what congenital malformation is commonly linked to acute leukemia in children

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Research Article

Babyhood cancer risk in those with chromosomal and not-chromosomal built anomalies in Washington State: 1984-2013

• Marlena Southward. Norwood,
• Philip J. Lupo,
• Eric J. Grub,
• Michael Due east. Scheurer,
• Sharon East. Plon,
• Heather E. 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

Background

The presence of a congenital bibelot is associated with increased babyhood cancer run a risk, likely due to big effects of Downward syndrome and chromosomal anomalies for leukemia. Less is known most associations with presence of non-chromosomal anomalies.

Methods

Records of children diagnosed with cancer at <twenty years of age during 1984–2013 in Washington State cancer registries were linked to their nascence certificates (North = 4,105). A comparing group of children born in the aforementioned years was identified. Congenital anomalies were assessed from birth records and diagnosis codes in linked infirmary discharge information. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for cancer, and for specific cancer types in relation to the presence of any anomaly and specific anomalies.

Results

Having any congenital anomaly was associated with an increased take chances of babyhood cancer (OR: ane.46, 95% CI 1.28–1.65). Non-chromosomal anomalies were also associated with increased childhood cancer risk overall (OR: 1.35; 95% CI: ane.eighteen–one.54), and with increased take chances of several cancer types, including neuroblastoma, renal, hepatoblastoma, soft-tissue sarcoma, and germ prison cell tumors. Increasing number of not-chromosomal anomalies was associated with a stronger risk of babyhood cancer (OR for 3+ anomalies: iii.xi, 95% CI: 1.54–half-dozen.xi). Although key nervous arrangement (CNS) anomalies were associated with CNS tumors (OR: six.05, 95% CI 2.75–xiii.27), there was no stiff 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 risk of several cancer types. Additionally, we establish that increasing number of not-chromosomal anomalies was associated with a stronger chance of cancer. Pooling similar information from many regions would increase power to identify specific associations in social club to inform molecular studies examining possible mutual developmental pathways in the etiologies of birth defects and cancer.

Commendation: Norwood MS, Lupo PJ, Chow EJ, Scheurer ME, Plon SE, Danysh HE, et al. (2017) Childhood cancer take a chance in those with chromosomal and non-chromosomal congenital anomalies in Washington State: 1984-2013. PLoS One 12(6): e0179006. https://doi.org/10.1371/periodical.pone.0179006

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

Received: March eight, 2017; Accepted: May 22, 2017; Published: June eight, 2017

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

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

Funding: This project was supported, in part, by inquiry back up from the Alex'due south Lemonade Stand Foundation for childhood Cancer (B. Mueller and P. Lupo), as well as the Cancer Prevention & Enquiry Plant of Texas (CPRIT RP140258; P. Lupo). The funders had no role in study design, information collection and analysis, determination to publish, or preparation of the manuscript.

Competing interests: The authors take declared that no competing interests exist.

Introduction

Congenital anomalies (i.due east., birth defects) are i of the strongest and nigh consistent gamble factors for childhood cancer. Birth defects are generally categorized as chromosomal or non-chromosomal anomalies.[1] The role of chromosomal anomalies on babyhood cancer take a chance has been described. For example, children with Down syndrome (DS) take a 20-fold increased risk of astute lymphoblastic leukemia (ALL) compared to those without DS.[2, 3] Similarly, children with chromosome 13q14 deletion syndrome, characterized past dysmorphic facial features, have increased risk of retinoblastoma.[4] Four recent population-based registry linkage studies in the U.s. (U.South.)[2, 5–7] suggest that children with non-chromosomal anomalies may also be more likely to develop cancer compared to their unaffected contemporaries.

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

Few studies have evaluated possible associations of specific non-chromosomal anomalies with specific cancer types, largely due to the rarity of both childhood cancer and congenital anomalies. Relatively large study sizes tin can be conducted in different geographic regions using population-based linked health registry information assuasive uniform measurement of both the built anomaly 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 birth-cancer-registry-infirmary discharge data from Washington Land in a case-control epidemiological study, nosotros examined the relationships of built anomalies with childhood cancers, with a focus on major non-chromosomal anomalies.

