PHRM3031 interventions RCTS I/II

Question 1

Study Types

Answer 1

Experimental - RCT

Observational - cohort (longtudinal), case-control, cross-sectional, ecological (population-based)

Question 2

Study Types & their questions

RCT

Answer 2

interventions

Question 3

Study Types & their questions

Cohort

Answer 3

Aetiology
Prognosis
Diagnosis
Risks

Question 4

Study Types & their questions

Case Control

Answer 4

Prognosis
Diagnosis
Risks

Question 5

Study Types & their questions

Cross Section

Answer 5

Aetiology
Diagnosis
Frequency

Question 6

Study Types & their questions

Case Reports

Answer 6

Next Steps

Question 7

Which Study is best for:

Intervention/Therapy

Answer 7

RCT

Question 8

Which Study is best for:

Diagnosis

Answer 8

Cohort>Case-Control>cross-sectional

Question 9

Which Study is best for:

Risk, prognosis

Answer 9

cohort>case-control

Question 10

Which Study is best for:

aetiology

Answer 10

cohort>cross-sectional

Question 11

Which Study is best for:

frequency

Answer 11

cross-sectional

Question 12

Which Study is best for:

observational

Answer 12

qualitative

Question 13

Cross Sectional Study

Answer 13

• the study population is ascertained at one point in time - a snap shot
• participants are asked about their current disease status (outcome) and their current and past treatments (exposure)

Question 14

Case Control Study

Answer 14

-compares disease outcomes in cases and controls
Cases: patients with a particular disease outcome
Controls: have similar attributes (age, sex, ses) to the cases but do not have the disease

Question 15

Cohort Study

Answer 15

Cohort: a group of individuals with a common characteristic
Cohort Study: cohrts are followed up (observed) over time
Aim –> is exposure to a risk factor associated with new disease outcome in the future

Question 16

Prospective Study

Answer 16

observe outcomes or events that occur after identification of subjects
-RCTs, cohort or longitudinal studies

Question 17

Retrospective Study

Answer 17

review records from the past or obtain information about past events
-case-controls studies

Question 18

Randomised Controlled Trial (RCT)

Answer 18

• a sample of patients are selected from the population with a particular condition
• patients are randomised into the treatment group or the control group
• the two groups are treated in exactly the same ways in everything apart from the treatment
• clinical measures are made over time and any differences are attributed to the intervention

Question 19

Critical Appraisal -definition

Answer 19

• structured summary
• are the results of the study valid?
• what are the clinically relevant results?
• will the results help care for my patient?

Question 20

Critical Appraisal - Design

Answer 20

Parallel - common, patients are randomised to either group A or group B at the start of the study and the patient receives the assigned medication for the duration of the trial
Cross-over - fairly rare, patients are randomised to either group A or group B at the start the study and midway through the study, are swapped to the other group
Factorial - rare, sometimes used when interactions between various drugs are to be investigated

Question 21

Assessing Bias: Seven Questions

Answer 21

1. were patients randomised?
2. was group allocation concealed?
3. were groups similar at baseline (start of trial)?
4. were participants, health professional and study personnel blinded to group allocation?
5. were all participants who entered the trial properly accounted for at it conclusion and how complete was follow-up?
6. Aside fro the experimental intervention, were the groups treated equally?
7. were patients analysed in the groups to which they were first allocated?

Question 22

Randomisation: defintion

Answer 22

• process by which patients in a clinical trial are allocated to a group
• assignment is according to chance rather than any systematic approach
• randomisation tables, often computer generated
• patients have an equal chance of being assigned to either group (treatment or control)
• does not mean that the treatments are evenly allocated to all patients

Question 23

why randomise?

Answer 23

• aims to ensure that the control and intervention groups are as similar as possible
• known prognostic factors (such as age, weight, gender)
• unknown factors (cofounder eg. adherence, genetics, socioeconomic status)
• -> reduces the chance of representation of any one characteristic with the study groups

Question 24

randomisation levels

Answer 24

simple: at level of patient
cluster - intact clusters of individuals
stratified - participants are grouped into ‘blocks’ and the allocated to treatment groups; often uses stratification

Question 25

baseline characteristics

Answer 25

the treatment and the control group should be similar for all prognostic characteristics except for treatement

Question 26

blinding

Answer 26

-concealing the treatment status from the patient, investigators or analysts -used to guard against bias on the part of investigators or subjects when assessing or reporting the outcome of treatment Four Types: -single -double -triple -open label (non blinded)

Question 27

single blind

Answer 27

- the investigator, but not the patient, knows the identity of the assigned treatment - can be subject to investigator bias

Question 28

double blind

Answer 28

neither the investigator nor the patient knows the identity of the assigned treatment

Question 29

the ultimate triple blind

Answer 29

no one knowns what is going on | -most rigorous but least commonly performed blinding

