What Congenital Malformation Is Commonly Linked to Acute Leukemia in Children?

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Open Access

Peer-reviewed

Research Article

Childhood cancer risk in those with chromosomal and not-chromosomal built anomalies in Washington Land: 1984-2013

• Marlena S. Norwood,
• Philip J. Lupo,
• Eric J. Chow,
• Michael E. Scheurer,
• Sharon E. Plon,
• Heather Due east. Danysh,
• Logan G. Spector,
• Susan E. Carozza,
• David R. Doody,
• Beth A. Mueller

x

• Published: June 8, 2017
• https://doi.org/10.1371/periodical.pone.0179006

Figures

Abstract

Groundwork

The presence of a built anomaly is associated with increased childhood cancer risk, likely due to big furnishings of Down syndrome and chromosomal anomalies for leukemia. Less is known about associations with presence of non-chromosomal anomalies.

Methods

Records of children diagnosed with cancer at <20 years of historic period during 1984–2013 in Washington State cancer registries were linked to their nativity certificates (N = 4,105). A comparison grouping of children born in the same years was identified. Congenital anomalies were assessed from birth records and diagnosis codes in linked hospital discharge information. Logistic regression was used to gauge odds ratios (OR) and 95% conviction intervals (CI) for cancer, and for specific cancer types in relation to the presence of whatsoever anomaly and specific anomalies.

Results

Having any built anomaly was associated with an increased risk of childhood cancer (OR: one.46, 95% CI 1.28–1.65). Not-chromosomal anomalies were also associated with increased childhood cancer risk overall (OR: i.35; 95% CI: 1.18–1.54), and with increased take chances of several cancer types, including neuroblastoma, renal, hepatoblastoma, soft-tissue sarcoma, and germ cell tumors. Increasing number of non-chromosomal anomalies was associated with a stronger risk of childhood cancer (OR for three+ anomalies: 3.eleven, 95% CI: ane.54–six.11). Although central nervous system (CNS) anomalies were associated with CNS tumors (OR: 6.05, 95% CI two.75–xiii.27), there was no potent evidence of other non-chromosomal anomalies being specifically associated with cancer occurring in the same organ system or anatomic location.

Conclusions

Non-chromosomal anomalies increased take chances of several cancer types. Additionally, we found that increasing number of not-chromosomal anomalies was associated with a stronger risk of cancer. Pooling like information from many regions would increase power to identify specific associations in order to inform molecular studies examining possible mutual developmental pathways in the etiologies of birth defects and cancer.

Citation: Norwood MS, Lupo PJ, Chow EJ, Scheurer ME, Plon SE, Danysh HE, et al. (2017) Childhood cancer risk in those with chromosomal and not-chromosomal congenital anomalies in Washington State: 1984-2013. PLoS ONE 12(half dozen): e0179006. https://doi.org/10.1371/journal.pone.0179006

Editor: Jeffrey South. Chang, National Health Research Institutes, TAIWAN

Received: March 8, 2017; Accepted: May 22, 2017; Published: June viii, 2017

Copyright: © 2017 Norwood et al. This is an open access article distributed nether the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are aggregated and within the paper and its Supporting Information files.

Funding: This project was supported, in role, by inquiry support from the Alex's Lemonade Stand up Foundation for childhood Cancer (B. Mueller and P. Lupo), too as the Cancer Prevention & Research Institute of Texas (CPRIT RP140258; P. Lupo). The funders had no role in study design, data collection and assay, determination to publish, or preparation of the manuscript.

Competing interests: The authors have alleged that no competing interests exist.

Introduction

Built anomalies (i.eastward., birth defects) are 1 of the strongest and virtually consistent risk factors for childhood cancer. Nascence defects are generally categorized every bit chromosomal or non-chromosomal anomalies.[ane] The function of chromosomal anomalies on babyhood cancer risk has been described. For example, children with Down syndrome (DS) have a 20-fold increased hazard of acute lymphoblastic leukemia (ALL) compared to those without DS.[2, three] Similarly, children with chromosome 13q14 deletion syndrome, characterized past dysmorphic facial features, have increased take chances of retinoblastoma.[4] Iv recent population-based registry linkage studies in the United States (U.S.)[2, 5–7] suggest that children with non-chromosomal anomalies may likewise be more likely to develop cancer compared to their unaffected contemporaries.