Materials and methods

Subject identification

This project was conducted later on appropriate Institutional Review Board approvals (expedited reviews with waivers of consent for data linkage to construct assay files without names) were received from Washington State and the Fred Hutchinson Cancer Research Center. We linked records of all children <20 years old diagnosed with cancer in 1974–2014 as identified in the Washington State population-based cancer incidence registries to Land birth records for the same years to identify children born in-country (N = 5,876). The cancer registries included the Surveillance, Epidemiology, and Endpoints (SEER) Program-affiliated Cancer Surveillance System of Western WA, and the Centers for Disease Control (CDC) National Plan of Cancer Registries (NPCR)-affiliated Washington State Cancer Registry. Linkage of cancer registry and birth records databases was performed in a stepwise deterministic procedure based on identifiers contained inside both resources including: kid name, sexual activity, and nascence date; parental names and maternal birthdate; residential accost at delivery and diagnosis; and race/ethnicity. Birth-infirmary discharge records take been routinely linked since 1987 in Washington Country and thus the ICD codes within the infirmary discharge records and the nascency record information were available from this linkage. Updated linkages of these cancer registry-nativity records data have been conducted periodically during the past several decades, with birth records by and large located for approximately fourscore% of cancer cases <xv at diagnosis (ranging from 66% - 85% of those 10–14, and <five years onetime at diagnosis, respectively.) For each example, we randomly selected x control children without cancer during the study period from the remaining nascency records, frequency matched on twelvemonth of nascence and sex (North = 58,462). Information virtually the presence of built anomalies began in the birth records in 1984, and thus our potential subjects included iv,590 cases and 45,653 controls born in 1984 or subsequently. Later on excluding subjects with nonmalignant tumors (N = 480), and cervical cancers (N = 5) (due to their likely association with HPV infection), there were 4,105 cases for analyses.

Built anomaly ascertainment

Washington birth certificates contain checkboxes indicating the presence of maternal and infant conditions, including congenital anomalies identified at delivery. Additionally, since 1987, Washington birth certificates have routinely been linked to hospital belch records for the nascence hospitalization of the babe; these were also used to identify congenital anomalies in case and command children, as birth certificate and hospital discharge records used in combination have been demonstrated to improve identification of several conditions,[9–11] and considering nascence document data enriched by hospital discharge information for identification of congenital anomalies has greater validity.[12] Washington Country hospital discharge records include all hospital discharges in non-Federal facilities. For the study menstruum, this land-wide system contains International Classification of Diseases-Clinical Modification, nine^th Revision (ICD-9) diagnosis codes for hospitalizations based on Medicare-Medicaid billing standards. During the report years, upwardly to 25 diagnostic code fields were present for nascence hospitalizations. Nosotros initially screened these for the presence of whatsoever congenital bibelot (ICD-nine 740–759), and further refined by categorizing weather condition as major or minor (S1 Tabular array for ICD-ix-CM codes).[13] This was further refined using a Centers for Affliction Control and Prevention/British Pediatric Clan (CDC/BPA)-modified lawmaking with greater detail. If the modified code for a built anomaly did not have a direct translation to ICD-9-CM, it was included equally inside the larger ICD-9-CM category. Anomaly types included: central nervous organization (CNS); heart/circulatory; oral clefts; gastrointestinal; genital/urinary; chromosomal; musculoskeletal; integument/skin; and other built anomalies. Children with both a chromosomal (e.g., Downwards syndrome) and a non-chromosomal anomaly (e.g., oral cleft) were included in the "chromosomal anomaly" category.

Information available.

Variables from the cancer registries included: ICD-O morphology and topography codes, stage, course, histology, age at diagnosis, and diagnosis year. Cases were classified into groups and subtypes co-ordinate to the International Nomenclature of Babyhood Cancer, 3^rd Edition,[xiv] and by age at diagnosis (<v, 5–nine, 10–19 years). Additional information bachelor from the birth records included demographic characteristics (east.k., parental age, race/ethnicity, education); maternal exposures and characteristics (e.1000., prenatal smoking, marital status); and birth characteristics (birthweight, gestational length). Information about the type of medical insurance used for the child's delivery or billed at hospital discharge was obtained from the birth certificate or from the hospital belch record (categorized every bit individual insurance vs. Medicaid/Medicare/Charity Care vs. individual/other insurance) for use as a proxy indicator of socioeconomic status.

Analyses.

