The relationship between congenital heart disease and cancer in Swedish children: A population-based cohort study.

BACKGROUND: Birth defects have been consistently associated with elevated childhood cancer risks; however, the relationship between congenital heart disease (CHD) and childhood cancer remains conflicting. Considering the increasing patient population with CHD after improvements in their life expectancies, insights into this relationship are particularly compelling. Thus, we aimed to determine the relationship between CHD and cancer in Swedish children. METHODS AND
FINDINGS: All individuals registered in the Swedish Medical Birth Register (MBR) between 1973 and 2014 were included in this population-based cohort study (n = 4,178,722). Individuals with CHD (n = 66,892) were identified from the MBR and National Patient Register, whereas cancer diagnoses were retrieved from the Swedish Cancer Register. The relationship between CHD and childhood cancer (<20 years at diagnosis) was evaluated using Cox proportional hazards regression models. We observed increased risks of cancer overall, leukemia, lymphoma, and hepatoblastoma in children with CHD, but after adjustment for Down syndrome, only the increased lymphoma (hazard ratio (HR) = 1.64, 95% confidence interval (CI) 1.11 to 2.44) and hepatoblastoma (HR = 3.94, 95% CI 1.83 to 8.47) risk remained. However, when restricting to CHD diagnoses from the MBR only, i.e., those diagnosed around birth, the risk for childhood cancer overall (HR = 1.45, 95% CI 1.23 to 1.71) and leukemia (HR = 1.41, 95% CI 1.08 to 1.84) was more pronounced, even after controlling for Down syndrome. Finally, a substantially elevated lymphoma risk (HR = 8.13, 95% CI 4.06 to 16.30) was observed in children with complex CHD. Limitations of the study include the National Patient Register not being nationwide until 1987, in addition to the rareness of the conditions under study providing limited power for analyses on the rarer cancer subtypes.
CONCLUSIONS: We found associations between CHD and childhood lymphomas and hepatoblastomas not explained by a diagnosis of Down syndrome. Stronger associations were observed in complex CHD.

Introduction

Birth defects or congenital anomalies affect about 5% to 7% of newborns [1] and are the leading cause of infant mortality [2]. They also have a profound impact on live-born children, causing an array of long-term physical, physiologic, or developmental disabilities—including cancer [2,3]. Congenital heart disease (CHD) constitutes the most common birth defect and occurs in approximately 1% of all births [4]. In recent years, the prevalence of CHD has increased due to advances in pediatric care and surgical therapies [5]; thus, children with CHD are increasingly living into adulthood [4].

Several studies have explored the relationship between birth defects and childhood cancer risk, with current evidence pointing toward a higher cancer incidence in children with birth defects [3,6,7]. A recent systematic review noted an increased risk for overall childhood cancer, as well as for certain specific birth defect and cancer subtype combinations [8]. A leading theory is that a common genetic abnormality impairing normal development is predisposing toward both birth defects and subsequent cancerous growth [8]. However, there is limited research regarding the relationship between CHD and cancer risk. Some studies suggest a potentially elevated cancer risk in both children and adults among patients with a diagnosis of CHD [4,7,9,10]. The suggested biological mechanisms underlying such a relationship include shared genetic mutations [11], radiation exposure from imaging and therapeutic cardiac procedures, lifestyle adaptations owning to the disease [10], and the association with cancer-linked syndromes such as Down syndrome [12,13]. In fact, in a recent register-based Danish study, the modestly elevated cancer risk observed among persons with CHD disappeared when excluding persons with Down syndrome [12].

The relationship between CHD and cancer risk, therefore, remains conflicting and poorly understood. Thus, our aim was to utilize the population-based Swedish health data registers to determine the relationship between CHD and cancer risk in Swedish children and adolescents and evaluate whether CHD complexity affects the association.

Methods

This population-based cohort study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (S1 STROBE Checklist) and was conducted according to a prospective analysis plan (S1 Analysis Plan). In addition to this plan, we evaluated the relationship between CHD complexity and childhood cancer risk, as well as 2 additional cancer subtypes: hepatoblastoma and neuroblastoma.

The Swedish Medical Birth Register (MBR), established in 1973 and comprising data on practically all deliveries in Sweden [14], was used to identify the study population: All individuals born in Sweden between 1973 and 2014 and registered in the MBR were eligible for inclusion (n = 4,282,914; S1 Fig). The MBR records, among other information, health conditions detected during prenatal, delivery, and neonatal care, coded according to the International Classification of Diseases (ICD). To identify children with CHD not diagnosed at birth, we also linked the study population to the National Patient Register, by using the unique personal identity number [15]. The Patient Register, initiated in 1964, achieved universal coverage of inpatient care in Sweden in 1987; outpatient care is also covered since 2001 [16]. Individuals were considered as having CHD if they had been assigned at least 1 diagnostic code for CHD in either register (n = 66,892). As potentially increased medical monitoring in relation to a cancer diagnosis might result in detecting mild forms of CHD that might have remained otherwise unnoticed, only individuals with a CHD diagnosis from the Patient Register at least 2 years before any cancer diagnosis were classified as having CHD—whereas all children diagnosed with CHD in the MBR, i.e., at birth, were classified as having CHD. As the criterion introduced for considering diagnoses from the Patient Register might lead to individuals who do not develop cancer having more time to be diagnosed with CHD, we further restricted the CHD diagnosis up to age 19 (a deviation from our original analysis plan). As CHD is a condition present from birth regardless of when it is diagnosed, individuals with a diagnosis from the Patient Register who fulfilled the above criteria were considered exposed from birth. Additionally, CHD was categorized into mild–moderate and severe based on the ICD codes reported in the MBR or the Patient Register, according to the categorization used by Collins and colleagues [4], adapted from Warnes and colleagues [17] (S1 Table). If several codes were reported for the same individual, the categorization was based on the most severe condition. The ICD codes used were often nonspecific, leading to an imperfect demarcation of CHD complexity. As this was most pronounced among mild and moderate CHD, we combined these 2 categories. Finally, when the registered ICD code was general enough that it could apply to any category, the condition was categorized as mild–moderate.

