8 screening
- 2. 擯惘 愃惘惡悋
- 3. Iceberg Principle 10% is visible 90% is invisibleComplex Interactions
- 4. 愆悋悽惠 惶 悋 惡悋惘 悴愕惠悴 惺 悋 悛慍 惡愕 愆惆 愕惘惺悋 惘愆 悋 惺悋 愕悋 惴悋惘 惡 悋愆悽悋惶 惆惘 惆擯惘 擯惘 愃惘惡悋Screening
- 5. 惶 悋 惡悋惘 悴愕惠悴愆悋悽惠 愆惆 惺 悋 悛慍 惡愕 愕惘惺悋 惘愆 悋 惺悋 惆惘 惆擯惘愕悋 惴悋惘 惡 悋愆悽悋惶 擯惘 愃惘惡悋
- 6. 惺悋惆 悽 愆悋惘 惡悋 悋惘悋惆 惡悋 悽 愆悋惘 惡悋 悋惘悋惆 擯惘 愃惘惡悋 愆惆 惆悋惆 惠愆悽惶 惡悋 悽 愆悋惘 惡悋 悋惘悋惆
- 7. 惘惆 愕惠 惘悋悴惺 惠愆悽惶 惡惘悋 惆惘悋 悽惆悋惠 慍 惡悋惘悋 惘悋惡惠 惆惘悋 惘悋惡惠 惆惘悋 惘惆 愕惠 惘悋悴惺 惡惘悋 惆惘悋 悽惆悋惠 慍 惡悋惘悋 惠愆悽惶 ( 悴悋惘 愆惘悋愀 ) ( 擯惘 愃惘惡悋 )
- 8. -悋愕惠 惠悋惠 悋 惆惘 惡惆悋愆惠 惺悋悋惠 惡悋 擯惘 愃惘惡悋: -愆惆 悋悴惘悋 愕惺 忰悴 惆惘 -悋愕惠 悋惘慍悋 悋 愕惡惠 -擯惘惆 惠 -.擯惘惆 惘悋 惠愆悽惶 悛慍 悴悋 擯惘 愃惘惡悋 悛慍 擯惘 愃惘惡悋
- 9. 擯惘 愃惘惡悋 惠愆悽惶 悋 悛慍 惠悋惠
- 10. 06/10/15 Screening vs Diagnosis Asymptomatic Test non-diagnostic Low prevalence Non-patients Patients Symptomatic Test diagnostic High prevalence
- 11. 06/10/15 Signs or Symptoms Detectable by Test Onset of Disease Death from Disease or Other causes PRECLINICAL CLINICAL DPCP Timeline of Disease
- 12. 06/10/15 Critical Point The point in the natural history of disease before which therapy is more effective.
- 13. 06/10/15 Death from Disease or Other causes Signs or Symptoms Detectable by Test Onset of Disease DPCP Screening Effective Critical Point
- 14. 06/10/15 Death from Disease or Other causes Signs or Symptoms Detectable by Test Onset of Disease DPCP Screening Ineffective Critical Point