Evidence of shared biological pathways for congenital anomalies and cancer is express, just possible mechanisms proposed include non-genetic exposures (e.g., environmental exposures) that pb to both conditions;[2] somatic mutations in developmental genes early in embryogenesis leading to tissue mosaicism;[8] or chromosomal microdeletions that include both developmental and cancer predisposition genes.[7] The biological underpinnings of these associations are likely to vary by specific birth defect and specific cancer type.

Few studies take evaluated possible associations of specific not-chromosomal anomalies with specific cancer types, largely due to the rarity of both babyhood cancer and congenital anomalies. Relatively large report sizes can be conducted in dissimilar geographic regions using population-based linked health registry information assuasive compatible measurement of both the congenital bibelot and cancer incidence. Such big linked databases provide rich opportunities to examine the associations of specific anomalies, particularly those that are not chromosomal in origin, with specific cancers. Using linked population-based nascency-cancer-registry-infirmary belch data from Washington State in a case-command epidemiological study, we examined the relationships of built anomalies with babyhood cancers, with a focus on major not-chromosomal anomalies.

Materials and methods

Subject identification

This project was conducted after advisable Institutional Review Lath approvals (expedited reviews with waivers of consent for data linkage to construct analysis files without names) were received from Washington State and the Fred Hutchinson Cancer Inquiry Center. We linked records of all children <20 years onetime diagnosed with cancer in 1974–2014 as identified in the Washington Land population-based cancer incidence registries to Country birth records for the aforementioned years to identify children born in-land (N = 5,876). The cancer registries included the Surveillance, Epidemiology, and Endpoints (SEER) Program-affiliated Cancer Surveillance Organization of Western WA, and the Centers for Disease Control (CDC) National Program of Cancer Registries (NPCR)-affiliated Washington Land Cancer Registry. Linkage of cancer registry and nativity records databases was performed in a stepwise deterministic procedure based on identifiers contained within both resources including: kid name, sex, and nascence date; parental names and maternal birthdate; residential address at delivery and diagnosis; and race/ethnicity. Nascence-infirmary discharge records have been routinely linked since 1987 in Washington State and thus the ICD codes within the hospital discharge records and the nascency record information were available from this linkage. Updated linkages of these cancer registry-birth records data have been conducted periodically during the past several decades, with nativity records generally located for approximately 80% of cancer cases <15 at diagnosis (ranging from 66% - 85% of those 10–14, and <5 years one-time at diagnosis, respectively.) For each case, we randomly selected 10 command children without cancer during the study flow from the remaining birth records, frequency matched on year of birth and sex (Due north = 58,462). Data about the presence of congenital anomalies began in the birth records in 1984, and thus our potential subjects included four,590 cases and 45,653 controls built-in in 1984 or later. After excluding subjects with nonmalignant tumors (Northward = 480), and cervical cancers (Northward = v) (due to their likely clan with HPV infection), there were 4,105 cases for analyses.

Built anomaly ascertainment

Washington birth certificates incorporate checkboxes indicating the presence of maternal and infant conditions, including built anomalies identified at delivery. Additionally, since 1987, Washington nascency certificates accept routinely been linked to hospital discharge records for the birth hospitalization of the infant; these were as well used to identify built anomalies in example and control children, every bit nascence certificate and hospital discharge records used in combination have been demonstrated to improve identification of several weather,[9–eleven] and because birth document data enriched by infirmary belch information for identification of congenital anomalies has greater validity.[12] Washington State hospital discharge records include all hospital discharges in not-Federal facilities. For the study period, this state-wide organization contains International Classification of Diseases-Clinical Modification, 9^th Revision (ICD-9) diagnosis codes for hospitalizations based on Medicare-Medicaid billing standards. During the study years, upward to 25 diagnostic lawmaking fields were present for nascency hospitalizations. We initially screened these for the presence of any congenital anomaly (ICD-9 740–759), and further refined by categorizing atmospheric condition as major or pocket-sized (S1 Table for ICD-9-CM codes).[13] This was further refined using a Centers for Disease Control and Prevention/British Pediatric Clan (CDC/BPA)-modified code with greater item. If the modified lawmaking for a congenital anomaly did not have a direct translation to ICD-9-CM, it was included every bit within the larger ICD-nine-CM category. Anomaly types included: central nervous organisation (CNS); heart/circulatory; oral clefts; gastrointestinal; genital/urinary; chromosomal; musculoskeletal; integument/skin; and other congenital anomalies. Children with both a chromosomal (e.grand., Down syndrome) and a not-chromosomal anomaly (e.1000., oral cleft) were included in the "chromosomal anomaly" category.

Information bachelor.