Children were classified as indicated by nativity document and/or infirmary belch data as having: any major congenital anomaly (with or without any built minor anomaly); minor congenital anomalies only; or no congenital anomaly. Later initially evaluating the possible office of minor built anomalies for childhood cancer, the remainder of the analyses focused on major anomalies only. Nosotros evaluated the number of different types of congenital anomalies that a child had (e.1000., CNS, gastrointestinal). If a child had two built anomalies inside the same category, this was considered every bit having 1 type of anomaly. Nosotros then focused on not-chromosomal anomalies. We evaluated this association overall, and for cancer occurrence at different diagnosis age categories (<5, 5–9, 10–19 years) to exist consistent with previous assessments.[v] Because congenital anomalies may be associated with baby birthweight or gestational age at delivery, which may besides bear on the chance of cancer occurrence, nosotros conducted sub-analyses of our main exposures (whatsoever 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 summate odds ratios (ORs) and 95% confidence interval (CIs) for the evaluation of childhood cancer take a chance in relation to presence of any anomaly, as well as the presence of specific anomalies. We also estimated the risk of specific cancer types in relation to the presence of any anomaly, and (to the extent possible) in relation to specific type of anomaly. ORs were adjusted for the matching variables of nascence yr and gender, and for maternal age at delivery (12–xix, twenty–24, 25–29, 30–34, 35+ years). Other variables considered for their possible effects on the OR included maternal prenatal smoking (yes/no), marital status, race/ethnicity (White, Blackness, Hispanic, Asian, Native American, Pacific Islander, Other), didactics (<12, 12, and thirteen+ years), and type of health insurance. Every bit none of these meaningfully (>10%) contradistinct the ORs, results are adapted for nativity year, sex, and maternal age only. We assessed possible trends of increased chance with increasing numbers of anomalies (0,1,2,3+ and, among those with anomalies only, one,2,three+; 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 than probable than controls to have mothers aged 35 years or older, to be white, or to have a birthweight >4000g (Table 1). The virtually common types of cancer were leukemia (28%), central nervous organisation (CNS) tumors (22%), and lymphoma (eleven%).

A greater proportion of cases (seven%) than controls (five%) had at to the lowest degree ane major built anomaly identified (OR: one.46, 95% CI 1.28–one.65) (Tabular array 2). The presence of any minor anomaly in the absenteeism of a major anomaly (OR: 0.52, 95% CI 0.24–1.10) or an unspecified anomaly that could not exist classified as major or minor (OR: 1.01, 95% CI 0.90–one.fourteen) did non differ markedly in cases and controls. The ORs for babyhood cancer increased with increasing numbers of major anomalies, from 1.35 (95% CI one.17–1.55) for a single anomaly to 2.79 (95% CI 1.44–v.43) for three or more anomalies. When only non-chromosomal anomalies were considered in relation to any cancer, the OR remained increased (OR: i.35, 95% CI 1.xviii–1.54). A similar pattern was observed after 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–one.52), club pes (OR: 0.77, 95% CI: 0.18–3.22), dactyly (OR: 0.99, 95% CI: 0.23–4.xx), spina bifida (OR: 0.84, 95% CI: 0.eleven–6.38), other CNS anomalies (OR: 0.37; 95% CI: 0.04–3.54), and other circulatory anomalies (OR: 0.89, 95% CI: 0.41–i.93). The outcome sizes varied: the greatest OR was observed for chromosomal anomalies (OR: seven.52, 95% CI 5.21–10.84). Large and positive ORs were besides associated with gastrointestinal anomalies (OR: 3.07, 95% CI 1.85–5.11) and CNS anomalies (OR ii.99, 95% CI: ane.71–5.19). Within general anomalies, selected specific conditions had increased ORs, including microcephalus (OR: half dozen.64, 95% CI 1.94–22.75), hydrocephalus (OR: 3.95, 95% CI 1.45–10.74), anal atresia (OR: 4.75, 95% CI one.49–15.19), and Down's syndrome (OR: 10.86, 95% CI 7.02–16.81).

ORs were increased for the clan of anomalies in relation to babyhood cancer diagnosed in all age groups, although the magnitudes of the associations were greatest for cancers diagnosed at <v 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 meaning associations were noted for cancers diagnosed in the older (x–19 years) age grouping.

The presence of a chromosomal anomaly was generally associated with greater ORs for most types of cancer than was the presence of non-chromosomal anomalies (Fig 1). Non-chromosomal anomalies were associated with greater than two-fold increased risk of hepatoblastoma (OR: 2.50, 95% CI 1.13–5.53) and germ cell tumors (OR: 2.38, 95% CI 1.41–4.03), but besides with increased risk for neuroblastoma (OR: ane.93, 95% CI ane.32–2.83) and soft-tissue sarcomas (OR: i.71, 95% CI i.10–ii.65). The presence of a chromosomal anomaly was associated with large increased chance for leukemia (OR: 21.65, 95% CI: xiv.57–32.15), retinoblastoma (OR: fourteen.30, 95% CI: 4.38–46.72), and renal tumors (OR: 4.70, 95% CI 1.14–19.45). 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 confidence intervals included one.