Question 30

non blinded studies

Answer 30

- open label design - both the investigator and the patients know the identity of the assigned treatment - used when blinding is not possible (eg surgery, radiotherapy, diet) - subject to bias by patients and investigators and so there is a greater chance of seeing a positive result

Question 31

power of a trial

Answer 31

power is the ability to detect a difference between two groups when a difference actually exists - type I (alpha) error: is the detection of a difference when a difference does not exists (false positive) - Type II (beta) error: is the inability to detect a difference when a difference actually exists (false negative)

Question 32

data analysis

Answer 32

may be either: 1. according to the treatment to which patients were randomised 2. according to the treatment actually received

Question 33

analysis by randomisation

Answer 33

treatment the patient ws randomised to --> 'intention to treat' analysis evaluates medicine effectiveness: how the medicine work when people take it in an (almost) ordinary setting

Question 34

analysis by actual treatment

Answer 34

analysis is according to the treatment actually receive | evaluates medicine efficacy: doe the medicine work when it taken exactly as prescribed?

Question 35

size of effect

Answer 35

best estimate is the difference in means (or medians if reported) between the intervention and control group

Question 36

clinical vs statistical significance

Answer 36

clinical significance: the size of the effect is real (i.e) statistically significant) and that it is of a magnitude sufficient to change practice or to be considered clinically important statistical significance: the size of the effect and the 95% CI in relation to the null hypothesis (usually <5% error rate) trials can be statistically significant but not clinically significant

Question 37

P values

Answer 37

-measures of the probability that a result is purely due to chance a low p-value suggests that chance is an unlikely cause of the observed difference between groups if the p-value is love (p<0.05) then the probability that the result was due to chance is also low (<5%) --> a statistically significant effect

Question 38

Confidence Intervals (CIs)

Answer 38

-generally more informative than p-values -estimates of the range of values that are likely to include the real value usually quotes as 95% CIs -if the 95% CI for the difference between a treatment and control group is small and does not overlap the 'no effect' point(1 for a ratio an 0 for a difference) we are confident that the result is real

Question 39

Absolute Risk (INE)

Answer 39

AR (NE) absolute risk (incidence) of events in control (not exposed) group (%)

Question 40

Absolute Risk (IE)

Answer 40

AR (E) absolute risk (incidence, I) of events in treatment (exposed, E) group (%)

Question 41

Relative Risk (RR) - definition - formula

Answer 41

- tell us how many times more (or less) likely an event will occur in the treatment (exposed) group relative to the control (non-exposed) group - RR=ARe/ARne - RR=1 means no difference between the two groups - RR<1 means the treatment reduces the risk of the event - RR>1 means the treatment increases the risk of the events

Question 42

Relative Risk Difference (RRD) RRI - increase RRR - reduction (formula)

Answer 42

RRD = (ARne-ARe)/ARne | or (1-RR)

Question 43

Absolute Risk Difference (ARD) - definition - formula

Answer 43

-tells us the absolute difference in the rates of events between the two groups (treatment difference) ARD=ARe-ARne -ARD=0 means that there is no difference between groups (i.e treatment had no effect)

Question 44

Number needed to treat (NNT) - definition - formula

Answer 44

-is the number of patients that need to be treated (compared to the control group) for a period of time to prevent one extra event of interest NNT=(1/ARD)x100 Clinical outcome

Question 45

Number needed to harm (NNH) - definition - formula

Answer 45

-is the number of patients that need to be treated (compared to the control group) for a period of time to cause one extra event of interest NNH=(1/ARD)x100 safety outcome

Question 46

``` Summary Ratings Green Yellow Red Black ```

Answer 46

Green - therapies rated green are best you can get- there is clear evidence of patient-important benefits and these benefits clearly out-weigh any associated harm Yellow - these therapies require more study. the data is inconclusive or not substantial enough to be able to give a clear rating yet. these would benefit from a large, randomised controlled trial to give better sense of effect and harms Red - benefits and harms may be equal or equivocal, while there may be some benefits the benefits dont outweigh the harms Black - harms without benefits, these therapies have very clear harms to patients without any recognisable benefit

Question 47

Time to event analysis

Answer 47

-survival analysis -event= dichotomous clinical outcomes that can occur only once -outcomes may be negative (death), positive (still alive) or neutral (start glucose monitoring etc) -use the term 'survival' regardless of the type of outcome and whether it is related to survival time periods can . be continuous (months) or categorical (0-6 months)

Question 48

2 methods of analysing survival curves

Answer 48

1. kaplan-meier - compares two groups using log-rank test (expected vs observed) 2. cox-proportional hazards - cuts period o observation into small intervals, in each interval, compare rate of events (taking into account numbers of events in the intervals and number of person at risk in the interval) --> a relative risk - combines all the estimates of relative risk --> hazard ratio - can consider effects of variables (eg. gender, age, smoking)