For each article provide a one paragraph critique addressing the following below: For each article critique the study (how was it a good or bad study)Provide suggestions on how each study could be imp

Karasek, Laura L. Jelliffe-Pawlowski & Kelli K. Ryckman To cite this article: Sonia T. Anand, Elizabeth A. Chrischilles, Rebecca J. Baer, Mary E. Charlton, Patrick J. Breheny, William W. Terry, Monica R. McLemore, Deborah A. Karasek, Laura L.

Jelliffe-Pawlowski & Kelli K. Ryckman (2021): The risk of preterm birth among women with a history of leukemia or lymphoma, The Journal of Maternal-Fetal & Neonatal Medicine, DOI:

10.1080/14767058.2021.1907332 To link to this article: https://doi.org/10.1080/14767058.2021.1907332 View supplementary material Published online: 08 Apr 2021.Submit your article to this journal Article views: 108View related articles View Crossmark data ORIGINAL ARTICLE The risk of preterm birth among women with a history of leukemia or lymphoma Sonia T. Anand a , Elizabeth A. Chrischilles a, Rebecca J. Baer b,c , Mary E. Charlton a, Patrick J. Breheny d, William W. Terry e, Monica R. McLemore f , Deborah A. Karasek g, Laura L. Jelliffe-Pawlowski c,g and Kelli K. Ryckman a,e aDepartment of Epidemiology, University of Iowa, Iowa City, IA, USA; bDepartment of Pediatrics, University of California San Diego, La Jolla, CA, USA; cCalifornia Preterm Birth Initiative, University of California San Francisco, San Francisco, CA, USA; dDepartment of Biostatistics, University of Iowa, Iowa City, IA, USA; eDepartment of Pediatrics, University of Iowa, Iowa City, IA, USA; fDepartment of Family Health Care Nursing, University of California San Francisco, San Francisco, CA, USA; gDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA ABSTRACTObjective:Leukemia and lymphoma are top cancers affecting children, adolescents and young adults with high five-year survival rates. Late effects of these cancers are a concern in reproduct- ive-age patients, including pregnancy outcomes such as preterm birth. Our study aimed to evaluate whether diagnosis of leukemia or lymphoma prior to pregnancy was associated with preterm birth (<37 weeks gestation).

Methods:We conducted a cross-sectional study using a population-based dataset from California with linked birth certificates to hospital discharge records and an Iowa-based sample that linked birth certificates to Surveillance, Epidemiology, and End Results (SEER) cancer registry data. Preterm birth was defined using birth certificates. We ascertained history of leukemia and lymphoma using discharge diagnosis data in California and SEER registry in Iowa.

Results:Prevalence of preterm birth in California and Iowa was 14.6% and 12.0%, respectively, in women with a history of leukemia/lymphoma compared to 7.8% and 8.2%, respectively, in women without a cancer history. After adjusting for maternal age, race, education, smoking, and plurality, Women with history of leukemia/lymphoma were at an increased risk of having a pre- term birth in California (odds ratio (OR) 1.89; 95% confidence interval (CI) 1.56–2.28) and Iowa (OR 1.61; 95% CI 1.10–2.37) compared to those with no cancer history.

Conclusion:In both California and Iowa, women with a history of leukemia or lymphoma were at increased risk for preterm birth. This suggests the importance of counseling with a history of leukemia/lymphoma prior to pregnancy and increased monitoring of women during pregnancy. ARTICLE HISTORYReceived 21 August 2020 Revised 7 March 2021 Accepted 17 March 2021 KEYWORDSPreterm birth; leukemia; lymphoma; gestational age; premature Introduction Leukemias and lymphomas, which are among the most frequent cancers affecting children, adolescents and young adults, are highly curable with five-year survival approximately 80% for most types [1]. Once young people reach reproductive age, they are often concerned about the negative impact of their prior cancer on their reproductive health including infertility or adverse pregnancy outcomes such as preterm birth.

Preterm birth (PTB) is defined as having a baby born too early, specifically<37 weeks gestation.

