AYA-NAV,A Patient-Informed,Tailored Needs Navigation Intervention for Adolescents and Young Adults With Cancer: A Pilot Study

Abstract

Introduction

Adolescents and young adults (AYAs; 15-39 years old) with cancer experience poorer health outcomes and lower engagement in survivorship care often due to disproportionate financial toxicity and unmet health-related social needs (HRSN; e.g., food insecurity, housing instability, transportation barriers). Research has shown that needs navigation, the systematic screening, referral, and follow-up to resolve these barriers, is a potential strategy to reduce financial hardship. We assessed the feasibility of AYA-NAV, a centralized needs navigation intervention, through a pilot study involving AYAs with cancer.

Methods

A prospective pilot study at a comprehensive cancer center screened AYAs for financial toxicity (i.e., COmprehensive Score for financial Toxicity (COST) score ≤22) and unmet HRSN. Patients who screened positive received the intervention, AYA-NAV, including case management support and digital HRSN navigation. Participants completed monthly check-ins with the study navigator to assess needs and, if appropriate, request navigation support. Participants completed surveys at 6 months to explore changes in COST or HRSN.

Results

Thirty AYAs consented (23 female, mean age: 32.3 years, range: 18-39 years) to participate. Twenty-six (87%) screened positive for either financial toxicity or unmet HRSN, and 23 of them received AYA-NAV (88%). Retention at 6 months was 15 of 23 (65%). Participants who received AYA-NAV indicated that the intervention was acceptable and appropriately addressed needs through various referrals to community organizations. Among AYAs who participated in AYA-NAV and completed a 6-month questionnaire, COST scores increased significantly (P = 0.024).

Conclusions

Delivery of AYA-NAV is feasible among AYAs with cancer. These findings inform refinements to AYA-NAV and support the need for a larger, randomized study to determine the efficacy of AYA-NAV on improving financial toxicity, HRSN, and other health outcomes.

Plain Language Summary

Young people between the ages of 15 and 39 who have cancer often face serious challenges during and after treatment. These include financial problems and difficulties meeting basic needs like food, housing, and transportation. These issues can make it harder for them to stay engaged in follow-up care and can lead to worse health outcomes. To help address this, we created a program called AYA-NAV, which connects young cancer patients with a trained support person (navigator) who helps identify their needs and connects them to helpful resources. This includes support for money concerns, housing, food, and more. We tested AYA-NAV in a small pilot study at a large cancer center to see if it was possible to deliver this program and if young patients found it helpful. We screened 30 young people with cancer for money and social needs. Most (87%) had at least one concern, and almost all (88%) chose to participate. The program included monthly check-ins and help finding support from community organizations. After six months, most participants said AYA-NAV was helpful and met their needs. Importantly, participants who completed the program reported a significant improvement in their financial well-being. This pilot study shows that AYA-NAV is a promising way to support young people with cancer. The next step is to test this approach in a larger study to better understand how well it works and how it can improve health outcomes.

Keywords

oncology financial hardship health-related social needs

Introduction

An increasing number of adolescents and young adults (AYAs: age 15-39 years) are diagnosed with cancer every year in the United States (U.S.), and 85% are expected to become long-term survivors.^1-3 AYAs with cancer have higher rates of financial toxicity, the negative financial impact of healthcare, compared to their healthy peers and older cancer survivors.^4-8 Financial toxicity encompasses financial, psychological, and behavioral aspects, and is associated with poorer health outcomes, lower engagement survivorship care, and bankruptcy.⁹ In a recent systematic review, adults with cancer and their caregivers spent between $180 and $2600 per month on cancer-related out-of-pocket expenses.¹⁰ To manage these costs, patients in the United States have reported delaying treatments or not adhering to treatment recommendations.^11,12 Beyond direct medical expenses, financial toxicity and a cancer diagnosis has shown to negatively impact formal education, employment stability, and earnings for AYAs.^13-15

Among AYAs with cancer, higher rates of financial toxicity are seen in low-income and historically minoritized racial and ethnic groups.^16-23 Social determinants of health (SDOH) and unmet health-related social needs (HRSN: financial strain or difficulty affording food, housing, transportation, or utilities) may predict who is at greater risk of financial toxicity and could benefit from navigation services.²³ Needs navigation includes a comprehensive assessment of the patient’s needs and includes guidance and referrals to organizations that may be able to provide support.²⁴ Interventions have shown potential effectiveness in promoting resilience and hope in patients, reducing financial toxicity levels, and improving clinical outcomes.^25-29 To date, institutional support (i.e., social work teams and financial counselors) and prior financial navigation interventions have often addressed direct medical financial hardship (e.g., outstanding medical bills), rather than HRSN, and have not been AYA focused.

