Revision Q Flashcards
because of the epidemiological transition, the burden of infectious disease in developing countries is set to worsen
False
infectious diseases are the leading cause of death in Sub-Saharan Africa
True
chicken pox is one of the six most common causes of death from infectious disease worldwide
False
Malaria is one of the six most common causes of death from infectious disease worldwide
True
the best indicator of the burden of an infectious disease is the number of deaths
False
If an exposure and disease are statistically associated this means that the exposure causes the disease
False
evidence-based medicine has replaced clinical decision making over the last 30 years
False
systematic reviews and meta-analyses are at the top of the hierarchy of evidence
True
in the hierarchy of evidence, case-control studies provide stronger evidence than that from cohort studies
False
What is the hierarchy of studies
Systematic review and meta analyses RCT Cohort study Case control study Ecological study descriptive/cross sectional study case report/series
Definition of bias
A systematic error in design, conduct or analysis of a study which produces a mistaken estimate of an exposure on the risk of disease
What are the critical features of a clinical trial?
Objectives Patient selection Controls Study size Unbiased data collection Specific design Ethics Analysis
What are the advantages to randomisation?
Validates statistics
excludes biased allocation
equally distributes prognostic factors of known and unknown
Why use controls?
Placebo effect regression to the mean acclimatisation seasonal effect basis of study question
What is a regression to the mean?
Any intervention at bad times will be followed by an improvement
Bias in RCTs
Sponsorship study patient allocation/selection prejudice of patient prejudice of observer faulty method faulty analysis faulty interpretation
The 95% confidence intervals provide information that helps us determine whether a statistical association between an exposure and disease (expressed as a relative risk or odds ratio) could have occurred by chance
True
if increasing levels of an exposure lead to increasing risk of disease i.e. a dose-response relationship is found, this provides further evidence of causality
True
The association being assessed is less likely to be causal if it is consistent with evidence from animal experiments and known biological mechanisms
False
A lack of consistency between results from a number of studies using different study designs in different populations excludes a causal association
False
A strong association, as measured by the magnitude of the relative risk, is more likely to be causal than a weak association
True
for a putative risk factor to be the cause of a disease, it has to precede the disease
True
there is a systematic difference between the observed association between exposure and disease and the true association between exposure and disease
True
The presence of bias in an observational study of the effect of an exposure on disease risk implies: there are missing values in the response (disease outcome) measurements
False
The presence of bias in an observational study of the effect of an exposure on disease risk implies: there is a systematic difference between the observed association between exposure and disease and the hypothesized association between exposure and disease
False
The presence of bias in an observational study of the effect of an exposure on disease risk implies: the estimated relative risk of disease associated with the exposure is inaccurate
True
The presence of bias in an observational study of the effect of an exposure on disease risk implies: there are missing values in the exposure measurements
False
a study to assess the effect of regular exercise on the risk of coronary heart disease, by collecting information on exercise via a questionnaire as part of a health and lifestyle survey
Experimental?
False. Observational
a study of the prevalence of Down’s syndrome in babies born in the UK between 1995 and 2000
Experimental?
No. Observational
a study to assess the effect of regular exercise on the risk of coronary heart disease, by randomly allocating some patients to take part in a supervised exercise programme and the remaining patients to take no additional exercise
Experimental?
Yes
a comparison of glycaemic control (measured by plasma glycosylated haemoglobin levels) of patients with type 2 diabetes who were treated with either drug A or drug B in a randomized controlled trial
Experimental?
Yes
a comparison of fasting glucose levels in patients with type 2 diabetes registered at a GP practice who were treated either with twice daily insulin therapy alone or with twice daily insulin therapy plus a new drug (Exenatide) claimed to boost the number of insulin-producing cells in the pancreas. Data on treatment regime were obtained from the GP’s records
Experimental?
No, observational
a study of the prevalence of Down’s syndrome in babies born in the UK between 1995 and 2000
Experimental?
Observational
Prospective cohort studies cannot measure incidence
False
prospective cohort studies are necessary to estimate the prevalence of disease
False
Prospective cohort studies: select subjects for inclusion on the basis of their current disease status
False, A cohort study does not select subjects into a study on the basis of ANY disease status, including disease-free status.
A cohort study selects a group of people e.g. a particular ethnic group, or from a particular area, or a particular age group, or of a particular occupation or lifestyle that they are likely to have high levels of the exposure/risk factor of interest e.g. a cohort of asbestos workers or a cohort of mobile phone subscribers.
The exposure levels of the group are then characterised so that we know who has low/high exposure etc and we then follow the health of the cohort over time to obtain disease incidence.
We then compare the disease incidence in the different exposure groups and assess the association between exposure and disease.
