RCT

Prof. dr. Davor Eterović

EBM-2011/Klinička biostatistika

RCT

• T –pokus dokazuje kauzalnost

• C –kontrola male učinke razlučuje od nule, veće mjeri ...

• R - …bez omaški zbog randomskog usklađivanja

RCT: vrline i mane• Najjači dizajn (najpouzdaniji zaključci)• Nezamjenjiv za male, ali važne efekte ali ponekad i• Teško provodiv, kompliciran, skup • Etički dvojben • Dvojbene primjenjivosti na praksu (netipični bolesnici, netipični

tretmani, preintenzivno praćenje) Zbog toga:• Zahtijeva pilot pokus i detaljan protokol: obrazložena hipoteza,

plan izvođenja i analize podataka i • Hipoteza valja biti vrlo vjerojatna (etički problem kontrola kod

teških ishoda; alternativa- nekontrolirani pokus)• Većinom ne otkriva novo, već potvrđuje/precizno evaluira,

slijedi nakon opservacijskih istraživanja/nekontroliranih pokusa

Kako generirati slijed pridruživanja

• Jednostavna randomizacija (generator slučajnih brojeva)

• Korištenje blokova zbog podjednakih skupina

• Eksplicitna kontrola kovarijabli: stratifikacija ili minimizacija

Kako ne devalvirati randomizaciju

1. Zatajivanje pridruživanja (allocation concealment)- meta analize: vrlo važno, uvijek moguće

2. Maskiranje ispitanika, medicinskog osoblja, statističara; nekad nije moguće

3. ITT (intention-to-treat) analiza, žrtvuje se eventualni lažno negativan rezultat da se ne naruši randomska usklađenost; za nuspojave ne, već- PP (per protocol) analiza

Faze izvođenja RCT

Nakon planiranja (pilot pokusa) i dobivanja dopuštenja

1. Izbor ispitanika2. Mjerenje karakteristika3. Randomizacija4. Intervencija5. Praćenje (evaluacije) ishoda, mjerenja Slijedi izvješće, po strogim pravilima (CONSORT)

Kako izvijestiti rezultate RCT (1)

• CONSORT guidelines

1. Dijagram toka

2. Karakteristike ispitne i kontrolne skupine: tablica 1. + komentar uspjeha randomizacije, razlike ne testirati formalno (no p-values in table 1!)

3. Tablica 2: Jednostavni, neposredni rezultati ITT analize glavnih ishoda (x+-95%CI)

4. Ako je suradljivost bila slaba i (ili) varirala između skupina, ili ako je bilo dosta izgubljenih podataka, prikaži i PP rezultate

Kako izvijestiti rezultate RCT (2)5. Ako randomizacija nije perfektna, prikaži i usklađene

rezultate: (a) kontinuirane varijable: ANOVA, multipla regresija (b) kategorije: Mantel-Haenszelov test (jedna

kovarijabla) ili logistička regresija (više kovarijabli), Poissonova regresija (za stope), Coxova regresija (preživljenje)

6. Ako su planirane/opravdane, prikaži i analize po podskupinama

7. Prikaži nuspojave i neželjene učinke (bez formalnog testiranja; PP prikaz)

8. Analiziraj i (eventualne) sekundarne ishode

Simple 2-arm trial

• Patients are randomised to study or control group

Study population

Study Control

(50%) (50%)

• Can have n:m rather than 1:1 allocation– E.g. 2:1 active:control

Why extend simple 2-arm RCT?

• #1: Compare >1 intervention– May be the ‘more’ ethical design – Can be cheaper to do 1 trial investigating 2 interventions

than two separate trials

• #2: simple RCTs exclude those patients with strong preferences– With a chance of getting 1 of 2 interventions more subjects

may be willing to be randomised– With data on those unwilling to be randomised the trial may

be more generalisable

• #3: Contamination of treatment effects?– So instead of randomising a patient, randomise a family, or a

GP surgery, or a hospital – cluster randomisation

RCTs for more than one intervention

• Multi-arm trials

• Factorial designs

• Crossover designs

Multi-arm trial

• Simplest extension to simple RCT

• Patients randomised to two or more study groups or control group

Study population

Intervention 1 Intervention 2 Control

(33%) (33%) (33%)

Multi-arm trial (2)