AYA-NAV is a community-partnered, tailored needs navigation intervention. The intervention was adapted from adult-focused financial navigation interventions through qualitative input from AYAs and caregivers.^26,30,31 The conceptual framework³² was adapted from the World Health Organization SDOH Framework and existing financial toxicity frameworks,^7,33,34 informing our intervention. AYA-NAV aims to intervene on intermediary determinants of health, commonly experienced unmet HRSN (e.g., insurance navigation, local food, or transportation resources), and provides a hybrid model of community-organization support and digital delivery. The primary objective of this study was to pilot and report on the feasibility of delivering AYA-NAV to AYAs with cancer.

Methods

Study Design

The AYA-NAV pilot study was funded by the National Institutes of Health (NIH) (KL2TR001874, NCT06072833). Patients treated for cancer at an urban, academic medical center in the United States were enrolled in a prospective, single-arm interventional study to evaluate AYA-NAV. The reporting of this study conforms to the STROBE guidelines (see Supplemental File 1).³⁵ The full study protocol was previously published³⁶ and all study procedures were approved by the Columbia University Institutional Review Board (IRB #AAAU2405). The initial approval date was 11/16/2022. All participants provided verbal informed consent prior to enrollment in the study and consented to anonymized data for publication. All patients have been de-identified in this manuscript. This study was conducted in accordance with the Helsinki Declaration of 1975, as revised in 2024.

Intervention

AYA-NAV is a community partnered, needs navigation and resource provision intervention that leverages a centralized, hybrid navigation model. It includes (1) a voucher ($100) as nominal resource provision for immediate needs provided after enrollment; (2) direct referral to community organizations: Patient Advocate Foundation (PAF) and findhelp.org; (3) monthly check-ins from the study team, including a digital navigation support session of findhelp.org during the first monthly check-in. PAF, a national 501(c)(3) non-profit organization dedicated to reducing financial and social barriers to care, provides high-touch (personalized) case management services and financial aid to Americans with chronic, life-threatening, and debilitating illnesses. Findhelp.org is a digital platform with local resources for individual needs of a family. The brief monthly check-in sessions were scripted to assess (a) if the AYA connected with PAF and/or organizations through findhelp.org; (b) if support was received, (c) in what form it was received, and (d) if it was helpful. If desired, the study coordinator facilitated a reconnection to PAF or organizations on findhelp.org.

Eligibility criteria and enrollment

Participants were eligible if they met the following criteria: (1) aged 15-39 years, (2) diagnosed with cancer or having initiated treatment within the past 6 months, and (3) receiving their initial course of treatment for cancer (non-relapse). Caregivers, as self-defined by the patients, were permitted to co-participate with the AYA if they chose to do so.

AYAs were recruited through reports generated from the Electronic Health Record (EHR). Identified potential participants who met the eligibility criteria (ie, age, clinic, encounter timeframe) were recruited from outpatient settings in the Columbia University Irving Medical Center including pediatric, medical (specifically breast, gastrointestinal, hematologic), and gynecologic oncology.

After introduction by the healthcare team, eligible patients were consecutively approached in-clinic or by telephone to discuss the study. If participants were interested in the study, verbal consent was obtained and documented in the study enrollment log, given the minimal risk nature of this study and as approved by the IRB. The participant completed the prescreening survey either on paper or through a digital link to the survey in REDCap.

Given the single-arm nature of the pilot study, all AYAs who screened positive for either financial toxicity (COmprehensive Score for financial Toxicity (COST) score ≤22^37,38 or unmet HRSN (endorsement of food insecurity, housing instability, or transportation insecurity) in the prescreening survey were invited to participate in the intervention. Participants who screened negative received a standard resource document by email or printed, per the participant’s preference, that was co-developed with the social work team and patient advisors. This document includes resources for people living with cancer and is specifically tailored to common unmet needs for AYAs.

