Abstract
Purpose
Previous assessments of childhood rhabdomyosarcoma have indicated maternal and birth characteristics may be associated with tumor development, however, much work remains to identify novel and confirm suspected risk factors. Our objective was to evaluate the associations between maternal and birth characteristics and childhood rhabdomyosarcoma.
Methods
This case-control study included 322 cases and 322 pair-matched controls. Cases were enrolled in a trial run by the Intergroup Rhabdomyosarcoma Study Group. Population-based controls were identified using random digit dialing and were individually matched to cases on race, sex, and age. Families of the case and control subjects participated in a telephone interview, which captured information on maternal characteristics (birth control use, number of prenatal visits, anemia, and abnormal bleeding during pregnancy) and birth characteristics (birth weight, preterm birth, and type of delivery (vaginal vs. Cesarean)). Conditional logistic regression models were used to calculate an odds ratio (OR) and 95% confidence interval (CI) for each exposure, adjusted for age, race, sex, household income, and parental education. As the two most common histologic types of rhabdomyosarcoma are embryonal (n=215) and alveolar (n=66), we evaluated effect heterogeneity of these exposures.
Results
The only characteristic that was associated with childhood rhabdomyosarcoma, and statistically significant, was abnormal vaginal bleeding during pregnancy (OR=1.75, 95% CI=1.12–2.74). Birth control use (OR=1.45, 95% CI=0.96–2.18), anemia during pregnancy (OR=1.27, 95% CI=0.81–1.99), and preterm birth (OR=2.51, 95% CI=0.74–8.49) were positively associated with childhood rhabdomyosarcoma, but were not statistically significant. Low birth weight (aOR=4.46, 95% CI=1.41–14.1) and high birth weight (aOR=2.41, 95% CI=1.09–5.35) were strongly associated with alveolar rhabdomyosarcoma. However, these factors did not display significant effect heterogeneity between histologic types (p>0.15 for all characteristics).
Conclusions
Overall, we found little evidence that these maternal and birth characteristics are strongly associated with childhood rhabdomyosarcoma.
Keywords: abnormal vaginal bleeding, epidemiology, rhabdomyosarcoma, soft tissue sarcoma
BACKGROUND
Rhabdomyosarcoma is the most common soft tissue sarcoma in children and young adults <20 years of age, with most cases occurring before 10 years of age [1, 2]. Rhabdomyosarcoma is a malignant tumor that originates primarily in connective tissues, such as muscle tissue, and therefore can develop anywhere in the body. There are two major rhabdomyosarcoma histologic subtypes including embryonal, with a peak incidence in children <5 years of age, and alveolar, which has an incidence evenly distributed throughout the childhood and adolescence [1]. The overall 5-year survival for childhood rhabdomyosarcoma is approximately 60–70% [3] and has made only modest improvements since the 1980s, likely due to the lack of new effective therapies [4].
Due to the rarity of childhood rhabdomyosarcoma and possible heterogeneity between the subtypes, very little is known about the etiology of childhood rhabdomyosarcoma. Birth defects and familial genetic syndromes, including Li-Fraumeni syndrome and neurofibromatosis type 1, are associated with a small proportion of childhood rhabdomyosarcoma cases [5–8]. Because the causes of most cases remain unknown, the majority of which occur in the first decade of life, recent epidemiological studies evaluating possible risk factors for childhood rhabdomyosarcoma have centered on exposures in utero and early life as well as pregnancy and birth characteristics. Previous studies have suggested few potential risk factors for childhood rhabdomyosarcoma including advanced maternal age [9], parental drug use [10], prenatal exposure to X-rays [11], as well an inverse relationship with childhood atopic exposures [12]. The associations between early life exposures and childhood rhabdomyosarcoma indicate that characteristics associated with the perinatal and neonatal periods may be important in understanding the etiologies of childhood rhabdomyosarcoma.
Birth characteristics have previously been found to be associated with childhood malignancies, including leukemia and central nervous system tumors [7, 9, 13–19]. In addition, several studies have evaluated birth characteristics and childhood rhabdomyosarcoma and suggest that increased birth weight [20], increased maternal age [13, 20–22], increased paternal age [20, 22], being born large for gestational age [20], and late or lack of prenatal care [22] are associated with an increased risk of childhood rhabdomyosarcoma. Similar to other childhood cancers, high birth order (3+) is suggested to have a protective effect on childhood rhabdomyosarcoma [9, 20]. A previous report indicated that being born as a twin or a multiple may be associated with higher risk of childhood rhabdomyosarcoma, but this finding was not statistically significant [22]. Few studies have assessed the associations between maternal characteristics and risk of childhood rhabdomyosarcoma, primarily focusing on prior pregnancy losses and risk of childhood rhabdomyosarcoma [21, 23, 24]. Two of these studies yielded inconsistent results on the association of prior miscarriages and rhabdomyosarcoma risk [21, 24], however these had small sample sizes; another study reported that maternal history of at least one stillbirth was associated with a nearly 4-fold increased risk of childhood rhabdomyosarcoma [23].
