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538 Background: In biliary tract cancer (BTC), TP53 is the most commonly altered gene and may co-occur with KRAS alteration. The presence of a co-alterations in of TP53 and KRAS is associated with poor prognosis in many cancers. In patients (pts) with advanced BTC, the prognostic implications of such co-alterations have not been fully investigated. Methods: This is a pooled analysis of SCRUM-Japan GOZILA and MONSTAR-SCREEN-1 and -2 studies. Genomic profiling was conducted with Guardant360 for plasma in GOZILA, FoundationOne CDx for tissue and FoundationOne Liquid CDx for plasma in MONSTAR-SCREEN-1, and CARIS MI Profile for tissue in MONSTAR-SCREEN-2. Pts with advanced BTC receiving systemic therapy were included in this study. Results: Among 636 pts with advanced BTC, 85 had TP53/KRAS co-alteration, 293 had TP53, 44 had KRAS, and 214 had neither KRAS nor TP53 alteration (WT/WT). Tumors with TP53 alteration had significantly higher level of tumor mutation burden (TMB) compared to the other groups (3.8 mut/Mb for TP53/KRAS, 5.0 mut/Mb for TP53, 2.8 mut/Mb for KRAS, and 2.5 mut/Mb for WT/WT, respectively, P<0.001). In addition, the frequency of microsatellite instability-high (MSI-High) in the TP53/KRAS group (11.0%) was significantly higher compared to the TP53 group (3.1%, P<0.05), and the WT/WT group (0.6%, P<0.001), respectively. The objective response rate of first-line therapy in the TP53/KRAS group (8.2%) was significantly lower than in the other groups (20.8% for TP53, 23.3% for KRAS, and 19.7% for WT/WT groups, P=0.035). There was no pts treated with durvalumab plus gemcitabine and cisplatin. Two pts with TP53/KRAS alteration and MSI-High received pembrolizumab monotherapy, and partial response was achieved with a progression-free survival of 9.4 and 22.0 months. The median overall survival (OS) for pts treated with first-line therapy of the TP53/KRAS, KRAS, TP53, and WT/WT groups were 13.6 (95% confidence interval [CI], 11.5-15.5), 14.3 (95%CI, 9.7-25.9), 18.8 (95%CI, 16.9-20.6), and 22.7 months (95%CI, 20.4-25.9), respectively. Multivariate analysis identified TP53/KRAS alteration (hazard ratio [HR] 2.14, 95%CI 1.43-3.22, P<0.001), number of detected variants (≥2) (HR 1.50, 95%CI 1.04-2.16, P=0.029), locally advanced (HR 1.72, 95%CI 1.05-2.83, P=0.033), and metastatic status (HR 1.78, 95%CI 1.39-2.28, P<0.001) as independent prognostic factors for shorter OS. Conclusions: Patients with advanced BTC with co-occurring TP53/KRAS alterations have worse prognosis. Interestingly, the presence of these co-alterations was associated with a higher likelihood of MSI-High phenotype.

