
This article provides a framework from which to view the subsequent articles devoted to screening for specific conditions or in specific patient groups. As medical technology advances, new screening tech-
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niques will be developed and physicians will be asked to use and recommend them appropriately. This article provides some of the basic tools needed for interpreting new medical evidence concerning screening techniques and screening situations, such as computed tomography for lung cancer quantitative ultrasound scans of the calcaneus for osteoporosis or mass screening for thyroid cancer.2o
References 1. Belcher DW, Berg AO, Inui TS: Practical approaches to providing better preventive care: Are physicians a problem or a solution? In Battista RN, Lawrence RS (eds): Implementing Preventive Services. New York, Oxford University Press, 1988 2. Canadian Guide to Clinical Preventive Health Care. Ottawa, Minister of Supply and Services Canada, Canada Communication Group, 1994 3. Dilhuydy MH, Barreau B: The debate over mass mammography: Is it beneficial for women? Eur J Radio1 24:86-93, 1997 4. Eddy DM: How to think about screening. In Eddy DM (ed): Common Screening Tests. Philadelphia, American College of Physicians, 1991 5. Fisher 8, Costantino J, Wickerman DL, et al: Tamoxifen for prevention of breast cancer: Report of the National Surgical Adjuvant Breast and Bowel Project P-1 study. J Natl Cancer Inst 901371-1388, 1998 6. Frame PS: Health maintenance in clinical practice: Strategies and barriers. Am Fam Physician 45:1192-1200, 1992 7. Garber AM, Browner WS, Halley SB: Cholesterol screening in asymptomatic adults, revisited. Ann Intern Med 124518-531, 1996 8. Grimes DA: Technology follies: The uncritical acceptance of medical innovation. JAMA 269~3030-3032,1993 9. Harris KM, Vogel VG: Breast cancer screening. Cancer Metastasis Rev 16:231-262, 1997 10. Harris R, Leininger L: Clinical strategies for breast cancer screening: Weighing and using the evidence. Ann Intern Med 122:539-547, 1995 11. Hayward RSA, Steinberg EP, Ford DE, et al: Preventive care guidelines: 1991. Ann Intern Med 114:758-783, 1991 12. Hristova L, Hakama M Effect of screening for cancer in the Nordic countries on deaths, cost and quality of life up to the year 2017. Acta Oncol 36(supp19):140, 1997 13. Jam NK, Becker MH: The health belief model: A decade later. Health Educ Q 11:l47,1984 14. Jenkins DC:Diagnosis and treatment of behavioral barriers to good health. In Last JM (ed): Maxcy-Rosenau public health and preventive medicine. Norwalk, CT, AppletonCentury-Crofts, 1986 15. Lang RS, Shainoff JD: Integrating clinical preventive service into office practice. In Matzen RN, Lang RS (eds): Clinical Preventive Medicine. St. Louis, MO, Mosby-Year Book, 1993 16. Leatt P;Frank J: Organizational issues related to integrating preventive services into primary care. In Battista RN, Lawrence RS (eds): Implementing Preventive Services. New York, Oxford University Press, 1988 17. Lefebvre RC, Hursey KG, Carleton RA: Labeling of participants in high blood pressure screening programs: Implications for blood cholesterol screenings. Arch Intern Med 148:1993-1997, 1998 18. Leutwyler K The price of prevention. Sci Am 272:124129, 1995 19. Mandel JS: Colorectal cancer screening. Cancer Metastasis Rev 16263-279, 1997 20. Miki H, Inoue H, Komaki K, et a1 Value of mass screening for thyroid cancer. World J Surg 22:99-102, 1998 21. Nelson RL, Abcarian H, Prasad ML: Iatrogenic perforation of the colon and rectum. Dis Colon Rectum 25:305-308, 1982
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22. Osborne DN, Gardner IL, Stacey BG, et al: Men’s estimates of prostate cancer risk and self-reported rates of screening. Med J Aust 169:57, 1998 23. Philbrick JT, Becker DM: Screening for early disease: Interpretation of diagnostic tests. In Becker DM, Gardner LB (eds): Prevention in Clinical Practice. New York, Plenum, 1988 24. Pocock NA, Noakes KA, Howard GM, et al: Screening for osteoporosis: What is the role of heel ultrasound? Med J Aust 164:367-370, 1996 25. Sackett DL, Rosenberg WM, Gray JAM, et al: Evidence-based medicine: What it is and what isn’t. BMJ 312:71-72, 1996 26. Sone S, Takashima S, Li F, et al: Mass screening for lung cancer with mobile spiral computed tomography scanner. Lancet 35:1242-1245, 1998 27. Topol EJ, Nissen SE: Our preoccupation with coronary luminology: The dissociation between clinical and angiographic findings in ischemic heart disease. Circulation 92:2333-2342, 1995 28. U.S. Preventive Services Task Force: Guide to Clinical Preventive Services: Report of the United States Preventive Services Task Force, ed 2. Baltimore, Williams & Wilkins, 1996 29. Woo B, Woo B, Cook FE, et al: Screening procedures in the asymptomatic adult, comparison of physicians’s recommendations, patients’ desires, published guidelines, and actual practice. JAMA 254:1480-1484, 1985 30. Woolf SH: Analytic principles in assessing the effectiveness of clinical preventive services. In Goldbloom RB, Lawrence RS (eds): Preventing Disease: Beyond the Rhetoric. New York, Springer-Verlag, 1990 31. Zyzanski SJ, Stanger KC, Kelly R, et al: Family physicians’ disagreements with the US Preventive Services Task Force Recommendations. J Fam Pract 39:140-147, 1994 Address reprint reqtiests to Craig Nielsen, MD Department of General Internal Medicine/S70 The Cleveland Clinic Foundation 9500 Euclid Avenue Cleveland, OH 44195
