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Ophthalmic Statistics Note 4: analysing data from randomised controlled trials with baseline and follow-up measurements.

Nash R, Bunce C, Freemantle N, Doré CJ, Rogers CA, Ophthalmic Statistics Gro - Br J Ophthalmol (2014)

View Article: PubMed Central - PubMed

Affiliation: Clinical Trials and Evaluation Unit, School of Clinical Sciences, University of Bristol, Bristol Royal Infirmary, Bristol, UK.

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In clinical trials, continuous outcomes, such as intraocular pressure and visual acuity, are often measured both before treatment (ie, at baseline) and after treatment... Analysing change scores (ie, the difference between the post-treatment measurement and baseline measurement for each participant)... The post-treatment measurements or change scores (methods (2) and (3)) would typically be compared using a two-sample t test... The 95% CI tells us that we are 95% confident that the difference in mean BCVA is somewhere between 4.8 letters in favour of ranibizumab and 1.4 letters in favour of bevacizumab... The mean difference between the two drugs (1.1 letters) is the vertical distance between the two parallel lines... In this example, all three methods led to the same conclusion, namely that mean BCVA at 24 months was similar between the two drugs... Further efficiency was then gained using the more flexible ANCOVA model compared to the analysis of change scores (SE 1.21 vs 1.25 letters, 95% CI (−3.4 to 1.3) vs (−3.3 to 1.6))... While in this example all three methods led to the same conclusion, it is possible for different models to yield estimates that might lead to different conclusions... If, for example, the more precise estimate had had a CI which excluded zero, while the less precise estimates did not, we might infer evidence of a treatment effect from one model only... This would test the hypothesis that the change from baseline is zero separately for each treatment group... The estimates obtained would give the mean change from baseline in each group, with a corresponding 95% CI, but we would not be able to draw a conclusion about, or quantify the difference between, the two drugs... If we were to perform two paired t tests on our data, we would conclude that there was a significant improvement in BCVA with both ranibizumab and bevacizumab, with a mean improvement of 4.9 letters (95% CI 3.1 to 6.7) and 4.1 letters (95% CI 2.4 to 5.8), respectively... Approaches include omitting the cases with missing data, which is an inefficient use of the data, reducing precision and power; imputing the missing values, which must be done with care; and fitting a more sophisticated model where the baseline and post-treatment measurements are modelled ‘jointly’, which allows participants with partial missing data to be included.

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Baseline and post-treatment Best Corrected Visual Acuity (BCVA) for the subset of patients with a post-treatment BCVA of more than 50 letters (n=425 patients). The estimated difference in mean BCVA between the two drugs groups from the analysis of covariance is the vertical distance between the two regression lines shown on the plot.
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BJOPHTHALMOL2014305614F1: Baseline and post-treatment Best Corrected Visual Acuity (BCVA) for the subset of patients with a post-treatment BCVA of more than 50 letters (n=425 patients). The estimated difference in mean BCVA between the two drugs groups from the analysis of covariance is the vertical distance between the two regression lines shown on the plot.

Mentions: This is the preferred method of analysis. Here, we are estimating the difference in the mean BCVA between the two groups, again taking account of how good the participant's vision was at the start of the trial, but relaxing the restriction on the relationship between baseline and post-treatment measurements. From the results, we would conclude that BCVA improved by an estimated 1.1 letters more, on average, in the ranibizumab group than in the bevacizumab group, with a 95% CI from 3.4 letters in favour of ranibizumab to 1.3 letters in favour of bevacizumab. As with the other two models, there is no suggestion of a difference between the groups because the CI includes zero. The estimated relationship between the baseline and post-treatment measurements for each drug is illustrated in figure 1. The mean difference between the two drugs (1.1 letters) is the vertical distance between the two parallel lines.


Ophthalmic Statistics Note 4: analysing data from randomised controlled trials with baseline and follow-up measurements.

Nash R, Bunce C, Freemantle N, Doré CJ, Rogers CA, Ophthalmic Statistics Gro - Br J Ophthalmol (2014)

Baseline and post-treatment Best Corrected Visual Acuity (BCVA) for the subset of patients with a post-treatment BCVA of more than 50 letters (n=425 patients). The estimated difference in mean BCVA between the two drugs groups from the analysis of covariance is the vertical distance between the two regression lines shown on the plot.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4215292&req=5

BJOPHTHALMOL2014305614F1: Baseline and post-treatment Best Corrected Visual Acuity (BCVA) for the subset of patients with a post-treatment BCVA of more than 50 letters (n=425 patients). The estimated difference in mean BCVA between the two drugs groups from the analysis of covariance is the vertical distance between the two regression lines shown on the plot.
Mentions: This is the preferred method of analysis. Here, we are estimating the difference in the mean BCVA between the two groups, again taking account of how good the participant's vision was at the start of the trial, but relaxing the restriction on the relationship between baseline and post-treatment measurements. From the results, we would conclude that BCVA improved by an estimated 1.1 letters more, on average, in the ranibizumab group than in the bevacizumab group, with a 95% CI from 3.4 letters in favour of ranibizumab to 1.3 letters in favour of bevacizumab. As with the other two models, there is no suggestion of a difference between the groups because the CI includes zero. The estimated relationship between the baseline and post-treatment measurements for each drug is illustrated in figure 1. The mean difference between the two drugs (1.1 letters) is the vertical distance between the two parallel lines.

View Article: PubMed Central - PubMed

Affiliation: Clinical Trials and Evaluation Unit, School of Clinical Sciences, University of Bristol, Bristol Royal Infirmary, Bristol, UK.

AUTOMATICALLY GENERATED EXCERPT
Please rate it.

In clinical trials, continuous outcomes, such as intraocular pressure and visual acuity, are often measured both before treatment (ie, at baseline) and after treatment... Analysing change scores (ie, the difference between the post-treatment measurement and baseline measurement for each participant)... The post-treatment measurements or change scores (methods (2) and (3)) would typically be compared using a two-sample t test... The 95% CI tells us that we are 95% confident that the difference in mean BCVA is somewhere between 4.8 letters in favour of ranibizumab and 1.4 letters in favour of bevacizumab... The mean difference between the two drugs (1.1 letters) is the vertical distance between the two parallel lines... In this example, all three methods led to the same conclusion, namely that mean BCVA at 24 months was similar between the two drugs... Further efficiency was then gained using the more flexible ANCOVA model compared to the analysis of change scores (SE 1.21 vs 1.25 letters, 95% CI (−3.4 to 1.3) vs (−3.3 to 1.6))... While in this example all three methods led to the same conclusion, it is possible for different models to yield estimates that might lead to different conclusions... If, for example, the more precise estimate had had a CI which excluded zero, while the less precise estimates did not, we might infer evidence of a treatment effect from one model only... This would test the hypothesis that the change from baseline is zero separately for each treatment group... The estimates obtained would give the mean change from baseline in each group, with a corresponding 95% CI, but we would not be able to draw a conclusion about, or quantify the difference between, the two drugs... If we were to perform two paired t tests on our data, we would conclude that there was a significant improvement in BCVA with both ranibizumab and bevacizumab, with a mean improvement of 4.9 letters (95% CI 3.1 to 6.7) and 4.1 letters (95% CI 2.4 to 5.8), respectively... Approaches include omitting the cases with missing data, which is an inefficient use of the data, reducing precision and power; imputing the missing values, which must be done with care; and fitting a more sophisticated model where the baseline and post-treatment measurements are modelled ‘jointly’, which allows participants with partial missing data to be included.

Show MeSH
Related in: MedlinePlus