How do we delay disease progress once it has started?

How do we delay disease progress once it has started?
Epidemiology matters: a new introduction to methodological foundations Chapter 13

Epidemiology Matters – Chapter 13
What is screening? When should we screen? How do we evaluate a screening test? How do we decide on a cut-off? PPV, NPV, and prevalence From screening test to screening program Summary Epidemiology Matters – Chapter 13

Screening Screening is the process in which we use a test to determine whether an individual likely has a particular health indicator or not or is likely to develop a particular health indicator or not Screening is not the same as diagnosis; screening tests give us information about whether the disease is likely to be present A screening test assesses the presence of an underlying marker that is associated with outcome of interest Epidemiology Matters – Chapter 13

Screening, examples Women receive regular screening tests beginning in young adulthood for cervical cancer (Pap smear) Physicians assess blood pressure and cholesterol as screening tools for the development of cardiovascular disease Women use home pregnancy tests to screen for presence of an embryo or fetus Epidemiology Matters – Chapter 13

When to screen We screen for disease when we have the opportunity to reduce costs and risk associated with diagnoses on large proportions of at-risk individuals We screen for health indicators that affect population health principally, not for rare diseases (although there are exceptions for rare diseases screen in utero) There should be sufficient time between biological onset of disease and appearance of signs and symptoms of the disease exist so that screening could detect the presence of the disease earlier than it would come to clinical attention There should be available treatment for the disease so that early detection improves the lives of affected Screening tests should be cheaper and less invasive than best available diagnostic tool Epidemiology Matters – Chapter 13

Screening test evaluation
Sensitivity Specificity Positive predictive value Negative predictive value Epidemiology Matters – Chapter 13

Epidemiology Matters – Chapter 13

Screening test evaluation, example
Questions: Should all men be tested for prostate cancer with the new screening tool? High rates of prostate cancer among Farrlandian men New test characterizes level of antigen in blood demonstrated to be associated with prostate cancer Test is inexpensive and requires only a blood specimen Epidemiology Matters – Chapter 13

Screening test evaluation, example
240 men with confirmed incident diagnoses of prostate cancer 2,500 men confirmed free of prostate cancer Measure antigen level for all men Epidemiology Matters – Chapter 13

Screening test evaluation antigen among sample
D- D+ Mean level of antigen is higher among men with prostate cancer Distributions of antigen overlap Between 37 and 56 ng/mL - both diseased and non-diseased men A cut-off if typically declared within this uncertain range Individuals above the cut-off are screening positive or below, screen negative Cut-off is often largely arbitrary and informs performance of screening test Epidemiology Matters – Chapter 13

Screening test evaluation sensitivity and specificity
To assess the validity of a screening tool in establishing the presence of disease we compare with a gold standard Sensitivity: Whether individuals with disease are correctly identified by the screening test as having the disease Specificity: Whether individuals without the disease are correctly identified by the screening test as not having the disease Epidemiology Matters – Chapter 13

Screening test evaluation cut-off
False Positives  Screens Negative Screens  Positive D+ Screening Cut-Off D- Antigen Lowest value on the antigen distribution of men with prostate cancer = 38 ng/mL. Cut-off score = 38 ng/mL Epidemiology Matters – Chapter 13

Screening test evaluation sensitivity
Among those with disease, what proportion does the screening test detect? Interpretation: With a cut-off of 38 ng/mL, we have a test with 100% sensitivity. Among those with prostate cancer, the test captures all cases. There are no false negatives. Epidemiology Matters – Chapter 13

Screening test evaluation specificity
Among those without disease, what proportion does the screening test correctly identify as disease free? Interpretation: With a cut-off of 38 ng/mL, screening test classifies 61.2% of men without prostate cancer as not having prostate cancer, remaining 38.8% are false positive cases. Epidemiology Matters – Chapter 13

Screening test evaluation sensitivity and specificity tradeoffs
Test cut-off is very sensitive: All those who have the disease will be captured by the test Test cut-off is very specific: Individuals who do not have the disease are will not screen positive High sensitivity/low specificity tests are common in practice; i.e., we will not miss many individuals with disease but we also will screen positive those who do not have disease Epidemiology Matters – Chapter 13

Screening test evaluation sensitivity and specificity, example
Primary care physicians query patients about whether they engaged in at least one episode of heavy drinking in the past year as a screening tool for identifying individuals with an alcohol disorder Almost all individuals with an alcohol disorder will have engaged in at least one episode of heavy drinking in the past year, but many individuals without an alcohol disorder may have engaged in one or more heavy drinking episodes as well. The test is sensitive, but not specific Epidemiology Matters – Chapter 13

Screening test evaluation PPV, NPV, and prevalence
How well does our screening test predict who is diseased and who is not? Epidemiology Matters – Chapter 13

Screening test evaluation positive predictive value
Among those who screen positive, what proportion actually has the disease? Interpretation: With a cut-off of 38 ng/mL, one fifth of the men who screen positive on test have prostate cancer, leaving about 80% of men screening positive falsely. Epidemiology Matters – Chapter 13

Screening test evaluation negative predictive value
Among those who screen negative, what proportion actually do not have the disease? Interpretation: With a cut-off of 38 ng/mL, the test has perfect negative predictive value. Among those who are negative on the screening test, we can be perfectly confident that none of those individuals actually have the disease. Epidemiology Matters – Chapter 13