The largest studies evaluating the association of birth characteristics and childhood rhabdomyosarcoma to date have primarily relied on a large dataset consisting of a pool of cancer registry data linked to birth records from five states across the United States [9, 13, 18, 20, 25]. This pooled dataset has provided sufficient statistical power to assess potential risk factors for rare childhood cancer types, and often their histologic subtypes; however, linkage studies may be subject to selection bias, as children who are born and diagnosed in separate states due to residential mobility are often excluded. Furthermore, it is common for many cases identified in cancer registries to have incomplete linkage to other databases. One study reported that only 77% of childhood cancer cases identified from the Texas Cancer Registry were able to be linked to their birth certificates, therefore excluding approximately 25% of cases [26]. In addition, information on exposures experienced by the mother before and during pregnancy is often not available on birth records.
To our knowledge, no study has extensively evaluated the associations between maternal characteristics and childhood rhabdomyosarcoma; additionally, there is a need to validate previous findings related to birth characteristics. The objective of this study is to explore maternal and birth characteristics as potential risk factors for childhood rhabdomyosarcoma. This evaluation is novel in that it uses data from one of the largest childhood rhabdomyosarcoma case-control studies to date, which includes detailed questionnaire information on pregnancy characteristics, birth outcomes, and maternal obstetric history from the families of both childhood rhabdomyosarcoma cases and pair-matched controls.
METHODS
Study Population
Cases and controls were enrolled in a trial previously coordinated by the Intergroup Rhabdomyosarcoma Study Group (IRSG), which became part of the Children’s Oncology Group in 2000 and coordinated treatment protocols for 80–85% of all childhood rhabdomyosarcoma cases in the United States [27]. The details regarding the case-control study have been previously described [7, 10, 11]. In summary, the cases were 0–20 years old when they were consecutively enrolled in the IRS-III study at the time of their rhabdomyosarcoma diagnosis in April 1982 to July 1988. Central expert pathology review confirmed all rhabdomyosarcoma diagnoses as well as the histologic subtype (i.e., embryonal, alveolar, or other). Of the 511 childhood rhabdomyosarcoma patients enrolled in IRS-III during the study period, 440 cases were eligible for the current study and 351 had completed interviews. Of the 71 ineligible cases, 29 had no home telephone, 9 were not United States’ citizens, 15 were from families that did not speak English or Spanish, 18 were treated in institutions where the study was not approved by the institutional review board. An additional 89 cases did not participate due to parental (n=41) or physician (n=30) refusal, and 18 families could not be located. Seventy-three percent (n=322) of eligible cases were interviewed and pair-matched with controls [7, 10, 11].
Controls were identified by random digit telephone dialing during the same period [7, 10, 11]. Specifically, the area code and first five digits of the each case’s phone number were used with two randomly selected terminal digits to search for a matching control. Controls were individually matched to cases on race (White, Black, or Other), sex, and age (within one year for cases aged 0–5 years at diagnosis, and within three years for cases aged 5–20 years at diagnosis). On average, 50 phone numbers were dialed and 118 calls were made to find a matching control for each case. Seventy-eight percent of homes with a matching child agreed to participate, a response rate which is comparable to that of other Children’s Oncology Group studies that utilized random digit dialing methods for control group selection in 1980’s [28]. Controls could not be identified for eight percent of cases and therefore these cases were excluded from this analysis [7, 10, 11].
Data Collection and Variables
Data were collected from case and control families by telephone interview using a structured questionnaire. The child’s mother and father were asked to participate in the interview, which for case and control families lasted on average 70 and 68 minutes, respectively. Interviews were conducted in English and Spanish (six case families and two control families were Spanish-speaking). The interview included questions about childhood environmental exposures, parental occupational exposures, family demographic characteristics, parental lifestyle and behavioral characteristics, and medical history. On average, parents were asked to recall exposures, which occurred eight to nine years prior to the interview.
For the current study, we focused on the assessment of maternal and birth characteristics as potential risk factors for childhood rhabdomyosarcoma. We evaluated the following questionnaire items directed to the child’s mother, as they relate to maternal characteristics during pregnancy: “Did you take fertility medicine to help you become pregnant with [index child]?”; “Were you using birth control when you became pregnant with [index child]?”; “Did you get prenatal care when you were pregnant with him/her?”; “How many prenatal visits did you have?”; “Did you have amniocentesis done during the pregnancy?”; “Did you have any spotting, cramping, or abnormal vaginal bleeding during the pregnancy?”; and “While you were pregnant with [index child] did you have any of the following: high blood pressure, nausea or vomiting, anemia, cold or flu”. In addition, the mother was asked about her obstetric history: “Did you ever use any kind of birth control before [the index child]’s birth?”; “How many times have you been pregnant? Include all live births, stillbirths, miscarriages, and abortions.” We evaluated the following questionnaire items to assess birth characteristics: “How much did [index child] weigh at birth?”; “Was the baby delivered vaginally or by Caesarian section?”; “Was [index child] born prematurely? Was s(he) overdue?”. In addition, we evaluated birth order (1, 2, ≥3) and parental age at the time of birth.
Covariates for this analysis were selected a priori and included total annual household income (categorized as <$20,000, $20,000–$39,999,≥ $40,000), and maternal and paternal educational level (total number of completed years). All statistical models were adjusted for these covariates as well as the matching factors including the child’s sex (male or female), age at diagnosis (in years), and race (categorized as White, Black, or other). Birth weight and pregnancy length were highly correlated, and, therefore, models evaluating these variables were mutually adjusted.
