1 / 79

SCREENING TESTS

SCREENING TESTS. Dr. Khanchit Limpakarnjanarat Thailand MOPH – US CDC Collaboration (TUC). SCREENING TESTS. Settings: ANC, health check up, patient with fever, surveillance, other Primary prevention may be the best approach to prevent disease occurrence and/or epidemics.

ryan-bell
Download Presentation

SCREENING TESTS

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. SCREENING TESTS Dr. Khanchit Limpakarnjanarat Thailand MOPH – US CDC Collaboration (TUC)

  2. SCREENING TESTS • Settings: ANC, health check up, patient with fever, surveillance, other • Primary prevention may be the best approach to prevent disease occurrence and/or epidemics. • Two possible approaches to early diagnosis • Depends on awareness of warning signs • Active detection of disease in asymptomatic cases

  3. Know the Seven Warning Signs of Cancer… • Appearance of a lump in a breast or elsewhere • A change in a mole or wart • A sore that doesn't heal • Indigestion or difficulty swallowing • Nagging cough or hoarseness • Unusual bleeding • Persistent respiratory problems • [American Cancer Society]

  4. CAGEscreening for alcoholism • Have you ever felt you should Cut down on your drinking? • Have people Annoyed you by criticizing your drinking? • Have you ever felt bad or Guilty about your drinking? • Have you ever had a drink first thing in the morning to steady your nerves or to get rid of a hangover (Eye-opener)?

  5. The CAGE questions for alcohol abuse Alcohol abuse YES NO (True +) 60 (False +) 1 61 3 or 4 Positive answers to the 4 CAGE questions a a +b b 57 (False -) c d 400 (True -) c + d 2, 1 or 0 457 a + c b + d a + b + c + d 518 117 401 Sens. = 60/117=0.51 Spec. = 400/401=0.998 PVP = 60/61 = 0.98 PVN = 400/457 = 0.88 Suckett D. A Primer on the Precision and Accuracy of the Clinical Examination. JAMA 267(19):2638-2644, May 1992

  6. Schema relating path of detection to outcome [Dr. Maureen Handerson] A. CURRENT SITUATION B. FUTURE PROJECTION Care for chromic disease Care for chromic disease Self referral Self referral Diagnosis Diagnosis Surveillance Recovery Surveillance Recovery Source: Mausner & Bahn: Epidemiology-an introductory text, Chapter 9 - screening in detection of disease

  7. Screening test The basic tool of a screening program and must be thoroughly understood since screening is designed to be applied to large group of people, screening test should be easy to use, rapid and inexpensive. They should also be able to carried out largely by technicians 1.2

  8. Definition: PRESUMPTIVE identification of unrecognized disease or defect by the application of tests, examinations, or other procedures which can be applied rapidly to sort out apparently well persons who probably have a disease from those who probably do not. A screening test is not intended to be diagnostic. Persons with positive or suspicious findings must be referred to their physicians for diagnosis and necessary treatment. [Commission on Chronic Illness, 1951] Screening Test

  9. Goal of Screening Test • To reduce morbidity or mortality from the disease among the people screened by early treatment of the cases discovered. (Clinical Medicine) • To help guide preventive and control measures in general or specific populations. (Epidemiology and Public Health)

  10. Positives (abnormal) - persons presumed to have the disease or be at increased risk in future + + + + + Rescreen at prescribed interval + + Negatives (normal) - persons presumed to be free of disease under study + Rescreen at prescribed interval + + + + + DIAGNOSTIC PROCEDURES + + Disease or risk factor present Disease or risk factor absent THERAPEUTIC INTERVENTION APPARENTLY WELL POPULATION TO BE TESTED (Well persons plus those with undiagnosed disease) + + + + SCREENING TEST Negatives on test Positives on test, no disease + Positives on test, disease present Flow diagram for a mass screening test

  11. PURPOSES OF SCREENING • DIAGNOSIS • IDENTIFY TOXIC CHEMICAL AGENTS • ESTIMATE MAGNITUDE OF DISEASE OR PUBLIC HEALTH CONDITIONS • IDENTIFICATION OF PEOPLE AT HIGH RISK

  12. PURPOSE OF SCREENING (1) • DIAGNOSIS: Series of tests performed on a symptomatic patient for whom a diagnosis has not yet been established. • Example: Patients with hematuria may need UA, urine culture, cystoscopy, bladder biopsy, several types of X-rays, several blood chemistry studies

  13. PURPOSE OF SCREENING (2) • IDENTIFY TOXIC CHEMICAL AGENTS: Chemical agents may be screened by means of laboratory tests or epidemiologic surveillance in order to identify those substances likely to be toxic. • Example: Pb poisoning surveillance by Pb screening among children

  14. PURPOSE OF SCREENING (3) • ESTIMATE MAGNITUDE OF DISEASE OR PUBLIC HEALTH CONDITIONS: Some screening procedures can be used to estimate the prevalence of various conditions which may lead to disease control objectives. Major methodologic problem in this area is the relationship between ‘detected’ prevalence and the underlying ‘true’ prevalence, e.g., sample size, sampling technics. • Example: Serologic testing, GenProbe testing, Cervical Pap smear, Tuberculin skin test, CXR