544 Background: Biliary tract cancer (BTC) is an aggressive malignancy with poor prognosis and limited treatment options. The prevalence of HER2 amplification in BTC has been reported to be 5-20%, and clinical trials suggested the clinical benefit of HER2-targeted treatment in this disease subpopulation. In a global collaboration, we investigated the comprehensive clinico-molecular characterization as well as the efficacy of anti-HER2 therapy in HER2-amplified BTC. Methods: Patients with advanced BTC who received systemic therapy were included from the GOZILA and MONSTAR studies in Japan and from the COLOMATE trial in the US. Genomic alterations were detected by tissue next-generation sequencing (NGS), including FoundationOne CDx and TempuslxT, and plasma circulating tumor DNA NGS including Guardant360 and FoundationOne Liquid CDx. The clinico-molecular characteristics were evaluated in an exploratory cohort comprised of patients from Japan, whereas the efficacy of anti-HER2 therapy was assessed in a biomarker selected cohort with patients from both Japan and the US. Results: Of 439 patients included in the exploratory cohort, 43 (10%) had HER2 amplification. BTC with primary tumor location in the gallbladder accounted for 58% of primary sites of patients with HER2 amplification. TP53 mutation (84% vs 61%, p=0.003) and BRAF amplification (9% vs 2%, p=0.030) were significantly more frequent in patients with HER2 amplification compared to those without, and no KRAS mutation co-occurred with HER2 amplification. There was no significant difference in overall survival (OS) between patients with and without HER2 amplification (17.7 months [M] vs 16.9 M, hazard ratio [HR] 0.95, 95% confidence interval [CI] 0.65-1.40, p=0.799). Of 58 patients with HER2-amplified BTC included in the biomarker selected cohort (43 Japan, 15 US), 27 (47%) received anti-HER2 therapy. The median OS of patients treated with anti-HER2 therapy was significantly longer than that of patients who did not receive anti-HER2 therapy (24.3 M vs. 12.1 M, HR 0.43, 95% CI 0.23-0.82, p=0.011). Multivariate analysis also identified anti-HER2 therapy as an independent prognostic factor for OS (HR 0.42, 95% CI 0.20-0.85, p=0.015). Conclusions: HER2 amplifications were found in 10% of advanced BTC and did not represent an independent predictive factor for OS. Of clinical significance, patients with HER2-amplified BTC derive a significant benefit from anti-HER2 therapy.

Abstract Background Since November 2019, the SARS-CoV-2 pandemic has created challenges for preventing and managing COVID-19 in children and adolescents. Most research to develop new therapeutic interventions or to repurpose existing ones has been undertaken in adults, and although most cases of infection in pediatric populations are mild, there have been many cases of critical and fatal infection. Understanding the risk factors for severe illness and the evidence for safety, efficacy, and effectiveness of therapies for COVID-19 in children is necessary to optimize therapy. Methods A panel of experts in pediatric infectious diseases, pediatric infectious diseases pharmacology, and pediatric intensive care medicine from 21 geographically diverse North American institutions was re-convened. Through a series of teleconferences and web-based surveys and a systematic review with meta-analysis of data for risk factors, a guidance statement comprising a series of recommendations for risk stratification, treatment, and prevention of COVID-19 was developed and refined based on expert consensus. Results There are identifiable clinical characteristics that enable risk stratification for patients at risk for severe COVID-19. These risk factors can be used to guide the treatment of hospitalized and non-hospitalized children and adolescents with COVID-19 and to guide preventative therapy where options remain available.