Fig 1. Odds Ratios (OR) for the associations of specific childhood cancer types in relation to presence of major non-chromosomal and chromosomal anomalies, amidst children built-in in Washington State, 1984–2013.

Estimates adjusted for birth twelvemonth, sex, and maternal age. Not-chromosomal anomalies results exclude individuals with concurrent chromosomal anomalies. *Indicates number of cases <v.

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

We explored the associations of specific anomaly types in relation to specific types of babyhood 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 four.38–46.72), and for the presence of gastrointestinal anomalies in relation to soft-tissue sarcoma (OR: 12.17, 95% CI 4.86–30.46). CNS tumors were associated with CNS anomalies (OR: half-dozen.05, 95% CI 2.75–thirteen.27) but not with other anomalies. About 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. Center anomalies were associated with hepatoblastoma, neuroblastoma, and other unspecified malignancies.

Fig 2. Odds ratios for the associations of major anomaly types in relation to types of childhood cancer among children born in Washington State, 1984–2013.

Estimates adjusted for birth year, sexual practice, and maternal age. Non-chromosomal bibelot results exclude individuals with concurrent chromosomal anomalies. *Indicates number of cases <v.

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

Word

Congenital anomalies have been associated with babyhood cancer in several prior studies. Our observed overall increased risk for cancer in relation to congenital anomalies is consistent with results of other U.Due south. population-based data linkage studies based on data from California,[6] Texas,[2] Oklahoma,[5] and a pooled analysis of information from three other states (Utah, Arizona, and Iowa, i.e., UTAZIA).[7] Like results have been reported in population-based health registry studies in Australia,[15] Canada,[16] the United kingdom,[17] and Kingdom of norway and Sweden.[18] While the association of chromosomal anomalies with childhood cancer occurrence has been fairly well established in previous population-based information linkage studies, with population-based studies reporting estimates of >10-fold increased risk.[2, vi, 7], the bulk of anomalies are non-chromosomal in origin. Our study lends to the growing trunk of evidence that non-chromosomal anomalies are likewise associated with childhood cancer adventure.[two, 5–7] Additionally, our results indicate that an increasing number of non-chromosomal anomalies was more than strongly associated with increased cancer chance compared to those children with only one not-chromosomal anomaly (OR for iii or more anomalies: 3.11, 95% CI: 1.54–six.11 vs. OR for one bibelot: 1.29, 95% CI: ane.12–i.49). This may suggest that children with previously unidentified multiple malformation syndromes (and no obvious chromosomal anomaly) may be at a meaning risk of cancer.

Our data confirm the association betwixt chromosomal anomalies and childhood cancer, including the well documented association of Downwardly syndrome and acute leukemia. Although there accept been efforts to identify factors associated with astute lymphoblastic leukemia in children with Down syndrome (east.g., maternal health conditions and irradiation), most results take been cypher.[19, xx] Our results too support an clan between having a chromosomal anomaly with risk of retinoblastoma, which is consistent with other studies.[2] Information technology is likely the primary driver behind this association is an autosomal deletion of 13q14, which includes the RB1 gene, a germline predisposition factor for retinoblastoma.[21] We too observed an association of chromosomal anomalies with renal tumors (eastward.g., Wilms tumor). Notably, Wilms tumor, aniridia, genitourinary anomalies, and mental retardation (i.east., WAGR syndrome) are a set 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 historic period groups. When only non-chromosomal anomalies were considered, the risk estimates by and large remained increased, supporting results of other studies indicating an association with childhood cancer diagnosed at different ages, only with a slight decrease in risk with attained age.[five] We as well observed increased cancer risk in relation to increasing number of anomalies present, which is consistent with one before written report.[18] As well consistent with other population-based data linkage studies that examined non-chromosomal anomalies, we observed increased risks of selected cancer types. We found associations between having major non-chromosomal anomalies and increased risks of neuroblastoma, hepatoblastoma, soft-tissue sarcoma, and germ prison cell tumors. With the exception of leukemia, retinoblastoma, and bone tumors, we observed increased risks among all other cancer types notwithstanding these associations were not statistically significant.

Notably, our study supports other contempo population-based registry linkage studies in demonstrating the relationship between non-chromosomal anomalies and childhood cancer.[5–vii] Our overall outcome estimate for the risk of cancer among children with non-chromosomal anomalies (OR = 1.35) was only slightly adulterate compared to those reported by Janitz et al. (HR = two.l)[5], Botto et al. (incidence rate ratio [IRR] = ii.00),[7] and Fisher et al. (HR = 1.58).

