# Comment on the change in p-value following adjustment for confounders

The Second Australian National Blood Pressure Study (ANBP2) was a prospective, randomised, open-labelled, blinded to endpoint (PROBE) trial of Angiotensin Converting Enzyme (ACE) inhibitors versus diuretic in the treatment of mild to moderate hypertension in the elderly – defined as 65 to 84 years of age at last birthday. It was carried out in over 1500 general practices in Australia in the mid-late 1990s. The primary (combined) endpoint was the incidence of all defined cardiovascular events and deaths from any cause. There were several secondary outcomes, including incidence of first cardiovascular events and various measures of blood pressure control. The main entry criterion (there were, of course, many criteria) was a systolic BP ≥160mmHg, or a diastolic BP of ≥90mmHg if systolic BP was >140mmHg, prior to randomisation. It was intended that all subjects would be followed for 5 years.

The ANBP2 protocol specified that the primary endpoint analysis would be adjusted for a limited number of pre-specified potential confounders, should these variables actually confound the results of this study. The ANBP2 statisticians, blind to (i) the assigned treatment (ii) the p-values with and without adjustment, and (iii) the direction of any change in the treatment effect between adjusted and unadjusted analyses, found that age and sex were the only potential confounders in the defined list that actually changed the treatment effect by an appreciable amount. Accordingly, the final result was adjusted only for age and sex. The p-value associated with the adjusted analysis for the primary outcome was exactly 0.05 (to at least 4 decimal places). The p-value without adjustment for age and sex was 0.08.

Comment...?

I believe I need to make some form of judgement on the change in statistical significance following adjustment here.

I am unsure what information might also apply here when making a comment? Would it bo helpful to discuss the following of protocol for example?

Any clarification on what a comment could include would be helpful

• I'm not following. If the statisticians were by all meanings of the word except literal, blind, then how did they conclude which variables were confounding the effect of interest? In addition, the level of significance $\alpha$ is not mentioned anywhere. So at best you could say that there is mild evidence against the null, with little change after correction. Oct 31 '19 at 9:31
• A good point, I had taken that as the protocol specified that the primary endpoint analysis would be adjusted for a limited number of pre-specified potential confounders lead statisticans to conclude on the variables. This is perhaps a relevant point for commenting. Thanks
– Bery
Oct 31 '19 at 9:46