Prevention, Screening & Health Maintenance Basics & Essentials XHypothesis Driven History Taking.htm _______________________________________________________ Ideal Screening Test: Real Clinical Testing: Always correct Know operating characteristics of test Repeatable Standardization, controls Safe, painless, quick, inexpensive Quantify risks, cost effectiveness Results make clinical difference Actual or significant benefit vs. bias _______________________________________________________ Screening Decisions: [scroll down] What diseases warrant screening? Who should be screened? How should I screen? What test? When should screening begin? For how long? Consider - Natural History of Disease Morbidity & Mortality Treatment Effective if Given Early ______________________________________________________ Concepts in Screening: Sensitivity and Specificity = functions of the operating characteristics of test Predictive Values are related to disease prevalence or pre-test probability Sensitivity: True positives by screening test / All with disease by gold standardSpecificity: True negatives by screening test / All without disease by gold standard Positive Predictive Value: True Positives / All who test positive (true and false positives) Negative Predictive Value: True Negatives / All who test negative (true and false negatives) Rule: As Prevalence Increases- PPV increasesNPV decreases As Prevalence Decreases- PPV decreases NPV increasesNumber Needed to Treat: (NNT): the number of patients who must be exposed to an intervention before the clinical outcome of interest occurred; for example, the number of patients needed to treat to prevent one adverse outcome. ( Therapy) To Calculation ______________________________________________________ Levels of Evidence [U.S. Preventive Services Task Force Formula] treatment and control groups. Case Control Study: Retrospective comparison of exposures of persons with disease (cases) with those of persons without the disease (controls). _______________________________________________________ EBM : The User's Guide to the Medical Literature1. Was the assignment of patients to treatment randomized? 2. Were all patients who entered the trial accounted for and attributed at its conclusion? 3. Was follow-up complete? 4. Were patients analyzed in the groups to which they were randomized (intention to treat analysis)? 5. Were patients, their clinicians and study personnel kept `blind' to treatment received? 6. Were the groups similar at the start of the trial? 7. Aside from the experimental intervention, were the groups treated equally? ?1. How large is the treatment effect? 2. How precise is the estimate of the treatment effect? What is the confidence interval around the effect? Will the results help me in my patient care 1. Can the results be applied to my patients? 2. Were all clinically relevant outcomes considered? 3. Are the benefits worth the harms and costs? REMEMBER: Evidence makes an important contribution to good clinical decision making but evidence, In addition to clinical expertise, a good clinician must demonstrate compassion, sensitive listening skills, and broad perspectives from the humanities and social sciences. These attributes allow for an understanding of patients' illnesses in the context of their experience, personalities, and cultures. _______________________________________________________________________________ Clinical Epidemiology Glossary Clinical Epidemiology Glossary Absolute risk: The observed or calculated probability of an event in the population under study. Absolute risk difference: the difference in the risk for disease or death between an exposed population and an unexposed population. Absolute risk reduction (ARR): the difference in the absolute risk (rates of adverse events) between study and control populations. Adjustment: A summarizing procedure for a statistical measure in which the effects of differences in composition of the populations being Association: Statistical dependence between two or more events, characteristics, or other variables. An association may be fortuitous or may Bias (Syn: systematic error): Deviation of results or inferences from the truth, or processes leading to such deviation. See also Referral Bias,Selection Bias. Blind(ed) study (Syn: masked study): A study in which observer(s) and/or subjects are kept ignorant of the group to which the subjects are assigned, as in an experimental study, or of the population from which the subjects come, as in a nonexperimental or observational study. Where both observer and subjects are kept ignorant, the study is termed a double-blind study. If the statistical analysis is also done in ignorance of the group to which subjects belong, the study is sometimes described as triple blind. The purpose of "blinding" is to eliminate sources of bias. Case-series: Report of a number of cases of disease. Case-control study: Retrospective comparison of exposures of persons with disease (cases) with those of persons without the disease (controls) Causality: The relating of causes to the effects they produce. Most of epidemiology concerns causality and several types of causes can be distinguished. Co-interventions: Interventions other than the treatment under study that are applied differently to the treatment and control groups. Cointervention is a Cohort study: Follow-up of exposed and non-exposed defined groups, with a comparison of disease rates during the time covered. Comparison group: Any group to which the index group is compared. Usually synonymous with control group. Co-morbidity: Coexistence of a disease or diseases in a study participant in addition to the index condition that is the subject of study. Confidence interval (CI): The range of numerical values in which we can be confident (to a computed probability, such as 90 or 95%) that the population value being estimated will be found. Confidence intervals indicate the strength of evidence; where confidence intervals are wide, they indicate less precise estimates of effect. The larger the trial's sample size, the larger the number of outcome events and the greater becomes the confidence that the true relative risk reduction is close to the value stated. Thus the confidence intervals narrow and "precision" is increased. In a "positive finding" study the lower boundary of the confidence interval, or lower confidence limit, should still remain important or clinically significant if the results are to be accepted. In a "negative finding" study, the upper boundary of the confidence interval should not be clinically significant if you are to confidently accept this result. Confounding variable, Confounder: A variable that can cause or prevent the outcome of interest, is not an intermediate variable, and is associated with the factor under investigation. A confounding variable may be due chance or