The study population was further linked to the Swedish Cancer Register to retrieve cancer diagnoses. The Cancer Register was established in 1958 and covers the whole population; it is considered to have high quality and completeness and underreporting is generally low [18]. Cancers occurring before age 20 were considered as childhood and adolescent cancer, and the ICD versions used by the Cancer Register were categorized by the authors according to the International Classification of Childhood Cancer, third edition (ICCC-3) [19]. We included all childhood cancers, with separate analyses of the most common cancer types: central nervous system (CNS) tumors, leukemia, and lymphoma. In addition, based on findings in previous studies [7], we also conducted separate analyses of hepatoblastoma and neuroblastoma.

Children enrolled in this population-based cohort study were followed from birth until the first of the following events: cancer diagnosis, death, emigration, 20th birthday, or end of follow-up (December 2015). Information regarding emigrations was obtained from the Total Population Register [20], while date of death was retrieved from the Cause of Death Register [21].

Descriptive statistics were used to report baseline characteristics of the study cohort. Hazard ratios (HRs) for total childhood cancer and subtypes and corresponding 95% confidence intervals (CIs) comparing children with and without CHD were estimated using Cox proportional hazards regression with attained age as the underlying time scale. Analyses were first adjusted for sex, birth decade, parental age, parental education, and region of residence at birth. In a separate model, we additionally adjusted for genetic syndromes predisposing to nervous system tumors (neurocutaneous syndromes)—as neurofibromatosis type I, the most common among these syndromes, has been associated with higher than expected frequency of CHD [22]. The fully adjusted model also included Down syndrome. These analyses were repeated for CHD diagnosed at birth, as a proxy of complexity. Subsequently, we also investigated CHD complexity, based on the categorization denoted above, to investigate if associations were particularly pronounced among children with more severe CHD. Finally, separate sensitivity analyses were performed: first including maternal smoking in the models to investigate whether it might drive some of the associations [23,24] (data only available in the MBR from 1982 onwards), and second with different lag periods between the CHD and cancer diagnoses (1 day, 6 months, 1 year, and ±2 years). Finally, we restricted to the years when the Patient Register had achieved nationwide coverage of inpatient care (1987 to 2015) to allow for better detection of CHD not diagnosed at birth.

Information on potential confounders such as sex, birth decade (1973 to 1979, 1980 to 1989, 1990 to 1999, 2000 to 2009, 2010 to 2015), region of residence at birth (six regions), and parental age (categorized as <20, 20 to 29, 30 to 34, 35 to 39, >39 years) was retrieved from the MBR. Moreover, information on conditions such as Down syndrome or neurocutaneous syndromes was obtained from the MBR, the Patient Register, and the Cause of Death Register. Parental education (categorized as primary, secondary, postsecondary) was retrieved from the national censuses and the longitudinal integrated database for health insurance and labor market studies (LISA) [25]. Those with missing information on the main covariates (i.e., the covariates in model 1) were excluded from the analysis (n = 104,192; 2.4%, S2 Table). Data were prepared with SAS 9.4, whereas all analyses were performed with STATA 16.1. Ethical approval for the current study was granted by the Regional Ethical Review Board, Stockholm, Sweden.

Results

This study included 4,178,722 children accumulating a total of 64,642,606 person-years of follow-up time (median follow-up: 15.1 years). Among them, 66,892 (1.6%) had a diagnosis of CHD: 33,818 had a CHD diagnosis in the MBR, and, additionally, 33,074 had a CHD diagnosed only in the Patient Register. Among all individuals with a CHD diagnosis, 4,729 (7.0%) had severe CHD; most of the children with severe CHD (n = 3,169) were diagnosed at birth. Individuals with CHD were more likely to have Down syndrome compared to the general population (4.3% versus 0.1%; Table 1).

Table 1

Baseline characteristics of the study cohort by CHD status.

	CHD-free	CHD
	n (%)	n (%)
Sex
Male	2,114,396 (51.4)	33,256 (49.7)
Female	1,997,434 (48.6)	33,636 (50.3)
Maternal age (years)
≤20	215,901 (5.3)	2,994 (4.5)
20–29	2,139,319 (52.0)	31,911 (47.7)
30–34	1,167,759 (28.4)	19,966 (29.9)
35–39	493,540 (12.0)	9,729 (14.5)
≥40	95,311 (2.3)	2,292 (3.4)
Paternal age (years)
≤20	60,942 (1.5)	925 (1.4)
20–29	1,579,981 (38.4)	23,068 (34.5)
30–34	1,309,548 (31.9)	21,580 (32.2)
35–39	748,449 (18.2)	13,105 (19.6)
≥40	412,910 (10.0)	8,214 (12.3)
Maternal education
Primary	517,859 (12.6)	8,208 (12.3)
Secondary	1,877,081 (45.6)	30,047 (44.9)
Postsecondary	1,716,890 (41.8)	28,637 (42.8)
Paternal education
Primary	762,826 (18.6)	11,325 (16.9)
Secondary	1,995,423 (48.5)	33,222 (49.7)
Postsecondary	1,353,581 (32.9)	22,345 (33.4)
Neurocutaneous syndromes	2,677 (0.1)	123 (0.2)
Down syndrome	2,392 (0.1)	2,899 (4.3)

CHD, congenital heart disease.

