BMSC 5260 Midterm Review PDF
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This document is a midterm review for a course on epidemiology, public health surveillance, and clinical trials. It covers topics such as primary, secondary, and tertiary prevention, endemic, epidemic, and pandemic diseases, the chain of infection, and different types of clinical questions. It also includes information about measures of frequency, the surveillance loop, and clinical trials.
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BMSC 5260 Midterm Review ======================== A. **Modules 1 & 2: Epidemiology Basics/Measures of Frequency/Public Health Surveillance** 1. **What is the difference between primary, secondary, and tertiary prevention?** - Table the 3 types of prevention. Column 1 T...
BMSC 5260 Midterm Review ======================== A. **Modules 1 & 2: Epidemiology Basics/Measures of Frequency/Public Health Surveillance** 1. **What is the difference between primary, secondary, and tertiary prevention?** - Table the 3 types of prevention. Column 1 Type of Prevention column 2 Definition and column 3 Examples Row 1 Primary prevention; Preventing the initial development of a disease. Examples are Immunization, reducing exposure to a risk factor Column 2 Secondary prevention is Early detection of existing disease to reduce severity and complications. Examples are Screening for cancer. row 3 Tertiary prevention: Reducing the impact of the disease. Example Rehabilitation for stroke 2. What does subclinical and clinical mean and how do they fit into the natural history of disease? - **[Subclinical]** is the same as asymptomatic- there are biological changes occurring by no signs or symptoms of the disease. - **[Clinical]**: those with signs and symptoms of disease ![](media/image2.png) 3. **Describe endemic, epidemic, and pandemic.** - **[Endemic]** is defined as the [consistent presence] of a disease within a given geographic area. It may also refer to the usual occurrence of a given disease within such an area (sometimes referred to as the "background rate of disease"). - **[Epidemic]** is defined as the occurrence in a community or region of a group of illnesses of similar nature, clearly more than normal expectancy and derived from a common or a propagated source. - **[Pandemic]** refers to a worldwide epidemic. ![The difference between endemic, pandemic and epidemic \| Baptist Health](media/image4.jpeg) A. Epidemic B. Pandemic C. Endemic 4. Describe surveillance in terms of the surveillance loop. - **[Surveillance]** is the process of collecting data, analyzing the data, interpreting the data, and providing feedback and recommendation (disseminating the data). This is what the epidemiologist does to provide the data for a **public health action**. **[DOES NOT ANSWER THE WHY AND HOW (only the who what when where)]** (For example, data might drive the decision to vaccinate those at highest risk (elderly) first against the COVID-19 vaccine) - Collected data undergoes detailed analysis and interpretation. The information is then used to provide feedback and recommendations to the healthcare system so that action can be taken to prevent or control the events.. 5. **What is required for the chain of infection (disease transmission)?** - **Agent: pathogen** - **Host: must be susceptible, capable of or at risk of developing disease** - **Mode of transmission: allows pathogen to spread** 6. What is the formula for the following and provide an example calculating each: NOTE- these are measures of **[FREQUENCY]**! - **Cumulative Incidence:** ![A white text with black text Description automatically generated](media/image6.png) - **Incidence rate:** A text on a white background Description automatically generated - **Prevalence:** ![A close-up of a text Description automatically generated](media/image8.png) [Prevalence = Incidence x Duration of disease] - **Point prevalence**: prevalence of disease at certain point in time A screenshot of a chat Description automatically generated - **Period prevalence:** \# of people have had disease at any point during certain time - **Mortality rate** aka annual death rate (of total population, number who died in a specified period of time) ![A white background with black text Description automatically generated](media/image10.png) - **Proportionate mortality** (of those who died, number who died of a specific cause; NOT a rate) A close-up of a white background Description automatically generated - **Case fatality rate** (of those with a specific disease, number who died in a specified period of time) ![A close up of a text Description automatically generated](media/image12.png) 7. What is the difference between the direct and indirect adjustment? - Goal of adjustment is to compare at least two populations while eliminating the possible effect of a given factor such as age on the rates being compared. Major point- adjusted rate are not "real"- they are just for comparison purposes only. If you see an adjusted rate of 150 per 100,000- know that is not the real rate- is for comparison! 