Statistical Analysis
Descriptive statistics were used to characterize the demographic variables among the case and control groups. Frequency distributions were tabulated for categorical variables, and means and standard deviations were calculated for continuous variables. Conditional logistic regression was used to evaluate maternal and birth characteristics and their associations with childhood rhabdomyosarcoma by generating adjusted odds ratios (aOR), 95% confidence intervals (CI), and p-values. An association was considered statistically significant if p<0.05. Because the rhabdomyosarcoma histologic subtypes are suspected to have heterogeneous etiologies and possibly different risk factors, we used polytomous logistic regression to evaluate effect heterogeneity (as described by Glynn and Rosner [29]) between birth and maternal characteristics and the rhabdomyosarcoma histologic subtypes, embryonal and alveolar rhabdomyosarcoma. The polytomous logistic regression models included a term to account for the intra-class correlation introduced by the pair-matched cases and controls. All analyses were conducted using STATA 12.1 (StataCorp LP, College Station, TX).
RESULTS
The demographic characteristics among the case and control groups are presented in Table 1. The matching factors of sex, age at diagnosis/enrollment, and race were balanced between the 322 childhood rhabdomyosarcoma cases and 322 controls. One-fourth of the sample (28.6%) had an annual household income of less than $20,000, with a higher proportion of the case group falling in this category compared to the control group (32.8% versus 24.3%, respectively; p=0.014). Maternal and paternal education levels were similar between the case and control groups, where approximately half of the sample had a maternal and paternal education level higher than high school (46.5% and 50.2%, respectively). The majority of cases in this sample were diagnosed with embryonal rhabdomyosarcoma (66.7%), whereas 20.5% were diagnosed with alveolar rhabdomyosarcoma and 12.8% are not otherwise specified (NOS).
Table 1.
Demographic characteristics of childhood rhabdomyosarcoma cases and controls
| Characteristic | Controls n = 322 |
Cases n = 322 |
|---|---|---|
| Sex of child, n (%) | ||
| Male | 215 (66.8) | 215 (66.8) |
| Female | 107 (33.2) | 107 (33.2) |
| Race of child, n (%) | ||
| White | 291 (90.4) | 287 (89.1) |
| Black | 21 (6.5) | 20 (6.2) |
| Other | 10 (3.1) | 15 (4.7) |
| Ethnicity of child, n (%) | ||
| Non-Hispanic | 307 (95.9) | 303 (94.7) |
| Hispanic | 13 (4.1) | 17 (5.3) |
| Age at diagnosis/enrollment (years), mean (SD) | 7.5 (5.4) | 7.6 (5.3) |
| Maternal education, n (%) | ||
| <High school | 39 (12.2) | 45 (14.1) |
| High school | 126 (39.4) | 132 (41.4) |
| >High school | 155 (48.4) | 142 (44.5) |
| Paternal education, n (%) | ||
| <High school | 37 (11.8) | 54 (17.1) |
| High school | 111 (35.5) | 112 (35.3) |
| >High school | 165 (52.7) | 151 (47.6) |
| Total annual household income, n (%) | ||
| <$20,000 | 77 (24.3) | 104 (32.8) |
| $20,000–$39,999 | 155 (48.9) | 131 (41.3) |
| ≥$40,000 | 85 (26.8) | 82 (25.9) |
| Histologic subtypes, n (%) | ||
| Embryonal | 215 (66.7) | |
| Alveolar | 66 (20.5) | |
| NOSa | 41 (12.8) | |
Not otherwise specified
Maternal characteristics during pregnancy and their associations with childhood rhabdomyosarcoma are presented in Table 2. Among the maternal characteristics evaluated, the occurrence of spotting, cramping, or abnormal vaginal bleeding during pregnancy was associated with increased risk for childhood rhabdomyosarcoma (aOR=1.75, 95% CI=1.12–2.74). Overall, the maternal characteristics evaluated in this assessment were not significantly associated with childhood rhabdomyosarcoma risk, including 12+ prenatal visits (aOR=1.16, 95% CI=0.77–1.76), anemia during pregnancy (aOR=1.27, 95% CI=0.81–1.99), high blood pressure during pregnancy (aOR=0.66, 95% CI=0.36–1.22), and having an amniocentesis during pregnancy (aOR=0.90, 95% CI=0.33–2.44). Interestingly, there was a positive association with birth control use at the time of pregnancy (aOR=1.53, 95% CI=0.61–3.87) and childhood rhabdomyosarcoma risk, as well as with ever birth control use and childhood rhabdomyosarcoma risk (aOR=1.45, 95% CI=0.96–2.18); however, these associations are not statistically significant.
Table 2.