0025-7125/99 $8.00
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PRINCIPLES OF SCREENING Craig Nielsen, MD, and Richard S. Lang, MD, MPH
Physicians are asked to perform many tasks, which primarily have been directed at diagnosis, treatment, and management of disease processes. Increasingly, they have become involved in the area of preventive medicine. Conceptually, preventive medicine encompasses three tasks for the clinician: screening, counseling, and immunization or chemoprophylaxis. Although touching on all of these areas, the focus of this issue and article is on screening. The importance of preventive medicine has led to the development of major advisory groups, such as the U.S. Preventive Services Task Forcez8and the Canadian Task Force on the Periodic Health Examination.z These groups have developed guidelines for screening based on a critical appraisal of the medical literature. Other organizations, such as the American College of Physicians, have also developed preventive care guidelines.ll The basic terminology used in describing screening can be confusing. Terms such as diagnosis, screening, early detection, mass screening, routine screening, individualized screening, and case finding are often employed inter~hangeably.~ The concept of screening usually refers to laboratory tests, physical examination, or radiologic tests performed on asymptomatic patients in the hope of discovering subclinical disease. In general, a positive result of a screening intervention leads to further diagnostic workup. Early detection refers to finding a condition or disease before obvious signs or symptoms have appeared. The term diagnosis implies confirming a disease process in symptomatic patients and is therefore ideologically different from screening. The process of screening can then be further classified as mass
From the Section of Preventive Medicine (RSL), Department of General Internal Medicine, The Cleveland Clinic Foundation, Cleveland, Ohio (CN, RSL)
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screening, routine screening, or individualized screening. The term routine screening refers to automatic or repetitive testing based on age or gender.4 An example of mass screening is blood pressure or cholesterol screening done in a shopping mall. Mass screening implies a more universal approach to screening without much thought about the individual patient and his or her risk profile. Mass screening has its place, but physicians are most often involved in individualized screening (i.e., recommending screening tests to patients in private clinical settings in a oneto-one manner). Such an approach allows for individualized decision making and is the primary mode of screening that this issue of the Medical Clinics addresses. This issue looks at aspects of screening for common causes of mortality, such as cardiovascular, breast, prostate, and colon cancer as well as screening in specific patient populations, such as preemployment screening and geriatric and menopausal patient assessment. This opening article reviews the basic tenets underlying screening. This article (1)looks at the basic terminology, characteristics, and principles of screening situations; (2) reviews some barriers to screening; and (3) concludes with a call to proceed with prudence. CONCEPT OF PREVENTIVE MEDICINE
Preventive interventions have been categorized as primary, secondary, and tertiary. Primary prevention is the reduction of risk factors before a disease has occurred. Examples of primary prevention include immunizations, smoking cessation, counseling regarding the use of seatbelts and smoke detectors, dietary and exercise management, and chemoprophylaxis (e.g., hormone replacement therapy and tamoxifen in breast cancer prevention5).Secondary prevention is the detection of a condition or disease so as to reverse or slow the condition or disease and thereby improve prognosis. Examples of secondary prevention include mammograms, Papanicolaou (Pap) smears, and prostate-specific antigen testing. Tertiary prevention is the minimizing of future negative health effects of a disease or condition. An example of tertiary prevention is screening for hyperlipidemia in a person with documented coronary artery disease. EPIDEMIOLOGIC PRINCIPLES OF THE SCREENING TEST
Understanding the utility of screening tests requires knowledge of basic epidemiologic principles. The incidence is the number, of persons developing a condition or disease in a specific period of time (e.g., how many new cases of breast cancer will be found over the next year). In this example, the incidence rate excludes women who are already diagnosed with breast cancer. One cannot become a new case of breast cancer if one already has breast cancer before the start of the time period in question. The goal of primary prevention is to decrease the incidence of
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Table 1. 2 x 2 TABLE
Test Positive Test Negative Total
Disease Present
No Disease
Total
True positives (TP) False negatives (FN) All with disease
False positives (FP) True negatives (TN) All without disease
All positive All negative Total patients
Sensitivity = TP/(TP+FN); Specificity = TN/(TN+FP); Negative predictive value = TN/ (TN+FN); Positive predictive value = TP/(TP+ FP).
