2/1/2011Natural history; population screening1 Natural history of disease / population screening Principles of Epidemiology for Public Health (EPID600) Victor J. Schoenbach, PhD home page Department of Epidemiology Gillings School of Global Public Health University of North Carolina at Chapel Hill

2/3/20042 SHE shouldn’ts (courtesy of # 8: SHE's shouldn't let themselves get too tired – Last week I was going over some homeschooling with my 11yo DD when I realized I hadn't seen or heard my fast-crawling 13-month old DD in a while. I said, "Anyone know where the baby is?" My older daughter just looked at me and said, "Mom?" Lo and behold, I'm nursing the baby! - in Colorado

9/24/20013 What not to say in your job interview “Herb Greenberg, a leading authority on work- related personality testing, keeps a list of the dumbest things people have told his corporate clients during recent job interviews.” (Cheryl Hall, Knight Ridder, Herald-Sun, 1/26/2003: F2) (Greenberg is the 73-year-old chief executive officer of Caliper, in Princeton NJ)

9/24/20014 Have you ever thought of saying … “I will definitely work harder for you than I did for my last employer.” “I don’t think I’m capable of doing this job, but I sure would like the money.” “Do you know of any companies where I could get a job I would like better than this one?”

9/24/20015 Have you ever thought of saying … “I’m quitting my present job because I hate to work hard.” An apology for yawning “I usually sleep until my soap operas are on.”

2/1/2011Natural history; population screening6 Knowledge of the natural history of disease is fundamental for effective prevention Levels of prevention: - Primary – prevent the disease [Primordial – prevent the risk factors] - Secondary – early detection and Rx - Tertiary – treat and minimize disability Disease natural history and prevention

2/1/2011Natural history; population screening7 Phenomenon of disease - What is disease? - Natural history of disease Requirements for screening programs Detection of disease - Sensitivity - Specificity Interpreting diagnostic & screening tests - Predictive value Disease natural history & population screening

2/1/2011Natural history; population screening8 World Health Organization: “a state of complete physical, mental, [and] social well-being and not merely the absence of disease or infirmity” Phenomenon of health: what is health?

1/9/2007Natural history; population screening9 Difficult to define, e.g.: “a type of internal state which is either an impairment of normal functional ability–that is, a reduction of one or more functional abilities below typical efficiency–or a limitation on functional ability caused by environmental agents” (C. Boorse, What is disease ? In: Humber M, Almeder RF, eds. Biomedical ethics reviews. Humana Press, Totowa NJ, 1997, 7-8 (quoted in Temple et al., 2001) Phenomenon of disease: what is disease?

9/10/2002Natural history; population screening10 Difficult to define, e.g.: “a state that places individuals at increased risk of adverse consequences ” (Temple LKF et al., Defining disease in the genomics era. Science 3 Aug 2001;293: ) Phenomenon of disease: what is disease?

9/10/2002Natural history; population screening11 Disease is a process that unfolds over time Natural history – sequence of developments from earliest pathological change to resolution of disease or death Phenomenon of disease: natural history

9/10/2002Natural history; population screening12 Induction – time to disease initiation Incubation – time to symptoms (infectious disease) Latency – time to detection (for non- infectious disease) or to infectiousness Phenomenon of disease: natural history

9/10/2002Natural history; population screening13 Induction – time to disease initiation Incubation – time to symptoms (infectious disease) Latency – time to detection (for non- infectious disease) or to infectiousness Phenomenon of disease: natural history

1/29/2008Natural history; population screening14 Induction – time to disease initiation Incubation – time to symptoms (infectious disease) Latency – time to detection (for non- infectious disease) or to infectiousness Phenomenon of disease: natural history

1/9/2007Natural history; population screening15 Natural history of coronary heart disease “Spontaneous atherosclerosis” “Lipid lesion” Fibrointimal lesion Plaque growth, occlusion Chronic minimal injury (blood flow, CHL, smoking, infection?) (youth?) Accumulation of lipids and monocytes, toxic products, platelet adhesion (adolescence) Migration & proliferation of smooth muscle cells (adulthood) Disruption thrombi (adulthood)