Introduction: Risk stratification approaches using clinical criteria or biomarkers in acute graft-versus-host disease (GVHD) have traditionally been implemented at diagnosis or initiation systemic treatment with corticosteroids. For patients who require second-line treatment, the significance of biomarkers at salvage therapy and the relationship between biomarker risk and choice of therapy are unknown. Methods: We studied adult patients who received second-line treatment for acute GVHD between January 2016 and December 2021 in the Mount Sinai Acute GVHD Consortium (MAGIC) database, which collects clinical data and longitudinal serum samples from allogeneic HCT recipients using a rigorous PRoBE study design. Exclusion criteria included relapse of underlying malignant disease prior to second-line therapy, missing response data, or missing serum sample. Serum samples collected from 7 days prior to 3 days after initiation of second-line therapy met criteria for biomarker analysis. The MAGIC algorithm probability (MAP) was calculated as a single value based on concentrations of ST2 and REG3α and was stratified at a threshold of 0.290 to define high MAP and low MAP groups. The primary objective evaluated the association between MAP and survival for patients receiving second-line therapy for acute GVHD. The key secondary objective was to investigate the MAP and choice of second-line systemic agent on Day 28 overall response rate (ORR) and survival. Results: In total, 316 adult patients received second-line treatment for acute GVHD; 149 patients (47%) were excluded for disease relapse (n=27), missing response data (n=48), or missing sample (n=74).Of the 167 evaluable patients, most had steroid-refractory acute GVHD (n=146, 87%), rather than steroid-dependent (n=8, 5%) or steroid-sensitive (n=14, 8%) disease. 62 patients received ruxolitinib while 102 received other systemic agents (best available therapy: BAT). Baseline clinical characteristics of the study population according to treatment choice were similar, except for donor type (Rux: MRD 15%, MUD 74%, haplo 11%; BAT: MRD 30%, MUD 67%, haplo 3%; P=0.014) and median days from corticosteroids to second-line treatment (Rux: 18, BAT: 12; P=0.02).In total, 81 patients had high MAPs and 86 patients had low MAPs, with similar distribution in each treatment cohort (P=0.53). For the entire cohort, the median follow-up for survivors was 22 months (range, 1.5-27).The MAP separated patients into 2 groups (high vs low) with significantly different mortality (NRM at 2 years, 76% vs 29%, P&lt;.0001) and survival (OS at 2 years, 12% vs 63%, P&lt;.0001). Patients who received ruxolitinib as second-line therapy had lower mortality (NRM at 2 years, 35% vs 60%, P&lt;.002) and improved survival (OS at 2 years, 51% vs 32%, P&lt;.008), compared to those who received other systemic agents. However, the outcomes of patients with high MAP were poor, regardless of second-line treatment choice ( Figure 1A). The MAP (low vs high), time from corticosteroids to second-line treatment (≥14 days vs &lt; 14 days), GVHD grade at second-line (0-2 vs 3-4), and choice of second-line therapy (Rux vs BAT) were all significant (P&lt;0.05) predictors of lower NRM and higher OS in multivariate analysis. The MAP also separated patients into 2 groups with significantly different D28 ORR (low: 49%, high: 30%, P&lt;.0001). In agreement with prospective trials, ruxolitinib resulted in higher D28 response rates compared to other systemic therapies (ORR 54.9% vs 30.5%, P=0.005), which was observed in both low MAP (ORR, 64.5% vs 38.5%, P=0.017) and high MAP cohorts (ORR, 42.9% vs 22.6%, P=0.06) ( Figure 1B). The MAP (low vs high), GVHD grade at second line (0-2 vs 3-4), and choice of second-line therapy (Rux vs BAT) were significant predictors (P&lt;0.05) of higher D28 ORR in multivariate analysis. Conclusion: The MAP measured at the initiation of second-line systemic treatment for acute GVHD predicts NRM and OS, as well as treatment response. The outcomes of patients with high MAP are poor, regardless of second-line treatment choice, and the higher CR rate in low MAP patients may drive higher survival rates. Incorporation of MAP into clinical trials in this setting warrants investigation. The results also support the current use of ruxolitinib as second-line treatment for acute GVHD, particularly in patients with low MAP.

