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Abstract Introduction Hispanic and non-Hispanic Black (NHB) patients have worse HCT survival compared to non-Hispanic White (NHW) patients and were less likely to utilize an unrelated HCT donor (Khera et al. Blood Adv. 2024; Hahn et al. JAMA Netw Open. 2024), but this difference has not been evaluated in the PTCy era. PTCy reduces graft-versus-host disease (GvHD) and allows for increased availability of allogeneic donors in minority patients. It is important to know the best donor source for each ethnicity. In this study, we investigated the association of race/ethnicity and donor type on overall survival (OS). Methods We performed a secondary analysis of adult patients (>19 yrs) who were selected if they had a peripheral blood allogeneic HCT from 2013-2018 and received PTCy for GVHD prophylaxis using a publicly available dataset from the Center for International Blood and Marrow Transplantation Research Program. Kaplan-Meier curves estimated 2-year OS, and differences were compared using log-rank tests. X2 tests helped identify potential confounders. Analyses were stratified by donor type and self-reported race/ethnicity. The Cox Proportional Hazards model evaluated 2-year OS using a backwards elimination method to build the final prediction model. P<0.05 was considered statistically significant. Results Of 4,031 patients included, 70% were NHW, 16% were NHB, and 13% were Hispanic. The most common donor was Haploidentical (Haplo; 64%), followed by matched unrelated donor (MUD; 19%), matched related donor (MRD; 10%), and mismatched unrelated donor 7%). Hispanic patients were younger than NHW and NHB (P<0.0001) and more were transplanted in CR (P<0.0001). Additionally, most Hispanic and NHB patients received a Haplo HCT (77 and 83%, respectively). NHW patients also received Haplo HCTs (57%) as well as MUD HCTs (24%). Most patients had acute myeloid leukemia (40%) followed by myelodysplastic syndrome (22%) and received reduced intensity conditioning (58%). MUD patients who received PTCy had the highest 2-year OS compared to other donors (65 vs 58-61%; P=0.03). Higher OS was observed in younger patients (20-39 yrs: 69% vs 60+ yrs: 53%; P<0.001) and patients with non-malignant diseases (80%) or Hodgkin lymphoma (79%) compared to patients with plasma cell (52%) and myelodysplastic disorders (55%; P<0.0001). For NHW patients, patients transplanted with a MUD had higher OS than other donor types (67 vs 58-60%; p=0.0006). In contrast, NHB transplanted with MRD, Haplo, or MMUD had the highest OS compared to MUD, although this was not statistically significant (61-66% vs 42%; p=0.4). Hispanic patients transplanted with a related donor (MRD and Haplo) had higher OS compared to patients who had an unrelated donor (MUD and MMUD; 66-67 vs 48-58%; P=0.1). Within each donor source, we tested for a racial disparity in OS. There was no difference in OS by race/ethnicity in MRD or MMUD HCTs. In Haplo HCTs, Hispanic patients had the highest OS followed by NHB and then NHW (66, 61, vs 58%; P=0.005). In MUD HCTs, NHW patients had higher OS than Hispanic or NHB patients (67, 48, vs 42%; P=0.02). Significant factors associated with OS in multivariable analyses included donor type, age, disease, year of transplant, conditioning intensity, Karnofsky Performance Score, donor/recipient CMV serostatus, and disease risk index. Results were stratified by race/ethnicity. For NHW patients, mortality risk was higher for HCT patients receiving a MRD, Haplo, or MMUD compared to a MUD (HR=1.25-1.39; P=0.001). In contrast, NHB patients receiving a MUD had a higher risk of mortality compared to a Haplo, MRD, or MMUD (HR=1.67; P=0.06). In Hispanic patients, MUDs and MMUDs had a higher mortality risk than MRD or Haplo HCT (HR=1.48; P=0.07). Conclusion OS differed by race/ethnicity and donor type. Our findings should be validated by expanding the analysis to include patients treated with PTCy after the publication of BMT CTN 1703 results (Bolaños-Mead et al. NEJM. 2023). When selecting donors for HCT patients, consideration should be given to patient race/ethnicity.