Initial adjusted analyses (Table 2) showed an increased risk of childhood cancer overall (HR 1.49; 95% CI, 1.30 to 1.70), leukemia (HR 2.22; 95% CI, 1.80 to 2.73), lymphoma (HR 1.59; 95% CI, 1.07 to 2.36), and hepatoblastoma (HR 3.76; 95% CI, 1.75 to 8.09). Results remained unchanged when adjusting for neurocutaneous syndromes. However, after also adjusting for Down syndrome, the associations for childhood cancer overall and for leukemia disappeared, whereas the increased risk for lymphoma (HR: 1.64; 95% CI, 1.11 to 2.44) and hepatoblastoma (HR: 3.94; 95% CI, 1.83 to 8.47) remained essentially unchanged. Sex-stratified analyses showed that the increased risk for lymphoma was primarily observed among boys (HR: 1.94; 95% CI, 1.21 to 3.09), whereas the increased hepatoblastoma risk was seen in both boys (HR: 3.87; 95% CI, 1.41 to 10.65) and girls (HR: 4.07; 95% CI, 1.26 to 13.11). Results were not affected by adjustment for maternal smoking during pregnancy in a subset of the population (S3 Table), or when restricting to the years when the Patient Register has nationwide coverage of inpatient care (S4 Table). Shorter lag periods between obtaining a CHD diagnosis from the Patient Register and any cancer diagnosis revealed more pronounced overall cancer and lymphoma risks, although the difference between the main analysis and the analysis with a 1-year lag period was small (S5 Table). When considering CHD diagnoses that occurred in the period ±2 years from the cancer diagnosis, a small increased risk of leukemia was also observed (HR 1.29: 95% CI 1.03 to 1.61).

Table 2

Adjusted HRs (95% CIs) of cancer in children with CHD.

	CHD/No CHD no. of cases	UNADJUSTED HR (95% CI)	MODEL 1 HR (95% CI)	MODEL 2 HR (95% CI)	MODEL 3 HR (95% CI)
Total cancers	221/10,690	1.49 (1.30–1.70)	1.49 (1.30–1.70)	1.42 (1.24–1.62)	1.05 (0.91–1.22)
Males	103/5,756	1.33 (1.10–1.62)	1.33 (1.10–1.62)	1.27 (1.05–1.55)	0.96 (0.78–1.18)
Females	118/4,934	1.66 (1.39–2.00)	1.66 (1.38–1.99)	1.58 (1.32–1.90)	1.15 (0.94–1.41)
CNS	34/2,866	0.85 (0.61–1.20)	0.87 (0.62–1.22)	0.75 (0.54–1.06)	0.75 (0.53–1.05)
Males	14/1,493	0.69 (0.41–1.17)	0.71 (0.42–1.19)	0.61 (0.36–1.03)	0.59 (0.35–1.01)
Females	20/1,373	1.02 (0.66–1.59)	1.04 (0.67–1.62)	0.91 (0.58–1.41)	0.92 (0.59–1.44)
Leukemia	93/2,874	2.25 (1.83–2.76)	2.22 (1.80–2.73)	2.21 (1.80–2.72)	0.92 (0.72–1.18)
Males	39/1,585	1.78 (1.30–2.45)	1.75 (1.27–2.40)	1.75 (1.27–2.41)	0.77 (0.54–1.11)
Females	54/1,289	2.78 (2.12–3.65)	2.75 (2.10–3.62)	2.74 (2.08–3.60)	1.06 (0.76–1.48)
Lymphoma	25/1,248	1.54 (1.04–2.29)	1.59 (1.07–2.36)	1.58 (1.06–2.35)	1.64 (1.11–2.44)
Males	18/777	1.82 (1.14–2.90)	1.86 (1.16–2.97)	1.86 (1.16–2.96)	1.94 (1.21–3.09)
Females	7/471	1.13 (0.54–2.38)	1.15 (0.55–2.43)	1.14 (0.54–2.41)	1.19 (0.56–2.50)
Hepatoblastoma	7/115	4.08 (1.90–8.75)	3.76 (1.75–8.09)	3.77 (1.75–8.10)	3.94 (1.83–8.47)
Males	4/68	4.11 (1.50–11.28)	3.70 (1.35–10.18)	3.71 (1.35–10.20)	3.87 (1.41–10.65)
Females	3/47	4.08 (1.27–13.12)	3.88 (1.20–12.52)	3.89 (1.21–12.54)	4.07 (1.26–13.11)
Neuroblastoma	8/393	1.34 (0.66–2.69)	1.23 (0.61–2.47)	1.22 (0.61–2.46)	1.18 (0.58–2.41)
Males	4/220	1.24 (0.46–3.35)	1.15 (0.43–3.08)	1.14 (0.42–3.06)	1.03 (0.37–2.87)
Females	4/173	1.45 (0.54–3.92)	1.32 (0.49–3.56)	1.32 (0.49–3.57)	1.38 (0.51–3.72)

Model 1: adjusted for birth decade, maternal/paternal age and education, region of residence at birth.

Model 2: adjusted for birth decade, maternal/paternal age and education, region of residence at birth, neurocutaneous syndromes.

Model 3: adjusted for birth decade, maternal/paternal age and education, region of residence at birth, neurocutaneous syndromes, Down syndrome.

CHD, congenital heart disease; CI, confidence interval; CNS, central nervous system; HR, hazard ratio.

When restricting analyses to children diagnosed with CHD at birth, the risks for cancer overall (HR 1.45; 95% CI, 1.23 to 1.71) and leukemia (HR 1.41; 95% CI, 1.08 to 1.84) were more pronounced and less affected by Down syndrome (S6 Table). However, in this analysis, no statistically significant association was observed between CHD and lymphoma risk (HR 1.15; 95% CI, 0.62 to 2.14). When examining the impact of CHD complexity (mild–moderate or severe) on cancer risk, there was a substantially increased risk of lymphoma among children with severe CHD (HR 8.13; 95% CI, 4.06 to 16.30), compared to the CHD-free population (Table 3).

Table 3

Adjusted HRs (95% CIs) of cancer in children by CHD complexity.

