Early immune stimulation and childhood acute lymphoblastic leukemia in Costa Rica: A comparison of statistical approaches

The genetic risk of acute lymphoblastic leukemia and its implications for children of Latin American origin

Acute lymphoblastic leukemia (ALL) is the most common cancer in children, and disproportionately affects children of Hispanic/Latino ethnicity in the United States, who have the highest incidence of disease compared with other racial/ethnic groups. Incidence of childhood ALL is similarly high in several Latin American countries, notably in Mexico, and of concern is the rising incidence of childhood ALL in some Hispanic/Latino populations that may further widen this disparity. Prior studies have implicated common germline genetic variants in the increased risk of ALL among Hispanic/Latino children. In this review, we describe the known disparities in ALL incidence as well as patient outcomes that disproportionately affect Hispanic/Latino children across the Americas, and we focus on the role of genetic variation as well as Indigenous American ancestry in the etiology of these disparities. Finally, we discuss future avenues of research to further our understanding of the causes of the disparities in ALL incidence and outcomes in children of Latin American origin, which will be required for future precision prevention efforts.

Using machine learning methods to analyze the association between urinary polycyclic aromatic hydrocarbons and chronic bowel disorders in American adults

The etiology of chronic bowel disorders is multifaceted, with environmental exposure to harmful substances potentially playing a significant role in their pathogenesis. However, research on the correlation between polycyclic aromatic hydrocarbons (PAHs) and chronic bowel disorders remains limited. Using data from the National Health and Nutrition Examination Survey (NHANES) conducted in 2009-2010, we investigated the relationship between 9 PAHs and chronic diarrhea and constipation in U.S. adults. We employed unsupervised methods such as clustering and Principal Component Analysis (PCA) to identify participants with similar exposure patterns. Additionally, we used supervised learning techniques, namely weighted quantile sum (WQS) and Bayesian kernel machine (BKMR) regressions, to assess the association between PAHs and the occurrence of chronic diarrhea and chronic constipation. PCA identified three principal components in the unsupervised analysis, explaining 86.5% of the total PAH variability. The first component displayed a mild association with chronic diarrhea, but no correlation with chronic constipation. Participants were divided into three clusters via K-means clustering, based on PAH concentrations. Clusters with higher PAH exposure demonstrated an increased odds ratio for chronic diarrhea, but no meaningful connection with chronic constipation. In the supervised analysis, the WQS regression underscored a positive relationship between the PAH mixture and chronic diarrhea, with three PAHs significantly impacting the mixture effect. The mixture index showed no correlation with chronic constipation. BKMR analysis illustrated a positive trend in the impact of four specific PAHs on chronic diarrhea, given other metabolites were fixed at their 50th percentiles. Our results suggest a clear association between higher PAH exposure and an increased risk of chronic diarrhea, but not chronic constipation. It also underscores the potential role of specific PAHs in contributing to the risk of chronic diarrhea.

Application of targeted maximum likelihood estimation in public health and epidemiological studies: a systematic review

PURPOSE

The targeted maximum likelihood estimation (TMLE) statistical data analysis framework integrates machine learning, statistical theory, and statistical inference to provide a least biased, efficient, and robust strategy for estimation and inference of a variety of statistical and causal parameters. We describe and evaluate the epidemiological applications that have benefited from recent methodological developments.

METHODS

We conducted a systematic literature review in PubMed for articles that applied any form of TMLE in observational studies. We summarized the epidemiological discipline, geographical location, expertize of the authors, and TMLE methods over time. We used the Roadmap of Targeted Learning and Causal Inference to extract key methodological aspects of the publications. We showcase the contributions to the literature of these TMLE results.

RESULTS

Of the 89 publications included, 33% originated from the University of California at Berkeley, where the framework was first developed by Professor Mark van der Laan. By 2022, 59% of the publications originated from outside the United States and explored up to seven different epidemiological disciplines in 2021-2022. Double-robustness, bias reduction, and model misspecification were the main motivations that drew researchers toward the TMLE framework. Through time, a wide variety of methodological, tutorial, and software-specific articles were cited, owing to the constant growth of methodological developments around TMLE.

CONCLUSIONS

There is a clear dissemination trend of the TMLE framework to various epidemiological disciplines and to increasing numbers of geographical areas. The availability of R packages, publication of tutorial papers, and involvement of methodological experts in applied publications have contributed to an exponential increase in the number of studies that understood the benefits and adoption of TMLE.

