Presentation on theme: "Screening in Disease Detection. Natural history of disease Onset of symptoms Usual time of diagnosis Exposure Pathologic changes Stage of susceptibility."— Presentation transcript:
Screening in Disease Detection
Natural history of disease Onset of symptoms Usual time of diagnosis Exposure Pathologic changes Stage of susceptibility Stage of subclinical disease Stage of clinical disease Stage of recovery, disability or death PRIMARY PREVENTION SECONDARY PREVENTION TERTIARY PREVENTION
Screening is the application of a test to people who are asymptomatic for the purpose of classifying a person with respect to their likelihood of having a particular disease A Key Assumption of Screening Programs: Early detection will lead to more favorable prognosis
Screening, in and of itself, does not diagnose disease. Persons who test positive are referred to physicians for more detailed assessment Physicians determine the presence or absence of disease. Screening is one of the most practical applications of epidemiology. Its goal is to promote health and prevent disease.
When is it appropriate to initiate screening programs? 1. When the disease is serious 2. When the prevalence of pre-clinical disease is high 3. When medical care is available and health interventions are known to be effective 4. When failure to screen could be considered unethical
World Health Organization Criterion for Screening Is it a health problem? Is there treatment? Are there facilities in place? Is it detectable pre-clinically? Is there a suitable screening test? Is the screening test acceptable to people? Is the natural history of disease understood? Are the costs acceptable? Wilson JMG, Junger G. (1967) The principles and practice of screening for Disease. Public Health Paper 34: Geneva, Switzerland: World Health Organization
Screening involves: Organizing a deployment of public health resources, policies, and procedures Defining the target population Setting priorities among diseases and conditions Choosing effective screening tests
It also involves: Assessing the effectiveness of screening procedures and programs Adopting practice guidelines to local needs Dealing with controversial and conflicting guidelines Translating guidelines into programs through public health departments, managed-care organizations, community based coalitions, and workplace coalitions.
Community Media Managed care Health Departments Universities Schools Workplaces Community Based Organizations (e.g. Churches) Clinic - Patient - Provider - Community Liaison Places of Recreation Conceptual framework relating screening at the individual, settings, and community levels
When examining a screening test we tend to look most closely at its Validity Reproducibility Efficacy
How do we judge the validity of a screening test? We compare the screening test against some gold standard Disease gold standard Test Result PresentAbsent Positive true positivefalse positive Negative false negativetrue negative
As a measure of the validity of the test we calculate: Sensitivity = Probability that a person having the disease is detected by the test = P (test positive | they have the disease) Specificity = Probability that a person who does not have the disease is classified that way by the test = P(test negative | they dont have the disease)
Disease gold standard Test Result PresentAbsentTotal Positive TPFPall who test + Negative FNTNall who test - Total All with All withoutDisease Sensitivity = TP Specificity = TN TP + FNFP + TN
How do we examine the reproducibility? We do the tests repeatedly in the same individuals and calculate measures of: Intrasubject Variation (Table 4-7 in Gordis) Interobserver Variation (Figure 4-12 in Gordis) Overall Percent Agreement Kappa Statistic
For a measure of the efficacy of the test we use... Positive Predictive Value = Probability that someone who tests positive for the disease will actually have the disease = P (have disease | positive test result) Negative Predictive Value = Probability that someone who tests positive for the disease will actually have the disease = P (dont have disease | negative test result)
Disease gold standard Test Result PresentAbsentTotal Positive TPFPall who test + Negative FNTNall who test - Total All with All withoutDisease Positive predictive value = TP / TP + FP Negative predictive value = TN / TN + FN
One of the reasons Positive Predictive Value is used as a measure of efficacy is because it depends on the prevalence of the disease For a given screening test with sensitivity fixed at X% and specificity fixed at Y%, if the prevalence then PPV or if the prevalence then PPV
For example, for a screening test with sens=99% and spec=95% (Gordis, 1996) Disease Prev Test Present Absent Total PPV 1% % - 19,4059,406 =99/594 Totals100 9,90010,000 5% % - 59,0259,030 =495/970 Totals 500 9,50010,000
What if we want to screen for a quantitative risk factor? Blood cholesterol levelsHeart Disease Plasma Glucose levelsDiabetes Cognitive functionDementia Body Mass IndexObesity Blood pressureHypertension
For quantitative tests, we have to think about screening a little differently Truly Diseased Not Diseased True Negatives False Negatives False Positives True Positives Disease Cutpoint for screening Risk factor level
So what would happen if we lowered the cut off? Truly Diseased Not Diseased True Negatives False Negatives False Positives True Positives Disease Cutpoint
Some notable features of sensitivity and specificity for a quantitative test: Lowering the cutpoint for the screening test will true positivessensitivity true negatives specificity And of course, increasing the cutpoint will have the exact opposite effect.