According to the World Health Organization, there are approximately 15 million babies every year who are born preterm, which is more than 1 in 10 babies [2].In the United States in 2018 alone, approximately 1 in every 10 newborns was born preterm; 2018 was the fourth straight year that the rate increased [3]. There are 1.1 million deaths due to preterm birth globally and it continues to be one of the single greatest con- tributors to infant mortality in the United States and to disability-adjusted life years worldwide [4,5].

Identifying women at higher risk for preterm birth is important to inform research that aims to improve pregnancy outcomes in women with preexist- ing conditions.

There have been several studies of the effects of childhood, adolescent and young adult leukemia/ lymphoma on pregnancy outcomes [6–14]. The major- ity of these studies were retrospective cohort studies CONTACTKelli K. Ryckman [email protected], 145 N. Riverside Drive, S400 CPHB, Iowa City, Iowa, USA Supplemental data for this article is available online athttps://doi.org/10.1080/14767058.2021.1907332. 2021 Informa UK Limited, trading as Taylor & Francis Group THE JOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE https://doi.org/10.1080/14767058.2021.1907332 with less than 500 individuals with leukemia and lymphoma. The studies with more than 500 individuals used self-reported outcomes and/or compared out- comes to control groups that included individuals with another cancer-type [7,12,14]. Prior studies have yielded mixed results with some showing an increased risk of preterm birth among those with a history of leukemia/lymphoma [7–10] while others showed no significant risk [6,8,11–14].

We evaluated the relationship using birth-certifica- te-based measures of preterm birth linked with cancer information for two different large population-based US samples. Our primary objective was to evaluate the relationship of diagnosis of leukemia or lymphoma prior to pregnancy with preterm birth.

Methods Data source, linkages, and study population We had access to two retrospective administrative data sources, which included women who gave birth from two different geographical areas: the State of California and the State of Iowa. From the State of California, we conducted secondary data analysis on an existing birth certificate-linked dataset with mother and infant hospital discharge information from one year prior to birth (mother only) to one year postdeliv- ery (mother and infant) for births that occurred in California from 2007 to 2012. We have used this data- set for previous studies of preterm birth [15,16]. This dataset is maintained by the California Office of Statewide Health Planning and Development (OSHPD).

In Iowa, we developed a new dataset by linking Iowa birth certificates with Surveillance, Epidemiology, and End Results (SEER) cancer registry data covering the State of Iowa. Eligible participants included women who were Iowa residents age 44 or under at the time of a leukemia or lymphoma diagnosis between 1973 and 2018, linked to the first Iowa birth certificate after their cancer diagnosis date. Up to two randomly selected unexposed births were selected by matching on birth month and birth year to each Iowa exposed infant. The unexposed infant had to have a mother who was an Iowa resident and 18 years of age or older at delivery.

For both California and Iowa, we only included live births. In both states, we included both singletons and multiples, and births with gestation between 20 and 44 weeks and maternal age of<45 years. Additionally, where possible, we included only the first pregnancy of mothers during the study period and first preg- nancy after diagnosis. This information was notcomplete for the California data. We also excluded women who did not have complete information for the primary outcome of preterm birth and had more than one type of cancer. Study variables The primary outcome variable in this study was pre- term birth. Preterm birth is defined as a gestational age at delivery less than 37 weeks. In both California and Iowa, data on gestational age were obtained from birth certificates. Women who had a gestational age at birth that was 37 weeks were categorized as hav- ing a term birth.

The primary exposure variable of this study was a diagnosis of leukemia or lymphoma prior to birth. For California, to identify women with a history of leuke- mia and lymphoma, we used the following ICD-9 codes: 201.x-202.x, 203.1x, 204.x-208.x, V10.6, and V10.7. There have been two validation studies for these ICD-9 codes including V10 history codes although not specifically for pregnancy discharge data [17,18]. The sensitivity ranged from 80% to 90% and positive predictive values from 63% to 76% [17,18]. In Iowa, we used the 3rd edition of theInternational Classification of Diseases forOncology: C024, C098- C099, C111, C142, C379, C422, C770-C779, C420, C421, and C424. The comparison group were women with- out a prior history of cancer.