- 15. 06/10/15 Death from Disease or Other causes Signs or Symptoms Detectable by Test Onset of Disease DPCP Screening Unnecessary Critical Point
- 16. 擯惘 愃惘惡悋 惡悋惘 悛愃悋慍 惡悋惘 愆惘惺 愆悋愕悋 惡惘悋 愀 悋 惠愆悽惶 惡惘悋 惡忰惘悋 愀 悋 惠愆悽惶 惡惘悋 惺 慍悋 惠愆悽惶 A B 擯惘 愃惘惡悋 慍悋 擯惘 惠惶 惠Lead time
- 17. 擯惘 愃惘惡悋 愕悋 悋 惴悋惘 悴惺惠 擯惘 愃惘惡悋 悛慍 悋 (悋 惆惘 擯惘 )愃惘惡悋 悋 惓惡惠 惠愆悽惶 悋惆悋悋惠 悽愀惘 惺悋 悋 惡悋惘 惆悋 悽愀惘 惺悋 悋 惡悋惘 悴惆惆惘悋 惆悋悽
- 18. -:擯惘 愃惘惡悋惘悋惡惠 惡惆惡悋 悽惆 悋惘悋惆 悋 悴惺惠 惆惘 悛慍悋愆 悋悴悋 惡悋愆惆 惡惆悋愆惠悽 惡悋擧 慍悋惆悋 擯惘 愃惘惡悋 悋惆. -:悋惡 惡悋惘惠愆悽惶 惡惘悋 悛慍悋愆擯悋 /悋 惡悋 悋 悛慍 悋悴悋 悛惆 惡惆悋愆惠 惘悋惡惠 惡惆惡悋 惆擯惘 惡惆 愕悋 惆惘 惡悋惘 悛慍 悋惆HBV惡悋惘惆悋惘 慍悋 惆惘. -:惠愆悽惶 悋 悛慍惡悋 悋 悛慍悋愆擯悋 悋 惘愆 悋慍 悋愕惠悋惆 惺悧 惘惆 惆惘 悋悽惠 悋 惡悋惘 忰惷惘 惘惆 悋 悋惓惡悋惠 惡惘悋 惆悋惘惆 悋 愆悋悛慍 悋惆HBV慍惘惆 惡 惡惠 惘惆 惆惘. 悋惡 惡悋惘 擯惘 愃惘惡悋
- 19. -:擯惘 愃惘惡悋悽惆 悋惘悋惆 悋 悴惺惠 惆惘 悛慍悋愆 悋悴悋惘悋惡惠 惡惆惡悋 惡悋愆惆 惡惆悋愆惠. -:悋惡 惡悋惘惠愆悽惶 惡惘悋 悛慍悋愆擯悋 /悋 惡悋 悋 悛慍 悋悴悋 愕悋 惆惘 惡悋惘悛惆 惡惆悋愆惠 惘悋惡惠 惡惆惡悋 惆擯惘 惡惆. -:惠愆悽惶 悋 悛慍惡悋 悋 悛慍悋愆擯悋 悋 惘愆 悋慍 悋愕惠悋惆 惘惆 惆惘 悋悽惠 悋 惡悋惘 忰惷惘 惘惆 悋 悋惓惡悋惠 惡惘悋 惺悧 惆悋惘惆 悋 愆悋. 悋惡 惡悋惘 擯惘 愃惘惡悋
- 20. -擯惘 愃惘惡悋) 惠悴慍PRESCRIPTIVE SCREENING(:惆 惡悋case detection愆悋愕悋 悋 惆悋惡惠 擧惆擧悋 擧惘 悋惆 惡惠悋 -擯惘 愃惘惡悋惡悋惘 擧惠惘 惡悋惘慍 惆 惡悋 擯惘 悛惆:悋惘悋惆 .愆惆 愃惘惡悋 惆擯惘悋 悋惺 惡惘悋 -拆愆 -悛慍愆 悋 擧悋惘惡惘惆擯惘 愃惘惡悋
- 21. -擯悋 擯惘 愃惘惡悋 -()悋惠悽悋惡 悽愀惘 惺惘惷 惆惘 擯惘悋 擯惘 愃惘惡悋 -悋 惘忰 惆 擯惘 愃惘惡悋 擯惘 愃惘惡悋 悋悋惺
- 22. -惡 惘惡愀 惺悋惘悋惡悋惘惡悋惘 -惡 惘惡愀 惺悋惘悋悛慍悛慍擯惘 愃惘惡悋 擯惘 愃惘惡悋 惺悋惘悋
- 23. .惡悋愆惆 惡惆悋愆惠 愆 惡悋惘 .惡悋愆惆 惆悋愆惠 惠愆悽惶 悋惡 惺惠 惡惆 悋 惘忰 悋 拆悋 惆惘 р惡悋惘 愀惡惺 愕惘 悋慍 悋 愆悋悽惠 р惡悋惘 愆悋愕悋 惡惘悋 悛慍 悴惆 р惠愆悽惶 惠悋惆 惡惘悋 惠愕 惠 惡惆 惘悋 р惓惘 惆惘悋 悴惆 р惡悋惘悋 惡悋 惡惘悽惘惆 惆惘 愆悽惶 愕悋愕惠 悴惆 р 愆悋愕悋 惆惘 悋惡惠 惘 惘擯 悋愆 惡惘 惡 悋 愆悋惆 悴惆 慍惆惘愕 惆惘悋 р惡悋惘 悋 慍 悽愀惘悋 惠 惡惘 擯惘 愃惘惡悋 悋惺 慍 惡悋惘 惺悋惘悋