Importance Despite treatment advances, metastatic recurrence continues to be a leading cause of morbidity and mortality. Empirical data on the incidence and survival after metastatic recurrence remain limited, as cancer registries historically do not collect data on recurrence. Objective To estimate the cumulative incidence (CMI) of metastatic recurrence among adolescents and young adults diagnosed with earlier-stage disease and compare survival to those with metastatic disease at diagnosis. Design, Setting, Participants This was a retrospective cohort study of adolescents and young adults aged 15 to 39 years who were diagnosed with nonmetastatic cancers from 2006 to 2018. Adolescents and young adults were identified from the California Cancer Registry linked with statewide hospitalization, emergency department, and ambulatory surgery encounters from the California Department of Health Care Access and Information. Data were analyzed from December 2023 to June 2025. Exposures Cancer types, including melanoma, sarcoma, and breast, cervical, colorectal, testicular, and thyroid cancers. Main Outcomes and Measures Metastatic recurrence was identified using International Classification of Diseases, Ninth Revision, Clinical Modification, and Tenth Revision, Clinical Modification, metastatic disease codes at least 6 months after cancer diagnosis or from an underlying cancer cause of death. Follow-up was through December 31, 2020. Results Of a total of 48 406 adolescents and young adults (median [IQR] age at diagnosis, 33.0 [28.0-37.0] years; 67.4% female), 9.2% had metastatic disease at diagnosis, and 9.5% had metastatic recurrence. Among 43 935 adolescents and young adults who presented with nonmetastatic disease, the 5-year CMI of metastatic recurrences was highest among patients with sarcoma (24.5%; 95% CI, 22.6%-26.6%) and colorectal cancer (21.8%; 95% CI, 20.3%-23.4%) and intermediate for cervical (16.3%; 95% CI, 15.0%-17.6%) and breast (14.7%; 95% CI, 14.0%-15.4%) cancers. The CMI for metastatic recurrence increased with increasing stage at diagnosis, with 5-year CMIs higher than 30% for all stage III cancers (except thyroid). The 5-year CMI of metastatic recurrence also increased over time for cervical cancer (2006-2009: 12.7% [95% CI, 10.8%-14.8%]; 2015-2018: 20.4% [95% CI, 17.5%-23.6%]) and decreased for colorectal cancer (2006-2009: 24.4% [95% CI, 21.3%-27.6%]; 2015-2018: 19.2% [95% CI, 16.4%-22.2%]). Survival after metastatic recurrence was worse than metastatic disease at diagnosis for all cancer types, except for testicular and thyroid cancers. Conclusions and Relevance The findings from this cohort study highlight the overall burden of metastatic disease in adolescents and young adults, expanding the knowledge of metastatic recurrences that help improve care for adolescent and young adult survivors throughout the cancer survivorship spectrum.

Abstract Background Computational phenotyping from electronic health records (EHRs) is essential for clinical research, decision support, and quality/population health assessment, but the proliferation of algorithms for the same conditions makes it difficult to identify which algorithm is most appropriate for reuse. Objective To develop a framework for assessing phenotyping algorithm fitness for purpose and reuse. Fitness for Purpose Phenotyping algorithms are fit for purpose when they identify the intended population with performance characteristics appropriate for the intended application. Fitness for Reuse Phenotyping algorithms are fit for reuse when the algorithm is implementable and generalizable—that is, it identifies the same intended population with similar performance characteristics when applied to a new setting. Conclusions The PhenoFit framework provides a structured approach to evaluate and adapt phenotyping algorithms for new contexts increasing efficiency and consistency of identifying patient populations from EHRs.

Abstract WSD0922-Fu is an oral, CNS-penetrant, small molecule EGFR inhibitor which potently inhibits EGFR aberrations specific to non-small cell lung cancer (NSCLC) and glioblastoma (GBM). MC1914 (NCT04197934) is a first-in-human phase 1 trial in patients with EGFR aberrant recurrent GBM and NSCLC. After determining the maximum tolerated dose, adults with recurrent GBM were treated in two expansion cohorts: (a) non-surgical cohort (6/12 patients thus far): EGFRvIII mutation, first recurrence; food-effect study included (b) surgical cohort (6/6 patients), any EGFR mutation, any recurrence; window-of-opportunity study (WOO) included. Among these 12 patients, median age = 60 years; 50% female; 58% ECOG 0). All patients received prior radiation and temozolomide. After the WOO or food-effect study, patients were dosed at 120 mg BID (5 days on, 2 days off), and escalated to 160 mg BID (5 days on, 2 days off) based on tolerability. Common adverse events (>40%) are comparable to other EGFR inhibitors (acneiform rash, diarrhea, fatigue, xerosis, pruritis). Treatment-related grade 3+ adverse events were limited to lymphopenia (n = 1). WSD0922-Fu exposure in the fed state exceeded the fasted state (median plasma Cmax and AUC0-24h are 1.6x and 1.3x, respectively) with a delayed Tmax (6.0 vs 1.8 hours). For the WOO, time between last dose administered to tumor collection ranged between 4 - 13.5 hours. Median tumor WSD0922-Fu concentration was 0.76 µg/g; estimated median unbound tumor concentration was 24.9 ng/g and within expectations for pharmacodynamic effect. Median brain/plasma ratio = 0.59; median unbound brain/unbound plasma = 0.88. Enrollment to the non-surgical cohort is ongoing, so formal efficacy data remain immature. However, examples of clinical efficacy will be shown along with data on recurrence patterns. Phase 2 clinical trial development is in progress.