We used birth certificate data from both Iowa and California to capture important covariates including maternal age, maternal race, maternal education, smoking during pregnancy, prior live births, plurality, and gestational hypertension. Maternal race was defined as non-Hispanic White, Asian, Black, Hispanic, or Other race; maternal education was trichotomized by years of education of<12 years, 12 years, and >12 years; smoking during pregnancy was dichotom- ized as either yes or no; prior live birth was catego- rized as 0, 1, 2, and 3 or more; plurality was dichotomized as having singleton and twins or more; and gestational hypertension was defined as a new onset of hypertension during pregnancy and included preeclampsia and eclampsia with Iowa using birth cer- tificate data and California using diagnoses codes of ICD-9 642.1-3, 642.4-642.7. Prior live births was defined as births that occurred prior to the diagnosis of cancer and/or those births that occurred prior to the study period. Overall, there was<5% missing from any one variable, except for prior live births, there was<13% missing in Iowa. Furthermore, Iowa’s SEER registry 2 S. T. ANAND ET AL. data included information about cancer diagnosis and treatment.

The Iowa Cancer Registry data allowed us to cap- ture the following covariates: age at leukemia/lymph- oma diagnosis, time since diagnosis to birth (<3 years, 3-5 years, 6-8 years, and 9 or more years), cancer stage (local, regional, distant, or unstaged), cancer treatment (chemotherapy only, chemotherapy and radiation, radiation only, and neither chemotherapy nor radi- ation), hormone therapy (yes/no), immunotherapy (yes/no), chemotherapy (yes/no), and radiation (yes/no).

Statistical analysis For both California and Iowa, we used Chi-square tests and t-tests to compare descriptive characteristics for categorical variables and continuous variables, respect- ively. To assess the relationship between preterm birth and leukemia/lymphoma, we used logistic regression models for the California data, and conditional logistic regression models to account for matching in the Iowa data. We also adjusted for potential confounders in the multivariate analyses. Additionally, we evaluated gestational hypertension as a potential mediator in the relationship between preterm birth and leuke- mia/lymphoma.

With SEER data providing cancer treatment informa- tion in Iowa, we conducted an Iowa-only analysis to evaluate treatment effects. In both California and Iowa, we also conducted a sensitivity analysis to evalu- ate preterm birth among only singleton pregnancies.

Additionally, among women with preterm births, we compared leukemia/lymphoma history for women with spontaneous preterm birth versus women with indicated preterm birth. We also assessed the relation- ship between preterm birth with each cancer, leuke- mia and lymphoma, separately (Supplementary Table A1). All analyses were conducted in SAS 9.4 (SAS Institute, Cary, NC). Ap-value<.05 was considered as statistically significant.

Methods and protocols for the study using California data were approved by the Committee for the Protection of Human Subjects within the Health and Human Services Agency of the State of California.

De-identified data was provided to the researchers by the California Office of Statewide Health Planning and Development (Protocol # 12–09-0702) and determined not to qualify as human subjects research by the University of Iowa Institutional Review Board (IRB no.:

201602793). For Iowa data, the study was approved by the University of Iowa Institutional Review Board.Data was approved for linkage by the Iowa Department of Public Health (RA 3873) and by the University of Iowa Institutional Review Board (IRB no: 201811805). Results The descriptive characteristics of both the California cohort and the Iowa cohort can be seen inTable 1 and the flowcharts are shown inFigures 1and2.In California, a total of 1024 women had a history of leukemia or lymphoma and 2,468,625 women had no history of cancer coded in the dataset. In Iowa, there was a total of 515 women with a history of leukemia or lymphoma and 1009 unexposed selected with no history of cancer. In both states, women were mostly nonsmokers and had singleton pregnan- cies. Women with a history of leukemia/lymphoma gave birth at an older age and had a higher educa- tion level than women without a history of cancer in both California and Iowa. The racial and ethnic distri- butions of the two samples were consistent with known demographic differences between the two states. In California, where there is more racial and ethnic diversity, particularly notable differences between women with and without a history of leu- kemia or lymphoma were that women with a history of leukemia or lymphoma were less likely to be Hispanic (34.5% vs 50.6%, respectively) or Asian (7.3% vs 12.3%).

