Prevalence of Poverty and Hunger at Cancer Diagnosis and Its Association with Malnutrition and Overall Survival in South Africa.

Many South African children live in poverty and food insecurity; therefore, malnutrition within the context of childhood cancer should be examined. Parents/caregivers completed the Poverty-Assessment Tool (divided into poverty risk groups) and the Household Hunger Scale questionnaire in five pediatric oncology units. Height, weight, and mid-upper arm circumference assessments classified malnutrition. Regression analysis evaluated the association of poverty and food insecurity with nutritional status, abandonment of treatment, and one-year overall survival (OS). Nearly a third (27.8%) of 320 patients had a high poverty risk, associated significantly with stunting (p = 0.009), food insecurity (p < 0.001) and residential province (p < 0.001) (multinomial regression). Stunting was independently and significantly associated with one-year OS on univariate analysis. The hunger scale was significant predictor of OS, as patients living with hunger at home had an increased odds ratio for treatment abandonment (OR 4.5; 95% CI 1.0; 19.4; p = 0.045) and hazard for death (HR 3.2; 95% CI 1.02, 9.9; p = 0.046) compared to those with food security. Evaluating sociodemographic factors such as poverty and food insecurity at diagnosis is essential among South African children to identify at-risk children and implement adequate nutritional support during cancer treatment.

Psychological distress of adolescent and young adult childhood cancer survivors in a South African cohort.

BACKGROUND: We investigated psychological distress in a South African childhood cancer survivor (CCS) cohort. METHODS: Adult CCSs treated at Tygerberg Hospital, Cape Town, completed the Brief Symptom Inventory-18. Internal consistency was acceptable: Cronbach's alpha values were 0.91 (Global Severity Index (GSI)), 0.85 (depression), 0.83 (somatization), and 0.75 (anxiety). We compared results utilizing different case rules (GSI T scores of ≥50, ≥57, and ≥63) for the identification of psychological distress. RESULTS: Forty CCSs (median age 24 years; median follow-up period 16 years) participated. Most (58%; 23 out of 40) completed school or tertiary education, were unmarried (90%; 36 out of 40), and unemployed (59.5%; 22 out of 37). The diagnoses included hematological malignancies (65%; 26 out of 40) and solid tumors (35%; 14 out of 40). The GSI T scores of ≥63, ≥57, and ≥50 identified 10% (four out of 40), 32.5% (13 out of 40), and 45% (18 out of 40) of survivors with psychological distress, respectively. Radiotherapy (odds ratio (OR) 4.6; p = .035), presence of ≥six late effects (OR 7.5; p = .026), and severe late effects (OR 6.6; p = .024) were significant risk factors (GSI T score ≥57). Follow-up period of 11-20 years (OR 7.3; p = .034) was significant for a GSI T score ≥50. CONCLUSION: This South African CCS cohort had higher levels of psychological distress utilizing the GSI T score ≥50 and ≥57 case rules than reported in the literature. Most were unmarried or unemployed. Significant contributing factors were radiotherapy, number and severity of late effects, and follow-up period. CCSs must be screened for psychological distress.

Health-Related Quality of Life of Adolescent and Young Adult-Aged Childhood Cancer Survivors in a South African Cohort: A Pilot Study Using the Minneapolis-Manchester Quality of Life Instrument.

Purpose: We investigated the health-related quality of life (HRQoL) of an adolescent and young adult (AYA)-aged South African childhood cancer survivor (CCS) cohort. Methods: Participants completed the Minneapolis-Manchester Quality of Life adolescent and adult forms. The overall Cronbach's alpha coefficients were 0.81 (adolescent form) and 0.92 (adult form). The scale-level content validity indexes were acceptable (0.88 and 0.89 for the adolescent and adult forms, respectively). The total domain and overall HRQoL scores were calculated. Results: Sixty-two survivors completed the adolescent form and 30 completed the adult form. The median age was 17.5 years (range 13-34 years), and the median time from diagnosis was 12 years (male:female ratio 1:1.2). Risk factors for poor physical functioning included age at study visit (p = 0.015), solid tumor diagnosis (p = 0.012), radiotherapy (p = 0.021), and surgery (p = 0.006). Six or more late effects impacted most domains negatively; severe late effects (p = 0.020) decreased physical functioning. Lower socioeconomic status was associated with poorer physical (p = 0.006) and cognitive (p = 0.047) functioning. The adult form cohort had poorer psychological (p = 0.014) and social functioning (p = 0.005) and body image (p = 0.016) than the adolescent form cohort. Conclusion: Older age, radiotherapy, surgery, solid tumor diagnosis, and the number and severity of late effects negatively influenced HRQoL in AYA-aged CCSs. A long-term follow-up (LTFU) risk stratification system should include HRQoL status to assist with holistic LTFU care.

Implemented nutritional intervention algorithm in pediatric oncology compared to standard nutritional supportive care outcomes.

AIM: To implement a childhood cancer-specific nutritional algorithm adapted for the South African context for interventions at time-set intervals to evaluate differences in the nutritional status of newly diagnosed children with cancer. METHOD: Children with newly diagnosed cancer were assessed for stunting, underweight, wasting, and moderate to severe malnutrition (MUAC < -2SD and < - 3 SD) between October 2018 and December 2020 in a longitudinal nutritional assessment study with monthly assessments. Two pediatric oncology units (POUs) served as the intervention group that implemented the nutritional algorithm-directed intervention and three other POUs formed the control group that implemented standard supportive nutritional care. RESULTS: A total of 320 patients were enrolled with a median age of 6.1 years (range three months to 15.3 years) and a male-to-female ratio of 1.1:1. The malnourished patients in the intervention group showed significant improvement at six months after diagnosis for stunting (P = 0.028), underweight (P < 0.001), and wasting until month five (P = 0.014). The improvements in the control group were not significant. Moderate acute malnutrition (MAM) significantly improved over the first six months of cancer treatment in the intervention group (P < 0.001), while MAM improvement was only significant in the control group for the children under five years of age (P = 0.004). The difference in mean z-scores over time for the nutritional parameters between the intervention and control groups was insignificant. CONCLUSION: We established that the nutritional algorithm adapted for South Africa as an intervention tool for childhood cancer assisted in optimizing nutritional interventions and improved nutritional outcomes over the first six months of cancer treatment.