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Principles of Epidemiology for Public Health (EPID600) Natural history of disease / population screening Victor J. Schoenbach, PhD home page Department of Epidemiology Gillings School of Global Public Health University of North Carolina at Chapel Hill www.unc.edu/epid600/ 2/1/2011 Natural history; population screening 1 SHE shouldn’ts (courtesy of www.flylady.net # 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 2/3/2004 2 What not to say in your job interview “Herb Greenberg, a leading authority on workrelated 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) 9/24/2001 3 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?” 9/24/2001 4 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.” 9/24/2001 5 Disease natural history and prevention • 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 2/1/2011 Natural history; population screening 6 Disease natural history & population screening •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 2/1/2011 Natural history; population screening 7 Phenomenon of health: what is health? World Health Organization: “a state of complete physical, mental, [and] social well-being and not merely the absence of disease or infirmity” 2/1/2011 Natural history; population screening 8 Phenomenon of disease: what is disease? 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) 1/9/2007 Natural history; population screening 9 Phenomenon of disease: what is disease? 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;293:807-808) 9/10/2002 Natural history; population screening 10 Phenomenon of disease: natural history • Disease is a process that unfolds over time • Natural history – sequence of developments from earliest pathological change to resolution of disease or death 9/10/2002 Natural history; population screening 11 Phenomenon of disease: natural history • Induction – time to disease initiation • Incubation – time to symptoms (infectious disease) • Latency – time to detection (for noninfectious disease) or to infectiousness 9/10/2002 Natural history; population screening 12 Phenomenon of disease: natural history • Induction – time to disease initiation • Incubation – time to symptoms (infectious disease) • Latency – time to detection (for noninfectious disease) or to infectiousness 9/10/2002 Natural history; population screening 13 Phenomenon of disease: natural history • Induction – time to disease initiation • Incubation – time to symptoms (infectious disease) • Latency – time to detection (for noninfectious disease) or to infectiousness 1/29/2008 Natural history; population screening 14 Natural history of coronary heart disease “Spontaneous atherosclerosis” Chronic minimal injury (blood flow, CHL, smoking, infection?) (youth?) 1/9/2007 “Lipid lesion” Accumulation of lipids and monocytes, toxic products, platelet adhesion (adolescence) Fibrointimal lesion Plaque growth, occlusion Migration & Disruption proliferation of thrombi smooth muscle cells (adulthood) (adulthood) Natural history; population screening 15 Natural history of coronary heart disease “Spontaneous atherosclerosis” Chronic minimal injury (blood flow, CHL, smoking, infection?) (youth?) 1/9/2007 “Lipid lesion” Accumulation of lipids and monocytes, toxic products, platelet adhesion (adolescence) Fibrointimal lesion Plaque growth, occlusion Migration & Disruption proliferation of thrombi smooth muscle cells (adulthood) (adulthood) Natural history; population screening 16 Natural history of coronary heart disease “Spontaneous atherosclerosis” Chronic minimal injury (blood flow, CHL, smoking, infection?) (youth?) 1/9/2007 “Lipid lesion” Accumulation of lipids and monocytes, toxic products, platelet adhesion (adolescence) Fibrointimal lesion Plaque growth, occlusion Migration & Disruption proliferation of thrombi smooth muscle cells (adulthood) (adulthood) Natural history; population screening 17 Natural history is central to screening Pre-detectable Age: 35 Detectable, preclinical 45 Possible detection via screening 9/10/2002 Clinical 55 65 Disability or death 75 Clinical detection Natural history; population screening 18 Population screening “application of a test to asymptomatic people to detect occult disease or a precursor state” (Alan Morrison, Screening in Chronic Disease, 1985) 9/10/2002 Natural