The cancer and treatment characteristics from the Iowa SEER registry are shown inTable 2. As expected, due to differences in age-specific incidence patterns and treatment options for leukemia and lymphoma, those with a history of leukemia had a more distant history of their cancer (78.6% were diagnosed 9 or more years prior to pregnancy) compared with lymph- oma patients (32.4% were diagnosed 9 or more years prior). Only 9.5% of leukemia patients were diagnosed within 3 years before pregnancy compared with 23.1% of those with prior lymphoma. Lymphoma patients were more likely to receive radiation or chemoradia- tion than leukemia patients who were most likely to receive chemotherapy only.

The prevalence of preterm birth in California among those without a history of cancer was 7.8%, compared to 14.6% in those with a history of leuke- mia/lymphoma (unadjusted odds ratio (OR) 2.03; 95% CI 1.71-2.42) (Table 3). The relationship between leuke- mia/lymphoma and preterm birth remained after adjusting for maternal age, race, education, smoking and plurality (OR: 1.89; 95% CI 1.56–2.28). In Iowa, the THE JOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE 3 Table 1.Descriptive characteristics by history of leukemia or lymphoma of California women who gave birth between 2007 and 2012 and Iowa women who gave birth between 1989 and 2018. CALIFORNIA IOWA Variable a Total (N¼2,469,649)Leukemia/ Lymphoma b(N¼1024) No Cancer (N¼2,468,625) P-value Total (N¼1524)Leukemia/ Lymphoma b(N¼515)No Cancer (N¼1009)pValue Preterm Birth<0.001 .016 Preterm birth (<37 weeks) 192524 (7.8%) 150 (14.6%) 192374 (7.8%) 145 (9.5%) 62 (12.0%) 83 (8.2%) No preterm birth (37weeks or more)2277125 (92.2%) 874 (85.4%) 2276251 (92.2%) 1379 (90.5%) 453 (88.0%) 926 (91.8%) Maternal Age at Birth<0.001 .002 <20 245360 (9.9%) 75 (7.3%) 245285 (9.9%) 92 (6.0%) 34 (6.6%) 58 (5.7%) 20-24 530999 (21.5%) 177 (17.3%) 530822 (21.5%) 359 (23.6%) 92 (17.9%) 267 (26.5%) 25-29 659507 (26.7%) 262 (25.6%) 659245 (26.7%) 505 (33.1%) 167 (32.4%) 338 (33.5%) 30-34 608744 (24.6%) 281 (27.4%) 608463 (24.6%) 400 (26.2%) 157 (30.5%) 243 (24.1%) 35-39 340692 (13.8%) 178 (17.4%) 340514 (13.8%) 138 (9.1%) 52 (10.1%) 86 (8.5%) 40-44 84347 (3.4%) 51 (5.0%) 84296 (3.4%) 30 (2.0%) 13 (2.5%) 17 (1.7%) Maternal Age (Continuous)<0.001 .003 mean and std 28.1 (6.3) 29.2 (6.2) 28.1 (6.3) 27.8 (5.4) 28.3 (5.4) 27.5 (5.3) median and IQR 28.0 (23.0, 33.0) 29.0 (25.0, 34.0) 28.0 (23.0, 33.0) 28.0 (24.0, 32.0) 28.0 (25.0, 32.0) 27.0 (23.0, 