	No. of cases	MODEL 2 HR (95% CI)	MODEL 3 HR (95% CI)
Total cancers
No CHD	10,690	ref	ref
Mild–moderate CHD	203	1.39 (1.21–1.60)	1.04 (0.89–1.20)
Severe CHD	18	1.84 (1.16–2.92)	1.29 (0.81–2.06)
CNS
No CHD	2,866	ref	ref
Mild–moderate CHD	31	0.74 (0.52–1.05)	0.73 (0.51–1.04)
Severe CHD	3	1.01 (0.33–3.13)	1.00 (0.32–3.11)
Leukemia
No CHD	2,874	ref	ref
Mild–moderate CHD	90	2.28 (1.85–2.81)	0.96 (0.75–1.23)
Severe CHD	3	1.20 (0.39–3.71)	0.42 (0.13–1.32)
Lymphoma
No CHD	1,248	ref	ref
Mild–moderate CHD	17	1.15 (0.71–1.85)	1.19 (0.74–1.93)
Severe CHD	8	7.73 (3.85–15.49)	8.13 (4.06–16.30)

Model 2: adjusted for birth decade, maternal/paternal age and education, region of residence at birth, neurocutaneous syndromes.

Model 3: adjusted for birth decade, maternal/paternal age and education, region of residence at birth, neurocutaneous syndromes, Down syndrome.

CHD, congenital heart disease; CI, confidence intervals; CNS, central nervous system; HR, hazard ratio.

Analyses regarding the association between CHD and subtypes of leukemia, lymphoma, and CNS tumors are presented in Table 4. The increased risk of lymphomas seemed to predominantly stem from non-Hodgkin’s lymphoma (HR 2.04; 95% CI, 1.01 to 4.13), which, as in overall lymphoma, was more pronounced in boys (HR 2.27; 95% CI, 1.01 to 4.13). As with previous results, Down syndrome accounted for the risk of leukemia but not lymphoma. There was a substantial coexistence of CHD and Down syndrome in cases of leukemia: 50 of 93 children with CHD who developed leukemia also had Down syndrome (lymphoid leukemia: 24/57, acute myeloid leukemia: 22/27).

Table 4

Adjusted HRs (95% CIs) of leukemia, lymphoma, and CNS cancer subtypes in children with CHD.

	CHD/No CHD no. of cases	MODEL 1 HR (95% CI)	MODEL 2 HR (95% CI)	MODEL 3 HR (95% CI)
Lymphoid leukemia	57/2,225	1.76 (1.35–2.29)	1.76 (1.35–2.29)	0.98 (0.73–1.32)
Males	20/1,244	1.14 (0.73–1.77)	1.14 (0.73–1.78)	0.62 (0.38–1.01)
Females	37/981	2.48 (1.79–3.45)	2.48 (1.79–3.45)	1.41 (0.96–2.07)
Acute myeloid leukemia	27/410	4.49 (3.04–6.64)	4.46 (3.02–6.59)	0.74 (0.46–1.19)
Males	13/208	4.50 (2.56–7.89)	4.50 (2.57–7.90)	0.96 (0.48–1.92)
Females	14/202	4.49 (2.61–7.74)	4.43 (2.57–7.63)	0.57 (0.29–1.10)
Hodgkin’s lymphoma	7/611	0.94 (0.45–1.99)	0.94 (0.45–1.98)	0.98 (0.46–2.06)
Males	5/323	1.30 (0.54–3.14)	1.30 (0.54–3.14)	1.35 (0.56–3.27)
Females	2/288	0.56 (0.14–2.25)	0.56 (0.14–2.24)	0.58 (0.14–2.32)
Non-Hodgkin’s lymphoma	8/271	1.97 (0.97–3.98)	1.96 (0.97–3.96)	2.04(1.01–4.13)
Males	6/185	2.20 (0.97–4.96)	2.17 (0.96–4.91)	2.27 (1.01–5.13)
Females	2/86	1.50 (0.37–6.11)	1.50 (0.37–6.11)	1.56 (0.38–6.36)
Astrocytoma/other glioma	31/2,030	1.13 (0.79–1.61)	0.94 (0.66–1.34)	0.93 (0.65–1.34)
Males	12/1,002	0.91 (0.52–1.61)	0.74 (0.42–1.31)	0.72 (0.41–1.29)
Females	19/1,028	1.33 (0.84–2.09)	1.12 (0.71–1.77)	1.14 (0.72–1.80)
Ependymoma	3/268	0.81 (0.26–2.53)	0.78 (0.25–2.43)	0.81 (0.26–2.53)
Males	2/153	0.97 (0.24–3.93)	0.96 (0.24–3.88)	1.00 (0.25–4.03)
Females	1/115	0.61 (0.09–4.38)	0.57 (0.08–4.07)	0.59 (0.08–4.23)

Model 1: adjusted for birth decade, maternal/paternal age and education, region of residence at birth.

Model 2: adjusted for birth decade, maternal/paternal age and education, region of residence at birth, neurocutaneous syndromes.

Model 3: adjusted for birth decade, maternal/paternal age and education, region of residence at birth, neurocutaneous syndromes, Down syndrome.

CHD, congenital heart disease; CI, confidence interval; CNS, central nervous system; HR, hazard ratio.

Discussion

In this population-based cohort study, we found an increased risk of lymphoma, stemming from non-Hodgkin’s lymphoma, and hepatoblastoma among children with CHD—while the effect of CHD on the risk of all childhood cancers combined and childhood leukemia, particularly acute myeloid leukemia, was explained by Down syndrome. However, for children diagnosed with CHD at birth, Down syndrome did not entirely account for the increased total cancer and leukemia risks observed. Attempting to explain this finding, we hypothesized that one key difference between those diagnosed at birth and those diagnosed later in life might be the severity of the underlying condition. Indeed, when examining CHD complexity, lymphoma risk was considerably increased in severe CHD.