a disease or condition-to intervene to prevent the disease or condition from occurring. Prevalence is the total number of individuals who have a condition or disease at a particular time (e.g., all women with breast cancer over the past year). The prevalence rate (and incidence rate) can vary depending on the population in question. For example, the prevalence rate of breast cancer is higher in women older than age 60 versus women younger than age 40. Similarly the prevalence of lung cancer is higher in smokers than in nonsmokers. The goal of secondary prevention is to decrease the prevalence of a disease or condition-to find a condition or disease in its early stage and cure it. The sensitivity and specificity of a particular test form the framework from which clinicians view its effectiveness. The sensitivity of a test equals the proportion of the diseased patients who have a positive test (true-positive rate). The specificity of a test equals the proportion of the nondiseased patients who have a negative test (true-negative rate). Physicians are often more interested in the predictive value of a test-not so much the ability of a test to confirm a disease, but the ability of the test to predict disease. The positive predictive value (PPV) of a test equals the proportion of patients with a positive test result who actually have the disease. The negative predictive value (NPV) of a test equals the proportion of the patients with a negative test result who do not have the disease. These principles are illustrated in a 2 X 2 table (Table 1). The 2 X 2 table is a common method for viewing the application of a screening test in a population (Table 2). The predictive value of a test is influenced by the prevalence of the disease or condition of concern. This relationship refers to Bayes' theorem. Bayes, an eighteenth century English mathematician, stated that the predictive value is proportional to prevalence. Bayes' theorem can be displayed in the following equations: PPV NPV
=
(sensitivity x prevalence) [(sensitivity x prevalence)] [(l - specificity) x (1 - prevalence)]
=
(sensitivity) x (1 - prevalence) [(specificity) x (1 - prevalence)] + [(l - sensitivity) x (prevalence)]
+
The concept is rather simple: As the prevalence of a disease or condition increases, the PPV of a test increases, and the NPV of a test decreases.
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Table 2 . 2 x 2 TABLE: HYPOTHETICAL EXAMPLE Coronary Artery Disease Present Test Y Positive Test Y Negative Total
150 pts (TP) 20 pts (FN) 170 pts
Coronary Artery Disease Absent
50 pts (FP) 180 pts (TN) 230 pts
Total
200 pts 200 pts 400 pts
Sensitivity of test Y = TP/(TP+FN) = 150/150+20 = 88%; specificity of test Y = TN/(TN+FP) = 180/180+50 = 78%; negative predictive value of test Y = TN/(TN+FN) = 180/180+20 = 90%; positive predictive value of test Y = TP/(TP+FP) = 150/150 +50 = 75%. pts = Patients; TP = true positives; FN = false negatives; FP = false positives; TN = true negatives.
Conversely, as the prevalence of a disease or condition decreases, the PPV falls, and the NPV rises. For example, if a test with sensitivity of 90% and specificity of 90% is applied to a population in which the prevalence of a condition is lo%, the PPV of the test is only 50%, and the NPV is 98.79'0. In another population in which the prevalence of the condition is 90%0,the same test has a PPV of 98.7% and an NPV of 50%. From a practical standpoint, in the office, physicians often do not have the data concerning the sensitivity, specificity, or prevalence at their fingertips. Physicians and health care providers should nonetheless consider screening tests for common (i.e., prevalent) conditions or whether likelihood of disease (based on risk factors, such as family history) is high. GENERAL PRINCIPLES OF SCREENING
The general principles that provide the backbone for optimal use and effectiveness of screening include the following: 1. The disease or condition should be an important problem (morbidity and mortality). The optimal use of screening requires a basic understanding of the common causes of mortality. Diseases or conditions with substantial morbidity and mortality are considered reasonable to screen for. Such data can be obtained from government mortality statistics. Year to year, the leading causes of 'death for the overall population are fairly consistent-heart diseases, cancer, stroke, chronic obstructive pulmonary disease, accidents, and pneumonia and influenza. Screening measures should generally focus on these common conditions. The morbidity of conditions can also be assessed by looking at parameters such as quality-adjusted life-years and disability-adjusted lifeyears. Discussion of these topics is beyond the scope of this article. 2. The disease or condition should be common (prevalence and incidence). The prevalence of disease in the overall population should be