1/9/2007Natural history; population screening16 Natural history of coronary heart disease “Spontaneous atherosclerosis” “Lipid lesion” Fibrointimal lesion Plaque growth, occlusion Chronic minimal injury (blood flow, CHL, smoking, infection?) (youth?) Accumulation of lipids and monocytes, toxic products, platelet adhesion (adolescence) Migration & proliferation of smooth muscle cells (adulthood) Disruption thrombi (adulthood)

1/9/2007Natural history; population screening17 Natural history of coronary heart disease “Spontaneous atherosclerosis” “Lipid lesion” Fibrointimal lesion Plaque growth, occlusion Chronic minimal injury (blood flow, CHL, smoking, infection?) (youth?) Accumulation of lipids and monocytes, toxic products, platelet adhesion (adolescence) Migration & proliferation of smooth muscle cells (adulthood) Disruption thrombi (adulthood)

9/10/2002Natural history; population screening18 Natural history is central to screening Pre-detectable Detectable, preclinical Clinical Disability or death Possible detection via screening Clinical detection Age:

9/10/2002Natural history; population screening19 “application of a test to asymptomatic people to detect occult disease or a precursor state” (Alan Morrison, Screening in Chronic Disease, 1985) Population screening

9/10/2002Natural history; population screening20 Immediate objective of a screening test – to classify people as being likely or unlikely of having the disease Ultimate objective: to reduce mortality and morbidity Population screening

2/1/2011Natural history; population screening21 Test that can help save your life

9/10/2002Natural history; population screening22 1. Suitable disease 2. Suitable test 3. Suitable program 4. Good use of resources Requirements for a screening program

9/10/2002Natural history; population screening23 Serious consequences if untreated Detectable before symptoms appear Better outcomes if treatment begins before clinical diagnosis 1. Suitable disease

9/10/2002Natural history; population screening24 Detect during pre-symptomatic phase Safe Accurate Acceptable, cost-effective 2. Suitable test

9/10/2002Natural history; population screening25 Reaches appropriate target population Quality control of testing Good follow-up of positives Efficient 3. Suitable program

9/10/2002Natural history; population screening26 Cost of screening tests Cost of follow-up diagnostic tests Cost of treatment Benefits versus alternatives 4. Good use of resources

2/1/2011Natural history; population screening27 Summary of Recommendations The USPSTF recommends biennial screening mammography for women aged 50 to 74 years. Grade: B recommendation. The decision to start regular, biennial screening mammography before the age of 50 years should be an individual one and take patient context into account, including the patient's values regarding specific benefits and harms. Grade: C recommendation. The USPSTF recommends against teaching breast self-examination (BSE). Grade: D recommendation.... Screening for Breast Cancer U.S. Preventive Services Task Force December 4, 2009

2/1/2011Natural history; population screening28 David Shabtai Faculty Peer Reviewed In a bold move, the U.S. Preventive Services Task Force recently changed their breast cancer screening guidelines – recommending beginning screening at age 50 and even then only every other year until age 75. Bold, because the Task Force members are certainly aware of the media circus that ensued when in 1997, an NIH group issued similar guidelines, prompting comparisons to Alice in Wonderland. Revisiting the USPSTF Breast Cancer Screening Guidelines: Ethics, and Patient Responsibilities

2/1/2011Natural history; population screening29 September 10, 2010 Recommended Weekend Reading By NATASHA SINGER “Can we trust doctors’ recommendations on cancer screening, given that the medical profession has a vested financial interest in treating patients? That is one of the questions posed in a provocative article this week in The New England Journal of Medicine that looks at the fallout last year after a government panel recommended that women start having mammograms later in life and less frequently.” Mammography Wars

2/1/2011Natural history; population screening30 September 29, 2010 Mammogram Benefit Seen for Women in Their 40s By GINA KOLATA Researchers reported Wednesday that mammograms can cut the breast cancer death rate by 26 percent for women in their 40s. But their results were greeted with skepticism by some experts who say they may have overestimated the benefit. Who should get a mammogram?