Spatial analysis and geoclimatic factors associated with the incidence of acute lymphoblastic leukemia in Iran during 2006-2014: An environmental epidemiological study

BACKGROUND AND OBJECTIVES

The present study aims to determine the cumulative incidence rate of acute lymphoblastic leukemia (ALL), the degree of spatial autocorrelation and clustering of ALL, the hotspot and coldspots of ALL and geoclimatic conditions affecting the incidence of ALL in Iran and to draw a comparison between global and local regression models.

MATERIALS AND METHODS

In this ecological study, an exploratory-etiologic multiple-group method has been adopted to investigate all children under 15 years of age with ALL in Iran during 2006-2014. Data analysis was performed using Mann Whitney U, Pearson correlation coefficients (PCCs), Global Moran's I, Optimized hotspot analysis (OHSA), Global Poisson regression (GPR), Geographically Weighted Poisson Regression (GWPR) at a significant level of α = 0.05.

RESULTS

The cumulative incidence rate of ALL was estimated at 21,315 per 100,000 Iranian children under 15 years of age. The value of Global Moran's I index was estimated 0.338 and significant (<0.001 P-value). Coldspots were observed in north and northwest of Iran and hotspots were identified in south, southwest and mid-east of Iran. In the present study, Max Temperature of Warmest Month (MTWM) and Direct Normal Irradiation (DNI) were risk factors and Precipitation of the Coldest Quarter (PCQ) and Altitude (AL) were protective factors in the incidence of ALL, even though the non-stationarity of local coefficients and local t-values was clear. GWPR, by capturing and applying spatial heterogeneity and spatial autocorrelation, had a greater performance and goodness of fit than GPR.

DISCUSSION

ALL has created spatial clusters in Iran. The incidence of ALL is the result of synergistic interaction between environmental, infectious, geographical and genetic risk factors. It is recommended to use of local models in ecological studies.

Identification of high-risk and low-risk clusters and estimation of the relative risk of acute lymphoblastic leukemia in provinces of Iran during 2006-2014 period: A geo-epidemiological study

BACKGROUND

The present study was conducted to determine the epidemiological status, identify high-risk and low-risk clusters, and estimate the relative risk (RR) of acute lymphoblastic leukemia (ALL) in provinces of Iran.

MATERIALS AND METHODS

This is an ecological study carried out using an Exploratory Multiple-Group design on 3769 children under 15 years of age with ALL from 2006 to 2014. Data analysis was performed using Mann-Whitney U, Global Moran's I and Kuldorff's purely spatial scan statistic tests at a significance level of 0.05.

RESULTS

The average annual incidence rate of ALL during 2006-2014 period was 2.25/100,000 children under 15 years of age. The most likely high-risk cluster with log-likelihood ratio (LLR) =327.47 is located in the southwestern part of Iran with a radius of 294.93 km and a centrality of 30.77 N and 50.83 E, which contained 1276 patients with a RR of 2.56. It includes Fars, Bushehr, Kohgiluyeh and Boyer-Ahmad, Khuzestan and Chahar Mahall and Bakhtiari provinces. On the other hand, the most likely low-risk cluster with 517 patients, and a RR 0.49 and LLR = 227.03 was identified in the northwestern part of Iran with a radius of 270.38 km and a centrality of 37.25 N and 49.49 E. It includes Zanjan, Qazvin, Gilan and East Azerbaijan, Ardabil, Alborz and Tehran provinces.

CONCLUSION

High-risk clusters were observed in Southwestern, central, and eastern Iran, while low-risk clusters were identified in Northern and Western Iran.

Vaccination and the Risk of Childhood Cancer-A Systematic Review and Meta-Analysis

INTRODUCTION

Infections may play a role in the etiology of childhood cancer and immunizations may be protective because vaccinations stimulate the immune system. Observational studies reported inconsistent associations between vaccination and risk of childhood cancer. Since a synthesis of the evidence is lacking, we conducted a meta-analysis stratified by histological and site-specific cancer.

METHODS

We performed a systematic review (CRD42020148579) following PRISMA guidelines and searched for literature in MEDLINE, Embase, and the Science Citation Index databases. We identified in three literature databases 7,594 different articles of which 35 met the inclusion criteria allowing for 27 analyses of 11 cancer outcomes after exposure to nine different types of vaccinations. We calculated summary odds ratios (ORs) and 95% confidence intervals (CIs) using random effects models.

RESULTS

We observed four inverse associations between childhood leukemia and certain vaccines as well as the number of vaccinations: OR 0.49 (95% CI = 0.32 to 0.74) for leukemia death after bacillus Calmette-Guérin vaccination; OR 0.76 (95% CI = 0.65 to 0.90) for acute lymphoblastic leukemia after Haemophilus influenzae type b vaccination; OR 0.57 (95% CI = 0.36 to 0.88) for leukemia; and OR 0.62 (95% CI = 0.46 to 0.85) for acute lymphoblastic leukemia after three or more vaccinations of any type. All other conducted analyses did not show any associations.