[Background] The current standard first-line treatment for acute graft-versus-host disease (GVHD), systemic high-dose steroids, induces clinical responses in a majority of patients. Flares of GVHD after initial improvement often occur during tapering or discontinuation of immunosuppression. There is no consensus regarding the definition of GVHD flare and little has been published regarding its natural history. [Methods] We retrospectively evaluated clinical data and blood samples from 968 allogeneic hematopoietic cell transplantation (HCT) recipients from 23 Mount Sinai Acute GVHD International Consortium (MAGIC) transplant centers who achieved complete response (CR) or very good partial response (VGPR) within 4 weeks of acute GVHD treatment between 2014 and 2021. VGPR was defined as the complete resolution of acute GVHD manifestations except residual stage 1 skin disease. Flares were defined as a recurrence of acute GVHD after achievement of CR/VGPR if (1) patients had an increased symptom severity of at least 1 organ stage; (2) received intensified treatment (increase in steroid dose ≥ 0.25 mg/kg or initiation of additional systemic immunosuppression); and (3) had no prior history of primary disease relapse or donor lymphocyte infusion preceding the flare. Serum samples obtained at the time of CR/VGPR and at the time of flares were analyzed for ST2 and REG3α concentrations that generated MAGIC algorithm probabilities (MAPs) resulting in previously validated Ann Arbor (AA) scores (1, 2, and 3). [Results] The median recipient age at HCT was 55 years (range: 0 to 79); 18.6% of patients had grades III-IV acute GVHD before CR/VGPR. The median maximum daily dose of corticosteroids before CR/VGPR was 1 mg/kg methylprednisolone equivalent (range, 0.1 to 3.2 mg/kg). Flares developed within 6 months following CR/VGPR in 210/968 (21.7%) patients with a median onset of 28 days (range: 2 to 448). Symptom severity at the onset of flare symptoms varied widely (grade I: 22%; grade II: 38%; grade III-IV: 41%) and the development of a flare was associated with a five-fold increase in NRM (hazard ratio [HR], 4.84 [95% CI, 3.19-7.36], P &lt; 0.001) when considered as a time-dependent covariate in a multivariate regression model. The large majority of non-relapse deaths after flares (54/71, 76%) were due to acute GVHD or complications from its treatment. The AA scores at the time of first CR/VGPR successfully stratified patients for risk of six-month NRM (AA1: 5%, AA2: 11%, AA3: 34%, P &lt; 0.001) (Figure A). Increasing AA score at CR/VGPR was also associated with significantly increased risk of GVHD flares (Figure B). Not only did the risk of flare increase with each rising AA score, but the number of patients with severe (grade III/IV) symptoms at flare onset also increased (AA1: 34%, AA2: 43%, AA3: 54%). We next generated a multivariate regression model of risk factors for the development of flares. High AA scores at the time of CR/VGPR (AA2: HR, 1.81 [95% CI, 1.32-2.48], P = 0.001; AA3: HR, 3.14 [95% CI, 1.98-4.98], P &lt; 0.001), HCT from HLA mismatched unrelated donor (HR, 1.74 [95% CI, 1.00-3.02], P = 0.049), and interestingly, rapid achievement of CR/VGPR from the time of initial treatment (≤14 days) (HR, 1.84 [95% CI, 1.21-2.80], P = 0.004) were all identified as significant risk factors. Meanwhile, no other transplant, GVHD, or treatment characteristics associated with the development of flares including maximum GVHD severity, maximum steroid dose, and use of additional immunosuppressive agents other than steroids before CR/VGPR. AA scores measured at the onset of flare symptoms in 98 patients also predicted six-month NRM (AA1, 6%; AA2, 19%; AA3 42%, P = 0.01). [Conclusion] Despite advances in treatment, flares of GVHD symptoms following excellent (CR/VGPR) responses still occur in over one fifth of patients in current practice and are associated with a five-fold increase in six-month NRM. AA scores from serum biomarkers predict outcomes despite the absence of symptoms, suggesting that MAGIC biomarkers detect subclinical damage to GI crypts that can drive later recrudescence of clinical GVHD. Measurement of the MAP at the time of response to GVHD treatment may thus help to risk-stratify tapering strategies of immunosuppressive therapy.

