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Build your knowledge with top universities and organisations. Learn more about how FutureLearn is transforming access to education. Learn more about this course. Identifying a good screening test: sensitivity, specificity and coverage Characteristics of a good screening test for diabetic retinopathy - high sensitivity, specificity, positive predictive value and high coverage. View transcript. A detailed examination of the retina, at the back of the eye, is the key procedure when screening for diabetic retinopathy.
Various examination methods are available, from ophthalmoscopy to digital retinal imaging - with or without pupil dilation. Whichever examination method is selected: Screeners must be able to find all cases of retinopathy correctly without causing unnecessary anxiety to the person being screened.
And, the health system must be able to: - Pay for, and manage the purchasing of, screening equipment and; - Train personnel to use and maintain it. We can use a 2 by 2 table to plot the presence of diabetic retinopathy against the ability of the test to detect the condition correctly. A good screening test for DR must have the following 4 key characteristics. The test must also have a high positive predictive value ensuring a high probability that each person with a positive screening test truly has retinopathy.
Lets look at a hypothetical example to understand why these characteristics are important. In our population of people with diabetes, 10 have retinopathy these are known as cases. If all people are screened, we have achieved high coverage. This is particularly so of screening.
If a patient asks a doctor for help the doctor is obliged to do his or her best to help but … if the doctor initiates a screening program there is a presumption that this must benefit the patient [3] ". It is very difficult to determine the benefit of screening for an individual. The distinction between benefits to the community and to individuals needs to be borne in mind when considering recommendations to participate in organised population screening programs.
Participants in screening programs are ostensibly healthy people, so a program should, at the very least, be able to demonstrate evidence of an overall benefit to the community and a minimum of risk that certain individuals may be disadvantaged by the program [1].
Not only is it important that information on the effectiveness of screening programs be available, it should also be disseminated widely. Regular monitoring and evaluation of screening programs is also vital to ensure that effectiveness is maintained and improved where possible. It is essential to recognise that an organised population approach to screening, which ultimately achieves a net health benefit to a community, can result in adverse outcomes for some individuals. There is a risk that people who receive false negative results may experience delays in diagnosis and treatment.
Some may develop a false sense of security and ignore warning symptoms. Increasingly, false negative results can give rise to legal action by people whose cancers appear to have been missed. A false positive result can mean that people without the disease undergo follow-up testing that may be uncomfortable, expensive, and, in some cases, potentially harmful.
Rarely, this can lead to unnecessary treatment. There may be psychological consequences such as anxiety for both the patient and their family. For example, a woman with a false positive mammogram undergoing surgical investigation e.
A person undergoing a colonoscopy as a result of a false positive faecal occult blood test faces the possibility of a bowel perforation during the procedure. This risk might be as high as one in [4]. There are concerns that false negative results can give rise to legal action by people whose cancers appear to have been missed. This must be communicated effectively to the potential participants in a screening program to allow informed consideration of their involvement before any test is done.
One way to avoid confusing this with sensitivity and specificity is to imagine that you are a patient and you have just received the results of your screening test or imagine you are the physician telling a patient about their screening test results.
If the test was positive, the patient will want to know the probability that they really have the disease, i. Conversely, if it is good news, and the screening test was negative, how reassured should the patient be? What is the probability that they are disease free? Another way that helps me keep this straight is to always orient my contingency table with the gold standard at the top and the true disease status listed in the columns.
The illustrations used earlier for sensitivity and specificity emphasized a focus on the numbers in the left column for sensitivity and the right column for specificity. If this orientation is used consistently, the focus for predictive value is on what is going on within each row in the 2 x 2 table, as you will see below. If a test subject has an abnormal screening test i. In the example we have been using there were 1, subjects whose screening test was positive, but only of these actually had the disease, according to the gold standard diagnosis.
Interpretation: Among those who had a positive screening test, the probability of disease was Negative predictive value: If a test subject has a negative screening test, what is the probability that the subject really does not have the disease?
In the same example, there were 63, subjects whose screening test was negative, and 63, of these were, in fact, free of disease. Interpretation: Among those who had a negative screening test, the probability of being disease-free was This widget will compute sensitivity, specificity, and positive and negative predictive value for you.
