EBP Flashcards

Question

Survival curve vs Survival rate

Answer 1

Survival curve: - Probability of survival starts at 100%, decreases over time - Shows proportion of study population that is still alive at successive time points - Patients are censored when lost from study Survival rate: - alternative to survival curve - survival rates at different time points (1 year, 5 years), median survival rate, disease-free survival rate etc.

Answer 2

All-cause mortality - includes all causes of mortality, even those seemingly unrelated to study exposure - ***less prone to misclassification ``` Disease-specific mortality - heavily relies on accuracy and completeness of death certification —> immediate cause —> intervening cause —> underlying cause - ***more prone to misclassification ``` —> intervention may just reduce one of the above (All-cause / Disease-specific mortality) Doctors when issuing death certificates, causes of death must be consistent with those in ICD-10 (classification system by WHO) Standardised mortality ratio (SMR): - Mortality of study group to Mortality of standard population - SMR =1: same mortality rate as standard population - SMR >1: higher mortality rate in study group - SMR <1: lower mortality rate in study group (Sometimes 100 is used rather than 1)

Answer 3

Diagnostic tests: - Laboratory tests - Imaging - Endoscopy - History + Physical examination - combination of above Diagnosis is a ***Probability based on: 1. Frequency of disease: - Prevalence (more commonly available) - Incidence 2. Index of suspicion: - Risk factors / risk predictors: age, smoking status etc. —> Effect measures: Odds ratios, Risk ratios - Careful history and clinical judgement 3. Accuracy and validity of diagnostic tests

Answer 4

Screening: - for Asymptomatic patients with early disease —> secondary prevention —> lower prevalence of disease - Aims to identify people with high risk of disease where interventions may reduce morbidity / mortality - NOT intended to diagnose ``` Diagnosis: - for Symptomatic patients —> higher prevalence of disease - Aim: make a definitive diagnosis / narrow down DDx - NOT intended to prevent disease ```

Answer 5

1. An appropriate “gold standard” (reference standard) - best available test to determine presence / absence of disease —> new test should not be compared to imperfect test - sometimes too invasive / costly —> simpler tests should only be used as proxies when risk of misclassification is low - disease may lack objective standards for diagnosis e.g. mental disorders 2. Lack of information on negative tests - clinicians reluctant to further test when initial test is negative

Answer 6

Describes performance of a test: LR = probability (test results if disease is present) / probability (test result if disease is absent) LR+ = P(+ve test in diseased) / P(+ve test in normal people) —> Sensitivity / 1-Specificity —> ***high LR+ —> better the positive test can rule in disease LR- = P(-ve test in diseased) / P(-ve test in normal people) —> 1-Sensitivity / Specificity —> ***lower LR- —> better the negative test can rule out disease LR = 1 —> no change in likelihood of disease —> not a useful test Use: 1. Allow application to individuals with different ***pre-test probabilities: - ∵ Predictive values are not transferable with different prevalence, but LR still applicable even though prevalence is low - ***Pre-test odds x LR = Post-test odds (need to convert probability to odds) 2. Summarise test performance for a range of possible ***test values - rather than SN and SP defined by a single cut-off point - disease should be more likely for extreme than borderline test results

Answer 7

Parallel testing (囊括越多人) —> ↓ False negative: - ↑ SN and NPV - but may ↑ false positive - clinical prediction rules may be used to combine multiple test results and pre-test probabilities Serial testing (逐漸縮窄範圍) —> ↓ False positive: - ↑ SP and PPV - but may ↑ false negative - serial LR may be calculated

Answer 8

1. Diagnosis does not necessarily lead to improvement in outcomes 2. Hazards of inappropriate diagnosis - false positive results - false negative results - overdiagnosis 3. Overuse / Misuse of diagnostic test is waste of resources

Answer 9

Any intervention intended to improve course of established disease May include: - medications - surgery - changes in organisation / financing of health care