Assess sensitivity and specificity to understand the proportion of diseased and non-diseased individuals correctly categorized as diseased and non-diseased Assess PPV and NPV to understand the proportion of positively screened and negatively screened individuals that have disease or are disease-free Epidemiology Matters – Chapter 13

Screening test evaluation cut-offs and tradeoffs, example
Hypothetical screening test for prostate cancer set a cut-off of 38 ng/mL Perfect sensitivity and negative predictive value Low specificity and positive predictive value Change cut-off for positivity to 45 ng/mL Individuals are positive on screening test if level of antigen is 45 ng/mL or above Epidemiology Matters – Chapter 13

Screening test evaluation cut-offs and tradeoffs, example
Compared with original cut-off of ≥ 38 ng/mL Sensitivity decreased and specificity increased Positive predictive value increased Epidemiology Matters – Chapter 13

Screening test evaluation cut-offs and tradeoffs
Original cut-off Why did sensitivity decrease? Epidemiology Matters – Chapter 13

Original cut-off Why did sensitivity decrease? Some individuals who have prostate cancer will screen negative now - false negatives As increase cut-off for positivity on a screening test, number of individuals with the disease who screen negative will increase - leading to lower sensitivity New cut-off Epidemiology Matters – Chapter 13

Ramifications of false positives vs. false negatives
Low rate of false negatives preferred Infectious diseases critical to maintain low rate of false negative When disease can be readily remediated if caught early but devastating if not Low rate of false positivity preferred When subsequent diagnostic test is invasive and expensive procedures Screening is done routinely on low burden diseases Epidemiology Matters – Chapter 13

A note Empirical guidelines for screening can be created to optimize screening cut-points; these are usually derived from receiver operating characteristic (ROC) curves Epidemiology Matters – Chapter 13

Multiple-stage screening
Two-stage screening test Screen individuals using test with high sensitivity Follow-up with test with high specificity Epidemiology Matters – Chapter 13

Prevalence of screening health indicator, example
Antigen screening test Cut-off of 45 ng/mL Screen two samples for prostate cancer 1,500 men with prostate cancer family history; > 60 years old 1,500 men with no prostate cancer family history; years old Epidemiology Matters – Chapter 13

Prostate cancer screening, sample A
Men with prostate cancer family history and > 60 Epidemiology Matters – Chapter 13

Prostate cancer screening, sample B
Men with no prostate cancer family history and Epidemiology Matters – Chapter 13

Prostate cancer screening example
Sensitivity and specificity Sample A and Sample B sensitivity = 90% Sample A and Sample B specificity = 83% PPV, positive predictive value Sample A (family history, >60) PPV = 72.7% Sample B (no family history, 40-60) PPV = 3.4% NPV, negative predictive value Sample A (family history, >60) NPV = 94.5% Sample B (no family history, 40-60) NPV = 99.9% PPV and NPV differ across samples. Why? Epidemiology Matters – Chapter 13

Why does PPV change? PPV is dependent on the prevalence of a health indicator in screened population As prevalence  probability that individual who screens positive will be true case  As prevalence  probability of being true negative case  Sensitivity and specificity are not directly influenced by prevalence Sensitivity and specificity look among those who have the health indicator versus those who do not PPV and NPV are dependent on prevalence, and PPV increases as the prevalence of disease increases. Epidemiology Matters – Chapter 13

Screening test to screening program
Example 1: Detection based on screening compared with detection based on symptoms Example 2: Detection based on screening compared with effect of screening on mortality Epidemiology Matters – Chapter 13

Example 1: Cancer duration in Farrlandia

Example 1: Cancer duration in Farrlandia, screening at 10 years

Example 1: Cancer duration in Farrlandia, screening at 10 years
Screening at single time point is estimating the prevalence of cancer at time point Cancer cases that are more likely to be detected have long duration and perhaps slow-growing tumors Problems with this Slow-growing tumors may not eventually cause death or disability - difficult to predict which tumors will become symptomatic and which will not Compare cancer-related mortality among screened sample to non-screened sample Screened group may have fewer cancer-related deaths because may have better cancer-related outcomes Because tumors that are detected more likely to be slow growing tumors that did not influence morbidity and mortality Length-time bias: Inability to estimate the causal impact of screening test on morbidity and mortality Epidemiology Matters – Chapter 13

Example 2: Disease detection by screening vs. symptoms

Example 2: Screening vs. symptom diagnosis
Person 1’s cancer detected through screening Person 2’s cancer detected due to symptoms Person 1 and person 2 have equal time from cancer onset to death Time from cancer detection to death is longer in Person 1 Lead time: The time from detection from screening and detection through symptoms afforded by screening test. This will always show a benefit in the screened group - even if early detection did not really lengthen life Epidemiology Matters – Chapter 13

Example 2: Disease detection by screening vs. symptoms

Example 2: observation time
When time from start of observation to death is the same in both individuals - no association between screening and length of life When the time from start of observation to death shorter for the not screened compared with screened - evidence that early detection through screening has benefit on mortality Epidemiology Matters – Chapter 13

Summary Screening for health indicators is integral part of improving population health Screening predicts who will develop a specific disease and detects disease among those in early stages Screening tests need to be studied for validity (sensitivity and specificity) We often have a trade-off between sensitivity and specificity Predictive value of screening test is maximized in populations with high prevalence of health indicator of interest Value of screening program will depend on cost-effectiveness, minimal invasiveness, availability of effective treatment Epidemiology Matters – Chapter 13

epidemiologymatters.org Epidemiology Matters – Chapter 1

How do we delay disease progress once it has started?

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