METHODS
Study population
A fifteen-year observational, longitudinal, and retrospective analysis
of patients < 20 years of age with ALL diagnosis,
classified according to the World Health Organization23 from 2004 to 2018 at the Hematology Department of
the Dr. Jose E. González University Hospital of the School of Medicine
of the Universidad Autonoma de Nuevo Leon, in Monterrey, México was
performed. The region is semiarid and has a latitude of 25°40′17″ North
and longitude of 100°18′31″ West. The institution is a referral center
for three States in Northeast Mexico adding up to a population of 11.5
million; patients with no formal healthcare services coverage are
referred from public primary and secondary care centers. Hence, taking
into consideration the lack of a national registry that records all
cases of ALL over the study period the patients included could represent
the uninsured population of Northeast Mexico.
We analyzed clinical and electronic files of 394 patients and included
patients’ age, sex, risk group and date of diagnosis. For the purposes
of this study we considered date of diagnosis as the date of first
pathological data registered and only consecutive patients with
symptom-diagnosis interval <4 weeks were included in the study
to minimize the bias generated due to delayed presentation on
seasonality. Also, for the purposes of this study, the term seasonality
refers to a pattern, variation, or fluctuation in the month of ALL
diagnosis. No patient was excluded due to lack of data. The
Institutional Ethics and Research Committee approved the study protocol
and waived informed consent due to its retrospective methodology.
Statistical Analysis
Patients were classified by age group, considering children those under
16 years of age and adolescents from 16 to 20 years. Children were
classified by risk group according to the Children’s Oncology Group
approach and the National Comprehensive Cancer Network 2020
Guidelines.24 Next, Poisson regression models were
used to determine the pattern of seasonality in the diagnosis date of
patients with ALL. This method fits sinusoidal (harmonic) models to the
data, using observed counts as the outcome and expected counts and month
of diagnosis as covariates. The significance of the sinusoidal model
assumption was evaluated with post-estimation Pearson chi-square tests
for goodness-of-fit and Akaike information criterion/Bayesian
information criterion. The overall temporal trend was also tested
applying a Poisson regression model.
All models were evaluated for significant trends using post-estimation
statistics.
Stratified analyses were also performed for gender and age groups as
well as for group of risk in children. We used a chi-square test of
homogeneity to prove the hypothesis of no difference in number of ALL
diagnoses by month. Tests were performed separately for males and
females, children and adolescents. SPSS v.26 (IBM SPSS Statistics, IBM
Corporation, Armonk, NY) was used for data analysis. A P-value ≤ 0.05
was considered statistically significant.