Answer 10

Observational studies: - Examine distributions and determinants of outcomes (observe exposed vs not exposed) - Without any attempt to influence them - Easier to conduct, less expensive - ***Residual confounding problem —> should equally allocate confounders on 2 side 1. Descriptive (cross-sectional, cohort) 2. Analytical (cross-sectional, cohort, case-control) Interventional / Experimental studies (e.g. clinical trials): - Modify an exposure within a population (observe intervention group vs control group) - Examine its effect on outcome - More time-consuming, costly - ***Randomisation minimise confounding - ***Selection bias, Information bias problem RCT: - gold standard study design to provide evidence for effectiveness due to randomisation - participants randomly allocated to different intervention group to minimise confounding - followed up prospectively for assessment of outcomes

Answer 11

Highest —> Lowest: - Evidence summaries - Meta-analysis / Systematic review - RCT - Cohort studies - Case-control / Cross-sectional / Ecological studies - Expert opinion

Answer 12

1. Ethics 2. Intervention 3. Control / Comparison 4. Outcomes / End-points

Answer 13

1. Equipoise: - randomisation is ethical when either of the allocated interventions is better than the other 2. Respect for rights of individual participants: - life, health, dignity, integrity, self-determination, privacy, confidentiality - informed consent - voluntary participation - specific consideration for vulnerable groups 3. Minimising risks: - measures to assess, monitor, minimise risk to human subjects 4. Research ethics committee: - research protocol should be submitted for consideration and approval - right to monitor ongoing studies, esp. for serious adverse events 5. Reporting and dissemination of results: - registration in publicly available database - full reporting + dissemination of results

Answer 14

1. Feasibility: - some interventions may not be available in all settings 2. Complexity: - treatment plan usually involve multiple interventions (will an intervention work with others?) 3. Effect size: - relative effects may exaggerate absolute effects (does the intervention has a clinically significant effect)

Answer 15

1. No treatment - Hawthorne effect: participants may change their behaviours even without interventions (modify an aspect of their behavior in response to their awareness of being observed) 2. Placebo - intervention intended to be indistinguishable from active treatment - intended to have no active effect - Placebo effect: report improvement even with placebo 3. Usual care / another intervention - ***meaningful if this is the most effective treatment available (i.e. “gold standard”)

Answer 16

1. Primary - outcome investigators are most interested in - basis for ***hypothesis testing + sample size calculation 2. Secondary - additional outcomes of interest - associations are only ***hypothesis-generating as may have occurred by chance —> study may not have enough power to detect these associations —> interpret with caution - e.g. SE, differences by subgroups 3. Hard - defined according to ***objective criteria, involves ***no subjective assessment - usually preferred over soft outcomes - e.g. All-cause mortality 4. Soft - require subjective assessment by investigator / participants - potential ***information bias —> blinding is important - e.g. Cause-specific mortality 5. Patient-oriented - focus on helping patients live longer and better - ***preferred over disease-oriented outcomes - e.g. mortality, morbidity, QOL 6. Disease-oriented - focus on pathophysiological mechanisms / markers of disease - not preferred but ***easier to measure

Answer 17

Function: - Prevention / Diagnosis / Treatment Design: - Cluster vs Individual - Randomised vs Non-randomised - Parallel-group vs Cross-over - Superiority vs Non-inferiorly / Equivalence Objective: - Explanatory (efficacy) vs Pragmatic (effectiveness) - Phases 1 to 4

Answer 18

Superiority trials - aim to establish that a new treatment is BETTER than another - e.g. a new drug more effective than usual care Non-inferiority trials - aim to establish that a new treatment is NOT WORSE (not clinically inferior) than current / control treatment by more than a non-inferiority margin —> smallest difference in effect considered to be clinically important —> control treatment must be more effective than placebo - one-sided - Equivalence trials: 2-sided (new treatment is not better not worse than current treatment) - e.g. a new drug with similar effectiveness is safer, cheaper, easier to administer - conducted when new treatment is ***not expected to be better than control in terms of primary health outcomes, but may offer other benefits ***Non-inferiority is only shown if 95% CI for different between test and reference treatments are > -Δ (過左-Δ —> 代表同之前一樣; 過曬-Δ —> 差過之前) Non-inferiority: CI well below non-inferiority threshold Superiority: CI well above non-inferiority threshold