AYA-NAV study procedures

Navigation was delivered either via phone call or in-person during a participant’s appointment; these sessions were scripted in English and Spanish, and included referral to PAF and introduction to findhelp.org, followed by a tailored list of resources from the session that was sent by email or text, per participant preference. Monthly check-ins were conducted by the study navigator to assess additional unmet needs, engagement with the intervention components (PAF or findhelp.org), and to offer additional navigation support as needed. These check-ins were documented by the study navigator on an iteratively developed intake form; qualitative comments from participants were also documented to provide further insight into the patient experience and the acceptability of the intervention. Participants were asked to complete additional survey items at 6 months to inform acceptability and feasibility. All participants, regardless of whether they received the intervention, were asked to complete a follow-up survey after 6 months similar to the baseline survey to assess financial toxicity, HRSN, and other health-related measures. Standard procedures were implemented to follow up with participants in an effort to ensure all data was complete for demographic and FT/HRSN measures. Participants received a $25 gift card after completing each survey to thank them for their time. All monetary support, including the $100 voucher for participants that received AYA-NAV, was in the form of an electronic gift card that was emailed or texted to the participant, depending on their preference.

Bimonthly meetings were established prior to study activation that included the PI (MPB), study coordinators (RK, SA), and at least 1 member of the PAF team (JP, EB, or KG). Failure to meet fidelity metrics (e.g., outreach attempts to participants, referrals to PAF or findhelp.org) was discussed at team meetings. The central study team conducted up to 3 outreach attempts to collect each baseline measure, monthly check-in, or 6-month survey. PAF conducted at least 1 outreach attempt per participant enrolled. If the participant did not answer the phone, they documented up to 3 attempts to reach them at various times during the day and week. All participants were sent an email with the case manager’s telephone extension in case they wanted to reach out directly. If the participant indicated to the study team that they did not receive any calls or they still would like to contact a case manager during the monthly check-ins, they were referred to PAF a second time.

Study Instruments and Outcomes

As this was a pilot study, our primary outcome was feasibility, defined as the acceptance rate (percent eligible who agreed to participate in AYA-NAV). We further assessed feasibility with measures of acceptability, appropriateness, and fidelity.³⁹ Acceptability was assessed through study engagement, retention rate, and qualitative feedback during the monthly check-ins, using standardized note-taking templates. Appropriateness was measured as the proportion of potential participants who screened positive for financial toxicity or endorsement of food insecurity, housing instability, or transportation insecurity, which was measured with an established HRSN screening instrument across the health system.⁴⁰ Demographic information was assessed by patient-reported survey. Fidelity process measures were documented on standardized templates, including participant outreach attempts and information provided to the study navigator during monthly check-ins.

Guided by our conceptual framework, published in our protocol paper, we explored preliminary efficacy of AYA-NAV on changes in financial toxicity (COST),^37,41 HRSN, resilience, and health-related quality of life (HRQoL). Resilience, a measure of an individual’s stress-coping ability, was measured by the Connor-Davidson Resilience Scale (CD-RISC)⁴² 10-item scale.^43,44 HRQoL was assessed with the Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health 10-item scale.^45-47

Analysis

Descriptive statistics were used to describe participant characteristics and measures of feasibility. Preliminary impact of AYA-NAV was assessed using a paired 2-sample t-test to detect a mean difference in COST, CD-RISC, and PROMIS scores between baseline and 6-month.

Qualitative data from monthly check-ins were analyzed using directed content analysis⁴⁸ to identify facilitators and barriers to the feasibility of the intervention.

Results

Recruitment and Participant Characteristics

During the 6-month study period, thirty AYA patients were screened (23 female, 7 male) with a mean age of 32.3 (SD = 5.1) and age range of 18 to 39 years. One AYA opted to co-participate with a caregiver; this analysis includes data only from AYA participants. The most common diagnoses were lymphoma (n = 13) and breast cancer (n = 11), reflected in the majority female sample. Majority of participants were non-White (77%), English-speaking (77%), and covered by Medicaid (60%) insurance. Half (50%) identified as Hispanic ethnicity. Table 1 provides all demographic characteristics of the entire cohort (n = 30) and of those who received the intervention (n = 23). The flow of participant outreach, consent, screening, and follow-up can be found in the study CONSORT diagram (Figure 1).

Table 1.