Previous research regarding the relationship between CHD and cancer risk is inconsistent. In agreement with our findings, a population-based Danish cohort study including 15,905 CHD patients found no effect of CHD on overall cancer risk after excluding Down syndrome patients [12], while a Californian population-based cohort study found elevated total childhood cancer and lymphoma risks in CHD patients (excluding chromosomal anomalies) [4]. Yet, contrary to our findings of increased risk only in childhood lymphomas and hepatoblastomas, a population-based cohort study in Taiwan [10] and a Swedish matched cohort study [26] reported increased risk of childhood cancer overall among individuals with CHD. However, they included a wide range of ages with no separate consideration of childhood cancers, no adjustment for Down syndrome, and a short or no lag period between the CHD and cancer diagnoses. As increasing use of primary healthcare among children with cancer has been found already 6 months before their diagnosis [27], not including a sufficient lag period might result in some CHD diagnoses being identified only because of the increased monitoring preceding a cancer diagnosis—leading to an overestimation of the association. In our data, childhood cancer and lymphoma risks were becoming increasingly pronounced as the lag period between the CHD and cancer diagnoses was getting shorter—to avoid overestimating the association, we opted for a 2-year lag period for CHD detected later in life (i.e., retrieved from the Patient Register) in the main analyses. Finally, a large US register-based study reported a more than 2-fold increased total cancer risk among children with a CHD diagnosis; the highest risk was observed for hepatoblastomas and neuroblastomas [7]. The more pronounced risk increase compared to our study could be attributed either to genetic differences in the populations, or to the mix of active and passive registers utilized in the US study: The passive registers might have identified mainly children with severe CHD, diagnosed at birth, whereas including no lag period between the CHD and cancer diagnoses for the active registers could have overestimated the association.

While Down syndrome has not been consistently considered as a confounder in previous studies examining the relationship between CHD and cancer, our observation of an attenuated association when adjusting for Down syndrome, mainly observed for leukemia, is in agreement with previous research regarding the effect of Down syndrome on cancer risk. Down syndrome has been shown to be a risk factor of considerable strength for childhood leukemia, but not for solid tumors, such as lymphomas [13,28]. Indeed, when taking Down syndrome into account, the association between CHD and leukemia decreased considerably when considering CHD diagnosed at birth and was entirely explained away when considering CHD diagnoses also from the Patient Register. Results for lymphomas, on the other hand, did not vary greatly after the addition of Down syndrome as a covariate.

The potential mechanisms underlying the relationship between CHD and childhood cancer remain poorly understood. It has been suggested that teratogenesis and carcinogenesis may share a common foundation, with shared point mutations in specific genes, or developmental gene mutations occurring during early embryogenesis [11,29]. Radiation exposure from cardiac imaging and therapeutic procedures is also regarded as a potential noteworthy risk factor for carcinogenesis in individuals with CHD [30]. Indeed, according to a recent large population-based study of adult patients in the Quebec CHD Database, higher exposure to low-dose ionizing radiation from cardiac procedures was associated with increased cancer risk, with indications of a dose–response relationship [31]. However, results from studies on low-dose ionizing radiation and cancer risk in children and young adults are conflicting [31] and have been criticized as likely to suffer from reverse causation or confounding by indication [32]. Additionally, there is some uncertainty regarding whether the induction period would be sufficient. While 3 to 5 years are considered sufficient for the manifestation of radiation-induced leukemia, solid tumors such as lymphomas typically will not appear for 10 to 15 years after radiation exposure (and commonly remain undiagnosed until adulthood) [30]. In our cohort, 8 of the 25 CHD patients with lymphoma had their CHD diagnosis <10 years before they were diagnosed with lymphoma. Finally, lifestyle adaptations owning to the disease (such as reduced physical activity) could potentially be another driving force behind the observed association between CHD and cancer risk; however, this might be more likely in adulthood, when lifestyle factors tend to play a larger role in carcinogenesis [10].

To our knowledge, this is the largest study to date on cancer risk among children with CHD in a European population. The register-based design allows for population-wide coverage and long-term follow-up, resulting in the largest possible number of cancer cases; additionally, it minimizes the potential for selection and recall bias. As such, we believe the data in this study to be representative of the Swedish population—and the findings generalizable to similar populations. The register link also allows for information on several relevant covariates, including the ability to identify patients with Down syndrome or neurocutaneous syndromes. Moreover, using both the MBR and Patient Register to retrieve CHD diagnoses allows for capturing children with CHD diagnosed later in life or not documented in the MBR.

One limitation of the current study is that both CHD and childhood cancer are rare: therefore, the statistical power for analyses of specific cancer subtypes was suboptimal for the rarer subtypes. Furthermore, in the beginning of the study, the Patient Register was not yet nationwide, although the coverage increased gradually during the first 14 years of the study period; it is therefore possible that some children whose CHD remained undetected at birth were not captured in the Patient Register either. If these children later developed cancer, they would have been considered as nonexposed, potentially leading to an underestimation of the association. However, when restricting to the 28 years of the study period when the Patient Register had nationwide coverage of inpatient care, results were similar. Therefore, we do not expect that this limitation has substantially impacted our estimates. Additionally, discounting diagnoses of CHD from the Patient Register less than 2 years before any cancer diagnosis might also lead to an underestimation of cancer risk among children with CHD. However, including them could have led to overestimating the association, as some might have remained undiagnosed if not for the increased monitoring in relation to the cancer diagnosis. Therefore, we have opted for a more conservative approach, but performed analyses with shorter lag periods as sensitivity analyses. We also performed an analysis in which we considered CHD diagnosis that occurred at least 2 years after the cancer, and in this analysis not only we observed stronger associations with overall childhood cancer risk, lymphomas, and hepatoblastomas, but we also found a small increased risk of leukemia. However, it is important to note that this sensitivity analysis could have overestimated some associations since it is likely that some children with cancer could have had an increased medical monitoring longer than 2 years after the cancer diagnosis. Further, the exclusion of individuals with missing information on the main covariates, albeit very small (2.6%), may potentially have introduced some selection bias. However, the distribution of both CHD and cancer was very similar in children with missing and complete information on covariates, rendering such an eventuality unlikely. Moreover, even though access to some potential lifestyle-related covariates was limited by the information available in the registers, it bears mentioning that lifestyle adaptations due to the disease (such as reduced physical activity) are mediators of the association, rather than confounders. Similarly, comorbidities that might occur to a larger extent in severe CHD and lead to increased cancer surveillance would also be mediators of the association. Finally, the only other well-established risk factors for childhood cancer—prior chemotherapy and high-dose ionizing radiation [6]—cannot predate the occurrence of CHD and therefore cannot be considered as potential confounders.