31.0) min and max (13.0, 44.0) (13.0, 44.0) (13.0, 44.0) (16.0, 43.0) (16.0, 43.0) (18.0, 43.0) Maternal Race/Ethnicity<0.001<.001 Asian 304811 (12.3%) 75 (7.3%) 304736 (12.3%) ccc Black 124112 (5.0%) 53 (5.2%) 124059 (5.0%) 55 (3.6%) 13 (2.5%) 42 (4.2%) Hispanic 1249865 (50.6%) 353 (34.5%) 1249512 (50.6%) 70 (4.6%) 9 (1.7%) 61 (6.0%) Other race 179609 (7.3%) 97 (9.5%) 179512 (7.3%) 48 (3.2%) 8 (1.6%) 40 (4.0%) Non-Hispanic White 611252 (24.8%) 446 (43.6%) 610806 (24.7%) 1351 (88.6%) 485 (94.2%) 866 (85.8%) Smoking History During Pregnancy0.016 .006 No smoking 2360594 (95.6%) 963 (94.0%) 2359631 (95.6%) 1298 (85.2%) 455 (88.3%) 843 (83.5%) Smoked during pregnancy 109055 (4.4%) 61 (6.0%) 108994 (4.4%) 215 (14.1%) 55 (10.7%) 160 (15.9%) Prior Live Births<0.001<.001 0 1157853 (46.9%) 555 (54.2%) 1157298 (46.9%) 433 (28.4%) 195 (37.9%) 238 (23.6%) 1 669706 (27.1%) 267 (26.1%) 669439 (27.1%) 495 (32.5%) 155 (30.1%) 340 (33.7%) 2 382400 (15.5%) 123 (12.0%) 382277 (15.5%) 257 (16.9%) 60 (11.7%) 197 (19.5%) 3 or more 258159 (10.5%) 79 (7.7%) 258080 (10.5%) 151 (9.9%) 32 (6.2%) 119 (11.8%) Maternal Education<0.001<.001 <12 years 636044 (25.8%) 135 (13.2%) 635909 (25.8%) 132 (8.7%) 29 (5.6%) 103 (10.2%) 12 years 625588 (25.3%) 215 (21.0%) 625373 (25.3%) 369 (24.2%) 101 (19.6%) 268 (26.6%) >12 years 1113706 (45.1%) 628 (61.3%) 1113078 (45.1%) 1013 (66.5%) 383 (74.4%) 630 (62.4%) Plurality<0.001 .178 Singleton 2425843 (98.2%) 988 (96.5%) 2424855 (98.2%) 1479 (97.0%) 504 (97.9%) 975 (96.6%) Twins and more 43806 (1.8%) 36 (3.5%) 43770 (1.8%) 45 (3.0%) 11 (2.1%) 34 (3.4%) aThe data source for gestational hypertension was from hospital discharge diagnoses for California and from birth certificate for Iowa. All other variables from both states came from birth certificates.bCalifornia: 324 Leukemia, 700 Lymphoma; Iowa: 126 Leukemia, 389 Lymphoma.cMaternal Race/Ethnicity: In Iowa, Asian was grouped with“Other race”due to<6 cell count. 4 S. T. ANAND ET AL. prevalence of preterm birth among women without a cancer history was 8.2%, compared to 12.0% in women with a history of leukemia/lymphoma (unadjusted OR 1.50; 95% CI 1.07–2.11) (Table 3) and this remained after adjusting for maternal age, race, education, smoking and plurality (OR: 1.61; 95% CI 1.10–2.37). There was no evidence of mediation through gestational hypertension as the odds ratio did not change in either Iowa (OR: 1.61 vs 1.56) or California (OR: 1.89 vs. 1.89) when this variable was added to the models (Table 3).

