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Non-compliance in randomised controlled

trials comparing vascular and endovascular

interventions for cardiovascular care

2nd CUTEHeart Workshop

Manuel Gomes

April 23, 2016

• Non-compliance in RCTs – cardiovascular care

• Defining the question of interest

• Specific challenges in HTA

• Methods for handling non-compliance

• Results from the IMPROVE trial

• Discussion

Overview

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Non-compliance in RCTs

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• Patients often do not comply with their randomised treatment:– Switch to other randomised arm (treatment switching)

– Change to non-trial treatment

– Stop receiving treatment altogether

• Reasons– Intervention not suitable (randomisation happens before assessment)

– Patient is responding poorly to their allocated treatment (unethical)

– Patient’s disease progresses and requires alternative treatment

– Clinical expert is more familiar with particular intervention

• Problem– Non-compliance is usually related to individual characteristics and

prognosis, and can lead to misleading inferences.

High levels of non-compliance

in cardiovascular trials

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• Drug therapies for treating patients with coronary heart disease– Uncertainty about the benefits of statins; perceived adverse effects

• Medication/diet for treating patients with chronic heart failure– Complicated drug regimens; difficulties in changing lifestyle

• Cardiac rehabilitation programmes– Low levels of physical activity; pain/depression/anxiety

• Surgical interventions (emergency setting)– Surgeon’s expertise; other clinical indications

Motivating example

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IMPROVE trial

• Aim: to compare a preferential endovascular strategy (EVAR) with emergency Open Repair for the management of suspected ruptured abdominal aortic aneurysm (AAA)

• Pragmatic RCT (EVAR: n=316; Open repair: n=297)– Randomisation happens before CT scan

– EVAR to Open Repair switch (42%); e.g. surgeon expertise

– Open Repair to EVAR (12%); e.g. not fit for general anaesthesia

• Cost-effectiveness outcomes (1-year)– Overall mortality (life – years)

– Quality of life (EQ-5D) at 3 and 12 months

– costs

Defining the question

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Clinically relevant:

1. De jure questions (efficacy):

• What are the relative benefits of actually receiving the interventions?

– How do EVAR and Open Repair compare, if patients had been operated as per clinical indication (e.g. after CT scan)

2. De facto questions (effectiveness):

• What is the relative effectiveness of a policy/strategy to provide EVAR?

– Under the conditions of the trial

– In other circumstances (if practice differs from trial setting)

Policy-relevant:

• What’s the decision problem?

– Which hospitals should patients with suspected ruptured AAA be sent to?

– Is a strategy to provide EVAR a good use of resources?

HTA-specific challenges

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• Decision makers require an assessment of the relative effectiveness and cost-effectiveness over a long-period of time– Clinically-relevant outcomes such as progression-free survival raise less

concerns about non-compliance, but are insufficient for decision making

• Levels of non-compliance may not be representative of those seen in practice

• Differences in costs often depend on intervention receipt, not on the intention to receive treatment– Drug trial: expensive drug is prescribed but may not always be taken

• Added complexity for analysis– E.g. correlations between the multiple outcomes

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Simple approaches

• Per-protocol analysis– Non-compliers are excluded (or censored at the time of switching)

– Breaks the randomisation balance and likely to introduce selection bias

• Intention-to-treat (ITT) analysis– Provides an unbiased treatment effect (to de facto questions); preserves

the randomisation design

– But tends to underestimates the ‘true’ treatment effect (e.g. ‘control’ patients may benefit from treatment)

• When is ITT insufficient?– The causal effect is of interest (e.g. efficacy)

– The level of compliance is not typical of that seen in practice

– Sensitivity analysis (recent NICE decisions differed according to method)

Handling non-compliance

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Randomisation-based methods: Instrumental variable (IV) estimation

Randomised treatment (Z)

Outcome (Y)Treatment

received (D)

Unobserved factors (U)

ITT estimates

- Patient underlying health status

- Surgeon ability- Centre context- …

Causal effect

Criteria for instrument- Strongly predicts D- Independent of U- Only affects Y via D

(Complier-Average) Causal Effect = ITT / 𝜶 (Wald estimate)

𝜶

IV methods

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Continuous outcomes (e.g. quality of life, costs)

- 2-stage methods (2SLS)- Stage 1: Regress D on Z

- Stage 2: Regress Y on the predicted D (Variance needs to be corrected)

- Likelihood-based methods (LIML, full-Bayesian analysis)- Joint estimation of the outcome and treatment models

- Usually assumes multivariate Normality

- Semi-parametric approaches (GMM, G-estimation)- Relaxes assumptions about error distribution and model specification

IV methods

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Limitations

- Survival outcomes (e.g. overall survival)

- Cox regression could be used (stage 2), but resulting estimates may differ from population-average hazard difference (marginal ≠ conditional effect)

- Rank-preserving structural failure time models: use randomisation to estimate counterfactual survival times, but assumes common treatment effect

- Multiple switches– Marginal Structural models: Compliers are re-weighted by the inverse of the

probability of being censored (switch treatment) at each time point

– Rely on the ‘no unobserved confounding’ assumption; i.e. non-compliance is independent of unobserved factors

- Clustered designs (e.g. cluster trials)- In principle, hierarchical approaches (ML) can be used, but properties unknown

IV methods

IMPROVE trial results

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1-year effectiveness and cost-effectiveness of EVAR vs Open Repair according to method

ITT estimate Complier-average

causal effect

Mortality (OR) 0.86 [0.62, 1.21] 0.65 [0.28, 1.51]

EQ-5D at 3 months 0.073 [0.007, 0.138] 0.193 [0.033, 0.352]

EQ-5D at 12 months 0.043 [-0.024, 0.110] 0.184 [0.009, 0.358]

Incremental QALY 0.053 [-0.008, 0.113] 0.138 [-0.004, 0.280]

Incremental cost (£) - 2329 [-5489, 922] - 4731 [-12967, 3504]

Incremental net-benefit (£) 3877 [253, 7408] 8871 [-393, 18 135]

• Non-compliance is a major issue in clinical trials of cardiovascular interventions

• Defining the question beforehand is crucial (does ITT answer it?)

• HTA raises additional challenges for design/methods of analysis

• IV methods promising - randomisation is a valid instrument

• Consider sensitivity analysis to departures from identifying assumptions

Discussion

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