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high enough to justify the cost of screening. Screening all individuals in the United States for parasitic infections or screening men younger than age 30 for prostate cancer is not justifiable because the incidence and prevalence of these conditions in these populations are low. Screening for rare diseases is not usually justifiable because the cost per case detected is too high. The prevalence of a disease or condition not only depends on its frequency, but also on its duration. Diseases with long preclinical durations, such as breast, cervical, and colon cancer, are more likely to benefit from screening than diseases with short preclinical durations, such as leukemia. 3. The disease or condition should have a readily available and acceptable treatment. The goal in screening is to change the natural outcome of the disease or condition being screened for. Therefore, a disease or condition detected by screening should have appropriate treatments available that influence the ultimate course of the disease or condition. Generally, cancer screening aims to diagnose cancer at an earlier stage than might occur if the patient were to wait until becoming symptomatic because, in general, lower-stage cancers are more easily treated and cured. Screening for diseases such as Huntington’s chorea, in which treatment that can change the clinical outcome of the disease is lacking, is generally not endorsed. 4. The screening test should be accurate (sensitivity, specificity, and predictive value). A good screening test has a high sensitivity (few false-negative results) and a high specificity (few false-positive results). The sensitivity and specificity of a test are often compared to a gold standard, or definitive test. For diseases such as cancer, the gold standard is often pathologic tissue. For other diseases, the gold standard may not be as definitive. For example, a coronary angiogram is generally viewed as the gold standard for coronary artery disease, but medical literature demonstrates the many limitations of coronary a n g i ~ g r a p h y . ~ ~ 5. The screening procedure should have a reasonable cost (health and financial risk and costs). The benefits of a screening intervention should justify the financial cost.= The goal is to use the limited health care financial resources in a cost-effective manner so that most of the population benefits. The factors involved in the determination of cost-effectiveness of clinical preventive services are large and complex. These include the cost of the screening test, physician visit, follow-up diagnostic tests, and side effects and iatrogenic complications; lost work time; and potential savings from avoided illness and disability. The health effect of the intervention is also included in the overall cost and is usually expressed in terms of years of life saved. Computer modeling can help determine years of life saved and financial cost of a screening program. For example, annual Pap smears can by computer modeling be compared with Pap smears done at varying time
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intervals. Total cost and years of life saved can be estimated to help determine an optimal approach to cost-effective cervical Pap screening. Such data analysis helps to determine the appropriate frequency of screening interventions. 6 . The screening procedure should be acceptable to the patient and society. Because screening tests are performed on asymptomatic individuals, these tests should be generally safe. The risks of complications from currently accepted screening interventions are small. Some procedures may have more significant associated risks (e.g., colonic perforation during screening sigmoidoscopy or colonoscopy).21The risks of colonic perforation are smaller for sigmoidoscopy than for colonoscopy. Therefore, although colonoscopy has the advantage of surveying the whole colon, its higher risk profile and cost make colonoscopy a less viable option for screening the general population. In patients at high risk for colon cancer, however, the benefit of screening via colonoscopy may outweigh this possible harm. In addition, many of the screening tests (e.g., pap smears, mammography, digital rectal examinations, blood draws and flexible sigmoidoscopy) physicians perform are invasive and have some degree of discomfort associated with them. This is an important consideration also in the viability of a screening intervention because patient discomfort influences compliance. The ideal screening situation involves the use of an inexpensive, noninvasive test with a high level of sensitivity and specificity to detect a common problem that can be treated and that left untreated leads to significant morbidity and mortality. Medical practice and the medical literature identify few such interventions that are this ideaI.
BARRIERS TO SCREENING Several barriers exist that impede application of even the best preventive screening interventions. A useful classification of the barriers to implementation of clinical prevention has been devised by Frame6(Table 3). He divides barriers into issues related to the individual patient, to the health care delivery system, and to the physician or health care provider.
Patient Barriers In an individual patient, the barriers to screening interventions may include social and cultural norms, perceptions of the likelihood of getting the disease, fear of finding a disease, discomfort, cost, and the implications should a problem be found.I5 At the same time, some of these same factors, such as a patient’s perception of getting a disease,
.
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Table 3. BARRIERS TO CLINICAL PREVENTION Patient Barriers
Ignorance of benefits Doubts about the physician’s ability to detect a hidden disease Cost of procedures Discomfort Conscious or unconscious desire not to change unhealthy habits Social and cultural norms Health System Barriers
Inadequate reimbursement Lack of health insurance Population mobility Patients with multiple physicians Categoric, sporadic screening programs such as health fairs Physician Barriers
Knowledge Uncertainty about conflicting recommendations Uncertainty about the value of tests or interventions Disorganized medical records Delayed and indirect gratification from screening Lack of time Attitudes and personal characteristics Modified from Frame PS Health maintenance in clinical practice: Strategies and barriers. Am Fam Physician 45:1192-1200, 1992; with permission.