In analyses aimed at examining the potential increased risk associated with cancer treatments in Iowa (Table 4), sample sizes were small and estimates imprecise. Although no statistically significant differen- ces in the odds of preterm birth by cancer treatment were observed, there was an indication that a history of radiation (14.8% had preterm birth) or chemo-radi- ation (16.9% had preterm birth) treatment was associ- ated with greater adjusted risk of preterm birth compared with treatment using chemotherapy alone (9.6% had preterm birth).

In our analyses evaluating the relationship between preterm birth and each of the cancer types separately in both California and Iowa (Supplementary Table S1), increased risk was seen with each cancer type, and especially with lymphoma. This indicates that results may have been driven by those with a history of lymphoma. However, leukemia had a smaller sample size, which led to imprecise estimates.

It has been shown that the risk for preterm birth is higher in multiples compared to singletons [19,20]. To address this, we conducted sensitivity analysis to assess the risk of preterm birth among women with a history of leukemia/lymphoma com- pared to women without a history of cancer using only singleton pregnancies. In both California and Iowa, the adjusted odds ratios did not appreciably change when restricted to only singletons (California:

OR¼1.94 (95% CI 1.59–2.35); Iowa: OR¼1.77 (95% CI 1.19–2.64)). Additionally, we evaluated spon- taneous and indicated preterm birth only among those with a preterm birth. In California, there was no significant difference in odds of a leukemia/ lymphoma history between those with spontaneous preterm birth and those with indicated preterm birth (OR 0.81; 95% CI 0.52–1.26). In Iowa, due to inad- equate sample size in sub-group analyses, we were not able to differentiate between spontaneous and indicated preterm birth as the model would not converge. Total observations: 18367 Total after excluding observations that were not the first cancer: 17718 Maternal age <45 years of age:

17672 Total after excluding observations that were not the first birth: 13733 Only leukemia/lymphoma and unexposed subjects: 1560 Other cancers and their unexposed and those in the exposed group without a match:

12173 Total subjects in study: 1524 Excluded:

- 31 with chronic hypertension - 5 with unknown preterm birth status Figure 1.Flowchart of Iowa dataset. Total observations: 3059186 Total after excluding observations that were not the first baby: 2531478 Maternal age <45 years of age:

2524811 Only leukemia/lymphoma and no cancer history: 2520574 Total subjects in study: 2469649 Excluded:

- 50925 with chronic hypertension - 0 with unknown preterm birth status Figure 2.Flowchart of California dataset. THE JOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE 5 Discussion In two unique populations (Iowa and California), we found that there was a statistically significant increase in the odds of preterm birth among women with a prior history of leukemia or lymphoma compared to women without any prior history of cancer. Our find- ings are consistent with previous studies assessing the risk of preterm birth in women with a history leuke- mia/lymphoma (Supplementary Table S2). Although there was variability in outcome ascertainment between the studies, the findings were consistent in directionality and magnitude. The risk estimates for preterm birth in these other studies were consistent with ours and ranged from 1.50 to 2.60 for leukemia and 1.59 to 2.11 for lymphoma [6–10]. Specifically, in a study by Haggar et al., the risk for preterm birthamong leukemia patients was 1.72 (95% CI 1.18–2.41), and in another study by Anderson et al., there was an increased risk of 1.59 (95% CI 1.06–2.37) among Hodgkin lymphoma patients [8,10]. Although these studies assessed leukemia and lymphoma separately, they both found results of the same magnitude and direction as we did. There were, however, other studies that found no statistically significant relationship between preterm birth and leukemia/lymphoma with risks ranging from 0.4–1.54 [6,8,11–14]. Some of these used self-reported outcome data from questionnaires, were conducted mostly outside of the United States and included mostly women diagnosed between 15–39 years of age.

Possible explanations for the increase in preterm births among women with a history of leukemia or Table 2.Cancer and treatment characteristics of Iowa study sample who were diagnosed between 1973 and 2018 by can- cer type.

Variable Description Data Source a Leukemia (N¼126) c Lymphoma (N¼389) c Cancer Stage Local ICR 56 (14.4%) Regional 139 (35.7%) Distant 126 (100.0%) 80 (20.6%) Unstaged 114 (29.3%) Age At Cancer Diagnosis<5 ICR 37 (29.4%)– 5-9 36 (28.6%) 11 (2.8%) 10–14 22 (17.5%) 36 (9.3%) 15–19 11 (8.7%) 79 (20.3%) 20–24 9 (7.1%) 129 (33.2%) 25–29 7 (5.6%) 81 (20.8%) 30–44 S 53 (13.6%) Hormone Treatment None ICR 22 (17.5%) 239 (61.4%) Yes 104 (82.5%) 150 (38.6%) Immune Treatment None ICR 118 (93.7%) 376 (96.7%) Yes 8 (6.3%) 13 (3.3%) Time From Diagnosis To Delivery<3 years CALCULATED FROM ICR AND BC 12 (9.5%) 90 (23.1%) 3–5 years 8 (6.3%) 99 (25.4%) 6–8 years 7 (5.6%) 74 (19.0%) 9þyears 99 (78.6%) 126 (32.4%) Chemotherapy No ICR S 86 (22.1%) Yes 123 (97.6%) 303 (77.9%) Radiation Treatment No ICR 92 (73.0%) 182 (46.8%) Yes 34 (27.0%) 207 (53.2%) Cancer Treatment Breakdown b Chemotherapy only GROUPED FROM ICR 89 (70.6%) 161 (41.4%) Both Chemotherapy and Radiation 34 (27.0%) 142 (36.5%) Radiation only S 65 (16.7%) Neither Radiation nor Chemotherapy S 21 (5.4%) aData source: ICR- Iowa Cancer Registry.bA total of 93 women received surgery, typically coded as lymph node surgery.cS¼suppressed cells (<6 cell count).