Answer 19

Explanatory (efficacy) trials: - Can treatment help under ***ideal circumstances (e.g. RCT)? - include highly selective and homogeneous patients who are adherent —> higher internal validity —> may have lower external validity / generalisability —> limitations: ***selection bias ``` Pragmatic (effectiveness) trials: - Can treatment help under ***ordinary circumstances? - done after efficacy is established - done in routine health care settings - include more diverse patients —> participants not followed as closely to ensure adherence —> ***higher external validity —> may have lower internal validity ```

Answer 20

Phase 1: - safety + dosage - 20-100 participants over several months - “is it safe in health people?” Phase 2: - efficacy + SE (i.e. explanatory trials) - several hundred participants over months - 2 years - “does it work?” Phase 3: - efficacy / effectiveness + adverse reactions (i.e. pragmatic trials) - hundred to thousands of participants over 1-4 years - “is it any better than current treatment?” Phase 4: - post-marketing surveillance of long-term benefits, risks - several thousand participants - “will it have any long term results?”

Answer 21

1. Confounding - ***Randomisation —> randomly distribute confounders in intervention / control groups 2. Selection bias - Healthy volunteer bias —> participants may be healthier than average patients —> need to note how ***sampling was done - Cherry-picking participants —> assign healthier participants to desired treatment group —> need to ensure ***allocation concealment - Attrition —> participants who drop out may not be representative of all enrolled participants —> need to note follow-up rates and whether ***intention to treat analysis was done 3. Information bias - ***Blinding 4. Practical limitations - time-consuming - cost - not feasible / ethical interventions

Answer 22

- Randomly distribute confounders in intervention / control groups - Bad examples: —> assignment based on day of admission (not random) —> assignment based on day of birth (not concealed) - Non-randomised studies: overestimate / underestimate effect of intervention - ***Check if baseline characteristics of participants are similar across groups —> if sample size is small —> baseline differences are even exaggerated —> significance tests of baseline differences (giving P values) may not be very useful Types of randomisation 1. Unrestricted (simple) randomisation - no constraints in generation of random allocation sequence (e.g. a table of random numbers) 2. Restricted randomisation - ensure particular allocation ratios to treatment groups (e.g. 1:1)

Answer 23

Meet strict criteria for participation Inclusion criteria: - diagnostic criteria to ensure patients have the condition under study - patients with unusual, mild / equivocal manifestations of disease may be excluded Exclusion criteria: - usually involve patients who have —> comorbidities that may affect outcomes —> limited life expectancy that may affect assessment of outcomes —> contraindications to treatment —> do not participant —> do not cooperate in early stages of trial However, problem of highly selective: - Limit ***external validity / generalisability Example of sampling: Sampled population —> Invited to participate —> Able to contact and agreed to participate —> Eventually randomised

Answer 24

Ensure investigators do not know / have no influence over which group participants are allocated to —> minimise selection bias Low risk of bias: - opaque sealed envelopes containing group assignment - central randomisation by a third party High risk of bias: - allocation based on day of admission - allocation sequence posted on staff room wall Inadequate allocation concealment yield ***larger effect estimates when differences in results did occur

Answer 25

Missing outcome data may: 1. Bias the observed effects - esp. when % missing differ across groups - patients who drop out / missing data may have worse prognosis 2. Reduce statistical power - esp. when % missing is high Attrition / Drop out because: - withdrawal (due to SE) - do not attend follow up (busy) - do not provide relevant data - cannot be contacted (migration / death) - later found to be ineligible - investigators ceased to follow up (inadequate funding)