Participant Demographics

Demographic	N (%) (out of 30)	Intervention group N (%) (out of 23)
Race/Ethnicity
Hispanic, any race	15 (50)	13 (57)
Non-hispanic black	6 (20)	5 (22)
Non-hispanic white	5 (17)	3 (13)
Non-hispanic other	3 (10)	1 (4)
Not reported	1 (3)	1 (4)
Language survey was completed in
English	24 (80)	17 (74)
Spanish	6 (20)	6 (26)
Language (most often spoken at home)
English	23 (77)	16 (70)
Spanish	10 (30)	9 (39)
Other	2 (7)	2 (9)
Highest level of schooling
Started high school but did not graduate	5 (17)	5 (22)
High school diploma/GED	7 (23)	4 (17)
Some college/special training after high school	3 (10)	3 (13)
Associate or bachelor’s degree	10 (33)	8 (35)
Graduate +	5 (17)	3 (13)
Employment status
Unemployed	11 (37)	10 (44)
Full-time	8 (27)	5 (22)
Part-time	6 (20)	5 (22)
Student	1 (3)	0 (0)
Other (i.e., babysitter)	2 (7)	1 (4)
Prefer not to answer	1 (3)	1 (4)
Marital status
Single	19 (63)	16 (70)
Married or living as married	9 (30)	6 (26)
Divorced or separated	1 (3)	0 (0)
Prefer not to answer	1 (3)	1 (4)
Insurance type
Medicaid or state-funded low-income insurance program (e.g,. CHIP)	18 (60)	17 (74)
Private insurance (through work or school)	7 (23)	2 (9)
Private insurance (purchased directly)	1 (3)	1 (4)
Missing data	4 (13)	3 (13)
Cancer type
Leukemia/Lymphoma	15 (50)	10 (44)
Breast cancer	9 (30)	8 (35)
Other	6 (20)	5 (22)

Figure 1.

Consort Diagram for Participants

Feasibility

Out of 30 participants who consented and completed the prescreening, 26 (87%) screened positive for financial toxicity or HRSN. Out of the 26 that screened positive, 23 agreed to participate in AYA-NAV, resulting in an 88% acceptance rate, surpassing our hypothesis of 80%.³² One participant declined participation and contact after initial screening assessment was not successful with the other 2 participants.

Of the 23 participants in AYA-NAV, 91% (n = 21) engaged with either PAF (74%, n = 17) or findhelp.org (78%, n = 18). Sixty-one (n = 14) percent engaged with both resources. Participants completed a total of 82 (71%) check-ins out of 115 (23 participants x 5 monthly check-ins). All (100%) participants connected at least once with the navigator. Month-to-month data can be found in Figure 1. Participants who re-engaged after a missed check-in often cited being busy, due to treatment or familial duties, and offered alternative contact methods such as in-clinic meetings or scheduling via text.

Eighty-seven percent of participants (n = 20) described AYA-NAV as easy to use, fitting, likeable, and helpful. Some AYAs suggested greater emphasis on vocational needs and preferred contact at more convenient times. Participants reported that they appreciated additional support or resource reconnection offered by the navigator during check-ins. However, due to minimal changes within a month, participants recommended and favored less frequent check-ins.

Of 23 participants that received AYA-NAV, 15 completed the 6-month assessment, resulting in a retention rate of 65%. Of note, the surveys for this single-arm pilot required that all data was completed prior to entry of participant identifying information (name), rather than a study-specific link sent to participants or initial ascertainment of participant identification. Multiple surveys were noted to be initiated but not completed; these data could not be used for analysis due to lack of individual participant identifying information. One participant withdrew for unknown reasons.

Fidelity

All (100%) of participants were referred to the Patient Advocate Foundation (PAF) for case management services. Of those referred, 17 (74%) participants reported they connected with a case manager. During study meetings with the PAF team, case managers reported to connect with 18 (78%) participants that were referred. This difference in reporting could be due to participants being involved in more than 1 support at once and potential confusion surrounding the components of AYA-NAV.

Ninety-six percent of participants who received the intervention were referred to findhelp.org at either Month 1 (n = 18; 78%) or Month 2 (n = 5; 22%) of the study. The 1 participant who missed the first 2 monthly check-ins and was not referred to findhelp.org was the participant who withdrew from the study.

Preliminary Efficacy

At baseline, 57% of 30 screened AYAs reported 2 or more HRSN with housing and food being the most common. HRSN data by domain is detailed in Table 2 and categorized similar to prior analyses of HRSN, also termed household material hardship, in caregivers of pediatric patient populations.⁴⁹ Of the 23 AYAs who received the intervention, most (87%) said that AYA-NAV addressed at least 1 of their needs, and, during check-ins, these needs were most commonly described to the study navigator as food costs (30%), high copays (17%), or cash assistance (17%). When comparing baseline HRSN to study completion, of the 15 AYAs that received the intervention and completed both assessments, prevalence of food insecurity changed from 8 (53%) to 9 (60%), housing instability changed from 10 (67%) to 7 (47%), transportation changed from 6 (40%) to 5 (33%), and utilities changed from 3 (20%) to 1 (7%). Overall, 8 unmet needs were resolved, and 3 new needs emerged (2, food; 1 transportation).

