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Disease screening

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Seminar

Publié dans : Santé & Médecine

Disease screening

  1. 1. DISEASE SCREENING DR. AMANDEEP KAUR JUNIOR RESIDENT DEPARTMENT OF COMMUNITY MEDICINE PGIMS, ROHTAK
  2. 2. CONTENTS • Introduction • Why screening? • Lead time • Uses of screening • Types of screening • Criteria of screening • Problem of borderline • Use of multiple tests • Bias in screening • Evaluation of screening programme • Examples
  3. 3. INTRODUCTION
  4. 4. DISEASE PREVENTION CATEGORIES: • Primordial prevention – prevention of development of risk factors • Primary prevention - The actual prevention of a disease before it has been able to occur. • Secondary prevention - The early detection of a disease while it is still curable. Screening is the major component of secondary prevention. • Tertiary prevention - The limiting of disease sequelae. 4
  5. 5. NATURAL HISTORY OF DISEASE outcome 5 (A) Biologic onset of disease (S) Signs & Symptoms of disease (M) Medical Care Sought (D) Diagnosis (T) Treatment (P) Pathologic Evidence of disease if Sought Pre-clinical phase Clinical phase Primary prevention Secondary prevention Tertiary prevention (L) Disability limitation (R) Rehabilitation
  6. 6. DEFINITION SCREENING: The search for unrecognized disease or defect by means of rapidly applied tests, examinations or other procedures in apparently healthy individuals. (in those populations or individuals who are NOT seeking health care) The active search for disease among apparently healthy people – fundamental concept.
  7. 7. DEFINITION CASE-FINDING: use of clinical and/or laboratory tests to detect disease in individuals seeking health care for other reasons. For example, the use of VDRL test to detect syphilis in pregnant women.
  8. 8. DEFINITION DIAGNOSTIC TEST: use of clinical and/or laboratory procedures to confirm or refute the existence of disease or true abnormality in patients with signs & symptoms presumed to be caused by the disease. For example, VDRL testing of patients with lesions suggestive of secondary syphilis.
  9. 9. Done on apparently healthy Done on those with indication or sick Applied to groups Applied to single patient Results are arbitrary and final Diagnosis not final, but sum of all evidence Based on one criterion or cut off point Evaluation of symptoms, signs and lab findings Less accurate and less expensive More accurate and more expensive Not a basis for treatment Basis of treatment Initiative comes from investigator Initiative comes from a patient
  10. 10. WHY SCREENING?
  11. 11. WHEN TO SCREEN?
  12. 12. LEAD TIME Detection programmes should be restricted to those conditions in which there is considerable time lag between disease onset and the usual time of onset. A B Disease onset & detection Final critical diagnosi s Lead time First possibl e point A – usual outcome of the disease B – expected outcome B – A : benefits of the programme OUTCOM E Usual time of diagnosi s Screening time
  13. 13. APPARENTLY HEALTHY (Screening tests) APPARENTLY NORMAL (Periodic re-screening) APPARENTLY ABNORMAL a. Normal – periodic – re-screening b. Intermediate - surveillance c. Abnormal - treatment POSSIBLE OUTCOMES OF SCREENING TEST
  14. 14. USES OF SCREENING  Case detection – (prescriptive screening) presumptive identification of unrecognized disease, which does not arise from patient’s request. People screened primarily for their own benefit. E.g., neonatal screening, bacteriuria in pregnancy, diabetes mellitus. Control of disease – (prospective screening) people screened for benefit of others. E.g. screening of immigrants from infectious disease.  Research purpose.  Educational opportunities.
  15. 15. TYPES OF SCREENING  Mass screening: screening of a whole population or a sub-group, e.g., all children; irrespective of the particular risk individual may run of contracting the disease in question. High risk or selective screening: applied selectively to high risk groups, the groups defined on the basis of epidemiological research, e.g., screening of cancer cervix in lower social groups. Multiphasic screening: application of two or more screening tests in combination to a large number of people at one time. It is very expensive.