2/1/2011Natural history; population screening31 Newsweek The Mammogram Hustle There is no evidence digital mammograms improve cancer detection in older women. But thanks to political pressure, Medicare pays 65 percent more for them. This story was reported and written by Center for Public Integrity. What should we pay for?

2/1/2011Natural history; population screening32 By Julie Steenhuysen CHICAGO | Wed Jan 26, :26pm EST (Reuters) - A new analysis of evidence used by a U.S. advisory panel to roll back breast cancer screening guidelines suggests it may have ignored evidence that more frequent mammograms save more lives, U.S. researchers said on Tuesday. New U.S. analysis backs annual breast screening

2/1/2011Natural history; population screening33 “The U.S. Preventive Services Task Force (USPSTF) “chose to ignore the science available to them” and brought about “potential damage to women’s health” in its 2009 recommendations for more limited mammography screening, costing an estimated 6,500 deaths in women each year, a study published in the February issue of the American Journal of Roentgenology concluded.” AJR: USPSTF mammo recommendations could cost 6,500 lives yearly

9/10/2002Natural history; population screening34 Survival time after diagnosis – lead time Pre-detectable Detectable, preclinical Clinical Disability or death Possible detection via screening Clinical detection Age: Lead time

9/10/2002Natural history; population screening35 Survival time must increase > lead time Pre-detectable Undetected (no screening) Clinical diagnosis & treatment Disability or death Age: Pre-detectable Early detect, diagnosis, & treatment Monitoring for recurrence ? Survival time after diagnosis Lead time

9/10/2002Natural history; population screening36 Slowly progressing diseases are easier to detect by screening Pre- detectable Clinical diagnosis, treatment Disability or death Age: Pre-detectable Detectable, pre-clinical Clinical diagnosis & treatment Disability or death Survival time after diagnosis

1/9/2007Natural history; population screening37 Early detection may over-diagnose Pre-detectable Undetected (no screening) Mild or no symptoms Favorable outcome Age: Pre-detectable Early detect, diagnosis, & treatment Monitoring for recurrence Favorable outcome Survival time after diagnosis Survival time after dx

9/10/2002Natural history; population screening38 Screening test Reliable – get same result each time Validity – get the correct result Sensitive – correctly classify cases Specificity – correctly classify non-cases [screening and diagnosis are not identical]

9/16/2003Natural history; population screening39 Reliability Repeatability – get same result Each time From each instrument From each rater If don’t know correct result, then can examine reliability only.

9/10/2002Natural history; population screening40 Reliability Percent agreement is inflated due to agreement by chance Kappa statistic considers agreement beyond that expected by chance Reliability does not ensure validity, but lack of reliability constrains validity

2/1/2011Natural history; population screening41 Validity: 1) Sensitivity Probability (proportion) of correct classification of cases Cases found / all cases

9/10/2002Natural history; population screening42 Validity: 2) Specificity Probability (proportion) of correct classification of noncases Noncases identified / all noncases

9/16/2003Natural history; population screening43         O O O O O O O O O O O Remember this slide? 2 cases / month O

9/16/2003Natural history; population screening44         O O O O O O O O O O Pre-detectable preclinical clinical old O O O O O

9/16/2003Natural history; population screening45         O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O Pre-detectable pre-clinical clinical old

1/29/2008Natural history; population screening46         O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O What is the prevalence of “the condition”?