provide the impetus for patients to seek physician services. For example, Osborne et alZ found that in a sample of men from Australia, approximately 30% undergoing prostate-specific antigen testing had personally requested the test from their physicians. Patients often want to be reassured about a condition they have heard or read about or want to address a condition at an early stage to prevent an adverse outcome. Similarly, patients’ perceptions of a condition may be influenced by a friend or an acquaintance having a health outcome. The most difficult patient barrier to overcome in preventive medicine is changing patient behavior. Primary prevention focuses on preventive health-related behavior. Preventive health-related behavior includes diet, exercise, sexual practices, alcohol consumption, tobacco use, and other personal habits. Changing these behaviors can influence the success of a screening intervention. Because these habits are often difficult to change, a screening intervention may be deemed cost-inefective. The health belief model implies that behavior to prevent a disease is influenced by a person’s perception of the personal threat of the disease or ~0ndition.l~ That is, the more severe the disease and the more susceptible to it the patient perceives himself or herself to be, the more likely he or she is to change a behavior that can influence the outcome of that condition. At the same time, changing a behavior is influenced by the ease of making the change, the perceived effectiveness of making the change, and particularly the social group influence of the change.14
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Identifying the influential people of a person’s social group and, where possible, using them as allies can assist in getting a person to change a negative health-related behavior. Often these behaviors are long-standing and ingrained into the upbringing, cultural background, and social norms of the individual. No quick solutions exist to overcome these barriers. The health care cost crisis in the United States; the efforts of the media; the increased exposure of medical information via the Internet; and the emphasis of preventive services via the work of the Canadian Task Force, the U.S. Preventive Service Task Force, and other major groups have helped push the responsibility for wellness and health back onto the individual. As good preventive habits, such as not smoking, condom use, eating a lowfat diet, and exercising regularly, become ingrained in society, people should become more motivated to seek preventive advice for themselves and their families.15 Health System Barriers
The mobility of the population, leading many patients to encounter multiple physicians over their lifetime, causes difficulties for tracking and ensuring clinical preventive services. As computer technology advances and the issue of basic health insurance for all people in the United States is addressed, problems of tracking clinical preventive services should decline.lSAnother challenge for clinical preventive medicine is the provision of appropriate reimbursement to the health care providers for risk assessment and counseling. To some extent, this situation is being addressed by incentives built into systems of care. Time and priorities of patients and physicians also influence the success or failure of preventive screening interventions. Patients often come to physicians with a prioritized list of problems that need to be addressed. Preventive screening may not be high on that list. The busy practitioner may be overtaxed by the activities of the day and thereby not allow time for effective, time-intensive preventive counseling. Delegating responsibility for tracking and providing preventive services to a nonphysician health care provider may be helpful. Organizational barriers for screening can be viewed as global or local. The global barriers include inadequate reimbursement to physicians for proviston of preventive services, lack of health insurance, and mobility of the population both geographically and individually from one health insurance provider to another.15A more useful view, however, is to look at the physician’s individual practice setting and to evaluate the local barriers to screening. Local barriers may include some of the same global factors, such as inadequate reimbursement and population mobility, but they also contain barriers that are more easily changeable for the individual physician. Organization of medical records, development of a health care maintenance flow sheet, and delegation of responsibility for these services to nonphysicians in the practice can allow for barriers
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to clinical preventive services to be overcome. Resources outside of the practice, such as hospital patient education programs and community and professionally sponsored programs, which can provide a variety of counseling services and education to the individual, may also be helpful.16 Physician Barriers
Are physicians a problem or a solution to providing better preventive care? This question, posed by Belcher et al,' is best answered both. Preventive services have not traditionally been a major focus of the basic medical school education curriculum. Medical education has focused on diseases after they have occurred, and the medical literature has a paucity of texts concerning the science and value of clinical prevention and its delivery. The role of the physician in providing preventive care has often been ambiguous. As Lang and Shainoff l5 state The physician trained in the curative approach to medical problems and faced with a patient with a specific problem or symptom is hard pressed to spend time on prevention of other medical issues that occur much later in a patient's life. Faced with a busy practice and time constraints, the time required for counseling and changing habits again presents itself as a barrier, particularly when reimbursement is not provided in a meaningful way. Another issue is that the practitioner does not see the "positive" health outcomes from prevention in the same patient in a mobile and ever-changing patient population. Clear consensus regarding clinical prevention screening recommendations has not existed and has led to confusion. Differences exist for recommendations regarding screening modalities, such as cholesterol screening7breast cancer screening? 