Family history of cancer and the risk of childhood brain tumors: a pooled analysis of the ESCALE and ESTELLE studies (SFCE)

PURPOSE: Although some specific genetic syndromes such as neurofibromatosis (NF) have been identified as risk factor of childhood brain tumors (CBT), the potential role of inherited susceptibility in CBT has yet to be elucidated. METHODS: To further investigate this, we conducted a pooled analysis of two nationwide case-control studies ESCALE and ESTELLE. The mothers of 509 CBT cases and 3,102 controls aged under 15 years who resided in France at diagnosis/interview, frequency-matched by age and gender, responded to a telephone interview conducted by trained interviewers. Pooled odds ratio (OR) and 95% confidence intervals (95% CI) were estimated using unconditional logistic regression. RESULTS: CBT was significantly associated with the family history of cancer in relatives (OR 1.2, 95% CI 1.0-1.5). The OR was slightly higher for maternal relatives than for paternal relatives, and when at least two relatives had a history of cancer. CBT was significantly associated with a family history of brain tumor (OR 2.1, 95% CI 1.3-3.7). This association seemed stronger for first-degree relatives (mother, father, and siblings), for whom, by contrast, no association was seen for cancers other than CBT. No specificity by CBT subtypes or by age of the children were found for any of these findings. CONCLUSION: Our findings support the hypothesis of a familial susceptibility of CBT, not due to being a known NF carrier

Outcome after failure of allogeneic hematopoietic stem cell transplantation in children with acute leukemia: a study by the Société Francophone de Greffe de Moelle et de Thérapie Cellulaire (SFGM-TC)

Allogeneic hematopoietic stem cell transplantation (SCT) contributes to improved outcome in childhood acute leukemia (AL). However, therapeutic options are poorly defined in case of post-transplantation relapse. We aimed to compare treatment strategies in 334 consecutive children with acute leukemia relapse or progression after SCT in a recent ten-year period. Data could be analyzed in 288 patients (157 ALL, 123 AML and 8 biphenotypic AL) with a median age of 8.16 years at transplantation. The median delay from first SCT to relapse or progression was 182 days. The treatment consisted in chemotherapy alone (n=108), chemotherapy followed by second SCT (n=70), supportive/palliative care (n=67), combination of chemotherapy and DLI (n=30), or isolated reinfusion of donor lymphocytes (DLI) (n=13). The median OS duration after relapse was 164 days and differed according to therapy: DLI after chemotherapy = 385 d, second allograft = 391d, chemotherapy = 174d, DLI alone = 140d, palliative care = 43d. A second SCT or a combination of chemotherapy and donor lymphocytes infusion yielded similar outcome (HR=0.85, p=0.53) unlike chemotherapy alone (HR 1.43 p=0.04), palliative care (HR=4.24, p<0.0001) or isolated DLI (HR=1,94, p<0.04). Despite limitations in this retrospective setting, strategies including immunointervention appear superior to other approaches, mostly in AML

Genotype–phenotype associations within the Li-Fraumeni spectrum: a report from the German Registry

Li-Fraumeni syndrome (LFS) is a cancer predisposition syndrome caused by pathogenic TP53 variants. The condition represents one of the most relevant genetic causes of cancer in children and adults due to its frequency and high cancer risk. The term Li-Fraumeni spectrum reflects the evolving phenotypic variability of the condition. Within this spectrum, patients who meet specific LFS criteria are diagnosed with LFS, while patients who do not meet these criteria are diagnosed with attenuated LFS. To explore genotype–phenotype correlations we analyzed 141 individuals from 94 families with pathogenic TP53 variants registered in the German Cancer Predisposition Syndrome Registry. Twenty-one (22%) families had attenuated LFS and 73 (78%) families met the criteria of LFS. NULL variants occurred in 32 (44%) families with LFS and in two (9.5%) families with attenuated LFS (P value < 0.01). Kato partially functional variants were present in 10 out of 53 (19%) families without childhood cancer except adrenocortical carcinoma (ACC) versus 0 out of 41 families with childhood cancer other than ACC alone (P value < 0.01). Our study suggests genotype–phenotype correlations encouraging further analyses. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13045-022-01332-1

Systematic review and meta-analysis of the value of initial biomarkers in predicting adverse outcome in febrile neutropenic episodes in children and young people with cancer

Background: Febrile neutropenia is a frequently occurring and occasionally life-threatening complication of treatment for childhood cancer. Many biomarkers have been proposed as predictors of adverse events. We aimed to undertake a systematic review and meta-analysis to summarize evidence on the discriminatory ability of initial serum biomarkers of febrile neutropenic episodes in children and young people. Methods: This review was conducted in accordance with the Center for Reviews and Dissemination Methods, using three random effects models to undertake meta-analysis. It was registered with the HTA Registry of systematic reviews, CRD32009100485. Results: We found that 25 studies exploring 14 different biomarkers were assessed in 3,585 episodes of febrile neutropenia. C-reactive protein (CRP), pro-calcitonin (PCT), and interleukin-6 (IL6) were subject to quantitative meta-analysis, and revealed huge inconsistencies and heterogeneity in the studies included in this review. Only CRP has been evaluated in assessing its value over the predictive value of simple clinical decision rules. Conclusions: The limited data available describing the predictive value of biomarkers in the setting of pediatric febrile neutropenia mean firm conclusions cannot yet be reached, although the use of IL6, IL8 and procalcitonin warrant further study

Predicting infectious complications in neutropenic children and young people with cancer (IPD protocol)

<p>Abstract</p> <p>Background</p> <p>A common and potentially life-threatening complication of the treatment of childhood cancer is infection, which frequently presents as fever with neutropenia. The standard management of such episodes is the extensive use of intravenous antibiotics, and though it produces excellent survival rates of over 95%, it greatly inconveniences the three-fourths of patients who do not require such aggressive treatment. There have been a number of studies which have aimed to develop risk prediction models to stratify treatment. Individual participant data (IPD) meta-analysis in therapeutic studies has been developed to improve the precision and reliability of answers to questions of treatment effect and recently have been suggested to be used to answer questions regarding prognosis and diagnosis to gain greater power from the frequently small individual studies.</p> <p>Design</p> <p>In the IPD protocol, we will collect and synthesise IPD from multiple studies and examine the outcomes of episodes of febrile neutropenia as a consequence of their treatment for malignant disease. We will develop and evaluate a risk stratification model using hierarchical regression models to stratify patients by their risk of experiencing adverse outcomes during an episode. We will also explore specific practical and methodological issues regarding adaptation of established techniques of IPD meta-analysis of interventions for use in synthesising evidence derived from IPD from multiple studies for use in predictive modelling contexts.</p> <p>Discussion</p> <p>Our aim in using this model is to define a group of individuals at low risk for febrile neutropenia who might be treated with reduced intensity or duration of antibiotic therapy and so reduce the inconvenience and cost of these episodes, as well as to define a group of patients at very high risk of complications who could be subject to more intensive therapies. The project will also help develop methods of IPD predictive modelling for use in future studies of risk prediction.</p