Discussion
The results of this multicentric study show that greater social deprivation and therefore poverty, is associated with learning difficulties in survivors after cancer treatment.
Learning difficulties were reported in 22% of the children in our study, but higher rates have been noted in the literature(21,24). Survivors are at greater risk for presenting learning difficulties with scholarly consequences(10,15,21,24), ultimately leading to a lower overall quality of life(25). School absenteeism induced by cancer care is the most commonly reported productivity loss(8,26). Even if we did not evaluate the rate of absenteeism in our cohort, we found that tumor relapse was a risk factor. The tumor relapse frequently requires extended hospital stays and therefore, induces school absenteeism.
In our study, the probability of declaring a learning difficulty at school was associated with greater social deprivation. Irrespective of the disease, there is a strong relationship between SES and scholarly achievement(27–29). This supports our results and those reported in the literature, even though different methods were used to estimate the SES across studies(14,15,25). Parental involvement should also be considered as a factor influencing academic achievement(30). Children with CNS tumors are the population of greatest concern. CNS tumors and CNS directed therapies (i.e., cranial radiotherapy and intrathecal chemotherapy) increase the risk of adverse psychosocial consequences(7,24,31). Academic and neurocognitive difficulties are described, as well as higher rates of school absenteeism(8,9,21). We did not confirm the inherent risk of radiotherapy in our CNS subgroup analysis, probably due to the lack of children receiving irradiation followed in our study. In this CNS subgroup, social deprivation remained a prognostic factor for learning difficulties, an observation also shown by Ach et al.(32).
HSCT was a risk factor for learning disabilities, in agreement with previous reports that a high number of children receiving HSCT present with academic difficulties and do not graduate high school(33).
Learning difficulties may be induced by a lack integration into the school environment, as adequate socialization is a contributing factor to academic success(29). Our data collection precludes this analysis; however, Duan et al. demonstrated that greater social deprivation negatively influences the relationship between academic socialization and academic achievement(29). Survivors suffer from poor social integration, potentiated by absenteeism(21,24,26,34). These difficulties are described more frequently in patients with CNS tumors.
Due to the high risk for learning disabilities in survivors, school-organized educational support remains necessary. Thirty-six percent of children received a such support in our study, a rate slightly higher than that reported in the literature, which ranged from 20% to 32.5%(24,31,35). Although greater deprivation was associated with learning disabilities, it was not associated with the probability of benefiting from academic support. Academic support seems to be equally shared between children according to the EDI score, whereas we showed a higher need in deprived areas.
Our analysis of psychological difficulties did not reveal an association with social deprivation. However, SES may participate in causal mechanisms for psychological problems (16,19). One study revealed that neighborhood SES affected the probability of benefiting from psychological support(36). Children with CNS tumors are at greater risk for psychological effects, whereas our results indicated that children with bone tumors were at risk(11,19). The psychological effects of bone cancer can be explained by physical damage secondary to the surgery, inducing vulnerability related to physical performance limitations, disruption to routine activities, and diminished ability to attend work or school(37,38).
This study is based on a prospective cohort and allowed us to evaluate the overall psychosocial status of survivors after hospital treatment and the evolution of psychosocial effects over time. However, this study presents some limitations.
Our population was based on a database which aims to represent all the children treated for cancer in the GOCE departments. However, one center was excluded from the study because it did not participate to patients’ psychosocial evaluation. This excluded 6% of the children of the cohort and therefore, we cannot exclude a selection bias (Figure 1).
Evaluation biases were present as a result of the variables’ measurement. Each outcome was evaluated during a consultation with the oncologist pediatrician at a time when the clinical evaluation remained the main objective to ensure remission persistence. The outcomes were self-reported by the parents and children, and the subjective aspect of self-reports cannot be ruled out. In addition, the data was only collected at the posttreatment period and no baseline at diagnosis was available. This precludes any analysis to evaluate the evolution of psychosocial difficulties before and after the cancer management. This limits us to an observation of post-treatment difficulties without taking account of some potential predisposed conditions. Indeed, in children with CNS tumors, preexisting predisposition syndromes (e.g., type one fibromatosis) can induce learning and psychological effects, as well as the tumor symptoms themselves (39–41). However, the evaluation of psychosocial status at diagnosis may be difficult. This time is a period when clinical management remains the absolute priority. This can explain the choice of investigators to defer the psychosocial evaluation to after treatment.
The measurement of social deprivation using the EDI score assesses the SES of the environment of each patient and can induce an ecological bias. This measurement considers homogeneity between children living in the same IRIS and could induce misclassification and underestimate the effect of SES. Data on individual deprivation could be a complementary method to precise the SES of children, but were not available in the database.
Our statistical analysis is another limitation. Each child had a different follow-up duration, which limited our utilization of the Cox model. These different follow-up times resulted in missing data organized in a monotone structure, resulting from dropout, and limited the use of multiple imputations to consider the missing data. Additionally, multiple imputation is not recommended for longitudinal data analysis because of the lack of obvious benefit in this context(42).