history; population screening 19 Population screening 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 9/10/2002 Natural history; population screening 20 Test that can help save your life 2/1/2011 Natural history; population screening 21 Requirements for a screening program 1. Suitable disease 2. Suitable test 3. Suitable program 4. Good use of resources 9/10/2002 Natural history; population screening 22 1. Suitable disease • Serious consequences if untreated • Detectable before symptoms appear • Better outcomes if treatment begins before clinical diagnosis 9/10/2002 Natural history; population screening 23 2. Suitable test • Detect during pre-symptomatic phase • Safe • Accurate • Acceptable, cost-effective 9/10/2002 Natural history; population screening 24 3. Suitable program • Reaches appropriate target population • Quality control of testing • Good follow-up of positives • Efficient 9/10/2002 Natural history; population screening 25 4. Good use of resources • Cost of screening tests • Cost of follow-up diagnostic tests • Cost of treatment • Benefits versus alternatives 9/10/2002 Natural history; population screening 26 Screening for Breast Cancer U.S. Preventive Services Task Force December 4, 2009 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. ... 2/1/2011 Natural history; population screening 27 Revisiting the USPSTF Breast Cancer Screening Guidelines: Ethics, and Patient Responsibilities 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. 2/1/2011 Natural history; population screening 28 Mammography Wars 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.” 2/1/2011 Natural history; population screening 29 Who should get a mammogram? 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. 2/1/2011 Natural history; population screening 30 What should we pay for? 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. 2/1/2011 Natural history; population screening 31 New U.S. analysis backs annual breast screening By Julie Steenhuysen CHICAGO | Wed Jan 26, 2011 12:26pm 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. 2/1/2011 Natural history; population screening 32 AJR: USPSTF mammo recommendations could cost 6,500 lives yearly “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.” 2/1/2011 Natural history; population screening 33 Survival time after diagnosis – lead time Detectable, preclinical Pre-detectable Age: 35 45 Clinical 55 65 Disability or death 75 Lead time Possible detection via screening 9/10/2002 Clinical detection Natural history; population screening 34 Survival time must increase > lead time Undetected (no screening) Pre-detectable Clinical diagnosis & treatment Disability or death Survival time after diagnosis Early detect, diagnosis, & treatment Pre-detectable Monitoring for recurrence ? Lead time Age: 9/10/2002 35 45 55 Natural history; population screening 65 75 35 Slowly progressing diseases are easier to detect by screening Clinical diagnosis, treatment Predetectable Disability or death Survival time after diagnosis Detectable, pre-clinical Pre-detectable Clinical diagnosis & treatment Disability or death Survival time after diagnosis Age: 9/10/2002 35 45 55 Natural history; population screening 65 75 36 Early detection may over-diagnose Undetected (no screening) Pre-detectable Mild or no symptoms Favorable outcome Survival time after diagnosis Early detect, diagnosis, & treatment Pre-detectable Monitoring for recurrence Favorable outcome Survival time after dx Age: 1/9/2007 35 45 55 Natural history; population screening 65 75 37 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] 9/10/2002 Natural history; population screening 38 Reliability Repeatability – get same result • Each time • From each instrument • From each rater If don’t know correct result, then can examine reliability only. 9/16/2003 Natural history; population screening 39 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 9/10/2002 Natural history; population screening 40 Validity: 1) Sensitivity Probability (proportion) of correct classification of cases / Cases found all cases 2/1/2011 Natural history; population screening 41 Validity: 2) Specificity Probability (proportion) of correct classification of noncases / Noncases identified all noncases 9/10/2002 Natural history; population screening 42 Remember this slide? 