1. **[Direct]**- uses an outside population- most common method used 2. **[Indirect]**- uses a population to calculate a standard number of observed/expected. B. **Modules 3 & 4: Evidence-based Medicine (EBM) Overview & Ask/Acquire** 8. Describe the difference and similarities between the three elements of EBM and the five steps in practicing EBM - The three elements are the best scientific evidence, clinical experience, and patient values. - The five steps are: **Ask** (formulate clinical question), **Acquire** (find best relevant evidence), **Appraise** (evaluate evidence assessing bias), **Apply** (results to patient care) and **Act** (implement evidence through shared decision-making). - In order to apply the steps of EBM, you need to consider and take them in context with your [clinical experience] and the [patient's values]. 9. Describe the 3 classification systems. A diagram of a diagram of a patient Description automatically generated with medium confidence - **[Hierarchy of evidence:]** each type of clinical question has a different hierarchy; most appropriate design and lowest risk of bias. ![](media/image14.png) - **[Level of processing:]** primary studies can be processed into systematic reviews, and can be further processed into clinical practice guidelines - **[EBM resources:]** resources can be placed into 3 broad categories: summaries and guidelines, preappraised research, and nonpreapparised research. 10. Describe the difference between a background and foreground question? What are the steps in developing a foreground question? - **[Background questions]** address fundamental knowledge about a condition, such as "what is type 2 diabetes mellitus?" or "what treatment options are available?" Traditional medical textbooks, whether in print or online, are excellent resources for answering these questions. - **[Foreground questions]** are asked by experienced clinicians focusing on specific clinical issues. These require detailed and specific answers from the literature. - Foreground questions of therapy or harm are divided into 4 parts following the PICO framework: patients or population, intervention(s) or exposure(s), comparator, and outcome. i. Questions of prognosis: Patients, exposure (time), and outcome ii. Questions of diagnosis: patients, exposure (test), and outcome (criterion standard) 11. For a therapy question, what is the best hierarchy of evidence and why? How does this differ for a harm question? - **RCT** (Randomized Control Trials)\>**Cohort**\>**Case-Control**\>**Cross-sectional**\>**Case Series** - When looking at questions of **[harm]**, it is not always ethical to use RCT because of harmful exposures. **Observational studies** are sometimes better for this reason. TLDR: - For **therapy** questions, RCTs are the top evidence because they control for confounding and bias, directly testing the efficacy of an intervention. - For **harm** questions, observational studies (cohort and case-control) are preferred because they allow for ethical study of risks in real-world settings, particularly when RCTs are not feasible or ethical. 12. Describe the 5 fundamental types of clinical questions. - 1\. **[Therapy]**: determining the effect of interventions on patient-important outcomes (symptoms, function, morbidity, mortality, and costs). - 2\. **[Harm]**: ascertaining the effects of potentially harmful agents (including therapies from the first type of question) on patient-important outcomes. - 3\. **[Differential diagnosis]**: in patients with a particular clinical presentation, establishing the frequency of the underlying disorders. - 4\. **[Diagnosis:]** establishing the power of a test to differentiate between those with and without a target condition or disease. - 5\. **[Prognosis]**: estimating a patient\'s future course. 13. Describe the EBM resource pyramid. The EBM pyramid is a visual of the hierarchy of different types of evidence in terms of reliability, validity, and usefulness for clinal decision-making. [Systematic Reviews]: At the top because it's a collection of all available evidence as they pool data from numerous studies, reducing bias [Summaries:] Under because it is useful, summarized evaluations of research [RCT]: gold standard for testing because it reduces bias [Cohort studies]: cohorts are followed over time to observe outcomes of interventions -- provide observational data The image is a hierarchical pyramid illustrating the levels of evidence in medical research, divided into primary and secondary research. The pyramid is organized as follows, from the base to the top: Primary Research (Base of the Pyramid) 1. Animal Studies / Laboratory Studies: Foundational research conducted on animal models or in laboratory settings. 2. Case Series / Case Reports: Descriptive studies on patient cases without a control group. 