Associations of maternal characteristics with childhood rhabdomyosarcoma
| Characteristic | Controls | Cases | ORa | 95% CI | p-value |
|---|---|---|---|---|---|
| Using birth control when became pregnant, n (%) | 9 (3.1) | 13 (4.4) | 1.53 | 0.61–3.87 | 0.365 |
| Used fertility medications to help become pregnant, n (%) | 7 (7.2) | 5 (1.6) | 0.71 | 0.22–2.27 | 0.556 |
| Number of prenatal visits, n (%) | |||||
| <12 | 79 (25.8) | 66 (21.4) | 1.00 | Reference | |
| ≥12 | 227 (74.2) | 242 (78.6) | 1.16 | 0.77–1.76 | 0.476 |
| Amniocentesis | 12 (3.8) | 11 (3.5) | 0.90 | 0.33–2.44 | 0.835 |
| Spotting/cramping/abnormal vaginal bleeding, n (%) | 37 (11.8) | 67 (21.1) | 1.75 | 1.12–2.74 | 0.014 |
| High blood pressure during pregnancy, n (%) | 37 (11.8) | 28 (8.8) | 0.66 | 0.36–1.22 | 0.190 |
| Nausea or vomiting during pregnancy, n (%) | 160 (51.0) | 151 (47.5) | 0.84 | 0.59–1.18 | 0.308 |
| Anemia during pregnancy, n (%) | 46 (14.7) | 53 (16.8) | 1.27 | 0.81–1.99 | 0.306 |
| Cold or flu during pregnancy, n (%) | 101 (35.1) | 104 (34.7) | 1.02 | 0.70–1.48 | 0.927 |
| Ever used any birth control, n (%) | 226 (70.9) | 237 (74.3) | 1.45 | 0.96–2.18 | 0.078 |
| Stillbirths/miscarriages/abortions, n (%) | |||||
| 0 | 196 (68.3) | 195 (73.0) | 1.00 | Reference | |
| 1 | 70 (24.4) | 49 (18.4) | 0.84 | 0.51–1.39 | 0.504 |
| ≥2 | 21 (7.3) | 23 (8.6) | 1.05 | 0.52–2.14 | 0.893 |
OR = odds ratio; CI = confidence interval
Adjusted for sex, age, race, household income, and maternal and paternal education.
Birth characteristics and their associations with childhood rhabdomyosarcoma are presented in Table 3. Overall, there were no statistically significant associations detected, however, the results show positive associations with childhood rhabdomyosarcoma risk for low birth weight (aOR=1.69, 95% CI=0.71–4.01), high birth weight (aOR=1.35, 95% CI=0.77–2.37), preterm birth (aOR=2.51, 95% CI=0.74–8.49), and being delivered by Cesarean (aOR=1.44, 95% CI=0.90–2.31). There were no apparent associations with childhood rhabdomyosarcoma risk and birth order, maternal age, or paternal age.
Table 3.
Associations of birth characteristics with childhood rhabdomyosarcoma
| Characteristic | Controls | Cases | ORa | 95% CI | p-value |
|---|---|---|---|---|---|
| Birth order, n (%) | |||||
| 1st | 138 (43.3) | 138 (43.4) | 1.00 | Reference | |
| 2nd | 101 (31.7) | 102 (32.1) | 0.94 | 0.64–1.37 | 0.731 |
| ≥3rd | 80 (25.1) | 78 (24.5) | 0.94 | 0.61–1.44 | 0.779 |
| Birth weightb, n (%) | |||||
| Normal (2,500g to <4,000g) | 267 (86.1) | 247 (77.7) | 1.00 | Reference | |
| LBW (<2,500g) | 10 (3.2) | 29 (9.1) | 1.69 | 0.71–4.01 | 0.236 |
| HBW (≥4,000g) | 33 (10.7) | 42 (13.2) | 1.35 | 0.77–2.37 | 0.287 |
| Length of pregnancyc, n (%) | |||||
| Normal | 258 (81.4) | 258 (81.1) | 1.00 | Reference | |
| Premature | 9 (2.8) | 26 (8.2) | 2.51 | 0.74–8.49 | 0.137 |
| Overdue | 50 (15.8) | 34 (10.7) | 0.70 | 0.41–1.18 | 0.177 |
| Type of delivery, n (%) | |||||
| Vaginal | 273 (85.8) | 260 (81.3) | 1.00 | Reference | |
| Cesarean | 45 (14.2) | 60 (18.8) | 1.44 | 0.90–2.31 | 0.132 |
| Paternal age (years) at child’s birth, mean (SD) | 29.0 (6.4) | 29.0 (5.9) | 0.99 | 0.96–1.02 | 0.395 |
| Maternal age (years) at child’s birth, mean (SD) | 26.3 (5.2) | 26.2 (5.2) | 0.99 | 0.96–1.02 | 0.435 |
OR = odds ratio; CI = confidence interval; LBW = low birth weight; HBW = high birth weight
Adjusted for sex, age, race, household income, and maternal and paternal education.
