Post-traumatic Stress Symptoms and Post-traumatic Growth in 223 Childhood Cancer Survivors: Predictive Risk Factors

Abstract

With modern therapies and supportive care, survival rates of childhood cancer have increased considerably. However, there are long-term psychological sequelae of these treatments that may not manifest until pediatric survivors are into adulthood. The prevalence of post-traumatic stress disorder in young adult survivors of childhood cancer ranges from 6.2 to 22%; associated risk factors are young age at the assessment, female gender, low education level, and some disease-related factors. The aim of this study was to investigate, in adolescent and young adult (AYA) survivors of childhood cancer, the incidence and severity of post-traumatic stress symptoms (PTSSs), and to identify the risk factors and the associated post-traumatic growth (PTG) index. Participants were 223 AYA cancer survivors recruited during follow-up visits in the Oncohematology Clinic of the Department of Child and Woman’s Health, University of Padua. Data were collected from self-report questionnaires on PTSS incidence, PTG mean score, perceived social support, and medical and socio-demographic factors. Ex-patients’ mean age at the assessment was 19.33 years (SD = 3.01, 15–25), 123 males and 100 females, with a mean of years off-therapy of 9.64 (SD = 4.17). Most (52.5%) had survived an hematological disorder and 47.5% a solid tumor when they were aged, on average, 8.02 years (SD = 4.40). The main results indicated a moderate presence of clinical (≥9 symptoms: 9.4%) and sub-clinical PTSS (6–8 symptoms: 11.2%), with the avoidance criterion most often encountered. Re-experience symptoms and PTG mean score were significantly associated (r = 0.24; p = 0.0001). A hierarchical regression model (R2 = 0.08; F = 1.46; p = 0.05) identified female gender (β = 0.16; p = 0.05) and less perceived social support (β = -0.43; p = 0.05) as risk factors to developing PTSS. Another hierarchical regression model assessed the possible predictors of the PTG total score (R2 = 0.36; F = 9.1; p = 0.0001), with female gender (β = 0.13; p = 0.04), actual age (β = 0.52; p = 0.0001), younger age at the diagnosis (β = -0.3; p = 0.02), and less years off-therapy (β = -0.58; p = 0.0001) impacting on PTG.

Predictors of Posttraumatic Stress and Posttraumatic Growth in Childhood Cancer Survivors

“…This result was further supported by regression analysis, where higher levels of PTG were connected to older age at the T2 assessment. However, Tremolada et al found an opposite relation between PTG and the age at diagnosis, with younger children reporting more PTG [35]. PTG further correlates with self-esteem and depressive symptoms and PTSS is associated with lower self-esteem and higher levels of negative emotionality and depressive symptoms, which corresponds to prior studies [13,29,30,31,32].…”

Correlates of post‐traumatic growth following childhood and adolescent cancer: A systematic review and meta‐analysis

“…Following data extraction and preliminary analyses, an email was sent to the authors of all 23 studies requesting unreported Pearson correlations for the specific variables measured in each study. Three authors provided additional relevant data; one indicated that the data requested from 2 studies were in fact from the same dataset. The more recent study was excluded from the results.…”

“…The more recent study was excluded from the results. Therefore, 22 studies were eligible for inclusion in the review. Four articles were excluded because the reported data were not in a format that could be used to calculate an effect size.…”

“…The results of 18 studies were synthesised. Thirteen analyses were conducted for the relationship between PTG and the following correlates: gender, age at diagnosis, age at survey, time since diagnosis, time since treatment completion, socio‐economic status, PTSS, social support, quality of life, optimism, pessimism symptoms, anxiety symptoms, and symptoms of depression (see Table ).…”

“…When a correlation was not reported, t tests, means, and standard deviations were used to calculate an effect size . A number of eligible studies reported odds ratios, or used multivariate or regression analyses with variables of interest, but did not report all variables in a format that would allow an effect size to be computed. These authors were contacted for the missing information.…”