Variables from the cancer registries included: ICD-O morphology and topography codes, stage, class, histology, age at diagnosis, and diagnosis yr. Cases were classified into groups and subtypes according to the International Classification of Childhood Cancer, 3^rd Edition,[xiv] and past age at diagnosis (<five, 5–nine, 10–19 years). Additional information bachelor from the birth records included demographic characteristics (east.g., parental historic period, race/ethnicity, education); maternal exposures and characteristics (e.g., prenatal smoking, marital status); and birth characteristics (birthweight, gestational length). Data about the blazon of medical insurance used for the kid'south delivery or billed at hospital discharge was obtained from the nativity certificate or from the hospital discharge record (categorized as private insurance vs. Medicaid/Medicare/Clemency Intendance vs. private/other insurance) for use as a proxy indicator of socioeconomic status.

Analyses.

Children were classified every bit indicated past nascence certificate and/or hospital discharge data as having: whatever major congenital anomaly (with or without whatsoever congenital minor anomaly); small-scale congenital anomalies only; or no congenital anomaly. Subsequently initially evaluating the possible function of minor congenital anomalies for childhood cancer, the remainder of the analyses focused on major anomalies only. Nosotros evaluated the number of dissimilar types of congenital anomalies that a child had (e.g., CNS, gastrointestinal). If a child had two congenital anomalies within the aforementioned category, this was considered as having 1 type of anomaly. Nosotros then focused on non-chromosomal anomalies. We evaluated this association overall, and for cancer occurrence at different diagnosis age categories (<v, five–9, 10–19 years) to be consistent with previous assessments.[v] Because congenital anomalies may be associated with babe birthweight or gestational age at commitment, which may too bear on the hazard of cancer occurrence, we conducted sub-analyses of our principal exposures (any major anomaly, major non-chromosomal anomalies) restricted to children with normal birthweight (2500 - <4000g) and term gestation (37 weeks or greater). When numbers permitted, associations between specific anomalies and childhood cancer were examined.

Mantel-Haenszel stratified analyses were initially used to describe group characteristics and evaluate confounding. Logistic regression was used to calculate odds ratios (ORs) and 95% confidence interval (CIs) for the evaluation of childhood cancer take chances in relation to presence of any anomaly, besides as the presence of specific anomalies. Nosotros also estimated the risk of specific cancer types in relation to the presence of whatever bibelot, and (to the extent possible) in relation to specific type of anomaly. ORs were adjusted for the matching variables of nascency year and gender, and for maternal historic period at delivery (12–19, xx–24, 25–29, thirty–34, 35+ years). Other variables considered for their possible furnishings on the OR included maternal prenatal smoking (yes/no), marital status, race/ethnicity (White, Black, Hispanic, Asian, Native American, Pacific Islander, Other), instruction (<12, 12, and 13+ years), and type of wellness insurance. As none of these meaningfully (>x%) altered the ORs, results are adapted for nativity year, sexual practice, and maternal historic period merely. We assessed possible trends of increased run a risk with increasing numbers of anomalies (0,1,ii,3+ and, among those with anomalies only, 1,2,3+; separately for all anomalies and non-chromosomal anomalies) using likelihood ratio tests for adding grouped-linear versions of categorical variables to models including the confounders.

Results

Childhood cancer cases were more likely than controls to accept mothers aged 35 years or older, to be white, or to accept a birthweight >4000g (Tabular array one). The most common types of cancer were leukemia (28%), cardinal nervous system (CNS) tumors (22%), and lymphoma (11%).

A greater proportion of cases (7%) than controls (5%) had at least one major congenital anomaly identified (OR: one.46, 95% CI ane.28–1.65) (Table 2). The presence of any minor bibelot in the absence of a major anomaly (OR: 0.52, 95% CI 0.24–1.ten) or an unspecified anomaly that could not be classified as major or minor (OR: one.01, 95% CI 0.xc–1.14) did non differ markedly in cases and controls. The ORs for childhood cancer increased with increasing numbers of major anomalies, from one.35 (95% CI 1.17–one.55) for a single anomaly to ii.79 (95% CI 1.44–5.43) for 3 or more anomalies. When only non-chromosomal anomalies were considered in relation to any cancer, the OR remained increased (OR: ane.35, 95% CI 1.18–1.54). A similar pattern was observed later brake of analyses to children with normal birthweight (2500 -<4000g) with term (37+ weeks) deliveries.

