Methods
Study subjects
All patients who had received trastuzumab at Osaka Medical and
Pharmaceutical University Hospital from January 1, 2017 to December 31,
2020 were identified and the following exclusion criteria were applied:
gastric cancer, missing information on HER2 status, missing eosinophil
information, or use of other treatments. This study was conducted in
accordance with the Declaration of Helsinki and approved by the ethics
committee of Osaka Medical and Pharmaceutical University (Approval ID:
2020-175). Since this is a retrospective observational study without
intervention or invasion, the requirement for informed consent was
waived. This study was conducted according to the STROBE
statement.45
Outcome variable
The severity of IRRs was assessed using the Common Terminology Criteria
for Adverse Events (CTCAE) version 5.0, and the outcome measure was the
occurrence of an IRR of grade 1 or higher after starting trastuzumab
administration. For each patient, all electronic medical record data at
the time of trastuzumab administration were retrospectively reviewed for
potential IRR cases by a clinical pharmacist with specific training in
screening and treatment of adverse effects in cancer chemotherapy.
Explanatory variables
Patients received repeated doses of trastuzumab. The data analyzed in
this study were obtained from multiple doses administered to the same
individual; that is, it had a two-level hierarchical structure
consisting of a macro-level (patient level, level 2) and micro-level
(infusion level, level 1). With reference to previous
studies,39,42 the following factors were examined in
this study. The macro-level variables were height, HER2 status, estrogen
receptor (ER) status, progesterone receptor (PR) status, allergy
history, and baseline eosinophil levels; the micro-level variables were
age, stage, metastasis, concomitant medications, number of courses,
weight, BMI, status (preoperative, postoperative, and/or recurrent
progression), trastuzumab dose, and dexamethasone dose. Eosinophils were
not measured for each dose of trastuzumab; therefore, baseline values
were used as macro-level variables.
Data processing
Centering at the pooled mean was performed for the following macro-level
variables: height, HER2 status, ER status, PR status, allergy history,
and baseline eosinophil levels. Although age, stage, metastasis, and
concomitant medications were micro-level variables, centering at the
pooled mean was applied because there was little variation within
individual patients. On the other hand, centering within the cluster was
applied to the following micro-level variables: the number of courses,
weight, BMI, status (preoperative, postoperative, and/or recurrent
progression), trastuzumab dose, and dexamethasone
dose.46
Statistical analysis
Descriptive statistics at the macro- and micro-levels were calculated.
Fisher’s exact test was used for nominal variables, Wilcoxon rank-sum
test was used for continuous variables, and Cochran-Armitage trend test
was used for ordered variables (stage, trastuzumab dose, and
dexamethasone dose) to examine the trends of IRR occurrence rate. Owing
to the hierarchical structure of the data, the independence of the
observed values was evaluated using the intraclass correlation
coefficient (ICC).47 Subsequently, four models,
including a null model, were tested using multilevel logistic regression
analysis to identify the preventive effects of dexamethasone
premedication on IRR occurrence as well as the relationships between the
macro- and micro-level independent risk factors and IRR development.
Model 0, the null model, is a model with no objective or explanatory
variables and was used to determine ICC. ICC is a measure to assess
similarity within a group,47 and in this study, the
patients represented the group and one infusion of trastuzumab
represented the individual. Model 1 incorporated micro-level variables,
Model 2 incorporated macro-level variables, and Model 3 incorporated
both micro- and macro-level variables. For the selection of candidate
explanatory variables, p -values from univariate analysis were
considered. Akaike’s information criterion (AIC), Bayesian information
criterion (BIC), and likelihood ratio tests were used to compare model
goodness-of-fit. Variance inflation factors (VIFs) of ≥10 were
considered evidence of multicollinearity. All p -values were
reported using two-tailed tests, and the significance level was set at
5%. Analyses were performed using R version 4.0.2 (R Development Core
Team, Vienna, Austria).