Adjusted for length of pregnancy
Adjusted for birth weight
The results of our evaluation of the effect for heterogeneity between selected maternal and birth characteristics with embryonal and alveolar rhabdomyosarcoma, the major histologic subtypes, are presented in Table 4. Tumors classified as NOS were not included in this analysis due to possible within-group heterogeneity. When evaluating embryonal rhabdomyosarcoma alone and associations with selected maternal and birth characteristics, there were no statistically significant associations with the exception of abnormal vaginal bleeding during pregnancy (aOR=1.80, 95% CI=1.10–2.92) and being born via Cesarean (aOR=1.60, 95% CI=1.00–2.56). There were strong positive associations with alveolar rhabdomyosarcoma and low birth weight (aOR=4.46, 95% CI=1.41–2.41), high birth weight (aOR=2.41, 95% CI=1.09–5.35), and abnormal vaginal bleeding during pregnancy (aOR=2.49, 95% CI=1.25–5.00). Overall, there are no statistically significant differences in effects between embryonal and alveolar rhabdomyosarcoma and their associations with selected maternal and birth characteristics. Although these associations are not statistically significant, there appears to be potential differences in magnitude of effect between the risk of embryonal and alveolar rhabdomyosarcoma and several characteristics, including preterm birth (Embryonal: aOR=2.47, 95% CI=0.93–6.59; Alveolar: aOR=0.95, 95% CI=0.23–4.00), being born past term (Embryonal: aOR=0.58, 95% CI=0.33–1.02; Alveolar: aOR=0.95, 95% CI=0.44–2.08), low birth weight (Embryonal: aOR=1.64, 95% CI=0.62–4.32; Alveolar: aOR=4.46, 95% CI=1.41–14.1), and high birth weight (Embryonal: aOR=1.61, 95% CI=0.93–2.79; Alveolar: aOR=2.41, 95% CI=1.09–5.35). The p for heterogeneity was greater than 0.150 for all exposures.
Table 4.
Evaluation of effect heterogeneity among selected maternal and birth characteristics and childhood rhabdomyosarcoma histologic subtypes
| Characteristic | Embryonal RMS n=215 |
Alveolar RMS n=66 |
|||
|---|---|---|---|---|---|
|
| |||||
| ORa | 95% CI | ORa | 95% CI | p for heterogeneity | |
|
|
|||||
| Ever used any birth control | 1.19 | 0.80–1.79 | 1.41 | 0.75–2.62 | 0.624 |
| Using birth control when became pregnant | 1.51 | 0.59–3.90 | 1.13 | 0.23–5.40 | 0.706 |
| Spotting/cramping/abnormal vaginal bleeding | 1.80 | 1.10–2.92 | 2.49 | 1.25–5.00 | 0.357 |
| Anemia during pregnancy | 1.17 | 0.72–1.88 | 1.26 | 0.61–2.62 | 0.842 |
| Type of delivery | |||||
| Vaginal | 1.00 | Reference | 1.00 | Reference | |
| Cesarean | 1.60 | 1.00–2.56 | 1.18 | 0.53–2.63 | 0.449 |
| Birth weightb | |||||
| Normal (2,500g to <4,000g) | 1.00 | Reference | 1.00 | Reference | |
| LBW (<2,500g) | 1.64 | 0.62–4.32 | 4.46 | 1.41–14.1 | |
| HBW (≥4,000g) | 1.61 | 0.93–2.79 | 2.41 | 1.09–5.35 | 0.169 |
| Length of pregnancyc | |||||
| Normal | 1.00 | Reference | 1.00 | Reference | |
| Premature | 2.47 | 0.93–6.59 | 0.95 | 0.23–4.00 | |
| Overdue | 0.58 | 0.33–1.02 | 0.95 | 0.44–2.08 | 0.155 |
RMS = rhabdomyosarcoma; OR = odds ratio; CI = confidence interval; LBW = low birth weight; HBW = high birth weight
Adjusted for sex, age, and race.
Adjusted for length of pregnancy.
Adjusted for birth weight.
DISCUSSION
The objective of this assessment was to evaluate maternal and birth characteristics as potential risk factors for childhood rhabdomyosarcoma. Overall, in our analyses, these exposures do not seem to be strongly associated with childhood rhabdomyosarcoma. Our analysis showed that cramping, spotting, or abnormal vaginal bleeding during pregnancy was positively associated with an increased risk of childhood rhabdomyosarcoma. A previous assessment by Grufferman et al. evaluated prenatal X-ray exposure and childhood rhabdomyosarcoma using the same data (study population) as that used in the current assessment. In the previous report, it was noted that there were more case mothers who reported abnormal vaginal bleeding compared to control mothers, and the authors suggested that abnormal vaginal bleeding during pregnancy may lead to increased exposure to X-ray examinations and therefore increased fetal X-ray exposure [11]. This may explain the association between abnormal vaginal bleeding and childhood rhabdomyosarcoma risk in the current assessment, as it was concluded by Grufferman et al. that prenatal X-ray exposure contributes to an increased risk of childhood rhabdomyosarcoma [11]. In addition, abnormal vaginal bleeding may be a marker for gynecological inflammation [30], inducing oxidative stress and DNA damage and, therefore, predisposing the fetus to developing a malignancy in childhood. Conversely, another report found that abnormal vaginal bleeding during pregnancy had a protective effect on leukemia risk in children with Down Syndrome, potentially due to early immune response activation [31]. The differential effects of abnormal vaginal bleeding on childhood cancer risk suggest that distinguished etiological mechanisms are responsible for the development of leukemia and rhabdomyosarcoma. Further studies evaluating samples independent from that of our assessment are needed to confirm the findings reported here. If these associations are consistent with our findings, more work is needed to understand the potential mechanism.
