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. 2022 May 24;31(Suppl 1):44–72. doi: 10.1002/hec.4524
Attribute Level Interpretation
Scenario 1: new drug therapy for management of neuromuscular symptoms of a metabolic myopathy
Question 1. Based only on the information provided so far in this scenario, would you consider that this is an acceptable (i.e. valid) surrogate for predicting changes in patient health‐related quality of life?
Source of evidence for the validation of the surrogate endpoint A meta‐analysis of several RCTs Stronger evidence
A large observational study Weaker evidence
Class of therapies providing evidence for the validation of the surrogate endpoint The same neuromuscular symptoms originated by metabolic myopathy The same class
The cardiac symptoms originated by metabolic myopathy A different class
Strength of association between the surrogate and patient‐relevant endpoint R 2 = 0.30 (95% confidence interval [0.20, 0.40] Weaker association
R 2 = 0.85 (95% confidence interval [0.77, 0.93] Stronger association
Surrogate threshold effect (i.e. the minimum effect on the surrogate to predict a significant effect on the patient‐relevant endpoint) −0.10 ng/ml (observed in about 70% of the studies in the indication) Lower STE
−0.90 ng/ml (observed in about 20% of the studies in the indication) Higher STE
Scenario 1 Question 2. Based solely on the data presented so far, would you support the full coverage of this therapy?
Disease prevalence One in 100,000 Lower prevalence
One in 1000 Higher prevalence
Baseline utility score (on 0–1 scale) 0.30 More severe disease
0.60 Less severe disease
Comparator (i.e. therapeutic alternatives) Best supportive care (i.e. there is no alternative) No alternative
Off‐label treatment with a pharmaceutical indicated for heart failure Existing alternative therapy
Effect on the final outcome at 18 weeks based on immature data Improvement, although not statistical significance (p = 0.10) Positive trend
Deterioration, although not statistical significance (p = 0.10) Negative trend
Scenario 2: new medical device for the treatment of resistant hypertension
Question 1: Based only on the information provided so far in this scenario, would you consider that this endpoint is an acceptable (i.e. valid) surrogate for predicting changes in the risk of stroke?
Source of evidence for the validation of the surrogate endpoint A meta‐analysis of several RCT Stronger evidence
A single RCT Weaker evidence
Class of therapies providing evidence for the validation of the surrogate endpoint Antihypertensive medication The same class
A non‐pharmaceutical technology in the same indication A different class
Strength of association between the surrogate and patient‐relevant endpoint 0.30 (95% confidence interval [0.20, 0.40]) Weaker association
0.85 (95% confidence interval [0.77, 0.93]) Stronger association
Surrogate threshold effect −4 mm Hg (observed in about 70% of the studies in the indication) Lower STE
−10 mm Hg (observed in about 20% of the studies in the indication) Higher STE
Scenario 2 Question 2: Based solely on the data presented so far, would you support the full coverage of this medical device?
Disease prevalence One in 11 hypertensive patients Higher prevalence
One in 1500 hypertensive patients Lower prevalence
Baseline utility score (on 0–1 scale) 0.57 Less severe disease
0.79 More severe disease
Comparator (i.e. therapeutic alternatives) No treatment reimbursed for resistant hypertension No alternative
Another treatment reimbursed for resistant hypertension Existing alternative therapy
Effect on the incidence of cardiovascular events based on immature data Appearing to favor the intervention Positive trend
Appearing to favor the control Negative trend

Note: R 2 = coefficient of determination, the proportion of the variance in the final endpoint that is predictable from the surrogate endpoint; RCT = randomised controlled trial; STE = surrogate threshold effect = the minimum treatment effect on the surrogate endpoint necessary to predict a non‐zero effect on the final endpoint.