Table 3.Risk of preterm birth among women<45 years of age with leukemia/lymphoma who gave birth, by state. California Iowa NWith preterm birth N With preterm birth Leukemia/Lymphoma,N(%) 1024 150 (14.6%) 515 62 (12.0%) No Cancer,N(%) 2,468,625 192,374 (7.8%) 1,009 83 (8.2%) Unadjusted model, OR (95% CI) 2.03 (1.71, 2.42) 1.50 (1.07, 2.11) Model 1: adjusted for age, race, education, plurality, smoking OR (95% CI)1.89 (1.56, 2.28) 1.61 (1.10, 2.37) Model 2: adjusted for covariates in Model 1 plus gestational hypertension (OR (95%CI)1.89 (1.56, 2.29) 1.56 (1.05, 2.30) p<.05. 6 S. T. ANAND ET AL. lymphoma include the late-effects of cancer treatment.

Chemotherapy drugs such as platinum agents and anthracyclines can cause renal impairments and cardi- otoxicities [21–24]. The renal impairments can lead to hypertension and preterm birth [25,26]. Additionally, obesity is a risk factor for preterm birth, and cortico- steroids, which are medications used in the treatment for cancer that can cause obesity [27–29]. The exact mechanism for corticosteroid and increases in body mass index are unknown, but a potential mechanism is that corticosteroids could cause changes in fat dis- tribution and metabolism and increase gluconeogene- sis [30,31]. Future studies, with carefully collected and longitudinal data on BMI before and during preg- nancy, are needed to investigate these potential mechanisms leading to preterm birth in women with a history of leukemia or lymphoma.

Furthermore, radiotherapy, especially to the abdom- inopelvic region such as for some lymphoma patients, can potentially damage the vagina, uterus, and/or ova- ries and thus lead to vaginal stenosis and fibrosis, uterine vasculature and musculature damage, and pre- mature ovarian insufficiency [32–38]. This damage can lead to adverse birth outcomes such as preterm birth [35,36].

Potential limitations of our study include misclassifi- cation of cancer history, lack of details on cancer type and treatment characteristics in the California data, and insufficient power for separate analyses of spon- taneous and medically indicated preterm birth. The California study used ICD-9 codes including V10 his- tory codes from the birth discharge abstract (86% of patients) and any discharges in the year prior to birth (14% of patients) to determine our primary exposure of leukemia or lymphoma. This could have potentially led to misclassification of our exposure by missing leu- kemia/lymphoma history in some subjects. Also, since we did not have the cancer date of diagnosis in California, we could not distinguish between women who had a recent cancer diagnosis, including some who were actively being treated for leukemia/ lymphoma during pregnancy, and women with a diag- nosis longer before pregnancy. In Iowa, we also didnot have the power to further stratify by different age groups and time intervals between diagnosis and childbirth. Additionally, in both California and Iowa we were unable to assessin vitrofertilization, which is a known risk factor for preterm birth and a potential mediator of the relationship between cancer and pre- term birth, given the observation that cancer patients are more likely to receivein vitrofertilization. Also, another limitation was that in Iowa, we were only approved to match on birth month and year for obtaining our unexposed births and could not match on other important factors such as maternal and paternal age at childbirth. Finally, we did not have adequate statistical power to assess indicated versus spontaneous preterm birth. However, the damage to the uterus and vagina caused by cancer treatment and impairments such as uterine vasculature and mus- culature damage, uterine fibrosis and cervical shorten- ing can potentially lead to either spontaneous or medically indicated preterm birth [32–40]. Despite these limitations, our study yielded results similar to previously conducted studies and it should be noted that any missed cancer diagnoses in the control group would have led to a dampening of our risk estimates which further bolsters our findings.