This large population-based cohort study demonstrates an increased risk of non-Hodgkin’s lymphoma and hepatoblastoma among children with CHD, independent of Down syndrome diagnosis. Strongest associations were found when taking CHD complexity into consideration. Physicians should be aware of this predisposition to cancer in individuals with CHD; this increased awareness may be key in facilitating early cancer diagnosis and improving subsequent management and outcome. Future research should investigate the causal mechanisms underlying these findings, such as genetics, or low-dose ionizing radiation from cardiac imaging and therapeutic procedures. In light of the increasing population with CHD, such insights can be particularly compelling.

Checklist of items that should be included in reports of cohort studies.

(DOCX)

Click here for additional data file.

Prospective analysis plan.

(DOCX)

Click here for additional data file.

Cohort flow chart.

(PNG)

Click here for additional data file.

List of ICD–10 codes and their representative lesions evaluated as severe.

(DOCX)

Click here for additional data file.

Distribution of exposure and main outcomes in the study population, according to completeness of data on the main covariates.

CHD, congenital heart disease; CNS, central nervous system.

(DOCX)

Click here for additional data file.

Adjusted HRs (95% CIs) of cancer in children with CHD born from 1982 onwards.

(DOCX)

Click here for additional data file.

Adjusted HRs (95% CIs) of cancer in children with CHD born from 1987 onwards.

(DOCX)

Click here for additional data file.

Adjusted HRs (95% CIs) of cancer in children with CHD—different lag periods between CHD diagnosis from the Patient Register and cancer diagnosis.

(DOCX)

Click here for additional data file.

Adjusted HRs (95% CIs) of cancer in children with CHD diagnosed from the MBR.

CHD, congenital heart disease; CI, confidence interval; CNS, central nervous system; HR, hazard ratio; MBR, Medical Birth Register.

(DOCX)

Click here for additional data file.

5 Jul 2021

Dear Dr Kampitsi,

Thank you for submitting your manuscript entitled "Cancer risk in children with congenital heart disease: results from a Swedish register-based study" for consideration by PLOS Medicine.

Your manuscript has now been evaluated by the PLOS Medicine editorial staff and I am writing to let you know that we would like to send your submission out for external peer review.

However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. To this end, please login to Editorial Manager where you will find the paper in the 'Submissions Needing Revisions' folder on your homepage. Please click 'Revise Submission' from the Action Links and complete all additional questions in the submission questionnaire.

Please re-submit your manuscript within two working days, i.e. by Jul 07 2021 11:59PM.

Login to Editorial Manager here: https://www.editorialmanager.com/pmedicine

Once your full submission is complete, your paper will undergo a series of checks in preparation for peer review. Once your manuscript has passed all checks it will be sent out for review.

Feel free to email us at plosmedicine@plos.org if you have any queries relating to your submission.

Kind regards,

Callam Davidson

Associate Editor

PLOS Medicine

7 Sep 2021

Dear Dr. Kampitsi,

Thank you very much for submitting your manuscript "Cancer risk in children with congenital heart disease: results from a Swedish register-based study" (PMEDICINE-D-21-02870R1) for consideration at PLOS Medicine.

Your paper was evaluated by an associate editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

In addition, we request that you upload any figures associated with your paper as individual TIF or EPS files with 300dpi resolution at resubmission; please read our figure guidelines for more information on our requirements: http://journals.plos.org/plosmedicine/s/figures. While revising your submission, please upload your figure files to the PACE digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at PLOSMedicine@plos.org.

We hope to receive your revised manuscript by Sep 28 2021 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please use the following link to submit the revised manuscript:

https://www.editorialmanager.com/pmedicine/

Your article can be found in the "Submissions Needing Revision" folder.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

We look forward to receiving your revised manuscript.

Sincerely,

Callam Davidson,

Associate Editor

PLOS Medicine

plosmedicine.org

-----------------------------------------------------------

Requests from the editors:

Please update your title to ‘The relationship between congenital heart disease and cancer in Swedish children: a population-based cohort study’.

Data Availability Statement (DAS) requires revision:

• Data availability statement: Please replace the word ‘secrecy’ with ‘privacy’.

• A study author cannot be the contact person for the data. Please see http://journals.plos.org/plosmedicine/s/data-availability and FAQs at http://journals.plos.org/plosmedicine/s/data-availability#loc-faqs-for-data-policy

Please structure your abstract using the PLOS Medicine headings (Background, Methods and Findings, Conclusions).

• Please combine the Methods and Findings sections into one section, “Methods and findings”.

• In the last sentence of the Abstract Methods and Findings section, please describe the main limitation(s) of the study's methodology.

Please remove the ‘Financial disclosures’ from the title page. This information is captured as metadata based on your responses to the submission form.

At this stage, we ask that you include a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary

Please update your citations throughout: these should be in square brackets.