Increased ORs for childhood cancer were observed for all anomalies, with the exception of oral clefts (OR: 0.56, 95% CI 0.20–ane.52), club human foot (OR: 0.77, 95% CI: 0.18–iii.22), dactyly (OR: 0.99, 95% CI: 0.23–4.xx), spina bifida (OR: 0.84, 95% CI: 0.11–6.38), other CNS anomalies (OR: 0.37; 95% CI: 0.04–three.54), and other circulatory anomalies (OR: 0.89, 95% CI: 0.41–1.93). The issue sizes varied: the greatest OR was observed for chromosomal anomalies (OR: 7.52, 95% CI 5.21–10.84). Large and positive ORs were as well associated with gastrointestinal anomalies (OR: three.07, 95% CI 1.85–v.11) and CNS anomalies (OR two.99, 95% CI: ane.71–5.19). Within general anomalies, selected specific atmospheric condition had increased ORs, including microcephalus (OR: 6.64, 95% CI 1.94–22.75), hydrocephalus (OR: iii.95, 95% CI 1.45–10.74), anal atresia (OR: 4.75, 95% CI 1.49–15.xix), and Down syndrome (OR: 10.86, 95% CI 7.02–16.81).

ORs were increased for the association of anomalies in relation to childhood cancer diagnosed in all age groups, although the magnitudes of the associations were greatest for cancers diagnosed at <5 years of age (Table 3). Modestly increased ORs with CIs including one were noted for cancer diagnosed between 5–9 years of age, although statistically significant associations were noted for cancers diagnosed in the older (x–xix years) age group.

The presence of a chromosomal anomaly was more often than not associated with greater ORs for most types of cancer than was the presence of not-chromosomal anomalies (Fig 1). Non-chromosomal anomalies were associated with greater than two-fold increased hazard of hepatoblastoma (OR: 2.50, 95% CI 1.13–5.53) and germ cell tumors (OR: 2.38, 95% CI one.41–4.03), but also with increased risk for neuroblastoma (OR: 1.93, 95% CI one.32–two.83) and soft-tissue sarcomas (OR: 1.71, 95% CI one.10–2.65). The presence of a chromosomal anomaly was associated with large increased risk for leukemia (OR: 21.65, 95% CI: 14.57–32.15), retinoblastoma (OR: 14.thirty, 95% CI: 4.38–46.72), and renal tumors (OR: 4.70, 95% CI 1.xiv–19.45). Increased ORs for all other cancer types examined except CNS tumors in relation to chromosomal anomalies were also observed, although the estimates were imprecise and conviction intervals included one.

Fig i. Odds Ratios (OR) for the associations of specific childhood cancer types in relation to presence of major non-chromosomal and chromosomal anomalies, amongst children born in Washington Country, 1984–2013.

Estimates adjusted for birth year, sex activity, and maternal historic period. Non-chromosomal anomalies results exclude individuals with concurrent chromosomal anomalies. *Indicates number of cases <5.

https://doi.org/10.1371/journal.pone.0179006.g001

We explored the associations of specific anomaly types in relation to specific types of childhood cancer (Fig 2). The largest ORs were observed for the presence of chromosomal anomalies in relation to leukemia (OR: 21.65, 95% CI 14.57–32.15) and retinoblastoma (OR: 14.30, 95% CI 4.38–46.72), and for the presence of gastrointestinal anomalies in relation to soft-tissue sarcoma (OR: 12.17, 95% CI 4.86–thirty.46). CNS tumors were associated with CNS anomalies (OR: 6.05, 95% CI ii.75–13.27) just not with other anomalies. Almost other not-chromosomal anomalies were associated with several types of cancer. The presence of a gastrointestinal anomaly was associated with increased ORs for germ prison cell, leukemia, neuroblastoma, and soft-tissue sarcoma. Heart anomalies were associated with hepatoblastoma, neuroblastoma, and other unspecified malignancies.

Fig two. Odds ratios for the associations of major bibelot types in relation to types of childhood cancer among children born in Washington State, 1984–2013.