Answer 26

Extent to which patients fail to follow treatment recommendations / take medications as prescribed Patient factors: illness, perceived benefits and risks Treatment factors: cost, complexity, duration, SE Other factors: poor doctor-patient communication Measuring adherence in clinical trials: - cheaper but less accurate —> self-report, diaries, pill counts, prescription refills, third party observations - more accurate but more costly —> measuring drug levels in plasma, directly observed therapy Dealing with non-adherence: 1. Exclude non-adherent patients during run-in period - patients given placebo and observed for adherence —> non-adherence patient then excluded before randomisation 2. Intention-to-treat analysis - analyse study outcomes in all participants according ***original assigned treatment group Advantages: - perserves randomisation (reduces confounding) —> provide more conservative estimate of effect —> selection bias may still exist if outcome data incomplete - more accurately reflects what happens in reality - ***different from per protocol analysis: include participants only if they received the intended intervention in accordance with the study protocol —> may ***overestimate treatment effect due to confounding (lose randomisation) —> may be done alongside ITT analysis to investigate influence of missing data

Answer 27

Keeping people unaware of which intervention is administered to which participants —> prevent ***information bias Done on various levels 1. Participants 2. Care providers 3. Assessors of outcomes (most important, always feasible) - non-blinded outcome assessors tend to ***overestimate effect of intervention Types of blinding 1. Single-blind, double-blind, triple-blind 2. Open-label —> usually assumes no attempt at blinding 3. Placebo-controlled —> usually assumes that participants are blinded Lack of blinding may have more influence on subjective outcomes than objective outcomes

Answer 28

Occur at different timeline Allocation concealment: Prevent ***selection bias Blinding: Prevent ***information bias

Answer 29

Consolidation of Standards of Reporting Trials - specifies content to be covered when reporting RCT e.g. Full trial protocol, to be repeated —> help us assess quality of reporting - consist of: 1. Checklist 2. Flow diagram (showing passage of subjects through RCT) - enrolment —> allocation —> follow-up —> analysis

Answer 30

- Only 1/3 medical practices = Beneficial / Likely to be beneficial - ~20% expenditure wasted on unnecessary diagnostic tests / treatments Overuse: interventions that yield little useful information Misuse: interventions that may be more harmful than beneficial Hospital: 1. Unsafe use of medication (Leading cause) 2. Healthcare-associated infections 3. Surgical complications Primary care: 1. Administrative errors 2. Diagnostic errors Combatting Overuse / Misuse: 1. Choose wisely 2. Prudent healthcare 3. NICE

Answer 31

Hospital-acquired infection: - Ventilator pneumonia - Wound infection - Decubitus ulcer (i.e. Bedsore) Operative / Post-op complications: - Complication of anaesthesia - Post-op sepsis - Post-op DVT Sentinel events: - Transfusion reaction - Wrong surgical site - Foreign body left Obstetrics: - Birth trauma Other care-related adverse effects: - Falls - Fractures