  16. 16. TYPES OF SCREENING  Opportunistic screening: individuals are entered into a screening programme whenever an opportunity arises, usually when they go to a doctor about something else. e.g., STIs, cervical cancer Systematic screening programmes: in which an attempt is made to identify everyone who should be screened and invite them to attend for the screening test
  17. 17. CRITERIA FOR SCREENING DISEASE
  18. 18. CRITERIA FOR SCREENING DISEASE  Important health problem  Recognizable latent or early asymptomatic stage.  Natural history of the condition should be known.  Presence of a test that can detect the disease prior to onset of signs and symptoms.  There should be an effective treatment
  19. 19. CRITERIA FOR SCREENING DISEASE  Facilities should be available for confirmation of the diagnosis.  Agreed on policy concerning whom to treat as patients.  Good evidence that early detection and treatment reduces morbidity and mortality.  The expected benefits of early detection should exceed the risks and costs. When the above criteria are satisfied, then only, the screening test is
  20. 20. CRITERIA FOR SCREENING SCREENING TEST
  21. 21. Acceptability. Repeatability/ Reliability/ Precision/ Reproducibility. Validity (accuracy) Yield Simplicity, safety, rapidity, easy and cost.
  22. 22. Acceptability • The test should be acceptable to the people at whom it is aimed. • It should not be painful, discomforting, or embarrassing
  23. 23. Repeatability Test must give consistent results when repeated more than once on same individual or material, under same conditions. Sometimes called reliability, precision or reproducibility. Factors contributing to variation in test results: • Biological (intrasubject) variation : • Changes in parameter observed with time. • Variations in the way patients perceive their symptoms and answers. • Observer variation : • Intra – observer variation. • Inter – observer variation. • Errors relating to technical methods • Perception variation
  24. 24. Repeatability • Can be assessed in various ways: • Intrasubject (multiple screening tests) - means, averages; paired t-tests • Inter-observer or inter-instrument (multiple observers or instruments) – Dichotomous outcome with paired samples – Percent agreement = a / (a + b + c) – Kappa statistic (test agreement, not quantify agreement) – McNemar’s test - non parametric test of agreement of paired samples • Continuous outcome – Differences in paired measurements – Coefficient of variation
  25. 25. Validity (accuracy) • To what extent the test accurately measures which it purports to measure. • Expresses ability of test to separate or distinguish those who have the disease from who do not. • Closeness with which measured values agree with true values. • Components of validity oSensitivity : ability of test to identify correctly all those who have the disease, i.e., true positives. oSpecificity : ability of a test to identify correctly those who do not have the disease, i.e., true negatives.
  26. 26. VALIDITY AND RELIABILITY 27
  27. 27. SCREENING TEST RESULT BY DIAGNOSIS SCREENIN G TEST RESULTS DIAGNOSIS TOTAL DISEASED NOT DISEASED POSITIVE a+b (all people with positive test results) NEGATIVE c+d (all negatives with negative test results)
  28. 28. SCREENING TEST RESULT BY DIAGNOSIS SCREENIN G TEST RESULTS DIAGNOSIS TOTAL DISEASED NOT DISEASED POSITIVE a (True Positives) b (False positives) a+b PPV NEGATIVE c (False Negatives) d (True Negatives) c+d NPV TOTAL a+c b+d a+b+c+d SENSITIVITY SPECIFICIT Y
  29. 29. True positive False positive True negativ e False negative True positives All cases Sensitivity = b a + c b + d = a a + c True negatives All non-cases Specificity = = d b + d a + b c + d TRUE DISEASE CasSesTATUNSon-cases Positiv e Negative SCREENING TEST RESULTS a d c
  30. 30. TRUE DISEASE CasSesTATUNSon-cases Positiv e Negative SCREENING TEST RESULTS a d 1,000 b c 60 Sensitivity = True positives All cases 200 20,000 = 140 200 Specificity = True negatives All non-cases = = 70% 19,000 20,000 1,140 19,060 140 19,000 = 95%
  31. 31. PRINCIPLES SCREENING PROGRAMMES • An ideal screening test would be 100% sensitive and 100% specific - that is there would be no false positives and no false negatives • In practice, these are usually inversely related • It is possible to vary the sensitivity and specificity by varying the level at which the test is considered positive 32
  32. 32. SENSITIVITY AND SPECIFICITY VERSUS CRITERION VALUE
  33. 33. INTERPRETING TEST RESULTS: PREDICTIVE VALUE Probability (proportion) of those tested who are correctly classified Cases identified / all positive tests Non cases identified / all negative tests
  34. 34. True positive False positive True negativ e False negative PPV = b a + c b + d True positives All positives = a a + b NPV = True negatives All negatives = d c + d a + b c + d TRUE DISEASE CasSeTsATUNSon-cases Positiv e Negative SCREENING TEST RESULTS a d c
  35. 35. TRUE DISEASE CasSesTATUNSon-cases Positiv e Negative SCREENING TEST RESULTS a d 1,000 b c 60 PPV = 200 20,000 True positives All positives = 140 1,140 NPV = True negatives All negatives = = 12.3% 19,000 19,060 1,140 19,060 140 19,000 = 99.7%
  36. 36. POSITIVE PREDICTIVE VALUE, SENSITIVITY, SPECIFICITY, AND PREVALENCE Prevalence (%) PPV (%) Se (%) Sp (%) 0.1 1.4 70 95 1.0 12.3 70 95 5.0 42.4 70 95 50.0 93.3 70 95
  37. 37. Relationship between disease prevalence and predictive value in a test with 95% sensitivity and 95% specificity.