Abstract INTRODUCTION The Consortium for Clarity in Alzheimer's disease related dementias (ADRD) Research Through Imaging (CLARiTI) is a study that aims to collect standardized imaging and plasma biomarkers on 2000 Clinical Core participants enrolled across all Alzheimer's Disease Research Centers (ADRC) sites. We sought to summarize the known heterogeneity across centers regarding scientific focus and initial enrollment plans for CLARiTI. METHODS We developed and distributed a survey capturing information on the 36 CLARiTI site's theme/expertise, recruitment plans, and the intersection of CLARiTI with other ADRC imaging efforts. RESULTS Anticipated CLARiTI enrollees spanned 11 different categories of suspected etiologies underlying impairment. A wide range of risk factors were endorsed across sites regarding the enrollment of unimpaired individuals. Variability also existed regarding site‐level strategies in enrollment into CLARiTI versus other imaging efforts. DISCUSSION We anticipate that the 2000 individuals that will enroll into CLARiTI will reflect the clinical heterogeneity already in place across the ADRC network. Highlights The ADRC Consortium for Clarity in ADRD Research Through Imaging (CLARiTI) will leverage and contribute to the existing Alzheimer's Disease Research Centers (ADRC) program by supporting standardized imaging and plasma collection across all centers. We summarize the variation in scientific focus and enrollment plans across ADRC sites participating in CLARiTI. The anticipated CLARiTI cohort will reflect the clinical heterogeneity that already exists across the ADRC network. CLARiTI will contribute to scientific goals related to the detection of multi‐etiological signatures relevant for Alzheimer's disease and related disorders (ADRDs).

Background: Susceptibility to cardiometabolic diseases (CDs) is shaped by genetic, socio-environmental, and lifestyle factors. We evaluated the associations of disease-specific polysocial risk scores (PSSs)— derived from social determinants of health (SDOH) and lifestyle factors—and genetic risk factors with six CDs, across self-identified race/ethnicity (SIRE) groups in the eMERGE IV cohort. Methods: The six CDs included: atrial fibrillation, coronary heart disease, chronic kidney disease, hyperlipidemia, obesity, and type 2 diabetes. Disease-specific PSSs were developed using machine-learning models based on 65 SDOH and lifestyle factors. Participants were grouped based on their SIRE as Asian, Black, Hispanic/Latino, and White. We evaluated PSS distributions across SIRE groups. Genetic risk was assessed through disease-specific polygenic risk scores (PRSs), monogenic etiologies, and family history (FamHx). High PSS and high PRS were defined as the top 5th percentile. Associations were tested using multivariable logistic regression; model performance was assessed using the C-statistic. Results: Among 20178 participants (50±15 years, 68% female, 40% non-White), the most frequently associated PSS components were physical activity, sleep, self-perceived health, and income. PSS distributions varied across SIRE groups, with Whites having the lowest and Black and Hispanic/Latinos the highest scores for most CDs (Figure 1). All PSSs were significantly associated with their respective CDs, independent of confounders (OR per 1 SD increase: 1.19–2.68; Figure 2-A). No significant interactions were observed between PSSs and PRSs or monogenic etiologies. However, significant interactions were noted between PSSs and FamHx for CKD and obesity. PSS and PRS effects on the odds of CDs were independent (Figure 2-B) and additive (Figure 2-C). Incorporating PSSs into models that included clinical and genetic risk factors improved predictive performance of risk prediction models (Figure 3). Conclusion: PSSs, reflecting socio-environmental and lifestyle disadvantage, varied significantly across SIRE groups and were associated with risk of six CDs, independent of and additive to PRS. Given the substantial variation in socio-environmental and lifestyle risks across SIRE groups, integrating these factors into risk prediction models for CDs may help address health disparities and enhance preventive efforts, especially in marginalized populations.