Lines 159 and 161: PLOS does not permit "data not shown.” Please remove this claim, or if you are the owner of the data relevant to this claim, please provide the data in accordance with the PLOS data policy, and update your Data Availability Statement as needed.

Please refer to your study as a population-based cohort study in the Methods and Abstract.

Line 249: Please update to ‘To our knowledge, this is the largest study to date on cancer risk among children with CHD in a European population’.

Please discuss the risk of selection bias that could have been introduced by the exclusion of subjects with missing data.

Please ensure that the study is reported according to the STROBE guideline, and include the completed STROBE checklist as Supporting Information. Please add the following statement, or similar, to the Methods: "This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist)."

The STROBE guideline can be found here: http://www.equator-network.org/reporting-guidelines/strobe/

When completing the checklist, please use section and paragraph numbers, rather than page numbers.

Did your study have a prospective protocol or analysis plan? Please state this (either way) early in the Methods section.

a) If a prospective analysis plan (from your funding proposal, IRB or other ethics committee submission, study protocol, or other planning document written before analyzing the data) was used in designing the study, please include the relevant prospectively written document with your revised manuscript as a Supporting Information file to be published alongside your study, and cite it in the Methods section. A legend for this file should be included at the end of your manuscript.

b) If no such document exists, please make sure that the Methods section transparently describes when analyses were planned, and when/why any data-driven changes to analyses took place.

c) In either case, changes in the analysis-- including those made in response to peer review comments-- should be identified as such in the Methods section of the paper, with rationale.

Comments from the reviewers:

Reviewer #1: The authors exanimated relationship between congenital heart disease (CHD) and childhood cancer risk. They aimed to determine the relationship between CHD and cancer in Swedish children. All individuals registered in the Swedish Medical Birth Register between 1973 and 2014 were included in the study. Individuals with CHD were identified from the MBR and National Patient Register, whereas cancer diagnoses were retrieved from the Swedish Cancer Register. The authors observed increased risks of childhood cancer overall, leukemia, lymphoma, and hepatoblastoma in children with CHD, but after adjustment for Down syndrome, only the increased lymphoma and hepatoblastoma risk remained. When restricting to CHD diagnoses from the MBR only, i.e., those diagnosed around birth, the risk for childhood cancer overall) and leukemia was more pronounced, even after controlling for Down syndrome. Moreover, they observed substantially elevated lymphoma risk in children with complex CHD. In conclusions: they found associations between CHD and childhood lymphomas and hepatoblastomas, not explained by a diagnosis of Down syndrome. They observed stronger associations in complex CHD.

The study was perfectly designed and conducted.

Reviewer #2: See attached document

Reviewer #3: I confine my remarks to statistical aspects of this paper. The general approach is fine, but i have some issues to resolve before I can recommend publication.

One big issue is that this is a population study -- that is, you have an entire population, not a sample. Many statisticians, including me, think that this makes inferential statistics odd. You don't have any inference to do, you have the whole population. Other statisticians say inference is still meaningful if you posit a sort of super-population (e,g, all Scandinavian children, all children anywhere ....) I'm not a big fan of this, but I wouldn't reject an article that did it. But it should be discussed. The authors (wisely, in my view) did not include p values but they did include confidence intervals. These have the same problem. I'd prefer leaving those out and putting in standard errors of the estimates.

On p. 6, lines 129-132, the authors categorize many continuous variables. This is nearly always a mistake. I wrote an article about this: https://medium.com/@peterflom/what-happens-when-we-categorize-an-independent-variable-in-regression-77d4c5862b6c but, briefly, leave the variables as is and use splines to investigate nonlinearity.

Peter Flom

Any attachments provided with reviews can be seen via the following link:

[LINK]

Submitted filename: PLOS_Review_CHD and Childhood Cancer risk among Swedish Children_20210805.docx

Click here for additional data file.

7 Oct 2021

Submitted filename: CHDcancer_editorial&reviewer comments with responses.docx

Click here for additional data file.

8 Nov 2021

Dear Dr. Kampitsi,

Thank you very much for submitting your revised manuscript "The relationship between congenital heart disease and cancer in Swedish children: a population-based cohort study" (PMEDICINE-D-21-02870R2) for consideration at PLOS Medicine.

The revised manuscript was seen again by the reviewers and their reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

In light of reviewer #2's remaining concerns, we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' comments. We cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by reviewer #2.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

In addition, we request that you upload any figures associated with your paper as individual TIF or EPS files with 300dpi resolution at resubmission; please read our figure guidelines for more information on our requirements: http://journals.plos.org/plosmedicine/s/figures. While revising your submission, please upload your figure files to the PACE digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at PLOSMedicine@plos.org.

We hope to receive your revised manuscript by Nov 29 2021 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please use the following link to submit the revised manuscript:

https://www.editorialmanager.com/pmedicine/

Your article can be found in the "Submissions Needing Revision" folder.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

We look forward to receiving your revised manuscript.

Sincerely,

Callam Davidson,

PLOS Medicine

plosmedicine.org

-----------------------------------------------------------

Comments from the academic editor:

The immortal bias is still a concern. The authors may want to perform additional sensitivity analyses to assess how much of their results could potentially be explained by this bias.

Comments from the reviewers:

Reviewer #2: I received the authors' responses and found that they acknowledged the critical issues raised for the most part. However, some important issues are left unsolved. I, therefore, request a further revision on the following points:

1. I find the problem of exposure definition in this paper to be two-fold. Firstly, unlike acquired conditions, CHD is a condition that is present from birth, regardless of when this condition is 'diagnosed'. This study defines the exposure based on CHD diagnosis from patient registries in addition to birth registries. That could lead to bias if the diagnose date is considered the start date of CHD condition. In this study, a patient not 'diagnosed' with CHD at birth but later had a CHD diagnosis (in NPR) were classified 'exposed' since the diagnosis and "unexposed" between birth to the diagnosis. This is wrong. The patient should be classified as "exposed" since birth even though his/her CHD condition was diagnosed later. Secondly, in response to my previous comment 1, the authors stated that they classified a patient as 'unexposed' if their cancer diagnosis precedes the CHD diagnosis (in NPR). This approach raised the second concern of misclassification on exposure. Indeed, according to this classification, the unexposed patient would survive less than the exposed patients, giving an artificial advantage to them (exposed patients). In this regard, I would like to refer this paper [Lévesque et al. 2010] to understand the problem under discussion better.