  38. 38. Amount of previously unrecognized disease that is diagnosed as a result of screening effort. Depends on :  Sensitivity  Specificity  prevalence and  participation of individuals. Calculated by :  prevalence of disease  positive predictive value Yield
  39. 39. Predictive accuracy • Reflects diagnostic power of test. • Depends upon sensitivity, specificity and disease prevalence. • Predictive value of a positive test (PPV): probability that a patient with positive test has, in fact, the disease in question. • Predictive value of a negative test (NPV): probability that a patient with negative test has does not have the disease in question.
  40. 40. PROBLEM OF THE BORDERLINE
  41. 41. UNIMODAL DISTRIBUTION BORDERLINE GROUP (C -- D) If cut-off point is set at level of C, test will be highly sensitive, but will yield many False Positives. If cut-off is set at D, it will increase specificity if the test
  42. 42. BIMODAL DISTRIBUTION
  43. 43. Where do we set the cut-off for a screening test? -The impact of high number of false positives: anxiety, cost of further testing -Importance of not missing a case: seriousness of disease, likelihood of re-screening
  44. 44. BASIS FOR CUT – OFF IN SCREENING Disease prevalence – highly prevalent – screening level is set at lower level – sensitivity increases The disease – lethal disease – greater sensitivity prevalent disease -- but treatment does not markedly alter outcome, e.g., diabetes – high specificity. PPV is useful index in making this decision.
  45. 45. ROC CURVE • Receiver operating characteristic curve. • In a ROC curve the true positive rate (Sensitivity) is plotted in function of the false positive rate (1-Specificity) for different cut-off points.
  46. 46. • The dotted diagonal line corresponds to a test that is positive or negative just by chance. • A test with perfect discrimination (no overlap in the two distributions) has a ROC plot that passes through the upper left corner (100% sensitivity, 100% specificity). Therefore the closer the ROC plot is to the upper left corner, the higher the overall accuracy of the test
  47. 47. USES OF ROC CURVES • For comparing two or more diagnostic tests. • For selecting cut-off levels for a test.
