Bone densitometry:
All patients had at least two dual X-ray absorptiometry (DXA) exams: one
before or at the time of DMAB initiation and one after
VF occurrence. Exams
were carried out with different machines for different patients, but the
same for each patient, allowing us to compare both exams. T-scores were
calculated using normal values for the Spanish population. For
biochemical determinations, fasting blood was drawn. The biochemical
parameters: creatinine, total proteins, calcium and phosphorus were
measured using standardized colorimetric methods.
Immunochemiluminescence was used to determine the biochemical parameters
of bone remodeling: P1NP, beta-crosslaps and osteocalcin.
VF diagnosis was confirmed by MRI assessed by a radiologist,
except in four patients in which it was based on shape changes in X-ray
exams as compared to recent previous images.
The study was carried out following the rules of the Declaration of
Helsinki (13), the protocol approved by the Insular University Hospital
of Gran Canaria Clinical Trials Committee. All patients were informed of
the study objectives and gave their informed written consent.
Statistical analysis Univariate analysis. Categorical variables are expressed as
frequencies and percentages and continuous as mean and standard
deviation (SD). Paired means were compared using the Wilcoxon test for
paired data.Poisson models. The effect of each factor (X ) on the
number of vertebral fractures after DMAB (nVF ) was analyzed by
means of the Poisson model: \(\text{nVFPoisson}\left(\mu\right)\),
being:
\begin{equation}
\log\left(\mu\right)=\alpha+\beta X\nonumber \\
\end{equation}Where \(\mu\) is the expected number of vertebral fractures, which may
depend on the X factor. When \(X\) is a binary variable
indicating presence or absence of a character its values were coded as 1
(presence) and 0 (absence). From this model it follows:
\begin{equation}
\frac{\mu\left(X=t+1\right)}{\mu\left(X=t\right)}=exp\left(\beta\right)\nonumber \\
\end{equation}Where \(\mu\left(X=t\right)\) corresponds to the expected number of
vertebral fractures when the factor X is in level t .
Therefore, \(\exp\left(\beta\right)\) correspond to the proportion of
variation of the expected number of vertebral fractures for each unit
that varies X.
Statistical significance was set at p < 0.05. Data were
analyzed using the R package, version 3.6.1 (R Development Core Team,
2019).