9, and colorectal cancer s~reening.'~ Disagreement exists among physicians regarding recommendations made by major advisory groups, such as the U.S. Preventive Services Task Force.31Finally, physicians often do not comply, even with their own recommendation^.^^ There is no easy solution to these obstacles. The key factors for overcoming these physician barriers are (1)consensus of clinical prevention recommendations, (2) appropriate reimbursement for preventive services, (3) education about the necessity of delivering appropriate services, (4)advancement of computer applications to ease recording and tracking patients and to provide reminders about clinical preventive services, and (5) planning and organization within the practice.15 PROCEEDING WITH PRUDENCE A primary goal of screening is to improve the health of patients and the population in general. Implied in this goal is the underlying
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principle, "Do no harm." Because screening tests are generally performed in asymptomatic patients, this principle of "Do no harm" conveys added significance. A positive screening test result is often followed by a diagnostic test, which may carry more risk than the screening test itself. If the screening test was not indicated or unnecessary in the first place, it is not an ideal situation to put the patient at risk by the subsequent diagnostic testing that follows. When an individual undergoes a screening intervention, there are four possible outcomes. 1. A true-positive result. The test correctly identifies the presence of an underlying disease or condition, and the patient can go on to further diagnosis and treatment. 2. A true-negative result. The intervention correctly indicates the absence of an underlying disease or condition, and the patient can be correctly assured that they do not have the disease or condition in question. Most screening interventions result in a true-negative result. 3. A false-positive result. The intervention falsely indicates that a disease or condition is present. The patient usually undergoes further testing, with its attendant risks, inconveniences, and costs. A false-positive result may also cause unnecessary anxiety and label a patient with a disease or condition that the patient does not actually have. Patients falsely labeled with a diagnosis of hypertension have been shown to have adverse outcomes (e.g., decreased work productivity and altered behavior pattems).17 4. A false-negative result. The screening intervention falsely indicates that a disease or condition is absent. In such a case, the patient may develop a mistaken sense of security and ignore symptoms when they occur. More importantly, diagnostic and therapeutic interventions may be delayed. Physicians should generally look to screening tests with good track records (e.g., screening tests that are both effective, the performance characteristics of the test, and efjicacious, the intervention results in more good than harm). The literature provides examples of obstetric and gynecologic tests, such as ovarian cancer screening with CA-125 and home uterine activity monitoring, that have been put into clinical practice before true demonstration of their clinical effectiveness has occurred.s The performance characteristics of a test (predictive value) depend on. the prevalence of the disease or condition in question. Even highly accurate screening tests generate a large number of false-positive results when applied to an uncommon disease or condition. For example, a test with a sensitivity and specificity of !%%, when applied to a population of 1 million with a disease X prevalence of 0.05% produces the following test results (Table 4): True positives (TP)-4750 individuals True negatives (TN)-945,250 individuals False negatives (FN)-250 individuals False positives (FP)-49,750 individuals
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Table 4. EFFECT OF PREVALENCE ON TEST CHARACTERISTICS
Test Positive Test Negative Total
Disease X Present
Disease X Absent
Total
4750 pts (TI') 250 pts (FN) 5000 pts
49,750 pts (FP) 945,250 pts (TN) 995,000 pts
54,500 pts 945,500 pts 1,000,000 pts
Testing conditions: population size = 1,000,000; disease X prevalence = 0.05%; sensitivity of test = 95%; specificity of test = 95%. pts = Patients; TP = true positives; FN = false negatives; FP = false positives; TN = true negatives.
The positive predictive value of the test in this population is thereby only 8.7%. In this hypothetical example, 49,750 individuals would be labeled as false-positives and could thereby suffer increased risks from follow-up testing. In this situation, the benefits (early detection) may not outweigh the risks (high number of false positives). The quest for doing more good than harm is an underlying concept of what today is commonly referred to as evidence-based medicine. Evidence-based medicine is important in the arena of preventive medicine to help determine preventive screening interventions of greatest utility to the population. Evidence-based medicine can be viewed as "the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients."25This concept generally implies having scientific backing from well-conceived, randomized, controlled clinical trials or other well-designed clinical trials, such as cohort studies. These clinical trials provide the scientific evidence and base of preventive medicine to integrate with the clinical judgment of the individual physician. Sackett et alZ5state, "External clinical evidence can inform, but can never replace, individual clinical expertise, and it is expertise that decides whether external evidence applies to the individual patient at all and, if so, how it should be integrated into a clinical decision." This is not, however, a call to disregard clinical evidence in regard for personal preference. To do so would be a disservice to patients. Clinical judgment and external evidence should go hand in hand. Major advisory groups have different recommendations for screening based on their different integrations of the external evidence and clinical judgment. The articles in this issue also present recommendations for screening in light of this integration. The U.S. Preventive Services Task Force and the Canadian Task Force on the Periodic Health Examination are prominent examples of evidence-based 'medicine at work. They attempt to make screening recommendations based on scientific evidence rather than relying on expert opinion. The underlying theme is that the benefits of an intervention should be clearly shown to outweigh possible harms before an intervention is used routinely on an asymptomatic population. The quality of