Table 2.

Frequency of Self-Reported HRSN Among Full Cohort of AYAs

Independent variable	No. (%), n = 30
HRSN domains present
Housing	17 (57)
Food	16 (53)
Transportation	9 (30)
Utilities	4 (13)
Any HRSN reported (binary variable)
No HMH reported (binary variable)	8 (27)
Yes, 1 or more	22 (73)
No. of reported HRSN domains (ordinal variable)
None	8 (27)
One	5 (17)
Two or more	17 (57)
Housing-based HRSN (categorical variable)
No HMH	8 (27)
Utilities and/or food, not housing	4 (13)
Housing only	2 (7)
Housing and at least 1 more (utilities and/or food)	15 (50)

Among these same 15 AYA participants, we observed an increase in mean COST scores from baseline (10.47, standard deviation [SD] 4.78) to 6 months (16.53, SD 8.58 [P = 0.024]), consistent with improvement in financial toxicity. HRQoL and resilience did not change significantly from baseline to study completion. These analyses are included in further detail in Supplemental File 2.

Refinements to AYA-NAV

This pilot study identified several refinements to improve intervention delivery; these refinements were documented during weekly study team meetings. Eight weeks into initial recruitment, study navigators began asking patients to save their contact number in their phone to facilitate the participant’s identification of the study navigator. The study team also began offering text messaging as a preferred mode of contact, in addition to offering phone calls and email. Both refinements resulted in higher engagement from participants.

Qualitative feedback from participants during study check-ins and assessments guided future refinements of AYA-NAV. These include reducing the number of check-ins from every month to months 3 and 6. Because some participants wanted visual interactions with the study navigator, we will offer flexible options for check-ins and survey completion (e.g., Zoom, Facetime, in clinic). To reduce confusion between AYA-NAV and other supports offered by the hospital, a study logo has been developed by our study team, which includes a patient advisory panel. To avoid missing data at 6 months and improve study retention rates, we have updated our survey distribution to automatically match with participant study ID, rather than asking for patient identifier at the end of the survey. Finally, AYA-NAV is being refined to include educational and vocational support for younger AYAs (NCT#06296641).

Discussion

Our pilot study of AYA-NAV supports continued development and testing of a hybrid, community-partnered needs navigation intervention. AYA-NAV was highly acceptable for AYAs with cancer and feasible to deliver to most participants. The study highlights important refinements, such as increased tailoring and flexible intervention delivery, that will be included in future iterations of AYA-NAV.

The high prevalence of financial toxicity and unmet HRSN (87%) and high acceptance rate (88%) confirm a significant need for and interest in this type of intervention within the AYA population. AYA-NAV can be feasibly delivered with high fidelity by a bilingual study navigator, as all but 1 participant were successfully referred to PAF and findhelp.org, and 91% of participants engaged with the intervention components. This indicates that a flexible, tailored intervention is appropriate to addressing the complex and evolving needs of AYAs with cancer. In addition to survey distribution processes, the observed lower-than-expected retention rate may be reflective of the frequent check-ins, many of which were completed but that may have resulted in participants being less likely to complete the lengthier survey at 6 months. We have reduced the frequency of check-ins, which has been directly incorporated into a refined AYA-NAV that is being tested in a larger, ongoing trial (NCT#06950983).

Documenting qualitative input from participants including how needs and engagement evolved throughout their cancer journey was helpful to interpreting the study findings and informing refinements at this stage of intervention development. Participant engagement is a documented challenge in prior navigation interventions, and, similar to prior research, the flexibility and support from a study navigator was highly valued by participants and may improvement engagement.^50,51 For example, some AYAs requested that check-ins be conducted via video call or in clinic, as they were often waiting for lab results during appointments. A real-time adjustment for how study check-ins were offered did not interfere with the primary components of the intervention but rather supported AYA engagement. This check-in format is also being tested in the ongoing trial (NCT#06950983).