While maternal characteristics have not been extensively studied, there are a few previous studies reporting on maternal history of stillbirths or miscarriages and risk of childhood rhabdomyosarcoma. Grufferman et al. reported a statistically non-significant positive association of history of miscarriage and risk of childhood rhabdomyosarcoma (OR=1.9, 95% CI=0.6–6.2), however, there were only 33 cases included in this assessment [21]. An assessment by Ghali et al. included 103 rhabdomyosarcoma cases and reported a strong positive association between maternal history of at least one stillbirth and risk of childhood rhabdomyosarcoma (OR=3.7, 95% CI=1.5–8.9) [23]. In contrast, Hartley et al. found that mothers of children with rhabdomyosarcoma (n=27) had fewer prior miscarriages compared to mothers of control children (p=0.008) [24]. Our results show no association between maternal history of total pregnancy losses and risk of childhood rhabdomyosarcoma. Additionally, there is previous evidence suggesting that assisted fertilization may increase the risk rhabdomyosarcoma in children [32], however, no association was detected between maternal use of fertility medications and childhood rhabdomyosarcoma risk in our sample. This may be due do limitations in sample size or differences in current fertility treatments and those used in the 1980’s and before, the birth period of all subjects included our sample.
Although there is a deficit of studies evaluating maternal characteristics and risk of childhood rhabdomyosarcoma, several studies have assessed the effect of various birth characteristics. A series of studies evaluating birth characteristics and childhood cancer using pooled cancer registry data from five states in the United States [9, 13, 18, 20], included two studies which reported a possible protective effect of low birth weight on childhood rhabdomyosarcoma risk (OR=0.66, 95% CI=0.38–1.14), however the associations in both studies were not statistically significant [18, 20]. In addition, a study using data from the California Cancer Registry found no relationship between birth weight and childhood rhabdomyosarcoma (OR=1.00, 95% CI=0.71–1.40) [22], and, similarly, a case-control study conducted in England found no difference in median birth weight among cases diagnosed with a soft tissue sarcoma and unaffected controls [24]. Conversely, our results suggest that low birth weight may possibly increase the risk of childhood rhabdomyosarcoma (OR=1.69, 95% CI=0.71–4.01), however these findings are not statistically significant. This association was particularly strong in the alveolar histologic subtype (aOR=4.46, 95% CI=1.41–14.1).
Previous work of other birth characteristics have suggested an inverse relationship between birth order and childhood rhabdomyosarcoma risk [9, 20], and a positive association between older maternal age at birth [13, 20–22] and older paternal age at birth [20, 22] and childhood rhabdomyosarcoma risk. However, Hartley et al. found no difference in median parental age at birth among soft tissue sarcoma cases and unaffected controls [24], and Johnson et al. found no association between paternal age at birth and risk of childhood rhabdomyosarcoma [13]. Associations for birth order and parental age were not detected for childhood rhabdomyosarcoma in our sample. The variation in the results reported in our study compared to previous studies may be due to differences in study design, sample size, confounders adjusted for in the regression models, and the years and ages in which the cases were diagnosed.
Although some investigators have looked at birth characteristics and maternal exposures during pregnancy in relation to childhood rhabdomyosarcoma, the largest of these studies have relied on the same set of cancer registry data. While registry data can be informative, use of these data requires linkage to birth records, which do not adequately capture maternal exposures during pregnancy. Our assessment relied on a case-control study design, which included extensive questionnaire data about the child as well as detailed information about previous parental exposures including the mother’s exposures during pregnancy and her obstetric history. Furthermore, selection bias may be introduced into linkage studies as only cases with a matching birth certificate are included; these studies often exclude those who were born outside the state where they were diagnosed. This case-control study drew rhabdomyosarcoma cases from the IRSG, which coordinated treatment for 80–85% of the all childhood rhabdomyosarcoma cases diagnosed in the United States in April 1982 through July 1988. Inclusion in this study did not rely on linkage to birth records reducing the likelihood of this form of selection bias.
There are several limitations to consider when interpreting the results presented in this report. First, as with any study that relies on questionnaire data, there is the potential for recall bias where mothers of cancer patients may be more likely to accurately report adverse pregnancy and birth outcomes in light of their child’s cancer diagnosis. Recall bias may also explain the significant finding reported in the current study that abnormal vaginal bleeding during pregnancy is positively associated with childhood rhabdomyosarcoma. It is impossible to know if recall bias influenced the results reported here as information from birth certificates and medical records were not available; however, a study evaluating the associations of maternal and birth characteristics with childhood leukemia reported good agreement between maternal interview and birth certificates with respect to maternal age, birth weight, and birth order [14]. Furthermore, it is possible that maternal recall could be differential across the varying ages of children at the time of interview, where mothers may have more accurate responses when reporting on a more recent pregnancy compared to those reporting on a more distant pregnancy. In this assessment, cases and controls were pair-matched by age at diagnosis/interview; therefore, if recall bias were present in those reporting on older pregnancies, the effect sizes would be biased toward the null.