Advantages:• still simple to design• allows head to head

comparisons

Disadvantages:• requires a larger

overall sample size to achieve the same level of power

• Multiple comparisons• rarely have power to

detect significant differences between the interventions

Factorial design (1)

• Compares more than one intervention

• Multiple layers of randomisation

• Notation:– 2x2 - indicates 2 trts each with 2 levels– 2x2x2 - indicates 3 trts each with 2 levels

• Fractional factorial designs– Many treatments, patients get a selection

Factorial design (2) - 2x2 example

• Vitamin D and/or calcium supplementation to prevent re-fracture (RECORD)

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Factorial designs (3)

Advantages:

• reduced loss of power compared with multi-arm trial

• very efficient - ‘two trials for the price of one’

• allows possibility of exploring interaction effects

Disadvantages:

• requires no interaction between treatments for full power*

• more difficult to operationalise

* There are however studies with a factorial design which specifically anticipate an interaction

Crossover trials

• Useful when studying patients with a chronic (long-term) disease

• Allows patients to receive both treatments sequentially – “patient acts as their own control”

A

B

First period B

A

Second period

Crossover trial - example

• Renal dialysis - each patient receives dialysis 3 times a week

• Two types of dialysis solution available - acetate and bicarbonate

• Thought that bicarb may reduce nausea and other symptoms

• Crossover trial:– each patient does a month on one solution followed by

month on the other– for each patient, the starting solution is assigned randomly

Crossover trials

Advantages:

• requires fewer patients as each get both treatments

• background “noise” reduced as comparison is within-patient

Disadvantages:• must be no “carryover”

effect– Washout periods– > 2 periods?

• Loss to follow up • can only be used for short

term outcomes e.g. symptom control

• requires chronic and stable illness - patients require same level of illness for both treatments

Why extend simple RCT - reason 2

• Some RCTs compare very different treatments eg surgery vs. long term medication

• Patients with strong preferences not willing to be randomised

• Simple RCTs have to exclude those patients

Patient preference trials

• If patients have a strong preference for a therapy they get that therapy

• If no strong preference, patients randomised

• Primary analysis still based on randomised groups

• Two studies – a randomised study and an observational study

Patient preference trial - example

• Two treatments for reflux disease:– medical management– surgical management

• Four trial groups:– prefer surgery– prefer medical – randomised to surgery– randomised to medical

Patient preference trials

Advantages:• recruitment maximised• motivational factors

maximised in the preference groups

• motivational factors equalised in the randomised groups

• results potentially more generalisable

Disadvantages:• harder to analyse

and possibly to interpret

• may be unequal distribution across the four trial groups

• more complex informed consent

Why extend a simple RCT - reason 3

• There is a worry that there will be contamination of treatments across patients eg trial comparing two dietary interventions - what if 2 members of same family randomised to different diets?

• Potential solution - randomise intact groups (families) rather than individuals

Cluster randomised trial

• Intact groups (known as clusters) rather than individuals randomised to each intervention

• Unit of randomisation should minimise risk of contamination eg family, practice, hospital ward

A cluster RCT

Control Experimental

Cluster trials - issues

• Outcomes within a group of patients, or cluster, may be more similar than those across clusters - they are no longer ‘independent’

• A statistical measure of this similarity within clusters is the intra-cluster correlation

• Because patients not independent, study loses power

• The larger the intra-cluster correlation the larger the inflation required to the sample size to redress the loss of power

Cluster trials

Advantages:• minimises

contamination between groups

• may be easier to organise practically

Disadvantages:• requires larger trial• patients within

clusters not independent

• standard analysis techniques not appropriate

• analysis more complex

Different model for randomisation (1)

• Standard procedure - get informed consent then randomise

• Potential problems:– patients may withdraw if they do not get the

treatment they hoped for– patients may comply poorly if they get the

control treatment - thinking the experimental treatment is better anyway

Different model for randomisation (2)

• Alternative approach - Zelen’s design:

– randomise before obtaining consent– only seek consent from those randomised to

experimental treatment– ‘control’ patients not approached for consent

• Debate surrounds ethics of this approach - eg MRC do not accept this design as ethical

Zelen’s design

Advantages:• does not raise hopes

of a new treatment which can then be denied by randomisation

• may avoid downward bias in those allocated to ‘control’

Disadvantages:• ethics are debateable