Answer 32

``` Structures - Resources and organisational arrangements in place that influence care —> Safety culture —> Inadequate Human Resources —> Stress and fatigue ``` ``` Processes - Activities of physicians and other providers of healthcare —> Misdiagnosis —> Poor test follow-up —> Inadequate measures of patient safety ``` Outcomes - Results / Consequcnes of clinical activities —> Adverse events due to medications —> Surgical complications Example: Adverse events to drug treatment 1. Health system level: - lack necessary information for safe use of drug - error-prone conditions: look-alike / sound-alike medication 2. Provider level: - lack of knowledge about drug - lack of follow-up - fail to recognise drug SE - fail to prescribe drug

Answer 33

1. Preventive - fail to provide prophylactic treatment - inadequate monitoring to follow-up 2. Diagnostic - delay in diagnosis - fail to use indicated tests - use of inappropriate tests - fail to act on test results 3. Treatment - error in administering drug - error in procedure / operation - delay in treatment - inappropriate treatment

Answer 34

- Little evidence that patient outcomes improved despite research - Investment in safety research is much lower than magnitude of problem - Medical errors are caused by faculty system, processes / conditions that lead people to make mistakes rather than result from individual recklessness

Answer 35

1. Respect for rights of individuals participants - informed consent - confidentiality - specific consideration for vulnerable groups 2. Minimising risk - measures in place to minimise risk 3. Research ethics committee - approve research protocol - monitor ongoing studies esp. adverse effects 4. Reporting and dissemination fo results - registration in publicly available database - full reporting and dissemination of results Ethical issues concerning patient safety research: 1. Subject may be system / healthcare provider rather than a patient 2. Tensions may arise between a researcher’s duty of care and aims of research 3. Liability of health care providers when health care failures are documented 4. Patient confidentiality 5. Dissemination of findings

Answer 36

Observational (e.g. Cohort studies): - Examine outcome without attempt to influence them —> too see Prognosis Interventional (e.g. RCT): - Modify an exposure and examine outcome —> measure effectiveness

Answer 37

``` Evidence summaries —> Systematic reviews / Meta-analysis —> RCT —> Cohort studies —> Case-control studies —> Expert option / Consensus —> Pathophysiologic reasoning ```

Answer 38

- Review of all available evidence on a specific topic - Apply ***Systematic, ***Explicit strategies that limit bias —> Assembly, Critical appraisal and Synthesis of evidence of all relevant studies —> provide more reliable evidence than individual studies —> identify gaps in existing evidence

Answer 39

Literature search, Selection of studies, Data extraction —> done by ***>=2 ***independent reviews to limit ***selection bias —> should declare conflicts of interests (financial / intellectual conflicts of interest) Steps: 1. Ask an answerable clinical question 2. Define inclusion + exclusion criteria 3. Develop search strategy + Identify relevant information sources - Search strategy: —> Determined by Eligibility criteria of studies for a specific research question —> PICO (Population, Intervention, Comparison, Outcome) —> Information sources: Databases (PubMed), Grey literature (Reports by government agencies), Bibliography —> Search terms: plus different combination —> Search filters: time period, language, document format 4. Select relevant studies 5. Extract relevant data 6. Explicitly and systematically assess quality (i.e. risk of bias) of individual studies: 7. Synthesise results from individual studies - Meta-analysis

Answer 40

Systematic review: - Systematic + Explicit methods to identify, appraise and synthesise evidence - 2 independent reviewers —> less selection bias - May involve Meta-analysis Narrative review (Summary review): - NO systematic / explicit methods to identify, appraise and synthesise evidence —> ***Uncertain validity - ***Content experts who pick and choose relevant studies —> ***prone to selection bias - NOT involve Meta-analysis

