Title: Impact of nausea/vomiting on EQ-5D-5L utility scores in patients taking iron preparations
for heavy menstrual bleeding or anemia
Version: 1 Date: 04 Jul 2023
Reviewer's report:
Summary of manuscript:
The authors hypothesised that nausea/vomiting experienced by patients taking iron for HMB or
anemia, reduces quality of life (QoL), determined through EQ-5D-5L utility scores. This study
aimed to measure the QoL of 385 patients taking iron for heavy menstrual bleeding (HMB) or
anemia and establish an estimating equation to predict a QoL utility score outcome. Based on
the estimating equation, the authors assessed whether nausea/vomiting is a predictive factor that
influences EQ-5D-5L utility scores. This was a cross-sectional survey of 385 patients taking
iron for anemia or HMB. The instrument used to survey participants was the EQ-5D-5L utility
scale, in addition to survey items on primary disease, medication use, menstrual period, and
presence of current symptoms.
Using the objective variable (EQ-5D-5L utility score), explanatory variable candidates were
identified and selected using correlation, multicollinearity and clinical validity. A predicting
model was established using three regression-based models (linear model, generalised linear
model, Tobit mode) and stepwise regression was used to select statistically significant
predictors, with goodness of fit tested using mean absolute error and mean squared error.
Out of 385 patients, the mean EQ-5D-5L utility scores of 96 patients with nausea/vomiting and
289 patients without nausea/vomiting were 0.67 ± 0.16 and 0.84 ± 0.14 respectively, with the
utility scores of patients with nausea/vomiting significantly lower than those without nausea/
vomiting (p<0.001). Following the stepwise analysis, the presence of nausea/vomiting was
found to be the most significant factor that reduced the utility score from the variable candidates.
When testing the goodness-of-fit, the generalised linear model had the smallest mean squared
error and was used to obtain the estimating equation. Using the equation, the decrement of utility
score related to nausea/vomiting was -0.117 in patients taking iron for HMB or anemia. This is
the first report to statistically assess that the presence of nausea/vomiting in patients taking iron
for HMB and anemia significantly reduces EQ-5D-5L utility scores, as a marker of QoL.
Comments:
Introduction
1. HMB and anemia are the conditions of interest in the patients so it would be good to define
them and provide more context on the disease-specific factors that affect patient’s quality of life,
and why it's a valuable outcome to explore.
2. The paragraph on cost-effectiveness evaluation needs some more context. While it explains
how QoL values are used to inform QALYs/economic evaluation, it’s not quite clear how
this links to the study. If QoL values are being determined to justify future cost-effectiveness
analyses, this connection should be made clearer.
3. Three studies (Ando et al., Peuranpää et al., Bai et al.) are cited as evidence to suggest that
nausea/vomiting related to iron administration influences QoL, however they don't all reach
that conclusion. It should be made clearer what the current evidence is regarding IDA, nausea/
vomiting, QoL. Also, the gap in evidence should be articulated and as a result, why the authors
are conducting this study. More could be done in the introduction to convey the value of
assessing QoL in this patient population and what the implications of the findings would be.
Methods
4. There is no explanation of how the sample population was recruited. It was not clear how it
was confirmed that the sample group had anemia or HMB (for example were they selected from
a patient database?). This information should be made explicit.
5. The inclusion criteria for the population surveyed needs to be more clearly defined. For
example, the dosage of iron should be specified (does not state how often iron is taken in the prior
three months to be included). Justification of the minimum age of 20 years could also be helpful.
6. There was little information on how consent was obtained and how anonymity was
maintained. More information could be included on how the survey was delivered and any
protocol provided to participants, as well as how the patient data was stored.
7. It would be good to comment on the validity of the survey/questionnaire
Results/Discussion
8. Were there any dropouts from those recruited to those that enrolled in the study?
9. The scale of the QoL utility score should be explained. It also could be helpful to know what
the QoL normal scores are in the wider population to be able to compare.
10. While the authors stated this is the first study of its kind, the implications of the findings
should be included, and how is this useful for the patients and what it means for them.
11. Limitations of cross-sectional design could be commented on