Given that there will be trade-offs between sensitivity and specificity, how do we decide which errors are more costly? 1. Failing to detect some true cases because of lower sensitivity or 2. Misclassifying some people as diseased because of lower specificity
It depends... On the prevalence of the disease On the severity of the disease On the potential fatality of the disease On how good the test is On the acceptability of the test to people
Whats the most appropriate cutpoint? (What if its a marker for a lethal disease? What its just a health indicator?)
What are other strategies for dealing with this tradeoff? Use parallel tests - here a positive result on any one test defines the person as a probable case Use serial tests - here a positive result on a first test are re- evaluated on a second test - individuals must test positive on both tests to be considered a probable case.
Biases when evaluating a screening program There are three possible sources of bias when evaluating a screening program that may result in a false picture of its efficacy: –1. Volunteer bias –2. Lead time bias –3. Length time bias
Biases when evaluating a screening program 1. Compliance (volunteer) bias: Volunteers for screening are generally more health conscious/concerned than the general population, apt to assume greater responsibility for their own care, hence, more likely to comply with therapy.
Biases when evaluating a screening program 2. Lead time bias Lead time is the amount of time by which the diagnosis was advanced due to screening. Lead time bias means that survival may erroneously appear to be increased among screen-detected cases simply because the diagnosis was made earlier in the course of the disease.
Fig. 1.Natural history of disease. Diagram illustrates that preclinical phase begins at onset and ends when signs or symptoms develop. Clinical phase then starts, ending with death. Detectable preclinical phase (DPCP) begins when disease is detectable by a test. Detection (X) during DPCP advances time of diagnosis by duration of lead time.
Fig. 2.Lead-time bias. Diagram shows that, with screening, time of diagnosis is advanced by lead time provided by positive test result. If earlier diagnosis has no effect on time of death from disease, then survival with testing is equal to survival without testing plus lead time.
Biases when evaluating a screening program 3. Length time bias Less aggressive forms of a disease are more likely to be picked up in a screening program because they have a longer detectable pre-clinical phase. Less aggressive forms of disease usually have better survival.
Fig. 3.Diagram shows how probability of detection is related to rate of disease progression. Length of each arrow represents length of detectable preclinical phase, from initial detectability to clinical diagnosis (Dx). Testing at a single moment detects four slowly progressive cases but only two rapidly progressive cases. Cases not detected by test (thin arrows) are diagnosed clinically either before or after time of testing. Thick arrows indicate detected cases.
Prostate Cancer Example
Prostate cancer It is the second most common form of cancer among men in the United States. It is also the second leading cause of cancer deaths. American Cancer Society estimates that 179,300 new cases of prostate cancer were diagnosed in 1999 and 37,000 men died in This cancer is most common among men 65 years and older.
Prostate cancer At all ages, African American men have the highest incidence of PCA in the world diagnosed with the disease at later stages die of prostate cancers at higher rates
Incidence of Prostate Cancer Recently, weve been better able to detect prostate cancer and hence our estimates of its incidence have increased
Death rates for Prostate Cancer Death rates for African American men is twice what it is for White men.
Age-dependent Incidence and Death Rates Incidence of PCA appears to level off above 70 yrs but the death rate becomes exponentially worse at that age.
Early Detection The benefits of early detection of prostate cancer are thought to be the same as for any cancer. However, Little is know about how to prevent the disease Scientific evidence is lacking about whether screening reduces deaths Evidence is lacking about whether current treatments really prolong mens lives.
Two commonly used methods for detecting prostate cancer 1. Digital rectal examination (DRE) This has been used for years... But its ability to detect PCA is limited It cant detect some small tumors It cant distinguish between benign tumors and cancer
2. Prostate-specific antigen (PSA) test PSA is an enzyme that increases with age and because of prostate abnormalities Its now used widely but medical consensus hasnt been reached on its utility It also cannot distinguish between benign and cancerous tumors.
