## INTRODUCTION

Universal newborn screening (NBS) has successfully decreased the morbidity and mortality of a wide range of severe pediatric-onset diseases including phenylketonuria, cystic fibrosis, and sickle cell disease.1 Genetic testing has the potential to augment universal NBS programs, and research exploring the medical, technological, public health, and ethical implications of universal newborn genetic screening is ongoing.2,3 Detection of germline pathogenic variants in genes associated with a high risk of early childhood tumors could be incorporated into expanded NBS programs; variant detection would prompt application of accepted clinical care recommendations currently utilized by pediatric oncologists for infants and children with known cancer predisposition syndromes (CPS).4

Decision modeling can evaluate the potential of genetic testing in NBS, as it can facilitate evidence synthesis, provide data to inform clinical guidelines,5,6 and evaluate new diseases for inclusion in NBS.7 This is especially useful in settings of rare diseases, like pediatric cancer, where sufficiently powered randomized clinical trials that test the clinical utility of NBS for early onset disease would be difficult. Using a decision-analytic framework, we asked: what are the potential clinical benefits, harms, and cost-effectiveness of newborn genetic screening, using a targeted next-generation sequencing (t-NGS) approach for a select panel of genes associated with early onset childhood cancer?

## MATERIALS AND METHODS

We developed the Precision Medicine Policy and Treatment (PreEMPT) model to estimate the potential risks and benefits of population-based genetic screening for pathogenic germline variants in RET, RB1, TP53, DICER1, SUFU, PTCH1, SMARCB1, PHOX2B, ALK, WT1, or APC. These autosomal dominant cancer predisposition genes were selected because of their association with very early onset malignancy and the availability of surveillance guidelines for early detection starting in infancy8,9,10,11,12,13,14 (Table 1). Using data from clinical studies, ClinVar,15 the Genome Aggregation Database (gnomAD),16 and the US Surveillance, Epidemiology and End Results (SEER) Program,17 we assigned each newborn a probability of carrying a pathogenic or likely pathogenic (P/LP) variant in each of the 11 genes (RET variants were restricted to those for multiple endocrine neoplasia type 2B [MEN2B]18). We limited variants to high-quality P/LP variants identified in ClinVar (i.e., 2-star) and confirmed the list via curation by the Mass General Brigham Laboratory for Molecular Medicine (Supplemental Tables 1, 2). The prevalence of P/LP variants was based on best available data from clinical studies for cancer cases and gnomAD data for noncancer cases (Supplemental Table 3). For genes without any P/LP variants in gnomAD, we assumed an allele frequency of 0.5 among the 282,912 alleles in gnomAD. We assumed that the occurrence of P/LP variants were independent and summed allele frequencies across all variants for each gene. Using Bayes’ theorem to synthesize data on the proportions of individuals with and without P/LP variants and who develop each cancer before age 20, we estimated the penetrance for each gene, defined as the probability an individual carrying a P/LP variant will develop a condition before age 20. See Supplemental Materials for additional details.

Cohorts of newborns representative of a modern US birth cohort were simulated under the scenarios of usual care and t-NGS at birth and followed throughout their lifetimes (Supplemental Fig. 1). Under t-NGS, we assumed newborns with identified P/LP variants would undergo cancer surveillance based on established guidelines (Table 1). As a best-case estimate of program efficacy, we assumed 100% adherence with t-NGS screening and surveillance recommendations.

Utilizing SEER data and published literature to estimate incidence, stage distribution, and outcomes, newborns were at risk for each cancer of interest (those associated with the 11 CPS). Treatment by stage for each diagnosis was based on standard care and included radiation and chemotherapy when indicated (Supplemental Table 4). Individuals who received chemotherapy and/or radiation as part of cancer treatment faced excess late mortality risks as adults starting at age 20 based on the Childhood Cancer Survivor Study.19,20 Newborns found to be heterozygotes of P/LP variants underwent surveillance, which resulted in early detection of malignancy, which, for specific cancers, resulted in reduced use of radiation and/or chemotherapy and improved outcomes (Table 1). Clinical benefit for t-NGS and associated surveillance was modeled as reductions in advanced disease, cancer deaths, and treatment-related late mortality.

Costs were estimated for direct medical costs, patient time costs, and genetic testing (for the t-NGS strategy) (Supplemental Table 5). For t-NGS, we assumed a cost of $55 for the 11-gene panel test (i.e.,$5 per gene) based upon expert input, current cost of NBS, and commercial cost for a panel test.21 We assumed that this cost reflected the incremental cost of adding the panel to a NBS program with existing infrastructure for genetic testing. Costs for surveillance and cancer treatment were based on published estimates and national databases. To account for patient time costs, we included parental time lost from work (see Supplemental Materials). All costs were expressed in 2018 dollars.