We did annotation specific cancer types associated with having not-chromosomal anomalies. For case, the OR for neuroblastoma in relation to non-chromosomal anomalies (OR = 1.ninety) was largely consistent with two previous U.Southward. registry linkage studies evaluating the risk of this malignancy in children with non-chromosomal anomalies (60 minutes = 2.85[6] and IRR = 2.21[7]). Also, we observed a positive association of not-chromosomal anomalies with hepatoblastoma, consistent with the but other U.Southward. registry linkage report (UTAZIA study) to evaluate this particular human relationship, although the consequence size was larger in that cess (IRR = 14.47 vs. our OR = 2.45).[vii] Having a not-chromosomal anomaly was associated with soft-tissue sarcomas, consistent with the one U.S. registry linkage study evaluating this specific relationship.[5] Our observed association with renal tumors (OR = 1.71) was stronger than reported in the California (Hour = 1.45) and UTAZIA (IRR = one.03) studies.[six, 23] Finally, our observation of a positive association between germ cell tumors and non-chromosomal anomalies supports results of other studies that were able to appraise this clan.[5, half-dozen, 23]

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

Aside from an association 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 strong evidence that non-chromosomal anomalies were likely to be specifically associated with babyhood cancer occurring in the aforementioned organ system or anatomic location, although our power to investigate this was limited past small numbers. Although neuroblastoma was associated with middle and gastrointestinal anomalies, information technology was as well associated with musculoskeletal and pare 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, eighteen, 24] equally we observed.

An of import strength of our study was utilize of linked population-based health registry data, allowing us to avoid some biases that may be present in clinic-based or interview studies. Nosotros besides increased the sensitivity of birth defect ascertainment by utilizing specific diagnostic codes in add-on to nascence record information. Nosotros were able to examine specific built anomalies. Our study must also exist considered in the light of certain limitations. In lodge to identify major and minor anomalies, we used the nomenclature system adult by Rasmussen and colleagues,[13] which utilizes CDC-BPA codes that are more specific than the ICD-ix codes bachelor to u.s. for this study. Despite our ability to use linked hospital belch 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 nascence defects surveillance programs simply monitor specific anomalies, whereas we evaluated all congenital anomalies. It is also possible that some children in the control grouping may have moved out-of-state and been diagnosed with cancer elsewhere, still as childhood cancer is quite rare, any upshot of this is likely minimal and would bias towards the null. Because of the availability of birth and cancer registry information during different fourth dimension periods, some children diagnosed in earlier written report years at older ages would not take been included, however sensitivity analyses restricting subjects to only those with similar opportunity (e.one thousand., at to the lowest degree 5 years; at least 10 years) to accept been identified in the cancer registry did not substantially change results (S2 Table). We were also limited in our ability to evaluate possible associations with small anomalies which may not be detected until later in a child's life, and would not appear on birth certificates or hospital discharge records for the nascency hospitalization. Finally, children with some types of built anomalies may die prematurely and therefore lack the opportunity to develop childhood cancer, which could possibly attenuate our associations.[5]

The etiologies of near non-chromosomal anomalies are largely unknown,[1] despite prove that factors such as maternal obesity, prenatal smoking, and some chemic or environmental exposures may increase the occurrence of certain defect types.[one, 25] Our knowledge of childhood cancer causes is similarly limited, with few recognized external etiologies (east.g., ionizing radiation) although mutual variation and intrinsic factors such as birthweight and parental age are consistently associated with babyhood cancers. Identification of factors associated with progression from defect presence to cancer occurrence, or of shared pathways (genetic and ecology) for both conditions may elucidate potential mechanisms to modify cancer risk. Future 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 work would exist to inform screening strategies for children at high risk of developing cancer.

Supporting data

Acknowledgments

This project was supported, in part, by research back up from the Alex'due south Lemonade Stand Foundation for Babyhood Cancer (B. Mueller and P. Lupo), as well as the Cancer Prevention & Research Constitute of Texas (CPRIT RP140258; P. Lupo). We besides give thanks the Washington State Department of Wellness for Data Admission and Mr. Pecker O'Brien for programming and data management assistance.

Author Contributions

1. Conceptualization: MN PL BM.
2. Data curation: MN DD BM.
3. Formal analysis: MN PL DD BM.
4. Funding acquisition: PL MS SP BM.
5. Investigation: MN PL BM.
6. Methodology: MN PL BM.
7. Project assistants: 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 Hard disk LS SC DD BM.

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