Although the case-control sample used in this assessment is one of the largest available for childhood rhabdomyosarcoma that includes extensive questionnaire information, it is possible that there was not sufficient power to detect the associations under evaluation. This may be particularly true for the sub analyses of the associations with the individual rhabdomyosarcoma histologic subtypes (Embryonal: n=215; Alveolar: n=66). Childhood rhabdomyosarcoma is a rare disease, which creates challenges in obtaining sufficient sample sizes to detect more subtle associations, particularly with exposures during the perinatal period, which requires data beyond that which is available from birth records.
In conclusion, our study evaluated maternal and birth characteristics as potential risk factors for childhood rhabdomyosarcoma. This assessment suggests that cramping, spotting, or abnormal bleeding during pregnancy may increase the risk of childhood rhabdomyosarcoma; however, this finding must be validated in an independent population. With this exception, there were no other maternal or birth characteristics in this assessment that were significantly associated with childhood rhabdomyosarcoma. Further studies are required to confirm these results and to further investigate potential risk factors for childhood rhabdomyosarcoma. Identifying risk factors for childhood rhabdomyosarcoma and furthering our understanding of the etiologies behind childhood rhabdomyosarcoma may inform future prevention strategies.
Acknowledgments
This work was supported by U.S. National Cancer Institute grants CA21244, CA24507, CA30318, CA30969, CA29139, and CA13539, and in part by Kurt Groten Family Research Scholars Award (P. Lupo).
Footnotes
CONFLICT OF INTEREST
The authors declare that they have no conflict of interest.
References
- 1.Ognjanovic S, Linabery AM, Charbonneau B, Ross JA. Trends in childhood rhabdomyosarcoma incidence and survival in the United States, 1975–2005. Cancer. 2009;115:4218–26. doi: 10.1002/cncr.24465. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Ries L, Smith M, Gurney J, et al. NIH Pub No 99-4649. Bethesda, MD: National Cancer Institute, SEER Program; 1999. Cancer Incidence and Survival among Children and Adolescents: United States SEER Program 1975–1995. [Google Scholar]
- 3.Gurney JG, Young JL, Jr, Roffers SD, Smith MA, Bunin GR. Cancer Incidence and Survival Among Children and Adolescents: United States SEER Program 1975–1995. National Cancer Institute SEER Program; 1999. Soft Tissue Sarcomas. [Google Scholar]
- 4.Malempati S, Hawkins DS. Rhabdomyosarcoma: review of the Children’s Oncology Group (COG) Soft-Tissue Sarcoma Committee experience and rationale for current COG studies. Pediatr Blood Cancer. 2012;59:5–10. doi: 10.1002/pbc.24118. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Ruymann FB, Maddux HR, Ragab A, et al. Congenital anomalies associated with rhabdomyosarcoma: an autopsy study of 115 cases. A report from the Intergroup Rhabdomyosarcoma Study Committee (representing the Children’s Cancer Study Group, the Pediatric Oncology Group, the United Kingdom Children’s Cancer Study Group, and the Pediatric Intergroup Statistical Center) Med Pediatr Oncol. 1988;16:33–9. doi: 10.1002/mpo.2950160109. [DOI] [PubMed] [Google Scholar]
- 6.Li FP, Fraumeni JF., Jr Soft-tissue sarcomas, breast cancer, and other neoplasms. A familial syndrome? Ann Intern Med. 1969;71:747–52. doi: 10.7326/0003-4819-71-4-747. [DOI] [PubMed] [Google Scholar]
- 7.Yang P, Grufferman S, Khoury MJ, et al. Association of childhood rhabdomyosarcoma with neurofibromatosis type I and birth defects. Genet Epidemiol. 1995;12:467–74. doi: 10.1002/gepi.1370120504. [DOI] [PubMed] [Google Scholar]
- 8.Diller L, Sexsmith E, Gottlieb A, Li FP, Malkin D. Germline p53 mutations are frequently detected in young children with rhabdomyosarcoma. J Clin Invest. 1995;95:1606–11. doi: 10.1172/JCI117834. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Von Behren J, Spector LG, Mueller BA, et al. Birth order and risk of childhood cancer: a pooled analysis from five US States. Int J Cancer. 2011;128:2709–16. doi: 10.1002/ijc.25593. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Grufferman S, Schwartz AG, Ruymann FB, Maurer HM. Parents’ use of cocaine and marijuana and increased risk of rhabdomyosarcoma in their children. Cancer Causes Control. 1993;4:217–24. doi: 10.1007/BF00051316. [DOI] [PubMed] [Google Scholar]
- 11.Grufferman S, Ruymann F, Ognjanovic S, Erhardt EB, Maurer HM. Prenatal X-ray exposure and rhabdomyosarcoma in children: a report from the children’s oncology group. Cancer Epidemiol Biomarkers Prev. 2009;18:1271–6. doi: 10.1158/1055-9965.EPI-08-0775. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Lupo PJ, Zhou R, Skapek SX, et al. Allergies, atopy, immune-related factors and childhood rhabdomyosarcoma: A report from the children’s oncology group. Int J Cancer. 2013 doi: 10.1002/ijc.28363. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Johnson KJ, Carozza SE, Chow EJ, et al. Parental age and risk of childhood cancer: a pooled analysis. Epidemiology. 2009;20:475–83. doi: 10.1097/EDE.0b013e3181a5a332. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Ma X, Metayer C, Does MB, Buffler PA. Maternal pregnancy loss, birth characteristics, and childhood leukemia (United States) Cancer Causes Control. 2005;16:1075–83. doi: 10.1007/s10552-005-0356-9. [DOI] [PubMed] [Google Scholar]