What are the treatment alternatives? Radical prostatectomy Radiation therapy Watchful waiting
Criterion Prostate Cancer Is it a health problem?Yes Is there treatment?Probably Are there facilities in place?Yes Is it detectable pre-clinically?Yes Is there a suitable screening test?Yes Is the screening test acceptable?Yes Is the disease understood?Partially Are the costs acceptable?Possibly Is continuous screening set up?Premature Meyer F, Fradet Y. Clinical basics:Prostate Cancer:4. Screening. Can Med Assoc J; (8):
Data from American Cancer Societys National Prostate Cancer Detection Project and the European Randomized Study of Screening for Prostate Cancer Prostate Cancer Test resultPresentAbsentTotal Positive Negative Total Positive test result = a PSA level >4ng/ml and DRE evidence False negatives detected by biopsy after transurethal ultrasonography yielded abnormal findings. Meyer F, Fradet Y. Clinical basics:Prostate Cancer:4. Screening. Can Med Assoc J; (8):
Data from Canadian National Breast Screening Study Breast Cancer Test resultPresentAbsentTotal Positive1423,2303,372 Negative 15 16,32416,339 Total226 19,555419,711 Positive test result = a suspicious finding by mammogram and/or physical exam False negatives are those in whom breast cancer was discovered in 1st yr follow-up Meyer F, Fradet Y. Clinical basics:Prostate Cancer:4. Screening. Can Med Assoc J; (8):
Comparison of Breast and Prostate Cancer ProstateBreastCancer Sensitivity,% Specificity, % Positive test, % Prevalence, % Positive predictive value, % Meyer F, Fradet Y. Clinical basics:Prostate Cancer:4. Screening. Can Med Assoc J; (8):
Other issues related to Screening Programs: Evaluating the effectiveness of the program Defining High Risk subgroups - Those subgroups for whom the prevalence of asymptomatic disease is expected to be higher Ethical considerations - Who should be offered the test? - Who should have access to the results?
Selected Examples of Prevention Effectiveness Annual US % of persons Prevention Undesired Incidence without Prevention Economic at Risk Covered Type* Outcome Intervention Method % Effectiveness Analysis by Method Primary Measles 4,000,000 Vaccination $16.85 per By age 2, 50-80%; case prevented by age 6, 98% Secondary Breast cancer 50,000 Mammography $45K to $165K per deaths screening year of life saved Tertiary Blindness from 24,000 Retinal screening, 50 $100 per year of Diabetes treatment vision saved * Primary prevention = directed at susceptible persons before they develop a particular disease (risk factor reduction); Secondary prevention = directed at persons who are symptomatic but who have developed biologic changes (early detection and treatment); Tertiary prevention = directed at preventing disability in persons who have symptomatic disease (prevent complications and rehabilitation). SOURCE: Thacker et. Al. (1994)
Group Health Cooperative of Puget Sounds Breast Cancer Risk Algorithm and Screening Protocol Mammography Risk Relative Percentage Frequency Level Risk-Level Criteria Risk Women Annual Every 2 Years Every 3 Years Not Recommended Previous breast cancer or atypia on biopsy results; at least 2 first-degree relatives with breast cancer One first-degree relative with breast cancer; >50 years of age and >2 MRFs >50 years of age and >1 MRF; or >50 years of age and > MRF <50 years of age and no MRF Source: Taplin et al. (1990)
Conditions for Which Screening Is Recommended, USPSTF 1996 Health Outcome Test(s) Populations(s) Age Group (years) HIV HbgSS/PKU/ Hypothyroidism Anemia Lead poisoning Rubella Tuberculosis Hearing Vision Lab Hgb/Phenylalanine T4&TSH Hgb/Hct Blood lead Lab PPD -- HR2/HR3 General/General general HR1/HR/P (female) HR7 General (female) HR1/HR3/HR6/HR7 General 0-10/11+ Birth/Birth Birth 0-10/ , /0-24/ , 65+ Source: U.S. Preventive Services task Force [USPSTF] (1996)
More Conditions for Which Screening Is Recommended Health Outcome Test(s) Populations(s) Age Group (years) Obesity CVD/HBP CVD Injury/Liver disease Colorectal cancer Breast cancer Cervical cancer Chlamydia Gonorrhea Syphilis Height/Weight Blood pressure Cholesterol Alcohol overuse Fecal Occult Blood Test Sigmoidoscopy Mammography /Clinical Breast Exam Pap Smear Lab General General/HR6 General General/HR4 HR2 HR1/HR9 All 25-64/ (female) 11+ (female) 11-24/ , /65+ Source: U.S. Preventive Services task Force [USPSTF] (1996)