  15. PURPOSE OF SCREENING (4) • IDENTIFICATION OF PEOPLE AT HIGH RISK: People at high risk may be who do not yet have the disease. The link between screening for a risk factor and a disease may not be sharp. • Example: Identify smokers, identify drinkers by MAST test, HT may be a risk factor for CVD or may be early disease detection itself

  16. Types of Screening Programs • Selective screening specific people at risk for disease • Mass screening test large number of people

  17. Selective screening • Selective screening: Tests are used to detect a specific disease among people who are at risk of having disease. • Single disease: e.g., CXR for pneumoconiosis in coal miners or FBS for evidence of DM in diabetic patients’ relatives • Multiphasic screening program: e.g., ANC in pregnant women

  18. Mass screening • Mass screening: Large number of people are tested for the presence of disease or condition without specific emphasis to their individual risk of having disease or condition • Single disease: e.g., cervical pathology for cancer of cervix, mammography for breast cancer • Multiphasic screening program: e.g., Biochemical profile in community survey

  19. Lead time and screening test • Lead time is the time interval from detection by screening test to the time at which diagnosis would have been made without that screening. • Length of lead time interval may vary from person to person (short and long lead time) • Importance of lead time is for disease control and by early detection and early treatment to prevent spread and disability of affected persons. Screening test is valuable in reducing severe morbidity and mortality

  20. Measurements used in screening tests • Validity – test is able to differentiate presence or absence of disease • Yield – brought unrecognized disease to diagnosis • Reliability – consistent results when tested more than once

  21. DISEASE “Gold standard” Yes No True pos False pos + TEST “Screening” a b c d - False neg True neg Creation of 2 x 2 table:initial step for calculation

  22. VALIDITY • Validity is the rate at which a test is capable of differentiating the presence or absence of a disease concerned SENSITIVITY = ability of test to detect people who actually have the disease (True Positives/All Positives) SPECIFICITY = ability of test to identify correctly people who actually do not have the disease (True Negatives/All Negatives)

  23. Validity of screening test • Sensitivity = proportion of subjects with disease who have the positive test from screening = a / a+c or = TP / TP + FN • Specificity = proportion of subjects without disease who have the negative test from screening = d / b+d or = TN / FP + TN • Accuracy of the test = a + d / a + b + c + d = TP + TN / Total screened

  24. YIELD • Yield is the amount of previously unrecognized disease which is diagnosed and brought to treatment as a result of the screening PREDICTIVE VALUE POSITIVE (PVP) is the likelihood that an individual with a positive test has the disease PREDICTIVE VALUE NEGATIVE (PVN) is the likelihood that an individual with a negative test does not have the disease

  25. Yield of screening test • Predictive Value Positive (PVP) • PVP = a / a + b • or = TP / TP + FP • Predictive Value Negative (PVN) • PVN = d / c + d • or = TN / TN + FN 9

  26. RELIABILITY (Precision) • Reliability is consistency of results when the test is performed more than once on the same individual under the same conditions. It is also called ‘Repeatability’

  27. Reliability**Precision**Repeatability Number of agreed positive = ------------------------------------- Number of positive either time a = -------------- (a + b + c)

  28. Trade off pointCut off point“Criterion of Positivity”

  29. Trade off point Real situation of screening test Persons without disease Number of persons d Persons with Disease a c b Persons with disease = a + c Persons without disease = b + d

  30. Trade off point Hypothetical best screening test Number of persons d a Healthy Sick

  31. d a b c Shifting of trade off point A Number of persons Healthy Sick Trade off point A

  32. c Setting of trade off point A on sensitivity and specificity of HIV EIA assay Negative test Positive test HIV-free population Number of persons FALSE POS HIV-positive population A B High SEN / Low SPEC

  33. d c a b X Shifting of trade off point B Number of persons Healthy Sick Trade off point B

  34. Setting of trade off point Bon sensitivity and specificity of HIV EIA assay Negative test Positive test HIV-free population Number of persons FALSE NEG HIV-positive population A B Low SEN / High SPEC

  35. DISEASE “Gold standard” Yes No True pos False pos + TEST “Screening” a b c d - False neg True neg Correlation of SCREENING TEST VS. GOLD STANDARD True results = True positive (a) = True negative (d) False results = False positive (b) = False negative (c) B A

  36. Validity of screening test • Sensitivity = proportion of subjects with disease who have the positive test from screening = a / a+c or = TP / TP + FN • Specificity = proportion of subjects without disease who have the negative test from screening = d / b+d or = TN / FP + TN

  37. Specificity should be increased relative to sensitivity: • When the false positive result can harm patient physically, emotionally, or financially, e.g., HIV infection • When the cost or risk associated with further diagnostic techniques are substantial, such as breast cancer, for which the definitive diagnostic evaluation of a positive screening test is a biopsy