The replication of findings in two large samples– the whole States of Iowa and California–is a strength of this study. The racial/ethnic diversity of the popula- tions, one a primarily urban population and the other a mix of urban and rural, and the two distinct meth- ods of measuring leukemia/lymphoma history, enhance generalizability of the findings. Additional strengths include use of birth certificate data for the outcome of preterm birth for both states, which is an improvement on studies that relied on self-reported data. We were also able to ascertain complete infor- mation on cancer diagnoses and treatments from the Iowa SEER Cancer Registry.

Overall, our study found that there was an increased risk of preterm birth among women with a history of leukemia or lymphoma in both Iowa and California. Though challenging, it would be beneficial for additional studies to be conducted based on data Table 4.Risk of preterm birth among Iowa women<45 years of age with leukemia/lymphoma who gave birth between 1989 and 2018 by cancer treatment. Unadjusted model Adjusted model a Cancer Treatment b Total With preterm birth,N(%) c OR (95% Confidence Interval (CI)) OR (95% Confidence Interval (CI)) Chemotherapy only 250 24 (9.6%) Ref Ref Both chemotherapy and radiation 176 26 (14.8%) 1.63 (0.90, 2.95) 1.72 (0.89, 3.33) Radiation only 65 11 (16.9%) 1.92 (0.89, 4.16) 1.62 (0.66, 3.96) Neither radiation nor chemotherapy 24 S 0.41 (0.05, 3.17) 0.33 (0.04, 2.77) Adjusted for time from diagnosis to delivery, diagnosis age, and cancer stage. bA total of 93 women received surgery, typically coded as lymph node surgery.cS¼suppressed cells (<6 cell count). THE JOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE 7 with verified pregnancy outcomes, cancer and its treatments, and further assessment of the risk of pre- term birth in leukemia and lymphoma patients separ- ately and with each subtype such as acute lymphoblastic leukemia and non-Hodgkin’s lymphoma.

Future studies also need to address how leukemia or lymphoma impact fertility decisions and fecundity. Our study supports the importance of early identification of pregnant women and newborns at risk for compli- cations, which should then inform preventive interven- tions. Moreover, the ability to characterize and understand the contributors to adverse birth out- comes such as preterm birth and complications in newborns is important as it provides the potential for improved, tailored prenatal care as women can be provided more information on their risks, options, and opportunities to prepare for an early birth.

Acknowledgements The authors express our sincere thanks to Dr. Paul Romitti and his team at the Iowa Registry for Congenital and Inherited Disorders (IRCID)/Iowa vital records for their assist- ance with the linkage to the birth certificate data. The authors also like to express our gratitude to Jason Brubaker at the Iowa Cancer Registry for his assistance on providing the SEER Registry data and for linkage with the birth certifi- cate data in Iowa. This research is supported by the National Cancer Institute (P30 CA086862-18S6). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.

Disclosure statement This research is supported by the National Cancer Institute under Grant number P30 CA086862-18S6. Dr. Kelli Ryckman and Dr. Sonia Anand received the grant during the conduct of the study. Additionally, Dr. Ryckman has a patent for Serum Screening and Lipid Markers Predicting Preterm Birth pending. All other authors report no conflict of interest.

Author contributions Sonia T. Anand: Conceptualization, Formal analysis, Writing– original draft, Writing–review & editing; Elizabeth A.

Chrischilles: Conceptualization, Project administration, Supervision, Writing–review & editing; Rebecca J. Baer:

Data curation, Writing–review and editing; Mary E.

Charlton: Conceptualization, Writing–review and editing; Patrick J. Breheny: Conceptualization, Writing–review and editing; William W. Terry: Conceptualization, Writing–review and editing; Monica R. McLemore: Writing–review and edit- ing; Deborah A. Karasek: Writing–review and editing; Laura L. Jelliffe-Pawlowski: Writing–review and editing; Kelli K.

Ryckman: Conceptualization, Funding acquisition, Project administration, Supervision, Writing–review & editing. ORCID Sonia T. Anand http://orcid.org/0000-0002-5494-1821 Monica R. McLemore http://orcid.org/0000-0001- 6539-4256 References [1] Miller KD, Nogueira L, Mariotto AB, et al. Cancer treat- ment and survivorship statistics, 2019. CA A Cancer J Clin. 2019;69(5):363–385.

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