  48. 48. • To illustrate sensitivity and specificity and the inter-relationship between them, let's look at a real-life example using a fasting blood glucose level as a screening test for diabetes. • By choosing different values to define a "positive" screening result, we can change the sensitivity and specificity of the test. • For diabetes, we can use the 2-Hour Glucose Tolerance Test as the "gold standard" to classify whether or not a person has the disease. 49
  49. 49. 3 different levels defining a "positive" test (100) (110) (120) 50 Serum Glucose Levels (mg/dL) Normal Cut-off 1 Cut-off 2 Cut-off 3 Diabetes
  50. 50. 2-Hour Glucose Tolerance Test (mg/ dL) Sensitivity % Specificity % 70 98.6 8.8 80 97.1 25.5 90 94.3 47.6 100 88.6 69.8 110 85.7 84.1 120 71.4 92.5 130 64.3 96.9 140 57.1 99.4 150 50.0 99.6 160 47.1 99.8 170 42.9 100.0 180 38.6 100.0 190 34.3 100.0 200 27.1 100.0 51
  51. 51. ROC curve for 2-Hour Glucose Tolerance Test (mg/ dL) 80 90 120 130 140 150 170 180 200 70 100 110 160 190 100 80 60 40 20 0 0% 50% 100% 1- Specificity Sensitivity 52
  52. 52. USE OF MULTIPLE TESTS INCREASING SENSITIVITY AND SPECIFICITY
  53. 53. SEQUENTIAL (TWO-STAGE) TESTING • Use >1 test in sequence, stopping at the first negative test. • Diagnosis requires all tests to be positive. • A cost saving measure. • This strategy – increases specificity above that of any of the individual tests, but – degrades sensitivity below that of any of them singly. • Serial test to rule-in disease • When treatment is hazardous (surgery, chemotherapy) we use serial testing to raise specificity.(Blood test followed by more tests,
  54. 54. SIMULTANEOUS TESTING • Use >1 test simultaneously, diagnosing if any test is positive. • Usual decision strategy diagnoses if any test positive. • This strategy – increases sensitivity above that of any of the individual tests, but – degrades specificity below that of any individual test. • Parallel test to rule-out disease • Used to rule-out serious but treatable conditions (example, breast cancer screening frequently employs a combination of mammography and breast physical examination . Any positive is considered
  55. 55. BIAS IN SCREENING TESTS Arise when screen detected cases are compared with cases detected by signs and symptoms.
  56. 56. • Lead time bias : overestimation of survival duration among screen detected cases when survival is measured from diagnosis.
  57. 57. Length time bias: • Overestimation of survival duration among screen-detected cases due to the relative excess of slowly progressing cases. • These are disproportionally identified by screening because the probability of detection is directly proportional to the length of time during which they are detectable.
  58. 58. Over diagnosis bias : • Over diagnosis occurs when all of these people with harmless abnormalities are counted as "lives saved" by the screening, rather than as "healthy people needlessly harmed by over diagnosis". • Screening may identify abnormalities that would never cause a problem in a person's lifetime. For example, prostate cancer screening; it has been said that "more men die with prostate cancer than of it". • Issues unnecessary treatment.
  59. 59. Early detection may over-diagnose Pre-detectable Undetected (no screening) Mild or no symptoms Favorable outcome Pre-detectable Survival time after diagnosis Early detect, diagnosis, & treatment Monitoring for recurrence Favorable outcome Survival time after dx Age: 35 45 55 65 75
  60. 60. Selection bias: • Not everyone will partake in a screening program. • If people with a higher risk of a disease are more likely to be screened, for instance women with a family history of breast cancer are more likely than other women to join a mammography program, then a screening test will look worse than it really is: negative outcomes among the screened population will be higher than for a random sample. • Selection bias may also make a screening test look better than it really is, if a test is more available to young and healthy people (for instance if people have to travel a long distance to get checked).
  61. 61. DISADVANTAGES OF SCREENING • The tests used in screening are not perfect, so there are false positives and false negatives. • Screening involves cost and use of medical resources on a majority of people who do not need treatment. • Adverse effects of screening procedure (e.g. stress and anxiety, discomfort, radiation & chemical exposure). • Unnecessary investigation and treatment of false positive results. • Stress and anxiety caused by prolonging knowledge of an illness without any improvement in outcome. • A false sense of security caused by false negatives,
  62. 62. EVALUATION OF SCREENING PROGRAM • Randomized control trials. • Uncontrolled trials. • Other methods: like, case control studies
  63. 63. COMMONLY SCREENED DISEASES • Cancer (Breast, lung, colorectal, prostate, pancreatic, cervical, ovarian, skin, testicular, thyroid) • Cardiovascular (AAA, Blood pressure, Lipid disorders, carotid artery stenosis, PAD) • Infectious disease (HIV, Hep B/C, STDs, Tuberculosis) • Injury and violence (domestic violence, Youth violence/gang activity, seatbelt use) • Mental health/substance abuse (Drugs, tobacco, depression, suicide risk) • Endocrine/Metabolism (Diabetes, IDA, obesity, physical activity) • MSK –osteoporosis • Obs/Gyn (Pre-eclampsia, Rh incompatibility, neural tube defects, asymptomatic bacteruria, Down’s syndrome) • Pediatrics (PKU, sickle cell disease, visual impairment, lead intoxication, hearing loss, dental caries)
  64. 64. THANK YOU

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