  38. Sensitivity should be increased at the expense of specificity: • When the penalty associated with missing a case is high such as disease is serious and definitive treatment exist, e.g., PKU • When the disease can spread, e.g., syphilis • When subsequent diagnostic evaluations of positive screening tests are associated with minimal cost and risk, e.g., series of B.P. readings to ascertain HT

  39. PROBLEMS WITH SCREENING TESTS • 1. Lack of information on negative tests : • Prostate specific antigen (PSA) for • prostate cancer • 2. Lack of information in the non-disease : • MRI to diagnose prolapse disk • 3. Lack of standards for disease • Consequence of imperfect standards : • diagnosis of gall stone by • U/S vs. Cholecystogram Clinical Epidemiology - KKU

  40. Blood Sugar level 2 hrs-post meal (mg %) Sensitivity (%) Specificity (%) Table : sensitivity and specificity of blood sugar to diagnose DM [Public Health Service, US, 1960] 98.6 97.1 94.3 88.6 85.7 71.4 64.3 57.1 50.0 47.1 42.9 38.6 34.3 27.1 8.8 25.5 47.6 69.8 84.1 92.5 96.9 99.4 99.6 99.8 100.0 100.0 100.0 100.0 70 80 90 100 110 120 130 140 150 160 170 180 190 200

  41. ROC of accuracy of blood sugar test (2 hours post meal) to diagnosis DM[Public Health Service, Diabetes program guide Publ. No. 506, Washington DC, US Government Printing Office, 1960] Specificity (%) Diagnosis point Sensitivity (%) [True positive] 1 - Sensitivity (%) 6.5B 1 - Specificity (%)

  42. Combination of tests To enhance sensitivity or specificity of the screening test • Test in series: person is called “positive” when he tests +ve to all of a series of test, “negative” if he tests –ve to any. This enhances the SPECIFICITY of the test • Test in parallel: person is labeled “positive” if he tests +ve to any of the tests, “negative” if he tests –ve to all. This enhance the SENSITIVITY of the test

  43. 6.6B MULTIPLE TESTS CONCEPT Types Step of event Result Serial testing sensitivity specificity + + + A B C Positive = all test +ve + + + A - - - sensitivity specificity Parallel testing B Positive = any test +ve C

  44. Perinatal HIV Outcome Monitoring System (PHOMS) • Criteria for diagnosis of HIV status in children = uninfected • HIV antibody negative at least 1 time in any age group; (serial or parallel) • PCR negative at least 2 times at a different interval and last test must be after 2 months old (serial or parallel) Serial to increase specificity Parallel to increase sensitivity

  45. Perinatal HIV Outcome Monitoring System (PHOMS) • Criteria for diagnosis of HIV status in children = infected • HIV antibody positive at least 2 times with different technic, age > 18 months; (serial or parallel) • PCR positive at least 2 times at a different interval in any age group (serial or parallel) Serial to increase specificity Serial to increase specificity

  46. Yield of screening test • Predictive Value Positive (PVP) is likelihood that an individual with a positive test has the disease PVP = a / a + b or = TP / TP + FP • Predictive Value Negative (PVN) is likelihood that an individual with a negative test does not have the disease PVN = d / c + d or = TN / TN + FN This measurement is useful to M.D. especially PVP

  47. Binomial Mathematical Model If p = prevalence of disease sens. = sensitivity of test spec. = specificity of test Then; PVP = p(sens) p(sens) + (1–p)(1-spec) PVN = (1-p) spec (1–p) spec + p(1-sens) PV or yield can be affected by Prevalence, and Specificity and slightly affected by Sensitivity

  48. Results of screening test in two different populations: sensitivity=.99, specificity=.99 Population A (prevalence = 100,000/1,000,000 = 0.10) Disease+ Disease- Total Test+ 99,000 9,000 108,000 Test- 1,000 891,000 892,000 100,000 900,000 1,000,000 PVP = TP / (TP+FP) = 99,000/(99,000+9,000) = .917 = 91.7% PVP = (p)(sens) = (.1)(.99) = .917 (p)(sens)+(1-spec)(1-p) (.1)(.99)+(1-.99)(1-.1)

  49. Test results of screening test in two different populations: sensitivity=.99, specificity=.99 Population B (prevalence = 1,000/1,000,000 = 0.001) Disease+ Disease- Total Test+ 990 9,990 10,980 Test- 10 989,010 989,020 1,000 999,000 1,000,000 PVP = TP / (TP+FP) = 990/(990+9,990) = .090 = 9.0% PVP = (p)(sens) = (.001)(.99) = .090 (p)(sens)+(1-spec)(1-p) (.001)(.99)+(1-.99)(1-.001)

  50. Relationship between prevalence of disease and predictive value, with sensitivity and specificity held constant at 95% [adapted from Vecchio, 1966] Positive test Negative test Predictive value (percentage) Prevalence of disease (percentage) 12

More Related