Estimates adjusted for nascence year, sex, and maternal age. Non-chromosomal anomaly results exclude individuals with concurrent chromosomal anomalies. *Indicates number of cases <five.

https://doi.org/10.1371/journal.pone.0179006.g002

Discussion

Built anomalies have been associated with childhood cancer in several prior studies. Our observed overall increased chance for cancer in relation to congenital anomalies is consequent with results of other U.S. population-based data linkage studies based on data from California,[half-dozen] Texas,[2] Oklahoma,[5] and a pooled analysis of information from 3 other states (Utah, Arizona, and Iowa, i.east., UTAZIA).[7] Similar results accept been reported in population-based health registry studies in Commonwealth of australia,[15] Canada,[16] the United Kingdom,[17] and Norway and Sweden.[eighteen] While the association of chromosomal anomalies with babyhood cancer occurrence has been fairly well established in previous population-based data linkage studies, with population-based studies reporting estimates of >ten-fold increased gamble.[ii, 6, 7], the majority of anomalies are non-chromosomal in origin. Our written report lends to the growing body of show that non-chromosomal anomalies are also associated with childhood cancer chance.[ii, 5–7] Additionally, our results indicate that an increasing number of non-chromosomal anomalies was more strongly associated with increased cancer risk compared to those children with only one non-chromosomal bibelot (OR for three or more anomalies: three.xi, 95% CI: 1.54–6.xi vs. OR for one anomaly: one.29, 95% CI: ane.12–1.49). This may suggest that children with previously unidentified multiple malformation syndromes (and no obvious chromosomal anomaly) may be at a significant risk of cancer.

Our data confirm the association between chromosomal anomalies and babyhood cancer, including the well documented clan of Downwardly syndrome and acute leukemia. Although in that location take been efforts to identify factors associated with astute lymphoblastic leukemia in children with Downwardly syndrome (due east.g., maternal health atmospheric condition and irradiation), most results accept been null.[19, 20] Our results also back up an association between having a chromosomal bibelot with risk of retinoblastoma, which is consistent with other studies.[2] It is likely the primary commuter backside this association is an autosomal deletion of 13q14, which includes the RB1 factor, a germline predisposition gene for retinoblastoma.[21] Nosotros besides observed an association of chromosomal anomalies with renal tumors (e.g., Wilms tumor). Notably, Wilms tumor, aniridia, genitourinary anomalies, and mental retardation (i.east., WAGR syndrome) are a prepare of conditions associated with a deletion on 11p13, which includes the WT1 gene.[22]

Our results indicate an increased risk of childhood cancer in relation to presence of anomalies for cancers diagnosed in all age groups. When only non-chromosomal anomalies were considered, the run a risk estimates generally remained increased, supporting results of other studies indicating an association with childhood cancer diagnosed at dissimilar ages, merely with a slight decrease in risk with attained age.[5] We also observed increased cancer risk in relation to increasing number of anomalies present, which is consistent with one before written report.[18] Also consistent with other population-based data linkage studies that examined non-chromosomal anomalies, we observed increased risks of selected cancer types. Nosotros found associations between having major non-chromosomal anomalies and increased risks of neuroblastoma, hepatoblastoma, soft-tissue sarcoma, and germ cell tumors. With the exception of leukemia, retinoblastoma, and bone tumors, we observed increased risks amongst all other cancer types still these associations were not statistically meaning.

Notably, our study supports other recent population-based registry linkage studies in demonstrating the relationship between non-chromosomal anomalies and childhood cancer.[5–7] Our overall effect approximate for the risk of cancer among children with not-chromosomal anomalies (OR = i.35) was only slightly attenuated compared to those reported by Janitz et al. (HR = 2.50)[five], Botto et al. (incidence rate ratio [IRR] = ii.00),[7] and Fisher et al. (Hour = one.58).

We did note specific cancer types associated with having non-chromosomal anomalies. For example, the OR for neuroblastoma in relation to non-chromosomal anomalies (OR = 1.90) was largely consequent with two previous U.Southward. registry linkage studies evaluating the adventure of this malignancy in children with non-chromosomal anomalies (Hour = two.85[half dozen] and IRR = 2.21[seven]). Besides, we observed a positive clan of non-chromosomal anomalies with hepatoblastoma, consequent with the just other U.Southward. registry linkage study (UTAZIA written report) to evaluate this item relationship, although the effect size was larger in that cess (IRR = fourteen.47 vs. our OR = 2.45).[vii] Having a not-chromosomal anomaly was associated with soft-tissue sarcomas, consistent with the i U.S. registry linkage study evaluating this specific human relationship.[5] Our observed association with renal tumors (OR = one.71) was stronger than reported in the California (Hr = ane.45) and UTAZIA (IRR = 1.03) studies.[6, 23] Finally, our observation of a positive association betwixt germ jail cell tumors and non-chromosomal anomalies supports results of other studies that were able to assess this clan.[5, 6, 23]

In our cess, non-chromosomal anomalies overall were non strongly associated with leukemia, lymphoma or CNS tumors, consistent with results of the other U.South. registry linkage studies.[five, 6, 23], despite differences in birth defect surveillance across studies. (Washington does not have an active birth defects surveillance program as in California, Utah, Iowa, and Oklahoma.) Notably, the prevalence of built anomalies was slightly higher in our assessment (v.5%) when compared to these states (e.g., ~4% [2, 5]), however, the ascertainment of anomalies was independent of case status in our assessment, and therefore uniform for those children who did and did not develop cancer, which reduces the likelihood of differential misclassification.