bias. Unless it is possible to adjust for confounding variables, their effects cannot be distinguished from those of factor(s) being studied. Control event rate(CER): The percentage of the control/nonexposed group who experienced outcome in question. Dose-response relationship: A relationship in which change in amount, intensity, or duration of exposure is associated with a change-either an increase or decrease-in risk of a specified outcome. Determinant: Any definable factor that effects a change in a health condition or other characteristic. Effectiveness: a measure of the benefit resulting from an intervention for a given health problem under usual conditions of clinical care for a particular group; Efficacy: a measure of the benefit resulting from an intervention for a given health problem under the ideal conditions of an investigation; it answers the question, Exclusion Criteria: Conditions which preclude entrance of candidates into an investigation even if they meet the inclusion criteria. Experimental event rate(EER): The percentage of intervention/exposed group who experienced outcome in question. Follow-up: Observation over a period of time of an individual, group, or initially defined population whose relevant characteristics have been assessed in order Gold standard: A method, procedure, or measurement that is widely accepted as being the best available. Incidence: The number of new cases of illness commencing, or of persons falling ill, during a specified time period in a given population. See also Prevalence. Intention to treat analysis: A method for data analysis in a randomized clinical trial in which individual outcomes are analyzed according to the group to which they have been randomized, even if they never received the treatment they were assigned. By simulating practical experience it provides a better measure of effectiveness (versus efficacy). Interviewer bias: Systematic error due to interviewer's subconscious or conscious gathering of selective data. Lead-time bias: If prognosis study patients are not all enrolled at similar, well-defined points in the course of their disease, differences in outcome over time may merely reflect differences in duration of illness. Likelihood ratio: Ratio of the probability that a given diagnostic test result will be expected for a patient with the target disorder rather than for a patient without the disorder. Number Needed to Treat (NNT): the number of patients who must be exposed to an intervention before the clinical outcome of interest occurred; for example, the Odds: a proportion in which the numerator contains the number of times an event occurs and the denominator includes the number of times the event does not occur. Odds Ratio (Syn: cross-product ratio, relative odds): a measure of the degree of association; for example, the odds of exposure among the cases compared with the Precision: The range in which the best estimates of a true value approximate the true value. See Confidence interval. Predictive value: In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., does have the disease), or that a person Prevalence: the proportion of persons with a particular disease within a given population at a given time. Prognosis: the possible outcomes of a disease or condition and the likelihood that each one will occur. Prognostic factor: Demographic, disease-specific, or co-morbid characteristics associated strongly enough with a condition's outcomes to predict accurately the eventual development of those outcomes. Compare with risk factors. Neither prognostic or risk factors necessarily imply a cause and effect relationship. Prospective study: Study design where one or more groups (cohorts) of individuals who have not yet had the outcome event in question are monitored for the Randomized controlled trial: Study design where treatments, interventions, or enrollment into different study groups are assigned by random allocation rather than by conscious decisions of clinicians or patients. If the sample size is large enough, this study design avoids problems of bias and confounding variables by assuring that both known and unknown determinants of outcome are evenly distributed between treatment and control groups. Recall bias: Systematic error due to the differences in accuracy or completeness of recall to memory of past events or experiences. Referral filter bias: The sequence of referrals that may lead patients from primary to tertiary centres raises the proportion of more severe or unusual cases, Relative risk (RR): the ratio of the probability of developing, in a specified period of time, an outcome among those receiving the treatment of interest or Relative risk reduction (RRR): the extent to which a treatment reduces a risk, in comparison with patients not receiving the treatment of interest. Reliability (Repeatability, Reproducibility): the results of a test or measure are identical or closely similar each time it is conducted. Retrospective study: study design in which cases where individuals who had an outcome event in question are collected and analyzed after the outcomes Risk factor: patient characteristics or factors associated with an increased probability of developing a condition or disease in the first place. Compare with Selection Bias: a bias in assignment or a confounding variable that arises from study design rather than by chance. These can occur when the study Sensitivity (of a diagnostic test): the proportion of truly diseased persons, as measured by the gold standard, who are identified as diseased by the test under study. Specificity (of a diagnostic test): the proportion of truly nondiseased persons, as measured by the gold standard, who are so identified by the diagnostic test under study. Stratification: division into groups. Stratification may also refer to a process to control for differences in confounding variables, by making separate estimates for Strength of Inference: the likelihood that an observed difference between groups within a study represents a real difference rather than mere chance or Survival curve: A graph of the number of events occurring over time or the chance of being free of these events over time. The events must be discrete and the time at which they occur must be precisely known. In most clinical situations, the chance of an outcome changes with time. In most survival curves the earlier follow-up periods usually include results from more patients than the later periods and are therefore more precise. Validity: the extent to which a variable or intervention measures what it is supposed to measure or accomplishes what it is supposed to accomplish. The internal validity of a study refers to the integrity of the experimental design. The external validity of a study refers to the appropriateness by which its results can be applied to non-study patients or populations. |