Additionally, study procedures, including navigation support and check-ins, have been structured to support the scalability of AYA-NAV while allowing each component of the intervention to be individually tailored. Navigation interventions are historically resource-intensive, and integration of a digital component through findhelp.org reduces the resource burden while still allowing the intervention to be delivered with a human connection using the contact mode preferred by the AYA participant. This balance achieved by AYA-NAV enhances the applicability of the findings since scalability and cost-effectiveness facilitate the integration of social care interventions into routine care practices.⁵²

Financial and social needs navigation interventions have primarily been developed and tested among older cancer patients or mostly White populations.^30,53-55 AYA-NAV is also one of the first interventions to engage AYAs that are majority non-White, Hispanic, and Medicaid-insured, groups all disproportionately affected by financial toxicity.⁵⁰ The centralized model that partners with community organizations, leverages technology for at-home support, and employs bilingual navigation may reduce barriers to engagement for these marginalized groups. Future work should examine differential uptake by socioeconomic and demographic indicators.

There are several limitations to this pilot study that should be acknowledged. The small sample size and single-site recruitment limited the reproducibility and generalizability of our findings. Given that this is a pilot study, we anticipated 30 participants would be eligible for AYA-NAV after approaching 60+ patients.⁵⁶ The final sample size was ultimately determined by the study period completion; however, procedures for recruitment were greatly improved through lessons learned in this pilot study and have been integrated into subsequent randomized trial of AYA-NAV. The Patient Advocate Foundation and findhelp.org are based in the United States, and may reflect a different landscape of resources available compared with other health systems. This study also lacks the perspective of caregivers, who are often critical to the AYA cancer experience. This is primarily due to the distinct needs that were identified prior to this single arm pilot and justified a separate, ongoing pilot study for caregivers of younger AYAs at the same study-site (NCT#06296641). Lastly, the single-arm pilot design and incomplete survey data limit the interpretation of exploratory efficacy outcomes. However, a significant improvement in COST scores was observed, and the currently recruiting randomized trial will provide further signal-finding data and illuminate trajectories of changes in financial toxicity or prevalence of HRSN.

Conclusion

In summary, this formative pilot study of AYA-NAV supports the acceptability and feasibility of delivering a tailored, digitally supported, community partnered needs navigation intervention to AYAs with cancer. At this stage of intervention development, we are optimistic that the refinements to the intervention informed by this study will continue to produce promising results in reducing financial toxicity and addressing HRSN for AYAs with cancer.

Supplemental Material

Supplemental Material - AYA-NAV, A Patient-Informed, Tailored Needs Navigation Intervention for Adolescents and Young Adults With Cancer: A Pilot Study

Supplemental Material for AYA-NAV, A Patient-Informed, Tailored Needs Navigation Intervention for Adolescents and Young Adults With Cancer: A Pilot Study by Rhea K. Khurana, Rohit Raghunathan, Sabrina Alvarado, Stephen Crespo, Kathleen D. Gallagher, Rebekah Angove SM, Erin Bradshaw, Janet Patton, Kimberly Judon, Marcela Algave, Helen Dinh, Katie DiCola, Dara M. Steinberg, Shikun Wang, Dawn L. Hershman, Melissa P. Beauchemin in Cancer Control

Footnotes

Acknowledgements

The author team would like to thank the participants in this study for their time and interest in this study.

ORCID iD

Rhea K. Khurana

Ethical Approval

All study procedures were approved by the Columbia University Institutional Review Board (IRB #AAAU2405). The initial approval date was 11/16/2022. All participants provided verbal informed consent prior to enrollment in the study. All participants consented to use anonymized data for publication.

Author Contributions

Rhea K. Khurana:Writing-review & editing. Writing- original draft, Data curation. Rohit Raghunathan: Writing-review & editing. Methodology. Formal analysis. Sabrina Alvarado: Writing-review & editing. Data curation. Stephen Crespo: Writing-review & editing. Formal analysis. Data curation. Kathleen D. Gallagher: Writing-review & editing. Resources, Methodology, Conceptualization. Rebekah SM Angove: Resources, Conceptualization. Erin Bradshaw: Resources, Conceptualization. Data curation. Janet Patton: Resources, Conceptualization. Data curation. Kimberly Judon: Writing-review & editing. Validation. Marcela Algave: Writing-review & editing. Helen Dinh: Writing-review & editing. Katie DiCola: Writing-review & editing. Validation. Dara M. Steinberg: Writing-review & editing. Shikun Wang: Writing-review & editing. Formal analysis. Dawn L. Hershman: Writing-review & editing. Conceptualization. Melissa P. Beauchemin: Writing- original draft, Supervision, Resources, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the This study was funded by a grant from the National Institutes of Health (NIH) (KL2TR001874, PI = Beauchemin). The content of this manuscript is the original work and solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Feasibility data are available from authors upon reasonable request.*

Supplemental Material

Supplemental material for this article is available online.

Appendix

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