2 cases / month OO OO O O O OOO O O 9/16/2003 Natural history; population screening 43 Pre-detectable preclinical clinical old OO OO O O O O O O O O OO O 9/16/2003 Natural history; population screening 44 Pre-detectable pre-clinical clinical old O O O OO O O OO O O O O O O O O O O O O O O O OOO O O O O O O O O O O O 9/16/2003 Natural history; population screening 45 What is the prevalence of “the condition”? O O O OO O O OO O O O O O O O O O O O O O O O OOO O O O O O O O O O O O 1/29/2008 Natural history; population screening 46 Sensitivity of a screening test Probability (proportion) of correct classification of detectable, preclinical cases 9/10/2002 Natural history; population screening 47 Pre-detectable (8) pre-clinical (10) clinical (6) old (14) O OO O O O O OO O O O O O O O O O O O O O O O OOO O O O O O O O O O O O 9/10/2002 Natural history; population screening 48 Correctly classified Sensitivity: ––––––––––––––––––––––––––– Total detectable pre-clinical (10) O OO O O O O OO O O O O O O O O O O O O O O O OOO O O O O O O O O O O O 9/10/2002 Natural history; population screening 49 Specificity of a screening test Probability (proportion) of correct classification of noncases Noncases identified / all noncases 9/10/2002 Natural history; population screening 50 Pre-detectable (8) pre-clinical (10) clinical (6) old (14) O OO O O O O OO O O O O O O O O O O O O O O O OOO O O O O O O O O O O O 2/1/2011 Natural history; population screening 51 Correctly classified Specificity: ––––––––––––––––––––––––––––– Total non-cases (& pre-detect) (162 or 170) O OO O O O O OO O O O O O O O O O O O O O O O OOO O O O O O O O O O O O 9/10/2002 Natural history; population screening 52 True Disease Status Screening Test Results Positive Cases Non-cases True positive False positive a+b True negative c+d a b c d Negative False negative a+c b+d a True positives = Sensitivity = a+c All cases True negatives d Specificity = = All non-cases b+d 9/10/2002 Natural history; population screening 53 True Disease Status Screening Test Results Positive Cases Non-cases 140 1,000 1,140 19,000 19,060 a b c d Negative 60 200 20,000 True positives 140 Sensitivity = = = 70% All cases 200 Specificity = True negatives = 19,000 = 95% 20,000 All non-cases 5/26/2008 Natural history; population screening 54 Interpreting test results: predictive value Probability (proportion) of those tested who are correctly classified Cases identified / all positive tests Noncases identified / all negative tests 1/9/2007 Natural history; population screening 55 True Disease Status Screening Test Results Positive Cases Non-cases True positive False positive a+b True negative c+d a b c d Negative False negative a+c b+d True positives a PPV = = All positives a+b True negatives d NPV = = All negatives c+d 9/10/2002 Natural history; population screening 56 True Disease Status Screening Test Results Positive Cases Non-cases 140 1,000 1,140 19,000 19,060 a b c d Negative 60 200 20,000 True positives 140 PPV = = = 12.3% All positives 1,140 19,000 NPV = True negatives = = 99.7% 19,060 All negatives 1/9/2007 Natural history; population screening 57 Positive predictive value, Sensitivity, specificity, and prevalence Prevalence (%) 0.1 PV+ (%) 1.4 Se (%) Sp (%) 70 95 1.0 12.3 70 95 5.0 42.4 70 95 50.0 93.3 70 95 1/29/2008 Natural history; population screening 58 Example: Mammography screening of unselected women Disease status Positive Negative Total Cancer 132 47 179 No cancer 985 62,295 63,280 Total 1,117 62,342 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 1/9/2007 Natural history; population screening 59 Effect of Prevalence on Positive Predictive Value Sensitivity = 93%, Specificity = 92% Surgical biopsy (“gold standard”) Cancer No cancer Prev. Without palpable mass in breast Fine needle aspiration Positive Negative 14 1 8 13% 91 PV+ = 64% 113 8 15 38% 181 PV+ = 88% With palpable mass in breast Fine needle aspiration Positive Negative See http://www.meddean.luc.edu/lumen/MedEd/ipm/IPM1/Biostats/diagnostic_test_example1_Solutions1011.pdf 2/2/2011 Natural history; population screening 60 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 9/10/2002 Natural history; population screening 61 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 9/16/2003 Natural history; population screening 62 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?” 9/24/2001 63