Screening

Screening refers to the application of a test to people who are as yet asymptomatic for the purpose of classifying them with respect to their likelihood of having a particular disease. The screening procedure itself does not diagnose disease.Those who test positive are sent on for further evaluation by a subsequent diagnostic test or procedure to determine whether they do in fact have the disease. The concept of screening is that early detection of disease, before the onset of symptoms will lead to a more favourable prognosis. Screening has played an important role in improving public health and medical care.

Diseases appropriate for screening : The disease should be serious, treatment given before symptoms development should be more effective in term of reducing morbidity and\ or mortality, and the prevalence of preclinical conditions should be high among the screened population. Examples of diseases for screening : Diabetes : Screening test is RBS, confirmatory test is FBS and after 2 hours. Hypertension : Hypertension follow up program

Cancer of uterine cervix : Screening is by Papanicolaou smear. Phenyl ketonuria : A serious disease with long-term sequences, 1 in births. Its pathology is congenital absence of phenyl alanine hydroxylase activity in the liver. Metabolites of phenyl alanine result in severe mental retardation, which is irreversible. Screening test is estimation of phenylalanine, which is easy and inexpensive. In USA all newborns are screened. Its prevention is by restriction of proteins containing phenylalanine in the child nutrition.

Criteria of a screening test : It should rapid and easy done Reliable and repeatable i.e. free of observer variation Valid i.e. sensitive and specific Acceptable by people under study Inexpensive – cost-effectiveness After screening a confirmatory test is done to diagnose the disease. After screening a confirmatory test is done to diagnose the disease.

Evaluation of screening programs. Feasibility and efficacy : Even after a disease is determined to be appropriate for screening and a valid test is available, it remains unclear whether a widespread screening program for that disease should be implemented. Evaluation of a screening program involves consideration of two issues : Whether the proposed is feasible and whether it is effective.

Feasibility is measured by a number of factors : * Acceptability of the program to the screenees * Cost-effectiveness * The subsequent diagnosis and treatment of individuals who test positive * The yield of cases : A successful screening program must also include provision of follow up of persons whose screening test are positive. This can be measured by considering the proportions of those with positive tests who are followed, diagnosed and treated.

* In the yield or number of cases detected by a screening program, one measure that is considered is the predictive value of the screening test. Predictive value measures whether or not an individual actually has the disease, given the result of the screening test. Predictive value positive ( PV+ ) is the probability that a person actually has the disease given that he tests positive, and is calculated using the notation PV+ = a\(a+b) from the table 2*2 Predictive value negative ( PV- ) is the probability that an individual is truly disease-free given a negative screening test. PV- = d \ ( c+d ). Sensitivity and specificity of breast cancer using the following table.

Screening program Health Insurance Plan ( HIP ) of Greater New York. Screening test is breast physical examination and confirmatory test is mammography.

Row total Di sease Yes no Exposure 1115 b( false negative )983 a ( true positive )132 yes d(true negative ) C(false positive) 45 no Grand total Grand total Column total

True positive is diagnosed by screening and confirmatory tests positive, while false positive is clinically diagnosed Sensitivity = a\(a+c) = 132\177 = 74.6%. It is defined as the probability of testing positive if the disease is true present. Specificity = d\(b+d) = 63650\64633 = 98.5%. It is defined as the probability of screening negative, if the disease is true absent. PV+ = a\(a+b) = 132\1115 = 11.8%, PV- = d\(c+d) =63650\63695 = 99.9%

The validity of a screening test is measured by sensitivity and specificity. It would be desirable to have a screening test that is highly sensitive and highly specific. In reality this is not possible, and there is a tradeoff between sensitivity and specificity. This tradeoff has to do with the fact for many tests, there are people who normal, others who are abnormal and some people who fall in the grey zone between the two. In these situations, the cutoff between normal and abnormal is an arbitrary decision. Because of this, any screening test based on such a scale will of necessity have increased ability to avoid missing a true case ( sensitivity ) only at the expense of an increase in the number of individuals without the disease who will by mistake be picked up by the screening program ( specificity )

Altering the criterion of positivity or abnormality influences both sensitivity and specificity. Lowering or making less strengthen the criterion increases sensitivity, while making the criterion more strengthen increases specificity and decreases sensitivity e.g. in hypertension screening program, if DBP is 88 this increases sensitivity, but if it is 100 this increases specificity and decreases sensitivity.. Sensitivity should be increased at the expense of specificity when the penalty associated with missing a case is high, such as when the disease is serious and effective treatment is available ( phenylketonuria ), when the disease spread is rapid ( syphilis or gonorrhea ) or when subsequent diagnostic evaluations of positive screening tests are associated with minimal cost and risk, such as a further series of blood pressure readings to ascertain hypertension. After the validity of the screening test has been evaluated, it is necessary to consider its reliability, which refers to the consistency of results when repeated examinations are performed on the same persons under the same conditions.

There are four sources of variability that can affect the reproducibility of a screening test : * Related to biological variation inherent in the actual manifestation being measured e.g. BP * Variation due to the test method of measurement, related to the reliability of the instrument itself * Intraobserver variability, refers to differences in repeated measurements by the same screener * Interobserver variability,refers to inconsistencies attributable to differences in the way different screeners apply or interpret the test results. This variability is minimized when end points are well defined quantified as in tonometry for glaucoma screening, and is greater when the criteria are vague as in the interpretation of chest X-rays.

Effectiveness of a screening program is whether it is effective in reducing morbidity and mortality from the disease. The evaluation of a screening program must based on measures that reflect thr impact of the program on the course of the disease. The most definitive measure of the efficacy of a screening program is a comparison of the cause- specific mortality rates among those whose disease was picked up by screening and those whose diagnosis was related to the development of symptoms. In determining the efficacy of screening, the group must be comparable to all factors affecting the end point under evaluation, with the exception of the screening test, as well as to look carefully for ascertainment of the outcomes.

There are three sources of bias : * Volunteer bias : Volunteers are either in a better health status than the general population or are worse who may represent the ( worried well ) that is asymptomatic individuals who are at higher risk of developing the disease because of medical of family history, or life-style. Both types are bad representatives of their population. * Lead – time is defined as the interval between the diagnosis of a disease at screening and when it would have been detected due to development of symptoms. It represents the the time by which the diagnosis has been advanced as a result of screening. If lead-time is not considered when comparing mortality among screened and unscreened groups, survival may, by mistake, appear to be increased among screened cases because the diagnosis was made earlier in the course of the disease.

The following figure presents lead-time : Age in years Age in years Women – A and B both died from Ca breast Women-B diagnosed by symptoms Women – A diagnosed at screening Disease detected by screening Biologic onset of disease

There are two ways that the effect of lead – time on evaluation of the efficacy of a screening program can be taken into account : a. Is to compare the age-specific death rates, and the length of survival from diagnosis to death. a. Is to compare the age-specific death rates, and the length of survival from diagnosis to death. b. If the lead-time for a given disease can be estimated, it can be taken into account and thus allow comparison of survival of screening and symptom- detected cases. b. If the lead-time for a given disease can be estimated, it can be taken into account and thus allow comparison of survival of screening and symptom- detected cases.

* Length bias refers to the overrepresentation among screening-detected cases and those with a long preclinical phase of a disease and thus a more favorable prognosis. Thus, those with a long preclinical phase are more readily detectable by screening than the more rapidly progressing cases with short preclinical phase. Study designs used to evaluate screening programs : * Co relational studies * Observational studies ( analytic studies, both case- control and cohort ) * Randomized trials, when the sample is sufficiently large, the control of confounding is assured by the process of randomization.