Prospective cohort studies: are studies where subjects are followed over time to determine the frequency of occurrence of the disease under study
True
Prospective cohort studies: can be subject to bias from the healthy worker effect
True
Specificity definition
Specificity (also called the true negative rate) measures the proportion of actual negatives that are correctly identified as such (e.g., the percentage of healthy people who are correctly identified as not having the condition).
Sensitivity definition
Sensitivity (also called the true positive rate, the recall, or probability of detection in some fields) measures the proportion of actual positives that are correctly identified as such (e.g., the percentage of sick people who are correctly identified as having the condition).
If the disease is rare then a population based approach is usually warranted
False
A population approach to vaccination is the most cost effective way of protecting children from measles.
True
Tertiary prevention is always preferable to other forms.
False
Screening may be primary or secondary prevention
False
Levels of health prevention?
Primordial
Primary
Secondary
Tertiary
High risk approach to disease intervention?
Identify th special need targeted rescue operation, then controlling exposure, providing protection against exposure, screening among certain ethnic groups for specific disorders
Population approach to disease intervention?
Begin with recognition that the occurance of common diseases and exposures reflects the behaviour and circumstances of society as a whole
Primary prevention?
Prevent disease before it occurs
Secondary prevention?
Reduce impact of disease that has already occured
Tertiary prevention?
Soften impact of disease that is ongoing or has lasting effects
Treating high blood pressure is secondary prevention
Yes
Clinical trials often involve “double blinding” where both the researcher and the participants are unaware who is in the intervention or control group
True
Clinical trials: Phase IV clinical trials are post-marketing studies that aim to provide additional information on the drug’s risks, benefits and optimal use
True
Clinical trials assign participants randomly to intervention and control groups for ethical reasons
False
Clinical trials are the only experimental design in epidemiology
True
Clinical trials: Phase II clinical trials aim to determine the metabolic and pharmacologic actions of drugs in humans and the maximum tolerated dose
False
Clinical trials stage 0
Whether the drug reaches the cancer
How the drug behaves in the body
How cells in the body respond to the drug
Clinical trials stage 1
How much of the drug is safe to give
What the side effects are
How the body copes with the drug
If the treatment works
Clinical trials stage 2
If the new treatment works well enough to test in a larger phase 3 trial
Which conditions the treatment works for
More about side effects and how to manage them
More about the best dose to use
Clinical trials stage 3
A completely new treatment with the standard treatment
Different doses or ways of giving a standard treatment
A new way of giving radiotherapy with the standard way
Uses more people than stages 1 and 2
Clinical trials stage 4
More about the side effects and safety of the drug
What the long term risks and benefits are
How well the drug works when it’s used more widely
Meta-analyses; the random effects model should be used when it is reasonable to assume that the underlying treatment effect is the same in all studies that are part of the meta-analysis
False
Meta-analyses: Publication bias refers to the greater likelihood of research that has not found a significant result to be published in peer-reviewed literature compared to research that has found a significant result
False
Meta-analyses: the main difference between a systematic review and a meta-analysis is that the meta-analysis involves a quantitative method to calculate an overall summary (average) effect of a treatment/exposure
True
Meta-analyses should contain clearly defined eligibility criteria for the studies chosen to be included
True
Meta-analyses are original research studies
False
ASSERTION: The attributable risk is especially useful in evaluating the impact of introduction or removal of risk factors.
REASON: The attributable risk will be the incidence of disease in the exposed divided by the incidence of disease in the unexposed.
Assertion True
Reason False, it is the difference between the incidence of the diseased and incidence of the unexposed
Attributable risk definition
difference between the risk of an outcome in the exposed group and the unexposed group
ASSERTION: Researchers following a group of 100 vegetarians and 200 non-vegetarians for heart disease incidence, report a relative risk of 0.8 and 95% confidence intervals of 0.6 to 0.9. Vegetarians were significantly less likely to develop heart disease than non-vegetarians.
REASON: Where confidence intervals do not include 1, chance can be excluded as a likely explanation of the findings.
Assertion True
Reason True
Reason is a correct explanation
ASSERTION: Findings from a case control study can contribute evidence of the temporal sequence of events between exposure and disease.
REASON: Bradford Hill criteria for causality include the temporal sequence of events between exposure and disease.
Assertion false
Reason True
ASSERTION: Health promotion initiatives in the UK include a Sure Start programme that provides effective parenting sessions for teenage parents on a council estate.
REASON: Health promotion initiatives can include an educational component.
ASSERTION is True
REASON is True
REASON is correct explanation
ASSERTION: A meta analysis is at the top of the hierarchy of evidence.
REASON: A meta analysis combines the results from individual studies to produce an overall effect estimate that is more reliable and precise.
ASSERTION is True
REASON is True
REASON is correct explanation