3. Cross-Sectional Studies: Observational studies analyzing data from a population at a specific point in time. 4. Case-Control Studies: Observational studies comparing patients with a condition (cases) to those without (controls). 5. Cohort Studies: Observational studies following groups with different exposures over time to determine outcomes. 6. Randomized Controlled Trials (RCTs): Experimental studies where participants are randomly assigned to different treatment groups. Secondary Research (Top of the Pyramid) 1. Synopses of Studies: Summaries of individual studies providing key findings and implications. 2. Syntheses: Includes systematic reviews and meta-analyses that aggregate results from multiple studies. Systematic Reviews: Comprehensive reviews of the literature using a structured methodology. Meta-Analyses: Statistical techniques combining results from multiple studies to derive a pooled estimate. 3. Synopses of Syntheses: Summaries of systematic reviews and meta-analyses. 4. Summaries: Comprehensive overviews combining information from various studies and syntheses, often found in clinical guidelines. 5. Systems: Integrated systems providing decision support by synthesizing all relevant research evidence for clinical practice. Quality of Information An arrow along the side of the pyramid indicates that the quality of information increases as one moves from the base (primary research) to the top (secondary research). This pyramid visually represents the increasing quality and reliability of information as one moves from individual primary studies to comprehensive systems of synthesized research evidence. **C. Modules 5 & 6: Appraise Overview/Intro to Epi Studies/Experimental Studies (therapy)** 14. What are the primary questions asked for the appraisal process? - **[How serious was the risk of bias? ]** i. Blinding, randomization, comparable groups, follow-up complete, analysis (as treated vs. as assigned), stopped early, etc. - **[What are the results? ]** ii. Magnitude and precision of the impact of the intervention (point estimate -mean -and confidence intervals). 15. Explain the difference between the 2 major types of epidemiology. - **[Descriptive epidemiology]** serves to answer the who, what, where, and when; uses descriptive statistics to describe the characteristics of the sample of individuals that represent the population from which they came from. - **[Analytic epidemiology]** compares two or more groups to make associations; uses inferential statistics to make inferences or predictions about the whole population from a sample taken of that population. 16. How does a type I error differ from a type II error? - **[Type 1 error]** occurs when a test indicates there is a difference in the between-groups when in fact there is not. **(False positive)** - **[Type 2 error]** occurs when a test indicates there is no difference between groups when in fact there is. **(False negative)** 17. Differentiate between descriptive, observational, and experimental studies. Provide an example of two study designs in each major study type. - **[Descriptive studies]** focus on describing (the who, what, when, where) while **[analytic studies]** (such as observation and experimental studies) focus on the why and how. **[Observational]** differ from experimental studies in that there is no assignment of the treatment or exposure by the investigator. - Descriptive studies include case reports, case series, ecological, and n-of-1 - Observational studies include cohort studies (prospective and retrospective), case-control, and cross-sectional studies. - Experimental studies include RCT and non-randomized studies. ![](media/image16.png) - Select patients based on exposure & outcome status - Can be done at different times in relation to when exposure & outcome occurred (Ex: patients who exercise 3x a week and their score on depression index exam) 8. **[Case-report:]** describing an interesting case about a disease in a patient (Ex: when HIV was fist ID, there was a paper describing an unusual presentation of infectious diseases in a man...led to **[case-series]** in which more individuals were reported for similar sexual activity) 9. **[Ecological study:]** when you have a group (ex: state masking laws on the outcome of COVID hospitalization rates; looking at entire states based on the hospitalization rates, not individuals) 10. **[N-of-1 study]**: when doctors tries a specific treatment on 1 patients and sees their condition improve after 18. What is the purpose of randomization? Describe stratified randomization and its purpose. - The purpose of **[randomization]** is to **prevent any potential biases** as well as any known and **unknown confounders** by increasing comparability between different treatment groups. -- does not enure comparitability - **[Stratified randomization]** increases the **likelihood of comparability** of the study groups. iii. first stratify (stratum = layer) our study population by each variable that we consider important and then randomize participants to treatment groups within each stratum. -- **TLDR**: participants are divided into subgroups based on important characteristics (age, sex, baseline risk) before randomization iv. 19. What is the purpose of blinding? What does it mean to double-blind? - **[Blinding]** helps ensure results are measured comparably in all study groups. Prevents participants from self-reporting a positive response due to enthusiasm, and certain psychological factors and researchers measuring outcomes more carefully in those receiving a new drug than in those receiving currently available therapy - The masking of both participants and study personnel is called **[double blinding.]