EPI-820 Evidence-Based Medicine

1. EPI-820 Evidence-Based Medicine LECTURE 5: SCREENING Mat Reeves BVSc, PhD

2. Objectives • Two components of screening (Dx & Tx). • Determinants of pre-clinical phase • Concept of lead time • Characteristics of screening tests (Se, Sp, yield) • Biases - lead time, selection, length-biased • The only valid measures of screening efficacy • Evaluations and criteria for screening

3. I. Introduction • Objective: to reduce mortality and/or morbidity by early detection and treatment. • Secondary prevention. • Asymptomatic individuals are classified as either unlikely or possibly having disease.

4. Introduction • Screening involves both diagnostic and treatment components • Screening differs from diagnostic testing:

5. Screening - Introduction • There are two forms of screening which involve fundamentally different formats, organization and intent: • Mass or population-based screening • Case finding • This lecture covers mass screening for non-infectious (chronic) diseases only.

6. Pathology begins Disease detectable Normal Clinical Presentation Pre-Clinical Phase II. Characteristics of Disease The Pre-Clinical Phase (PCP) • the period between when early detection by screening is possible and when the clinical diagnosis would usually be made.

7. Prevalence of Pre-clinical disease • A critical determinant of the potential utility of screening. • Prevalence is affected by: • disease incidence • average duration of the PCP • previous screening • sensitivity of the test • Example • long PCP= Colorectal cancer • short PCP = childhood diabetes

8. Pathology begins Disease detectable Normal Clinical Presentation Lead Time Screen Lead Time Lead time = amount of time by which diagnosis is advanced or made earlier

9. Relationship between screening, pre-clinical phase, clinical phase and lead time

10. Lead Time • Equals the amount of time by which treatment is advanced or made “early” • Not a theory or statistical artifact but what is expected and must occur with early detection • Does not imply improved outcome • Necessary but not sufficient condition for effective screening.

11. Lead Time • Impossible to determine lead time for any individual, can only compare distribution between screened and non-screened populations (RCT) • Knowledge of expected lead time useful to: • Indicates amount of time diagnosis and treatment must be advanced • Determine frequency of screening • Example lead times: • Mam screening women 40-49 = 1-2 years • Mam screening women 50-69 = 3-4 years • Invasive Colo-rect cancer = 7-10 years

12. Screened Group Non-screened Group Example of Estimation of Lead Time Distributions within an Screening RCT Cumulative Number of Cases Years after Screening Total lead time = 5 + 4 + 5 + 2.5 + 2 = 18.5 years Average lead time = 18.5/ 9 = 2.05 years

13. IV. Characteristics of screening tests a) Sensitivity (Se) • Definition: the proportion of cases with a positive screening test among all individuals with pre-clinical disease • Influences: • the prevalence of pre-clinical disease • the distribution of lead times • Concept of the Sensitivity Function • Average probability of detection for cases a certain time away from clinical diagnosis

14. Issues Related to Determining Sensitivity • Determining the denominator • who are the false negatives? (FNs) • Cannot justify full work-up of negative test results • Verification bias • FN’s estimated by counting number of interval cases • Spectrum bias • Se varies with spectrum of disease • Screening intensity • No previous screening = more advanced PCP = higher Se • Se decreases with repeat screening

15. IV. Characteristics of screening tests • b) Specificity (Sp) • Definition: the proportion of individuals with a negative screening test result among all individuals with no pre-clinical disease • Imperfect Sp affects many (the healthy), imperfect Se affects few (the sick) • Screening PVP usually low because prevalence of PCP is low • Influences: • the number of false-positive test results • the PVP and thereby the feasibility and efficiency of the screening program

16. IV. Characteristics of screening tests c) Yield • Definition: the amount of previously unrecognized disease that is diagnosed and treated as a result of screening. • Another measure of screening efficiency . • Influenced by: • Se • Prevalence of PCP

17. V. Effects of screening on disease incidence

18. V. Effects of screening on disease mortality

19. VI. Evaluation of Screening Outcomes • Study Designs • RCT • Compare disease-specific cumulative mortality rate between those randomized (or not) to screening • Eliminates confounding and lead time bias • But, problems of: • Expense, time consuming, logistically difficult, ethical concerns, changing technology.

20. VI. Evaluation of Screening Outcomes • Study Designs • Observational Studies • Cohort: • Compare disease-specific cumulative mortality rate between those who choose (or not) to be screened • Case-control: • Compare screening history between those with advanced disease (or death) and healthy. • Ecological: • Compare screening patterns and disease experience (both incidence and mortality) between populations

21. Problems with Observational Studies • Confounding due to health awareness - screenees are more healthy (selection bias) • More susceptible to effects of lead-time bias and length-biased sampling • Poor quality, often retrospective data • CCS: Difficult to determine appropriate control group • Difficult to distinguish screening from diagnostic examinations

22. b) Measures of Effect of Screening • Disease-specific Mortality Rate (MR) the number of deaths due to disease Total person-years experience • The only gold-standard outcome measure for screening • NOT affected by lead time, • when calculated from a RCT - not affected by selection bias or length-biased sampling.

23. Effects of screening on disease survival - I

24. Effects of screening on disease survival - II

25. Effects of screening on disease survival - III

26. Biases that effect survival duration • The efficacy of screening cannot be assessed by comparing survival rates (or CFR) because: • Selection bias: • Volunteers are more healthy • Lead-time bias • Introduced into survival experience of screen detected cases • Length-biased sampling • Screening preferentially identified slower growing or less progressive cases with a better prognosis

27. Length-biased Sampling DX DX Worse Prognosis Cases DX DX X X Better Prognosis Cases X X SCREENING

28. VII. Pseudo-disease and Over-diagnosis • Over-diagnosis • Limited malignant potential • Extreme form of length-biased sampling • Examp: Ductal-carcinoma in-situ • Competing risks • Cases detected that would have been interrupted by an unrelated death • Examp: Prostate CA and CVD death • Serendipity • Chance detection due to diagnostic testing for another reason • Examp: PSA and prostate CA, FOBT and CR CA

29. Over-diagnosis – Effect of Mass Pap Screening in Connecticut (Laskey 1976)

30. VIII. Assessing the feasibility of screening • Acceptability • convenience, comfort, efficiency, economical • Efficiency • Low PVP • Potential to reduce mortality • Effectiveness of treatment without screening • Effect of competing mortality • Cost-effectiveness • Mam screening = $30 – 50K /YLS

31. Efficacy Effectiveness Cost-effectiveness Should we screen? (scientific) Can we screen? (practical) Is it worth it? (scientific, practical, policy, political) IX. Summary • Three questions to ask before advocating screening:

32. Need and Feasibility of Screening? • All cases of disease can be classified into three groups relevant to screening: 1. Cure is necessary but not possible (Group I) 2. Cure is possible but not necessary (Group II) 3. Cure is necessary and maybe possible (Group III = only group that could benefit!)

33. Lung Cancer?

34. Colorectal Cancer?

35. Prostate Cancer?