- 15.Oksuzyan S, Crespi CM, Cockburn M, Mezei G, Kheifets L. Birth weight and other perinatal factors and childhood CNS tumors: A case-control study in California. Cancer Epidemiol. 2013;37:402–9. doi: 10.1016/j.canep.2013.03.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Partap S, MacLean J, Von Behren J, Reynolds P, Fisher PG. Birth anomalies and obstetric history as risks for childhood tumors of the central nervous system. Pediatrics. 2011;128:e652–7. doi: 10.1542/peds.2010-3637. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Schmidt LS, Schuz J, Lahteenmaki P, et al. Fetal growth, preterm birth, neonatal stress and risk for CNS tumors in children: a Nordic population- and register-based case-control study. Cancer Epidemiol Biomarkers Prev. 2010;19:1042–52. doi: 10.1158/1055-9965.EPI-09-1273. [DOI] [PubMed] [Google Scholar]
- 18.Spector LG, Puumala SE, Carozza SE, et al. Cancer risk among children with very low birth weights. Pediatrics. 2009;124:96–104. doi: 10.1542/peds.2008-3069. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Westergaard T, Andersen PK, Pedersen JB, et al. Birth characteristics, sibling patterns, and acute leukemia risk in childhood: a population-based cohort study. J Natl Cancer Inst. 1997;89:939–47. doi: 10.1093/jnci/89.13.939. [DOI] [PubMed] [Google Scholar]
- 20.Ognjanovic S, Carozza SE, Chow EJ, et al. Birth characteristics and the risk of childhood rhabdomyosarcoma based on histological subtype. Br J Cancer. 2010;102:227–31. doi: 10.1038/sj.bjc.6605484. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Grufferman S, Wang HH, DeLong ER, Kimm SY, Delzell ES, Falletta JM. Environmental factors in the etiology of rhabdomyosarcoma in childhood. J Natl Cancer Inst. 1982;68:107–13. [PubMed] [Google Scholar]
- 22.Shrestha A, Ritz B, Ognjanovic S, Lombardi CA, Wilhelm M, Heck JE. Early life factors and risk of childhood rhabdomyosarcoma. Front Public Health. 2013;1:17. doi: 10.3389/fpubh.2013.00017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Ghali MH, Yoo KY, Flannery JT, Dubrow R. Association between childhood rhabdomyosarcoma and maternal history of stillbirths. Int J Cancer. 1992;50:365–8. doi: 10.1002/ijc.2910500306. [DOI] [PubMed] [Google Scholar]
- 24.Hartley AL, Birch JM, McKinney PA, et al. The Inter-Regional Epidemiological Study of Childhood Cancer (IRESCC): case control study of children with bone and soft tissue sarcomas. Br J Cancer. 1988;58:838–42. doi: 10.1038/bjc.1988.321. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Puumala SE, Carozza SE, Chow EJ, et al. Childhood cancer among twins and higher order multiples. Cancer Epidemiol Biomarkers Prev. 2009;18:162–8. doi: 10.1158/1055-9965.EPI-08-0660. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Sprehe MR, Barahmani N, Cao Y, et al. Comparison of birth weight corrected for gestational age and birth weight alone in prediction of development of childhood leukemia and central nervous system tumors. Pediatr Blood Cancer. 2010;54:242–9. doi: 10.1002/pbc.22308. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Grufferman S, Delzell E, Delong ER. An approach to conducting epidemiologic research within cooperative clinical trials groups. J Clin Oncol. 1984;2:670–5. doi: 10.1200/JCO.1984.2.6.670. [DOI] [PubMed] [Google Scholar]
- 28.Bunin GR, Spector LG, Olshan AF, et al. Secular trends in response rates for controls selected by random digit dialing in childhood cancer studies: a report from the Children’s Oncology Group. Am J Epidemiol. 2007;166:109–16. doi: 10.1093/aje/kwm050. [DOI] [PubMed] [Google Scholar]
- 29.Glynn RJ, Rosner B. Methods to evaluate risks for composite end points and their individual components. J Clin Epidemiol. 2004;57:113–22. doi: 10.1016/j.jclinepi.2003.02.001. [DOI] [PubMed] [Google Scholar]
- 30.Strobino B, Pantel-Silverman J. Gestational vaginal bleeding and pregnancy outcome. Am J Epidemiol. 1989;129:806–15. doi: 10.1093/oxfordjournals.aje.a115195. [DOI] [PubMed] [Google Scholar]
- 31.Ognjanovic S, Puumala S, Spector LG, et al. Maternal health conditions during pregnancy and acute leukemia in children with Down syndrome: A Children’s Oncology Group study. Pediatr Blood Cancer. 2009;52:602–8. doi: 10.1002/pbc.21914. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Williams CL, Bunch KJ, Stiller CA, et al. Cancer risk among children born after assisted conception. N Engl J Med. 2013;369:1819–27. doi: 10.1056/NEJMoa1301675. [DOI] [PubMed] [Google Scholar]