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the evidence is believed to be as important as the results of the study itself. The hierarchy of evidence, in decreasing order of importance, is randomized, controlled trials; nonrandomized, controlled trials; cohort studies; case-control studies; uncontrolled experiments; descriptive studies; and expert opinion. The U.S. Preventive Services Task Force quality of evidence criteria and strength of recommendations are outlined in Table 5. Such a hierarchial approach is valid because all clinical trials have inherent weaknesses and biases. The main biases affecting the internal validity of the randomized, controlled trials are diIution and cont~minution.~ Dilution implies that some patients who are offered screening may not actually receive it, and contamination implies that some of the patients who were not randomized to the screening arm may receive the test anyway. Also, the patient population of the randomized, controlled trials may not mirror the general population secondary to the imposed exclusion criteria that most randomized clinical trials use. Additionally, individual clinicians in the community may not perform the screening test in the same manner as the investigator who usually has special expertise and a standardized Cohort studies, which are prospective in design, and case-control studies, which are retrospective in design, are also prone to bias. Both study designs can be affected by patient-selection bias and confounding variables (i.e., related factors that may be more directly responsible for the outcome of the study than the intervention itself). Uncontrolled
Table 5. QUALITY OF EVIDENCE AND STRENGTH OF RECOMMENDATIONS Quality of Evidence I Evidence obtained from at least one properly designed randomized, controlled trial 11-1 Evidence obtained from well-designed controlled trials without randomization II-2 Evidence obtained from well-designed cohort or case-control analytic studies, preferably from more than one center or research group 11-3 Evidence obtained from multiple time series with or without the intervention or dramatic results in uncontrolled experiments (such as the results of the introduction of penicillin treatment in the 1940s) 111 Opinions of respected authorities, based on clinical experience, descriptive studies, or reports of expert committees Strength of Recommendations A There is good evidence to support the recommendation that the condition be specifically considered in a periodic health examination B There is fair evidence to support the recommendation that the condition be specifically considered in a periodic health examination There is poor evidence regarding the inclusion of the condition in a periodic health C examination, but recommendations may be made on other grounds D There is fair evidence to support the recommendation that the condition be excluded from consideration in a periodic health examination E There is good evidence to support the recommendation that the condition be excluded from consideration in a periodic health examination From US. Preventive Services Task Force: Task Force Ratings: Guide to Clinical Preventive Services. Washington, DC, U.S. Department of Health and Human Services, 1996, p 862.
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studies can also be affected by patient-selection bias and confounding variables but are subject to lead-time bias and length bias as well. In lead-time bias, the Zead-time is the time between the screening diagnosis and the clinical diagnosis. This lead-time often overestimates the effectiveness of screening. For example, suppose disease X is diagnosed through a screening intervention in 1990, and despite treatment the patient dies in 1995. Suppose a similar patient has the same-stage disease in 1990 but is not screened and is not diagnosed until he or she develops clinical symptoms in 1992. This patient undergoes treatment as well and dies in 1995. Studies may report a 2-year survival benefit for screening when in reality no clinical benefit is gained. The observed increase in survival time is related to the earlier diagnosis and not to any true prolongation of life. This is an inherent difficulty when comparing screened and unscreened populations. Length term bias also overestimates the effectiveness of screening. Screening tests are more likely to detect chronic, slowly progressive conditions than fast, aggressive conditions or diseases. Fast, aggressive conditions are usually present in the population only for short periods of time. Length term bias refers to the overrepresentation of slowly growing conditions in the screened population. These chronic conditions carry a longer survival time that is unrelated to the screening intervention itself. Interpretation of a clinical trial should consider the type of trial used and the biases that may be affecting it. A secondary goal of screening is the cost-efficient use of the medical resources available. The resources to screen for all diseases simply do not exist. The actual cost-effectiveness and economic consequences of prevention can be difficult to clarify.Is Although some economic models have demonstrated the cost-effectiveness of screening tests using a population-based model,1z it is difficult to obtain hard evidence for such conclusions. For example, if colorectal cancer in a 65-year-old woman is prevented through appropriate screening, she may develop coronary artery disease or breast cancer at a later date, and the ultimate monetary cost is higher than the original treatment of colon cancer. Alternatively, if it were possible to prevent most diseases, such as cancer, would a burgeoning nursing home population and the high costs associated with nursing home care result? These are difficult questions. It is generally agreed on that the use of screening tests without demonstrated clinical effectiveness in place of tests that have demonstrated effectiveness would not be in the best interest of society and are probably not in the best interest of patients either. Physicians are best to endorse screening tests with established track records. CONCLUSION