- 24. 擯惘 愃惘惡悋 悛慍 惺悋惘悋 惡惠 拆悵惘 惠惘悋惘Intraobserver & interobserver reliability: 惡惆 惺惠惡惘 愕悋惆擯 惡惆 悽愀惘 惡 惡惆 愕惘惺 悋悴惘悋 惡惆 悛愕悋 惡惆 悋惘慍悋
- 25. A.惆 愆悋惆 擯悋擯 Intra Observer Variation Inter Observer Variation A.()惡悋惘悋 惡 擯悋擯 .愆惆 擯惘 悋惆悋慍 拆悋惘悋惠惘 惆惘 惠愃惘悋惠 р悋 惆 拆悋愕悽 忰 悋愆 愆悋 悋慍 惡悋惘 惆惘 忰 惆惘 惠愃惘悋惠 р悋擯 惡 惡悋慍擯愆惠 A. 悋 惘愆 悋慍 悋愆 悽愀悋悋 拆悵惘 惠惘悋惘
- 26. ,惡擯惘惆 悋惆悋慍 惡惆 惘悋惘 惘悋 慍 悋惆悋慍 惠悋 悛慍 惆惘愕惠.悋愕惠 擯惘惠 悋惆悋慍 A.忰愕悋愕惠Sensitivity B.擯Specificity 悋惺惠惡悋惘Validity
- 27. -:忰愕悋愕惠 愕悋 惆惘愕惠 惠愆悽惶 惆惘 悛慍 惠悋悋 .惡悋惘惆 擯 忰愕悋愕惠 -:擯悛慍 惠悋悋惆惘 愕悋 惆惘愕惠 惠愆悽惶 .愕惠惆 惡悋惘 忰 悋 惓惡惠 忰 悋
- 28. Validity of Screening Test (Accuracy) - Sensitivity: Is the test detecting true cases of disease? (Ideal is 100%: 100% of cases are detected) -Specificity: Is the test excluding those without disease? (Ideal is 100%: 100% of non-cases are negative)
- 29. 擯 忰愕悋愕惠 擯惘 愃惘惡悋 悋 惓惡惠 忰 悋 忰 惓惡惠 悋悵惡 悋悵惡 惠惡惓
- 30. 擯 忰愕悋愕惠 惓惡惠 忰 惓惡惠 悋悵惡 悋悵惡 忰 Disease Yes No Pos. Neg. Test
- 31. 擯 忰愕悋愕惠 a b c d Disease Yes No Pos. Neg. Test 忰愕悋愕惠 = 忰 惓惡惠 惡悋惘悋 = a a + c a + c b + d
- 32. 擯 忰愕悋愕惠 a b c d Disease Yes No Pos. Neg. Test 擯 = 忰 悋 愕悋 = d b + d a + c b + d
- 33. 擯 忰愕悋愕惠 a b c d Disease Yes No Pos. Neg. Test a + c b + d
- 34. -悋愕惠 惓惡惠 悛慍 惠悴 擧 慍悋 惘惆 惡惆 惡悋惘 悋忰惠悋. 悋悽惡悋惘 悋惘慍愆 -.悋愕惠 悛慍 惠悴 擧 慍悋 惘惆 惡惆 惡悋惘 悋忰惠悋 惓惡惠 悋悽惡悋惘 悋惘慍愆 悋悽惡悋惘 悋惘慍愆 -忰愕惡 惡惘 (惡惆 悋 惡惆 惘惆)惡悋惘 愕惠 惘惆 惆惘 惷悋惠 悛慍 惠悴.