Just enter the results of a screening evaluation into the turquoise cells. In the video below, he discusses predictive value. One factor that influences the feasibility of a screening program is the yield , i. This can be estimated from the positive predictive value.
Sensitivity and specificity are characteristics of the test and are only influenced by the test characteristics and the criterion of positivity that is selected. In contrast, the positive predictive value of a test, or the yield, is very dependent on the prevalence of the disease in the population being tested.
The higher the prevalence of disease is in the population being screened, the higher the positive predictive values and the yield. Consequently, the primary means of increasing the yield of a screening program is to target the test to groups of people who are at higher risk of developing the disease.
To illustrate the effect of prevalence on positive predictive value, consider the yield that would be obtained for HIV testing in three different settings. The examples below show how drastically the predicative value varies among three groups of test subjects. All three show the effects of screening , subjects. The only thing that is different among these three populations is the prevalence of previously undiagnosed HIV. The 1 st scenario illustrates the yield if the screening program were conducted in female blood donors, in whom the prevalence of disease is only 0.
What these three scenarios illustrate is that if you have limited resources for screening, and you want to get the most "bang for the buck," target a subset of the population that is likely to have a higher prevalence of disease, and don't screen subsets who are very unlikely to be diseased.
Diagnostic measures included the area under the receiver-operating characteristic curve, sensitivity, specificity, and likelihood ratios. The area under the ROC curve was 0. Question: What was the positive predictive value in this study? Hint: You have to use the information provided to piece together the complete 2x2 table; then compute the PPV. See if you can do this before looking at the answer. In the video below, he discusses serial and parallel diagnostic testing.
At first glance screening would seem to be a good thing to do, but there are consequences to screening that carry a cost, and the potential benefits of screening need to be weighed against the risks, especially in subsets of the population that have low prevalence of disease!
Specifically, one needs to consider what happens to the people who had a positive screening test but turned out not to have the disease false positives. Women between years old can get breast cancer, but the probability is extremely low and the sensitivity of mammography is low because younger women have denser breast tissue. Not only will the yield be low, but many of the false positives will be subjected to extreme anxiety and worry.
They may also undergo invasive diagnostic tests such as needle biopsy and surgical biopsy unnecessarily. In the case of fecal blood testing for colorectal cancer, patients with positive screening tests will undergo colonoscopy, which is expensive, inconvenient, and uncomfortable, and it carries its own risks such as accidental perforation of the colon. Cancer Epidemiol Biomark Prev. Screening strategies for atrial fibrillation: a systematic review and cost-effectiveness analysis.
Cost-effectiveness of Staphylococcus aureus decolonization strategies in high-risk total joint arthroplasty patients. J Arthroplast. The cost-effectiveness of using chronic kidney disease risk scores to screen for early-stage chronic kidney disease. Cost-effectiveness of cervical cancer screening and preventative cryotherapy at an HIV treatment clinic in Kenya. Cost Eff Resour Alloc. Immigrant screening for latent tuberculosis in Norway: a cost-effectiveness analysis.
Assessment of universal newborn hearing screening and intervention in Shanghai, China. Using G6PD tests to enable the safe treatment of plasmodium vivax infections with primaquine on the Thailand-Myanmar border: a cost-effectiveness analysis. Evaluation of a stratified National Breast Screening Program in the United Kingdom: an early model-based cost-effectiveness analysis.
John D, Parikh R. Cost-effectiveness and cost utility of community screening for glaucoma in urban India. Public Health. Estimating the cost-effectiveness of one-time screening and treatment for hepatitis C in Korea. Economic analysis of the breast cancer screening program used by the UK NHS: should the program be maintained? Breast Cancer Dove Med Press. Google Scholar. Revisiting annual screening for latent tuberculosis infection in healthcare workers: a cost-effectiveness analysis.