DISCUSSION

The results are consistent with the hypothesis that vaccinations reduce the risk of childhood leukemia. However, the robustness and validity of these results is limited due to the small number, substantial heterogeneity, and methodological limitations of available studies.

Prognostic Value and Outcome for ETV6/RUNX1-Positive Pediatric Acute Lymphoblastic Leukemia: A Report From the South China Children's Leukemia Group

PURPOSE

To analyzed the outcome of ETV6/RUNX1-positive pediatric acute B lymphoblastic leukemia (B-ALL) with the aim of identifying prognostic value.

METHOD

A total of 2,530 pediatric patients who were diagnosed with B-ALL were classified into two groups based on the ETV6/RUNX1 status by using a retrospective cohort study method from February 28, 2008, to June 30, 2020, at 22 participating ALL centers.

RESULTS

In total, 461 (18.2%) cases were ETV6/RUNX1-positive. The proportion of patients with risk factors (age <1 year or ≥10 years, WB≥50×10⁹/L) in ETV6/RUNX1-positive group was significantly lower than that in negative group (P<0.001), while the proportion of patients with good early response (good response to prednisone, D15 MRD < 0.1%, and D33 MRD < 0.01%) in ETV6/RUNX1-positive group was higher than that in the negative group (P<0.001, 0.788 and 0.004, respectively). Multivariate analysis of 2,530 patients found that age <1 or ≥10 years, SCCLG-ALL-2016 protocol, and MLL were independent predictor of outcome but not ETV6/RUNX1. The EFS and OS of the ETV6/RUNX1-positive group were significantly higher than those of the negative group (3-year EFS: 90.11 ± 4.21% vs 82 ± 2.36%, P<0.0001, 3-year OS: 91.99 ± 3.92% vs 88.79 ± 1.87%, P=0.017). Subgroup analysis showed that chemotherapy protocol, age, prednisone response, and D15 MRD were important factors affecting the prognosis of ETV6/RUNX1-positive children.

CONCLUSIONS

ETV6/RUNX1-positive pediatric ALL showed an excellent outcome but lack of independent prognostic significance in South China. However, for older patients who have the ETV6/RUNX1 fusion and slow response to therapy, to opt for more intensive treatment.

An Expanded Obstetric Comorbidity Scoring System for Predicting Severe Maternal Morbidity

OBJECTIVE

To develop and validate an expanded obstetric comorbidity score for predicting severe maternal morbidity that can be applied consistently across contemporary U.S. patient discharge data sets.

METHODS

Discharge data from birth hospitalizations in California during 2016-2017 were used to develop the score. The outcomes were severe maternal morbidity, defined using the Centers for Disease Control and Prevention index, and nontransfusion severe maternal morbidity (excluding cases where transfusion was the only indicator of severe maternal morbidity). We selected 27 potential patient-level risk factors for severe maternal morbidity, identified using International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes. We used a targeted causal inference approach integrated with machine learning to rank the risk factors based on adjusted risk ratios (aRRs). We used these results to assign scores to each comorbidity, which sum to a single numeric score. We validated the score in California and national data sets and compared the performance to that of a previously developed obstetric comorbidity index.

RESULTS

Among 919,546 births, the rates of severe maternal morbidity and nontransfusion severe maternal morbidity were 168 and 74 per 10,000 births, respectively. The highest risk comorbidity was placenta accreta spectrum (aRR of 30.5 for severe maternal morbidity and 54.7 for nontransfusion severe maternal morbidity) and the lowest was gestational diabetes mellitus (aRR of 1.06 for severe maternal morbidity and 1.12 for nontransfusion severe maternal morbidity). Normalized scores based on the aRR were developed for each comorbidity, which ranged from 1 to 59 points for severe maternal morbidity and from 1 to 36 points for nontransfusion severe maternal morbidity. The overall performance of the expanded comorbidity scores was good (C-statistics were 0.78 for severe maternal morbidity and 0.84 for nontransfusion severe maternal morbidity in California data and 0.82 and 0.87, respectively, in national data) and improved on prior comorbidity indices developed for obstetric populations. Calibration plots showed good concordance between predicted and actual risks of the outcomes.

CONCLUSION

We developed and validated an expanded obstetric comorbidity score to improve comparisons of severe maternal morbidity rates across patient populations with different comorbidity case mixes.