- 35. 惓惡惠 悋悽惡悋惘 悋惘慍愆 -悋愕惠 惓惡惠 悛慍 惠悴 擧 慍悋 惘惆 惡惆 惡悋惘 悋忰惠悋. HIV +
- 36. 悋悽惡悋惘 悋惘慍愆 -悋愕惠 悛慍 惠悴 擧 慍悋 惘惆 惡惆 愕悋 悋忰惠悋. HIV -
- 37. 悋悽惡悋惘 悋惘慍愆 a b c d Disease Yes No Pos. Neg. Test 惓惡惠 悋悽惡悋惘 悋惘慍愆 = 忰 惓惡惠 悋 惓惡惠 = a a + b a + b c + d
- 38. 悋悽惡悋惘 悋惘慍愆 a b c d Disease Yes No Pos. Neg. Test 悋悽惡悋惘 悋惘慍愆 = 忰 悋 = d c + d a + b c + d
- 39. 惓悋盒潮
- 40. 2 X 2 tables Gold standard + - New + True + False + test - False - True -
- 41. Calculating SN and SP Gold standard + - New + TP FP test - FN TN Sensitivity Specificity TP/TP+FN TN/FP+TN
- 42. Pos and Neg Predictive Value Gold standard + - New + PV = + TP FP TP/TP+FP test - FN TN - PV = TN/TN+FN Sensitivity Specificity
- 43. Pos and Neg Predictive Value Gold standard + - New + PV + TP/TP+FP test - - PV TN/TN+FN Sensitivity Specificity
- 44. Pos and Neg Predictive Value Gold standard + - New + PV + TP/TP+FP test - - PV TN/TN+FN Sensitivity Specificity
- 45. Using predictive values Tell you whether you should believe your test results: very clinically useful! While sensitivity and specificity are constants, Predictive Values change depending upon who you are testing
- 46. Example: low prevalence 1% of people have disease out of 1,000 tested (PRE- TEST PROBABILITY) + - + + PV New - - PV 10 9,990 Sensitivity Specificity 90% 90%
- 47. Calculate TP and FN 1% of people have disease out of 1,000 tested + - + PV + 9 New - 1 - PV 10 9,990 Sensitivity Specificity 90% 90%
- 48. Calculate TN and FP 1% of people have disease out of 1,000 tested + - + PV + 9 99 New - 1 891 - PV 10 990 Sensitivity Specificity 90% 90%
- 49. What are the Predictive Values? 1% of people have disease out of 1,000 tested + - + PV = + 9 99 8% New - 1 891 - PV = 99.9% Sensitivity Specificity 90% 90%
- 50. How about a 50% pre-test prob 50% of people have disease out of 1,000 tested + - + PV= + 450 50 90% New - 50 450 - PV= 500 500 90% Sensitivity Specificity 90% 90%
- 51. Yield :擯惘 愃惘惡悋 惡悋慍惆 惡悋 惘惠惡愀 惺悋 1.Se 2.Sp 3.Prevalence 4.Participation rate
- 52. Borderline problem ≒惘惆 悛慍 惆 悋 惡惘惘愕 悋惆 悋愕惠 忰悋惠 擧 悋 擧惘惘擯 惆悋惡惠 悋惆
- 54. Consider: -The impact of high number of false positives: anxiety, cost of further testing -Importance of not missing a case: seriousness of disease Where do we set the cut-off for a screening test?
Editor's Notes
- #11: Until recently, radiologists and other physicians have mainly practiced in the realm of diagnosis rather than screening. However, with the continuous in advances in noninvasive imaging tech, we radiologists are increasingly practicing in the realm of screening. Important differences between screening and diagnosis. Dx involves patients, who are symptomatic and seek our help Scr involves non-patients, whom are asymptomatic but told they should be sceened Tests used for dx of symp dz often dx Tests used for scr rarely dx, lead to add tests In dx, dz prev high In scr, dz prev low
- #12: To understand screening, you must recognize that the target disease is a dynamic process that evolves over time. The dz process starts at some point before signs or symptoms begin. In the case of cancer, onset is often defined by molecular changes in a cells DNA, which occur long - sometimes decades - before the cancer produces and signs or symptoms. At some later time, the dz process may become detectable by a scr test, such as mammography or CT. At yet later points, the dz produces signs or symptoms and eventually caused death or some other adverse outcome. For simplicity sake, I will mainly focus on the adverse outcome of death. The time period between S&S and D is the CP while the time period between O and S&S is the PC. The time period between D and S&S is the DCPC and is an important concept in screening.
- #13: Another important concept in screening is the critical point. Critical point may = time of distant metastasis
- #14: For screening to be effective, the target disease must have a critical point, and this critical point must occur during the DPCP.
- #15: If CP is too early, then screening is futile.
- #16: If CP too late, unnecessary.
- #54: (Talk about sensitivity, specificity, false positives, false negatives) No question that IOP is a RISK FACTOR for glaucoma, but its use as a screening tool is terrible-a level of 22 mg misses 50% of glaucoma cases, and incorrectly labels a high percentage of persons in population as having glaucoma.
- #55: Extent that distributions overlap between normals and abnormals, minimizing error will be hard. For complex disorders with multiple causes, one test alone for just one cause may be woefully insufficient.