BMC Med. Performance and cost-effectiveness of computed tomography lung cancer screening scenarios in a population-based setting: a microsimulation modeling analysis in Ontario, Canada. PLoS Med. Cost-utility analysis of extending public health insurance coverage to include diabetic retinopathy screening by optometrists. Cost-effectiveness of implementing computed tomography screening for lung cancer in Taiwan. Lung Cancer. Group B streptococci screening before repeat cesarean delivery: a cost-effectiveness analysis.
Obstet Gynecol. The cost-effectiveness of high-risk lung cancer screening and drivers of program efficiency. J Thorac Oncol. Optimal cervical cancer screening in women vaccinated against human papillomavirus. J Natl Cancer Inst. Long-term evaluation of benefits, harms, and cost-effectiveness of the National Bowel Cancer Screening Program in Australia: a modelling study.
Lancet Public Health. Cost-effectiveness and budget effect analysis of a population-based skin cancer screening. JAMA Dermatol. Echocardiographic screening for rheumatic heart disease in indigenous Australian children: a cost-utility analysis. J Am Heart Assoc.
Cost-effectiveness of increasing cervical cancer screening coverage in the Middle East: an example from Lebanon. A screening program to test and treat for helicobacter pylori infection: cost-utility analysis by age, sex and ethnicity. Diabetes Res Clin Pract. The cost impact of outreach testing and treatment for hepatitis C in an urban drug treatment unit.
Liver Int. Early detection and curative treatment of hepatocellular carcinoma: a cost-effectiveness analysis in France and in the United States. Cost-effectiveness of the Norwegian breast cancer screening program.
Int J Cancer. A cost-utility analysis of prostate cancer screening in Australia. Appl Health Econ Health Policy. Screening for chronic kidney disease in Canadian indigenous peoples is cost-effective.
Kidney Int. The medical value and cost-effectiveness of an exercise test for sport preparticipation evaluation in asymptomatic middle-aged white male and female athletes. Arch Cardiovasc Dis. Cost-effectiveness of a new strategy to detect pulmonary tuberculosis in household contacts in Myanmar. Int J Tuberc Lung Dis.
Cost-effectiveness analysis of universal screening for carbapenemase-producing Enterobacteriaceae in hospital inpatients. Cost-effectiveness of screening for active cases of tuberculosis in Flanders, Belgium. Bull World Health Organ.
Recommendations for methicillin-resistant Staphylococcus aureus prevention in adult ICUs: a cost-effectiveness analysis. Crit Care Med. Cost-effectiveness of screening for HIV in primary care: a health economics modelling analysis.
Lancet HIV. Health economic evaluation of immunization strategies of hepatitis E vaccine for elderly population. Hum Vaccin Immunother. Unsuspected malignancies in routine femoral head histopathologic examination during primary total hip arthroplasty: cost-effectiveness analysis. A model-based cost-effectiveness analysis of osteoporosis screening and treatment strategy for postmenopausal Japanese women.
Osteoporos Int. Histopathological examination of specimen following cholecystectomy: are we accepting resect and discard? Surg Endosc. Congenital toxoplasmosis in Austria: prenatal screening for prevention is cost-saving. Appropriate perspectives for health care decisions. Centre for Health Economics; Capturing all of the costs in NICE appraisals: the impact of inflammatory rheumatic diseases on productivity.
Rheumatol Oxford. Basu A, Meltzer D. Implications of spillover effects within the family for medical cost-effectiveness analysis. J Health Econ. Using cost-effectiveness analysis to quantify the value of genomic-based diagnostic tests: recommendations for practice and research.
Genet Test Mol Biomarkers. Cost-effectiveness of additional blood screening tests in the Netherlands. Download references. All data generated or analyzed during this study are included in this published article [and its supplementary information files]. Both authors contributed to i the conception of the review, ii data extraction and analysis, and iii manuscript drafting and revising. The authors agree to be accountable for all aspects of this work. Both authors approve this version to be published.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. You can also search for this author in PubMed Google Scholar. Correspondence to Eldon Spackman. Reprints and Permissions. Iragorri, N. Assessing the value of screening tools: reviewing the challenges and opportunities of cost-effectiveness analysis. Public Health Rev 39, 17 Download citation. Received : 13 December Accepted : 04 April Published : 13 July Anyone you share the following link with will be able to read this content:.
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