9/10/2002Natural history; population screening47 Sensitivity of a screening test Probability (proportion) of correct classification of detectable, pre- clinical cases

9/10/2002Natural history; population screening48         O O O O O O O O O O O O Pre-detectable pre-clinical clinical old (8) (10) (6) (14) O O O O O O O O O O O O O O O O O O O O O OO O O O

9/10/2002Natural history; population screening49         O O O O O O O O O O O O Correctly classified Sensitivity: ––––––––––––––––––––––––––– Total detectable pre-clinical (10) O O O O O O O O O O O O O O O O O O O O O OO O O O

9/10/2002Natural history; population screening50 Specificity of a screening test Probability (proportion) of correct classification of noncases Noncases identified / all noncases

2/1/2011Natural history; population screening51         O O O O O O O O O O O O Pre-detectable pre-clinical clinical old (8) (10) (6) (14) O O O O O O O O O O O O O O O O O O O O O OO O O O

9/10/2002Natural history; population screening52         O O O O O O O O O O O O Correctly classified Specificity: ––––––––––––––––––––––––––––– Total non-cases (& pre-detect) (162 or 170) O O O O O O O O O O O O O O O O O O O O O OO O O O

9/10/2002Natural history; population screening53 True positive True negative False positive False negative Sensitivity = True positives All cases a + c b + d = a a + c Specificity = True negatives All non-cases = d b + d a + b c + d True Disease Status Cases Non-cases Positive Negative Screening Test Results a d b c

5/26/2008Natural history; population screening54 True Disease Status Cases Non-cases Positive Negative Screening Test Results a d 1,000 b c 60 Sensitivity = True positives All cases ,000 = Specificity = True negatives All non-cases = 19,000 20,000 1,140 19, ,000 = = 70% 95%

1/9/2007Natural history; population screening55 Interpreting test results: predictive value Probability (proportion) of those tested who are correctly classified Cases identified / all positive tests Noncases identified / all negative tests

9/10/2002Natural history; population screening56 True positive True negative False positive False negative PPV = True positives All positives a + c b + d = a a + b NPV = True negatives All negatives = d c + d a + b c + d True Disease Status CasesNon-cases Positive Negative Screening Test Results a d b c

1/9/2007Natural history; population screening57 True Disease Status Cases Non-cases Positive Negative Screening Test Results a d 1,000 b c 60 PPV = True positives All positives ,000 = 140 1,140 NPV = True negatives All negatives = 19,000 19,060 1,140 19, ,000 = = 12.3% 99.7%

1/29/2008Natural history; population screening58 Positive predictive value, Sensitivity, specificity, and prevalence Prevalence (%) PV+ (%) Se (%) Sp (%)

1/9/2007Natural history; population screening59 Example: Mammography screening of unselected women Disease status Cancer No cancer Total Positive ,117 Negative 47 62,295 62,342 Total ,280 63,459 Prevalence = 0.3% (179 / 63,459) Se = 73.7% Sp = 98.4% PV+ = 11.8% PV– = 99.9% Source: Shapiro S et al., Periodic Screening for Breast Cancer

2/2/2011Natural history; population screening60 Effect of Prevalence on Positive Predictive Value PV+ = 64% PV+ = 88% Sensitivity = 93%, Specificity = 92% Surgical biopsy (“gold standard”) Cancer No cancer Prev. Without palpable mass in breast Fine needle Positive % aspiration Negative 1 91 With palpable mass in breast Fine needle Positive % aspiration Negative See

9/10/2002Natural history; population screening61 What is used as a “gold standard” 1. Most definitive diagnostic procedure e.g. microscopic examination of a tissue specimen 2. Best available laboratory test e.g. polymerase chain reaction (PCR) for HIV virus 3. Comprehensive clinical evaluation e.g. clinical assessment of arthritis

9/16/2003Natural history; population screening62 Main concepts 1. Requirements for a screening program 2. Concept of natural history – possible biases include lead time, “length”, over-diagnosis 3. Reliability (repeatable) – can occur by chance 4. Validity (correct) – sensitivity, specificity 5. Sensitivity and specificity relate to the detectable pre-clinical stage of the disease 6. Predictive value – the population perspective on disease detection

9/24/ Have you ever thought of saying … “My resume might make it look like I’m a job hopper. But I want you to know that I never left any of those jobs voluntarily.” “What job am I applying for anyway?”