** 20. Describe the difference between efficacy and effectiveness. How do these differ from efficiency? - **[Efficacy]** answers the question "does this treatment work under **ideal conditions**?" - **[Effectiveness]** answers the questions "Does the treatment work like it is supposed to in the real world?". - These concepts differ from efficiency which answers the questions "is the benefit of the treatment worth the cost (in terms of not just money but also side effect discomfort, stigma etc.) ![A close-up of a sign Description automatically generated](media/image19.png) 21. Describe the purpose of the different phases of clinical trials. - **[Pre-clinical phase]**: to ensure the possible treatment is not toxic prior to proceeding testing the treatment in humans. -- NO HUMANS - **[Phase 1]**: now that the treatment has been found to not be toxic, this is the first time the treatment is tested in humans. Here, the purpose is to **determine possible side effects** (safety) associated with dosage. In phase 1, this usually involves healthy participants. - **[Phase 2]**: the treatment is now given in the target population to provide information on general side effects and information on the **efficacy of the drug** (although this is a small trial so long-term adverse effects cannot be assessed). - In **[phase 3]**: as this is a much larger trial with longer follow-up, this is to further determine efficacy and rare adverse effects. Once phases 1-3 have been completed, the **FDA reviews** the data and the drug is approved for large scale use and you move into phase 4. - Note that phase 4 is not a clinical trial anymore- there is not manipulation of the treatment, there is no randomization. Here this is really completing several post-market monitoring studies to continue to look at effectiveness and not so much efficiency. A diagram of a health program Description automatically generated with medium confidence 22. Calculate the following: - **[RR (relative risk)-]** a measure of association; tells us how much the risk changes with treatment compared to no treatment (Rt= risk in treatment group, Rc=risk in control) ![](media/image21.png) - **[ARR]** -- absolute risk reduction (also known as risk difference) -- a measure of impact. Drug reduces AR by 10% - **[RRR]** (relative risk reduction)- a measure of association; drug reduces relative risk of event by 50% compared to control: ![](media/image23.png) - **[NNT]** (number needed to treat) or harm (NNH)- a measure of impact; 10 ppl needed to be treated to prevent 1 event: A mathematical equation with numbers and symbols Description automatically generated C. **Module 7: Error in Estimation, Bias, Causality** 23. What is the difference between precision and validity? - **[Precision]**: lack of random error 1. Reliability = precision; how close repeated measurements are (narrower CI) - **[Validity]**: lack of systematic error; extent to which the study measures what it is intended to measure. 2. Validity = accuracy - Factors can affect precision (sample size, treatment effect size) and validity (bias and confounding). ![A diagram of a diagram of a diagram Description automatically generated with medium confidence](media/image25.png) 24. What criteria must be met for a factor to be considered a confounder? Confounder variables: 2 variables are associated only because they're linked through a 3^rd^ variable - **Independent risk factor for the outcome** **([ex]: Smoking is also a known risk factor for lung cancer, independent of alcohol consumption)** - **Associated with the exposure in source population (population at risk of outcome)** **([ex]: Smoking is associated with alcohol consumption, as people who drink alcohol are more likely to smoke than non-drinkers)** - **The confounder is not an intermediate or in the causal pathway between the exposure and outcome.** **(ex: If alcohol consumption leads to liver damage, and liver damage causes cancer, liver damage would not be considered a confounder but rather a mediator on the causal pathway)** 25. Describe the Bradford Hill criteria. Helps determine whether observed association between an exposure and outcome is likely casual. - **[Temporal Relationship]: Exposure to the factor must occur before the disease develops. The order of the events is key here.