Reviewer's report 
 Quality of life and symptoms of menopause in the Estonian Postmenopausal Hormone Therapy trial Title: 
[ISRCTN35338757] 
 1  20 April 2007 Version: Date: 
 Helene Ekström Reviewer: 
Reviewer's report: 
General 
A very interesting study design combining blind and non-blind exposure to HT and no therapy 
------------------------------------------------------------------------------- 
Major Compulsory Revisions (that the author must respond to before a decision on publication can be 
reached) My major problem with this manuscript is that the method and result sections are unclear and difficult to follow. Information that is of no significance for the present study is given in detail while other important 
information is missing or difficult to grasp. 
The main design is clear except that you mention on page 14 that the higher proportion of women reporting sweats in the non-blind arm could be explained by women with these symptoms being more eager to join 
this arm? Could the women chose? This needs to be explained. It is also necessary to report the numbers of 
participants eligible each survey year as the final survey took place 2-5 years after recruitement. A flowchart 
perhaps? 
In an randomized trial each participant should have an equal and known probability to be assigned to the 
different arms and thus differences in base line background data does not indicate bias. The differences 
found may however indicate imbalances that need to be taken into account in the analysis. Here the authors 
state that there is no such differences except for the sweating. It is in my opinion thus unnecessary to 
display all the data in table one. The information could be summarized in a couple of sentences under the 
heading “participants”. But the found difference in reports of sweating at baseline should be given as 
number and percent for the different arms and not as OR. It is a fact to consider during the further analysis and interpretations of results. 
The comment in table 1 “ among those whose data available” What does it mean? You state on page 7 that 
all participants filled in the recruitment questionnaire. How large were the internal non-response rates at 
baseline and the surveys used in this study? And in table 2 considering response rates of 69% in survey 2 and in the final survey 81% -what are the given % percents of. The presented N can’t be the real ones. The different response rates is a problem. Thus is your statement “that there are no background 
characteristic differences between the arms” valid at survey 2 and in the final survey? If there are 
differences they should be presented. 
As you compare data from year 2 with the final survey one needs to know how many of the original as well 
as survey 2 participants who responded to both these surveys. 
Data taken from the same patient are paired and not independent. The differences in proportions presented in table 2 could be due to different participants and not changes during the period of time studied. Some 
women with no painful intercourse did perhaps not respond to survey 1 but to the final one? Also changes in 
the individuals’ measurement over time may be hidden by reporting only group means. Paired data should 
be reported together and tested using appropriate statistical methods so that changes within each patient can be evaluated. The ORs ( see below) in table 2 does not add any further information. 
In the General linear mixed modelling analysis you use baseline data and compare with the final survey - 
how many of the participants were included in this analysis considering the response rate and perhaps also 
internal non-response rates. And also as the final survey was performed 2-5 years from recruitment the 
problem with this fact has to be addressed more clearly. The results of these analysis’s are also only 
presented as statements about differences found and one p-value in the text – the numbers behind these 
statements and p-value have to be presented if of significance. 
Your choice of symptoms to ask for in the questionnaires needs to be motivated (see ref 23 and several 
others in the same supp of Am J Med or other ref about the same topic ) and more information about the 
EQ- 5D instrument given (such as the information underneath table 3 in your reference 21). A reader should 
not have to search for references in order to understand your results. 
Table 3 in your study does not provide me with any additional information that couldn’t easily be 
summarized in the text. 
You claim to have used regression analysis – which one. As you present OR is it a binary logistic regression 
or a Polytomous universal model? Have you dichotomized or made an ordinal scale out of the EQ-5D 
outcome? EQ-5D outcome isn’t it to be considered as a continuous variable? Why not a linear regression? 
This needs to be clarified. If it is OR then present how the dependent variable is constructed and if it’s crude 
or adjusted OR. If the latter than clarify which variables that were included in the model (and why) and if 
there were removals of variables using backward or forward procedures and so on 
Why did you compare the background characteristics effects on Qol development – when your stated aim 
was to analyze the effect of hormone treatment on health-related QoL. The need for such analysis' is when 
checking for potential confounders to control for in the main analyze such as the effect of hormone 
treatment on health-related QoL. But there is no such adjusted analysis presented. 
When you compare for instance EQ-5D scores for women with and without hot flushes it’s the absolute 
difference between the two scores with 95% CI that should be presented not the individual group values. 
I don’t understand the OR presented in paragraph 2 page 10 and paragraph 2 page 11. Why not present the 
actual measurements such as mean or median number bleeding episodes or the difference in EQ-5D score 
for mobility with 95% CI between the groups compared (which were?) 
In the discussion, conclusion and abstract information is given and statements done that lack underpinning 
in the method and result sections for instance the p values given in the abstract and the last part of the first sentence in the conclusion. This needs to be corrected by the authors. In the discussion section sort the “strengths and weaknesses” discussions together and in a logical order. 
Then speak about your results in comparison to other studies ( the “Supp” published in dec 2006 in AM J 
Med and Managing the menopause Roberts H a review article in BMJ 2007;334;736-41 are but some recent articles of interest here) and their clinical implications. Does the last paragraph in the introduction belong to that part or the method section. End the introduction with a clearly stated aim for the present 
study. The two sentences after the aim should be moved. 
------------------------------------------------------------------------------- 
Minor Essential Revisions (such as missing labels on figures, or the wrong use of a term, which the author 
can be trusted to correct) 
Figure Legends are missing. 
After the major revision the abstract needs to be overlooked. 
I prefer that when you compare groups or surveys you always state which group you compare with. 
Sometimes you do and sometimes you don’t. 
I also don’t like the labelling of the symptoms measured here as menopausal symptoms as there is no consensus about that. Such symptoms are prevalent in all ages and both sexes. 
Accordingly the title should be changed as you don’t measure only symptoms of menopause. Why not “QoL 
and symptom reporting in the Estonian …. 
------------------------------------------------------------------------------- 
Discretionary Revisions (which the author can choose to ignore) 
 Unable to decide on acceptance or rejection until the authors have responded to the major What next?: 
compulsory revisions 
 An article whose findings are important to those with closely related research interests Level of interest: 
 Needs some language corrections before being published Quality of written English: 
 No, the manuscript does not need to be seen by a statistician. Statistical review: 
Declaration of competing interests: 
I declare that I have no competing interests' below