Bated from an clan of CNS anomalies with CNS tumors (an association that may be due to reverse causation given the majority of these anomalies were hydrocephalus-related), there was no potent testify that non-chromosomal anomalies were likely to be specifically associated with babyhood cancer occurring in the same organ system or anatomic location, although our power to investigate this was limited past small numbers. Although neuroblastoma was associated with eye and gastrointestinal anomalies, it was also associated with musculoskeletal and skin anomalies. Few studies have been able to examine associations of specific non-chromosomal anomalies with specific cancer types, but of these, a generally consistent finding is an association of CNS defects with CNS tumors,[8, 18, 24] as nosotros observed.

An of import force of our study was utilize of linked population-based health registry data, assuasive us to avoid some biases that may exist nowadays in clinic-based or interview studies. We also increased the sensitivity of birth defect ascertainment by utilizing specific diagnostic codes in addition to birth record information. We were able to examine specific congenital anomalies. Our study must also exist considered in the light of certain limitations. In order to identify major and minor anomalies, we used the classification system developed by Rasmussen and colleagues,[13] which utilizes CDC-BPA codes that are more specific than the ICD-9 codes available to united states for this written report. Despite our ability to utilize linked hospital discharge records, our ascertainment of anomalies is probable less complete than for studies using data from active birth defects surveillance programs.[5, 15–17] Yet, several birth defects surveillance programs only monitor specific anomalies, whereas we evaluated all congenital anomalies. It is also possible that some children in the control group may take moved out-of-state and been diagnosed with cancer elsewhere, however as babyhood cancer is quite rare, any consequence of this is likely minimal and would bias towards the zip. Because of the availability of nascency and cancer registry information during different time periods, some children diagnosed in earlier study years at older ages would not have been included, however sensitivity analyses restricting subjects to only those with like opportunity (e.grand., at least 5 years; at least 10 years) to have been identified in the cancer registry did not substantially alter results (S2 Table). We were as well express in our power to evaluate possible associations with minor anomalies which may not be detected until later in a child's life, and would not appear on birth certificates or infirmary belch records for the birth hospitalization. Finally, children with some types of congenital anomalies may dice prematurely and therefore lack the opportunity to develop babyhood cancer, which could peradventure attenuate our associations.[5]

The etiologies of about non-chromosomal anomalies are largely unknown,[1] despite evidence that factors such as maternal obesity, prenatal smoking, and some chemical or environmental exposures may increase the occurrence of certain defect types.[one, 25] Our knowledge of childhood cancer causes is similarly express, with few recognized external etiologies (east.g., ionizing radiation) although common variation and intrinsic factors such as birthweight and parental age are consistently associated with childhood cancers. Identification of factors associated with progression from defect presence to cancer occurrence, or of shared pathways (genetic and environmental) for both conditions may elucidate potential mechanisms to modify cancer chance. Futurity assessments should include pooling efforts across multiple regions. This will optimize our ability to identify associations between specific congenital anomalies and specific cancers. The ultimate goal of this piece of work would exist to inform screening strategies for children at loftier gamble of developing cancer.

Supporting information

Acknowledgments

This project was supported, in role, by research support from the Alex's Lemonade Stand Foundation for Childhood Cancer (B. Mueller and P. Lupo), as well as the Cancer Prevention & Research Found of Texas (CPRIT RP140258; P. Lupo). We also thank the Washington State Department of Health for Data Access and Mr. Bill O'Brien for programming and data direction assistance.

Writer Contributions

1. Conceptualization: MN PL BM.
2. Data curation: MN DD BM.
3. Formal assay: MN PL DD BM.
4. Funding acquisition: PL MS SP BM.
5. Investigation: MN PL BM.
6. Methodology: MN PL BM.
7. Project administration: PL Hard disk drive BM.
8. Resources: MN PL BM.
9. Supervision: PL SP BM.
10. Validation: MN DD BM.
11. Visualization: MN DD.
12. Writing – original draft: MN PL BM.
13. Writing – review & editing: MN PL EC MS SP HD LS SC DD BM.

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Source: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0179006

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