** **[(]ex: history of smoking proceeds diagnosis of squamous cell carcinoma (cancer))** - **[Strength of the Association:]** The higher the relative risk, or odds ratio, the more likely an association is causal. Relative risk is determined by measuring the odds that event A occurs in **presence or absence of event B**. (Ex: smoking is a strong risk factor for SCC) - **[Biological Gradient]** (Dose-Response Relationship): As the dose of exposure increases, the risk of disease also increases. (ex: relationship between \# of cigarettes smoked per day and incidence of SCC is linear) - **[Replication of Findings:]** The association can be observed in multiple studies and across different populations. (ex: strength of association between smoking and SCC is same in both genders) - **[Biologic Plausibility:]** The causal association is logical given our current knowledge of the human body. (ex: compounds that have the potential to or known to cause cancer in other tissues of the body are found in cigar smoke) - **[Consideration of Alternative Explanations:]** Investigations have been conducted to explore other possible causes and they have been **ruled out**. (ex: other causes of SCC have been explored and are known to exist, but cigar smoking demonstrates strongest relationship) - **[Cessation of Exposure:]** When exposure to the causative factor is reduced or eliminated, the relative risk of disease declines. (ex: smoking cessation decreases person's risk of SCC) - **[Consistency with Other Knowledge:]** Evidence of the association is consistent with other available information about the affected population and causative agent, for example, the agent's availability and the potential for exposure. (ex: rates of SCC increase in the US when the \# of smokers and \# of cigar sales increase) - **[Specificity of the Association:]** The association is specific in that exposure to the causative agent is only associated with one disease. This guideline is now considered outdated based on the current understanding that multiple diseases can be caused by the same agent. Specificity can support causation, but it is not required. (ex: cigar smoking is associated with emphysema, cardiovascular disease, and cancer in other tissues of the body) 26. Describe the difference between random and non-random error. How can you detect these in primary studies? - **[Random error]** occurs because of parameters that are beyond the control of the experimenter and interfere with the results of the experiment. Random error is all about [chance] - **[Non-random errors]** (bias) ([systematic error]) are errors which tend to shift all measurements in a systematic and consistent way either high or low. A table with text on it Description automatically generated 27. Detail the role of sample size and event rate in the precision of a study. - An increase in sample size or event rate helps to increase the precision of a study. An increase of event rate has more of an impact on precision than does sample size. - **Sample size** is crucial for reducing random error and improving the precision of study estimates. Larger samples result in more reliable, consistent data. - **Event rate** affects the ability to detect and estimate effects. Higher event rates improve precision, while low event rates increase uncertainty and widen confidence intervals. 28. Describe selection bias, information bias, interaction (effect measure modification), and confounding. Be able to differentiate between these. - **[Selection bias]** occurs when the comparison groups are not equivalent in either exposure or disease. - **[Information bias]** occurs due to errors in the collection of data or errors in the measurements of data. - **Differential misclassification:** occurs when information collected differs in different study groups and this difference is related to the exposure or outcome (ex: asking participant more questions about outcome if they are on experimental treatment) - **Non-differential misclassification:** occurs when information collected differs in different study groups and this difference is not related to exposure or outcome (ex: measurement tool/diagnostic test that is not very sensitive) - **[Confounding]** is the confusion between the effect of the exposure of interest on the disease and the effect of another factor and can result in non-random error. NOT A BIAS\* True phenomenon - **[Interaction]**: occurs when the incidence rate of disease in the presence of 2+ risk factors differ from the incidence rate expected to result from their individual effects; interaction also referred to as effect modification. 3. Interaction and confounding are not the same. While both interaction and confounding are true phenomena, you want to control for confounding to better estimate the true causal pathway between your exposure and the outcome of interest (like treatment A on disease A). Interaction is part of the causal pathway and should be adjusted for via stratification to better highlight the interactions' role in the causal pathway.