2. As requested, the authors provided evidence supporting their claim against the hypothesis that exposure to LDIR from cardiac procedures explains the CHD-Cancer association. However, the evidence (S5 Table. Adjusted HRs (95% CIs) of cancer in children with Congenital Heart Disease (CHD), stratified by age at cancer diagnosis) is not convincing. The authors claim that solid tumors such as lymphomas typically need 10 to 15 years after radiation exposure to manifest. However, there still seems to be some uncertainty regarding the latency between low-dose ionization radiation exposures and cancer incidence. For example, in a large population study in Australia (Mathews, J. D., et al. Cancer risk in 680 000 people exposed to computed tomography scans in childhood or adolescence: data linkage study of 11 million Australians. Bmj (2013) 346.) that assessed the association between CT scan and cancer in children and adolescents, it was reported that " At 1-4, 5-9, 10-14, and 15 or more years since first exposure, IRRs were 1.35 (1.25 to 1.45), 1.25 (1.17 to 1.34), 1.14 (1.06 to 1.22), and 1.24 (1.14 to 1.34), respectively." Thus, simply comparing the CHD-cancer association between groups with age at cancer diagnosis before and after 10 years of age could not be used as evidence for assessing the LDIR-cancer association among CHD children population.

There is a knowledge base that says otherwise and is well established based on large epidemiological studies (refs). As in this study cohort, however, stated by the authors in lines 280-281, "8 of the 25 CHD patients with lymphoma had their CHD diagnosis <10 years before they were diagnosed with lymphoma" (with longer latency). This goes back to my first point; how did they define their exposure.

To summarize, the subgroup analysis by age at cancer diagnosis thus does not provide compelling evidence to claim that exposure to LDIR from cardiac procedures does not contribute the CHD-Cancer association. I would suggest that the authors refrain from including this sub-group analysis, which might question the internal validity, and to remove the unfounded statement on LDIR.

Reference

Lévesque, L. E., Hanley, J. A., Kezouh, A., & Suissa, S. (2010). Problem of immortal time bias in cohort studies: example using statins for preventing progression of diabetes. BMJ: British Medical Journal, 340(7752), 907-911. http://www.jstor.org/stable/40701710

Reviewer #3: The authors have addressed my concerns and I now recommend publication

Peter Flom

Any attachments provided with reviews can be seen via the following link:

[LINK]

28 Nov 2021

Submitted filename: R2_CHDcancer_editorialreviewer comments with responses_f.docx

Click here for additional data file.

22 Dec 2021

Dear Dr. Kampitsi,

Thank you very much for re-submitting your manuscript "The relationship between congenital heart disease and cancer in Swedish children: a population-based cohort study" (PMEDICINE-D-21-02870R3) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. If you haven't already, we ask that you provide a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract.

We expect to receive your revised manuscript within 1 week. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.

Please note, when your manuscript is accepted, an uncorrected proof of your manuscript will be published online ahead of the final version, unless you've already opted out via the online submission form. If, for any reason, you do not want an earlier version of your manuscript published online or are unsure if you have already indicated as such, please let the journal staff know immediately at plosmedicine@plos.org.

If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by Dec 29 2021 11:59PM.

Sincerely,

Callam Davidson,

Associate Editor

PLOS Medicine

plosmedicine.org

------------------------------------------------------------

Requests from Editors:

Please update the bullet point at line 69 to ‘These results suggest an association between CHD and childhood cancer and have the potential to facilitate early cancer detection by increasing awareness amongst physicians.’

Please provide the unadjusted comparisons as well as the adjusted comparisons in Table 2.

30 Dec 2021

Submitted filename: R3_CHDcancer_editorial comments with responses.docx

Click here for additional data file.

5 Jan 2022

Dear Dr Kampitsi,

On behalf of my colleagues and the Academic Editor, Dr Wei Zheng, I am pleased to inform you that we have agreed to publish your manuscript "The relationship between congenital heart disease and cancer in Swedish children: a population-based cohort study" (PMEDICINE-D-21-02870R4) in PLOS Medicine.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. Please be aware that it may take several days for you to receive this email; during this time no action is required by you. Once you have received these formatting requests, please note that your manuscript will not be scheduled for publication until you have made the required changes.

In the meantime, please log into Editorial Manager at http://www.editorialmanager.com/pmedicine/, click the "Update My Information" link at the top of the page, and update your user information to ensure an efficient production process.

PRESS

We frequently collaborate with press offices. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximise its impact. If the press office is planning to promote your findings, we would be grateful if they could coordinate with medicinepress@plos.org. If you have not yet opted out of the early version process, we ask that you notify us immediately of any press plans so that we may do so on your behalf.

We also ask that you take this opportunity to read our Embargo Policy regarding the discussion, promotion and media coverage of work that is yet to be published by PLOS. As your manuscript is not yet published, it is bound by the conditions of our Embargo Policy. Please be aware that this policy is in place both to ensure that any press coverage of your article is fully substantiated and to provide a direct link between such coverage and the published work. For full details of our Embargo Policy, please visit http://www.plos.org/about/media-inquiries/embargo-policy/.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Thank you again for submitting to PLOS Medicine. We look forward to publishing your paper.

Sincerely,

Callam Davidson

Associate Editor

PLOS Medicine