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.