Answer 41

``` 1. Use Explicit criteria should include: - Confounding - Selection bias - Information bias ``` Checklists: - Jadad score —> evaluate ***quality of reporting of RCT (評核三方面) —> Randomisation —> Blinding —> Account of all withdrawals and dropouts - ***NOT include allocation concealment - Newcastle-Ottawa Quality assessment scale: —> for Case-control studies, Cohort studies —> Selection, Comparability, Exposure 2. Sensitivity analysis - to assess potential influence of studies at high risk of bias —> repeating analysis by excluding them - many arbitrary assumptions are involved in a meta-analyses: —> Case definitions —> Study designs —> Study quality —> Type of analysis etc. - involve testing of different assumptions —> ***robustness of findings to different assumptions suggests that results from the meta-analysis are valid

Answer 42

Reporting guidelines for research studies according to study design - recommend ***required reporting items for systematic reviews - can be used as a framework to evaluate ***quality of reporting 1. PRISMA: systematic reviews - Identification - Screening - Eligibility - Included 2. CONSORT: RCT 3. STROBE: observational studies 4. STARD: diagnostic / prognostic studies 5. AGREE: clinical practice guidelines

Answer 43

When dissemination of research findings is influenced by nature of direction of results 1. Publication bias —> positive results more likely to be published 2. Time lag bias —> positive results published sooner 3. Language bias —> English studies more likely found 4. Citation bias —> positive results more likely to be cited 5. Selective outcome reporting bias —> outcomes with favourable associations more likely to be reported 解決方法: Funnel plot

Answer 44

Scatter plot of ***effect estimates (OR, RR) from individuals studies against ***measure of study size - Dotted vertical line: Combined effect - Solid vertical line: Null effect - Diagonal lines: Triangular region with which 95% of studies are expected to lie without bias / heterogeneity Precision of effect estimate ***↑ with larger sample sizes - smaller studies scatter more widely around bottom of funnel - “small-study effect”: tendency for smaller studies to show larger effects Interpretation: Plot should be symmetrical in the absence of bias / heterogeneity between studies —> 越高(越大sample size) —> 結果(effect estimate)應該越中庸之道 —> 三角形 —> scatter of studies only due to ***sampling variation * **Asymmetry could be due to 1. ***Reporting bias 2. ***Heterogeneity 3. Chance —> statistical tests (e.g. Egger test) help to determine likelihood Funnel plot ONLY suggest potential biases but do NOT address them

Answer 45

Statistical method to ***quantitatively ***combine results from individual studies - Usually a ***weighted average of estimates from individual studies Increase overall ***statistical power of individual studies —> increases chance of detecting small but potentially important effects Should only be done when studies are reasonably ***homogeneous (i.e. results from individual studies are reasonably similar / consistent)

Answer 46

- Graphical summary of results from individual studies and meta-analysis - Aid in ***identification of heterogeneity - Solid vertical line: Null line - Horizontal line: 95% confidence interval - Square: —> Centre: ***Mean effect —> Size: Proportional to ***% weight of study - Diamond (Only一粒): ***Combined result —> Centre + Dotted vertical line: ***Pooled estimate —> Horizontal tips: ***95% confidence interval How to identify heterogeneity: —> Use statistical tests —> when there is poor overlap of confidence intervals 1. I^2 statistic - estimated proportion of variability that is explained by heterogeneity rather than sampling variation - ***I^2 >30-40% usually suggests significant heterogeneity 2. Cochran’s Q (Chi^2) statistic - weighted sum of squared differences between individual study effects and pooled effect - has low power; ***P value <0.1 suggests significant heterogeneity 3. ***Identify potential sources of heterogeneity

Answer 47

1. Clinical diversity - variability in participants, interventions, outcomes studied 2. Methodological diversity - variability in study design / risk of bias

Answer 48

1. Meta-analysis may not be appropriate when studies too heterogeneous —> combined estimate not a meaningful representation of studies 2. ***Random effects model in meta-analysis —> assumes that there are different underlying effects between studies other than sampling variation —> Fixed effect model: assume that one true effect underlie all studies and that all differences in observed effects are due to sampling error (does not account for heterogeneity between studies)

Answer 49

Strengths: 1. Increase statistical power of individual studies to detect small but important effects 2. Explicit and more objective summary of evidence compared to narrative reviews Limitations: 1. Limited by quality of individual studies 2. Reporting biases 3. Meta-analysis may not be appropriate when studies are too heterogenous

Answer 50

1. Relevance: - PICO 2. Validity: - study design —> Observation / RCT - study conduct —> Search strategy, Selection bias, Validity / Risk of bias (Confounding, Selection bias, Information bias), Reporting bias (Asymmetry), Meta-analysis (Heterogeneity) - study results —> Statistically significant, Clinically significant, STEPS, Conflict of interest STEPS: 1. Safety 2. Tolerability 3. Effectiveness 4. Price 5. Simplicity