To capture uncertainty, we conducted 1,000 simulations in which each parameter was sampled from its underlying distribution and report the mean and 95% uncertainty interval (UI) for all outcomes. Given the goals of improving child health, the model did not include impact of early detection of adult-onset malignancy, which is increased in some CPS (for example, TP53), or impact on family member health/reflex genetic testing.

To assess the potential harms associated with t-NGS, most prominently the burden of a genetic diagnosis in the absence of a pediatric cancer occurrence, we defined individuals with P/LP variants who developed cancer before age 20 (true positives) as having “penetrant variant status” (PVS) and individuals with P/LP variants who did not develop cancer by age 20 as having “nonpenetrant variant status” (NPVS). This allowed us to illustrate the harm–benefit tradeoffs associated with t-NGS by estimating the number of NPVSs per PVS, cancer death averted, and life-year (LY) gained in the cohort.

## DISCUSSION

Leveraging data from ClinVar, gnomAD, SEER, and published literature, we used a model-based approach to estimate the potential clinical impact of universal genetic screening in newborns for pediatric CPS. Our findings suggest that under the best-case assumption of full adherence to screening and surveillance guidelines, t-NGS would identify approximately 1,580 individuals with P/LP CPS variants among 3.7 million newborns each year in the United States. If these newborns were evaluated, underwent genetic counseling, and offered cancer surveillance, more than half of cancer deaths among individuals with CPS variants would be averted. Further, as the costs of genetic screening decline, targeted newborn screening for pediatric cancer genes could be cost-effective given benchmarks for “good value.”23

Newborn screening for any disorder requires balancing the potential benefits (prevention or early detection of disease) and harms (unnecessary surveillance costs and parental anxiety). Inclusion of genetic testing for CPS risk as part of NBS programs will present new uncertainties, most importantly with respect to the “allowable” burden of tests detecting P/LP variants of unknown or low penetrance (e.g., parents who are told that the infant is at increased risk of cancer, but cancer may not manifest in childhood or at all). While we modeled 11 CPS genes as a panel, analyses on individual or subsets of genes can guide efforts to reduce potential harm by identifying genes with higher penetrance (e.g., RB1) or where the benefit is well understood (RET). Of importance, in our study, we assumed that the CPS test would be included as part of state-wide NBS programs, after completion of successful pilot testing. We recognize, however, that the process of adding new tests is complex and varies by state. In an alternative model, separate consent for this test (outside of usual NBS) would create added burden and require additional resources for implementation not reflected in our study.

While we provided estimates of the potential harm–benefit tradeoffs, we did not account for the impact of this knowledge on families, as well as other potential impacts of testing, such as risk of adult-onset cancer, family reproductive planning, and detection of cancer risk in family members; future studies should consider these important factors. Available data from families with CPS suggest that entering a child into a surveillance protocol based upon genetic testing decreased anxiety and did not create an excessive burden.24

We assumed full adherence to surveillance recommendations to estimate the potential survival benefit of surveillance for CPS-associated pediatric cancers. As the cost-effectiveness of screening was less favorable with lower adherence, ensuring adherence will be crucial to realize the projected benefits. Of note, other benefits of early detection to avert toxicity (such as avoidance of blindness after early detection of retinoblastoma) were not captured in our model.

We assumed, in our cost estimates, that NBS will move forward nationally to establish infrastructure that supports genetic screening in general. Additional resources will be needed to build this capacity, as well as support for families after genetic information disclosure. The benefits of surveillance, as modeled in our study, are based upon scant data, but represent current recommendations for clinically detected children with CPS. The National Cancer Institute (NCI) Childhood Cancer Data Initiative aims to collect data on every child diagnosed with cancer in the United States and may provide more precise data in the coming years. Our model can readily incorporate these and other new data as they become available to generate updated estimates.

While our findings are suggestive, using newborn genetic screening for pediatric CPS as an example, our study demonstrates how advances in genetics can be applied to populations, and what the implications might be for public health. Prospective clinical studies that investigate crucial factors—such as parental uptake of testing, impact of a genetic CPS diagnosis on families, adherence to surveillance, and effectiveness of surveillance in preventing advanced disease—are necessary before this testing can be proposed as a component of population-based newborn screening.