This article provides a framework from which to view the subsequent articles devoted to screening for specific conditions or in specific patient groups. As medical technology advances, new screening tech-
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niques will be developed and physicians will be asked to use and recommend them appropriately. This article provides some of the basic tools needed for interpreting new medical evidence concerning screening techniques and screening situations, such as computed tomography for lung cancer quantitative ultrasound scans of the calcaneus for osteoporosis or mass screening for thyroid cancer.2o
References 1. Belcher DW, Berg AO, Inui TS: Practical approaches to providing better preventive care: Are physicians a problem or a solution? In Battista RN, Lawrence RS (eds): Implementing Preventive Services. New York, Oxford University Press, 1988 2. Canadian Guide to Clinical Preventive Health Care. Ottawa, Minister of Supply and Services Canada, Canada Communication Group, 1994 3. Dilhuydy MH, Barreau B: The debate over mass mammography: Is it beneficial for women? Eur J Radio1 24:86-93, 1997 4. Eddy DM: How to think about screening. In Eddy DM (ed): Common Screening Tests. Philadelphia, American College of Physicians, 1991 5. Fisher 8, Costantino J, Wickerman DL, et al: Tamoxifen for prevention of breast cancer: Report of the National Surgical Adjuvant Breast and Bowel Project P-1 study. J Natl Cancer Inst 901371-1388, 1998 6. Frame PS: Health maintenance in clinical practice: Strategies and barriers. Am Fam Physician 45:1192-1200, 1992 7. Garber AM, Browner WS, Halley SB: Cholesterol screening in asymptomatic adults, revisited. Ann Intern Med 124518-531, 1996 8. Grimes DA: Technology follies: The uncritical acceptance of medical innovation. JAMA 269~3030-3032,1993 9. Harris KM, Vogel VG: Breast cancer screening. Cancer Metastasis Rev 16:231-262, 1997 10. Harris R, Leininger L: Clinical strategies for breast cancer screening: Weighing and using the evidence. Ann Intern Med 122:539-547, 1995 11. Hayward RSA, Steinberg EP, Ford DE, et al: Preventive care guidelines: 1991. Ann Intern Med 114:758-783, 1991 12. Hristova L, Hakama M Effect of screening for cancer in the Nordic countries on deaths, cost and quality of life up to the year 2017. Acta Oncol 36(supp19):140, 1997 13. Jam NK, Becker MH: The health belief model: A decade later. Health Educ Q 11:l47,1984 14. Jenkins DC:Diagnosis and treatment of behavioral barriers to good health. In Last JM (ed): Maxcy-Rosenau public health and preventive medicine. Norwalk, CT, AppletonCentury-Crofts, 1986 15. Lang RS, Shainoff JD: Integrating clinical preventive service into office practice. In Matzen RN, Lang RS (eds): Clinical Preventive Medicine. St. Louis, MO, Mosby-Year Book, 1993 16. Leatt P;Frank J: Organizational issues related to integrating preventive services into primary care. In Battista RN, Lawrence RS (eds): Implementing Preventive Services. New York, Oxford University Press, 1988 17. Lefebvre RC, Hursey KG, Carleton RA: Labeling of participants in high blood pressure screening programs: Implications for blood cholesterol screenings. Arch Intern Med 148:1993-1997, 1998 18. Leutwyler K The price of prevention. Sci Am 272:124129, 1995 19. Mandel JS: Colorectal cancer screening. Cancer Metastasis Rev 16263-279, 1997 20. Miki H, Inoue H, Komaki K, et a1 Value of mass screening for thyroid cancer. World J Surg 22:99-102, 1998 21. Nelson RL, Abcarian H, Prasad ML: Iatrogenic perforation of the colon and rectum. Dis Colon Rectum 25:305-308, 1982
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22. Osborne DN, Gardner IL, Stacey BG, et al: Men’s estimates of prostate cancer risk and self-reported rates of screening. Med J Aust 169:57, 1998 23. Philbrick JT, Becker DM: Screening for early disease: Interpretation of diagnostic tests. In Becker DM, Gardner LB (eds): Prevention in Clinical Practice. New York, Plenum, 1988 24. Pocock NA, Noakes KA, Howard GM, et al: Screening for osteoporosis: What is the role of heel ultrasound? Med J Aust 164:367-370, 1996 25. Sackett DL, Rosenberg WM, Gray JAM, et al: Evidence-based medicine: What it is and what isn’t. BMJ 312:71-72, 1996 26. Sone S, Takashima S, Li F, et al: Mass screening for lung cancer with mobile spiral computed tomography scanner. Lancet 35:1242-1245, 1998 27. Topol EJ, Nissen SE: Our preoccupation with coronary luminology: The dissociation between clinical and angiographic findings in ischemic heart disease. Circulation 92:2333-2342, 1995 28. U.S. Preventive Services Task Force: Guide to Clinical Preventive Services: Report of the United States Preventive Services Task Force, ed 2. Baltimore, Williams & Wilkins, 1996 29. Woo B, Woo B, Cook FE, et al: Screening procedures in the asymptomatic adult, comparison of physicians’s recommendations, patients’ desires, published guidelines, and actual practice. JAMA 254:1480-1484, 1985 30. Woolf SH: Analytic principles in assessing the effectiveness of clinical preventive services. In Goldbloom RB, Lawrence RS (eds): Preventing Disease: Beyond the Rhetoric. New York, Springer-Verlag, 1990 31. Zyzanski SJ, Stanger KC, Kelly R, et al: Family physicians’ disagreements with the US Preventive Services Task Force Recommendations. J Fam Pract 39:140-147, 1994 Address reprint reqtiests to Craig Nielsen, MD Department of General Internal Medicine/S70 The Cleveland Clinic Foundation 9500 Euclid Avenue Cleveland, OH 44195