Abstract Background Few studies have assessed the burden of chronic medical conditions in adolescent and young adult (AYA) cancer survivors. This study estimated the risk of these conditions among AYA survivors compared to a matched cohort without cancer. Methods This retrospective cohort study included 2‐year survivors ( n = 14,917) of 11 common AYA (15–39 years) cancers diagnosed at the integrated health care organizations of Kaiser Permanente (KP) Southern and Northern California during 2006–2020. A comparison cohort ( n = 149,164) without cancer (matched 10:1 by age, sex, calendar year, and KP site) was included. Cumulative incidence (CMI) accounting for death as a competing risk was calculated. Poisson regression estimated the incidence rate ratio (IRR) of each condition in cancer survivors versus the matched cohort, adjusting for age, sex, and race/ethnicity. Results The 5‐year CMI was highest for thyroid (17.4%), respiratory (6.6%), cardiovascular (5.0%), and liver (4.8%) diseases. At 10 years, the CMI of any condition was 39% in survivors versus 26% in the matched cohort. Survivors had a 2‐fold increased risk of being diagnosed with any medical condition (IRR, 2.0; 95% confidence interval [CI], 1.9–2.0) as well as two or more conditions (IRR, 2.3; 95% CI, 2.2–2.5). Risk was highest among survivors of hematologic cancers and those diagnosed with distant stage disease. Elevated risks were observed within all sociodemographic groups of this insured population. Conclusion AYAs with cancer had a higher risk of chronic medical conditions compared to those without cancer. Long‐term surveillance, risk mitigation through lifestyle modifications and effective disease management are crucial to reduce premature mortality.

Abstract Background In the current Canadian treatment landscape for relapsed or refractory diffuse large B-cell lymphoma (R/R DLBCL), eligibility for autologous stem cell transplantation (ASCT) guides the choice of salvage treatment. CD19 chimeric antigen receptor T-cell (CAR-T) therapies have improved outcomes in patients with chemorefractory DLBCL, but access is limited to eligible patients. This subanalysis of the RE-MIND2 observational retrospective cohort study investigated treatment patterns for R/R DLBCL in Canada. Patients and methods Data from patients enrolled in RE-MIND2 treated between 2010 and 2020 at 2 Canadian centers were retrospectively collected from health records. Descriptive statistics were used to analyze baseline characteristics, treatment initiated, and duration of treatment by line of therapy. Results One hundred and nine patients were included; 74.2% of patients were eligible for ASCT as 2L therapy, and 45.4% received transplants. ASCT eligibility for third- (3L) and fourth-line (4L) therapy declined to 17.1% and 5.9%, respectively. Patients received a wide variety of treatments in 3 and 4L. CAR-T therapy became available in 3 and 4L by the end of 2019. Median durations of treatment were <2.6 months in all lines of therapy; median time to next treatment ranged from 3.4 months in 4L to 5.3 months in 2L. Conclusion Results of our study support that ASCT-ineligible patients have a poor prognosis with conventional salvage chemotherapy. Before the availability of novel immunotherapies, no apparent standard of care was observed for Canadian patients with R/R DLBCL who were ineligible for or did not receive ASCT, especially after 2L treatment.

Objectives The ‘tumour, node, metastasis’ (TNM) classification of colorectal cancer (CRC) predicts prognosis and so is vital to consider in analyses of patterns and outcomes of care when using electronic health records. Unfortunately, it is often only available in free-text reports. This study aimed to develop regex-based text-processing algorithms that identify the reports describing CRC and extract the TNM staging at a low computational cost. Methods The CRC and TNM extraction algorithms were iteratively developed using 58 634 imaging and pathology reports of patients with CRC from the Oxford University Hospitals (OUH) and Royal Marsden (RMH) NHS Foundation Trusts (FT), with additional input from Imperial College Healthcare and Christie NHS FTs. The algorithms were evaluated on a stratified random sample of 400 OUH development data reports and 400 newer ‘unseen’ OUH reports. The reports were annotated with the help of two clinicians. Results The CRC algorithm achieved at least 93.0% positive predictive value (PPV), 72.1% sensitivity, 64.0% negative predictive value (NPV) and 90.1% specificity for primary CRC on pathology reports. On imaging reports, it demonstrated at least 78.0% PPV, 91.8% sensitivity, 93.0% NPV and 80.9% specificity. For the main T/N/M categories, the TNM algorithm achieved PPVs of at least 93.9% (T), 97.7% (N) and 97.2% (M), and sensitivities of 63.6% (T), 89.6% (N) and 64.8% (M). NPVs were at least 45.0% (T), 91.1% (N), 88.4% (M), and specificities 95.7% (T), 98.1% (N), 99.3% (M). Reductions in performance were mostly due to implicit staging. For extracting explicit TNM stages, current or historical, the algorithm made no errors on 400 pathology reports and six errors on 400 imaging reports. Conclusion The TNM algorithm accurately extracts explicit TNM staging, but other methods are needed for retrieving implicit stages. The CRC algorithm is accurate on non-supplementary reports, but outputs need additional review if higher precision is required.