The overall response rate (ORR) 28 days (D28) after treatment has been adopted as the primary endpoint for clinical trials of acute graft versus host disease (GVHD). ORR combines complete response (CR) and partial response (PR) because CR and PR have very similar non relapse mortality (NRM). D28 ORR has some disadvantages: first, physicians usually decide to modify immunosuppression much earlier than D28, and second, NRM does not always correlate well with ORR at D28, particularly for patients who present with intermediate risk or low risk disease. MAGIC serum biomarkers at day 14 (D14) of GVHD treatment have been shown to correlate better with NRM than clinical symptom response (Srinagesh et al, Blood Advances, 2019). We therefore hypothesized that a combination of clinical symptom severity and biomarkers at D14 of treatment would predict NRM at least as well and possibly better than clinical response at D28. We studied 1144 patients from 23 MAGIC sites who were systemically treated with at least 0.25 mg/kg/day of systemic steroids (prednisone equivalents) and had clinical data and serum samples available in the MAGIC database and biorepository. We divided the patients into a training set (n=764) and a validation set (n=380). We used 12-month NRM from the time of acute GVHD onset as the primary outcome of interest. We first trained a recursive partitioning algorithm in the training set to create a response model (MAGIC D14 clinical response) according to overall GVHD grade at both onset and D14 that predicted 12-month NRM and then applied it to the validation set. Patients that either progressed to grade III/IV GVHD, continued having grade III/IV GVHD, or only improved to grade II at D14 from grade III/IV at D0 had high NRM and were classified as non-responders. Patients with grade I/II GVHD at day 0 who had grade 0-II GVHD at day 14 and patients who improved to grade 0/I at day 14 from grade III/IV at day 0 had low NRM and were classified as responders. Although counterintuitive, responders included patients whose GVHD remained at grade II because the 12 month NRM of this group was only 20%. The new clinical model predicted NRM as well as the D28 standard response model in the validation set. When we integrated the D14 MAP biomarker score (low: ≤ 0.290 vs high: &gt;0.290) with the new D14 clinical response (D14 MAGIC integrated response), we observed three response groups of integrated response with strikingly different 12 month NRM (8%, 35%, 76%, p&lt;0.001), in contrast to the D28 standard response (Figure 1A, 1B). D14 complete response required MAGIC clinical response with low MAP; D14 partial response required either MAGIC clinical response with high MAP or MAGIC clinical non-response with low MAP; and D14 non-response required MAGIC clinical non-response with high MAP. The D14 response groups also displayed significant differences in 12 month OS (82%, 58%, 14% respectively, p&lt;0.001) We then compared the D14 integrated response with the D28 standard response for 12 month NRM prediction. This D14 integrated response model was superior for time-dependent AUC (0.78 vs 0.71, P=0.03), sensitivity (0.71 vs 0.54), positive predictive value (0.52 vs 0.48) and negative predictive value (0.92 vs 0.89), with minimal loss in specificity (0.85 vs 0.87) in the prediction of 12-month NRM compared to the D28 standard response model. Using decision curve analysis, the D14 integrated response displayed higher net benefit (correct identification of patients that will experience NRM by 12 months) over the whole range of threshold probabilities/preferences for changing immunosuppression when 12-month NRM was used as the outcome. We conclude first, that the definition of response that uses onset and D14 grades is as accurate as D28 ORR model; and second, that a model using clinical grades and biomarkers on D14 more accurately predicts long term NRM than the standard D28 definition and may be useful as a clinical trial endpoint.

Background: Ph-like ALL is a high-risk subset of B-lineage ALL that responds poorly to standard chemotherapy regimens. While allogeneic hematopoietic cell transplantation (HCT) is routinely recommended for patients with Ph-like ALL, large multicenter data addressing its role is limited. Here, we conducted a multicenter study to evaluate the role of HCT in adolescent and young adult (AYA) and adult patients (pts) with Ph-like ALL and compare their outcomes to pts with Ph-pos and Ph-neg (non-Ph-like) ALL. Methods: The study included pts (age ≥18) with B-lineage ALL who received HCT in first complete remission (CR1) at 3 academic centers (MD Anderson Cancer Center, City of Hope and Mayo Clinic) between 2006 and 2021. Pts were divided into 3 main subgroups: Ph-like, Ph-pos and Ph-neg ALL. Ph-like ALL cases were identified using cumulative data obtained by targeted RNA sequencing, conventional cytogenetics, FISH studies, whole genome chromosomal microarray and flow cytometry. Measurable residual disease (MRD) prior to HCT was measured using flow cytometry with a sensitivity of 0.01% for Ph-neg and Ph-like ALL, and with a PCR assay for BCR::ABL1 for Ph-pos ALL. MRD-negativity was defined as &lt;0.01%. Predictors of relapse were evaluated in univariate and multivariate analysis using Fine-Gray sub-distribution hazard models considering non-relapse mortality (NRM) as a competing risk. Results: 673 patients were identified, 83 (12.3%) had Ph-like ALL, of which 73% had CRLF2-alterations. The remaining patients were classified either as Ph-pos (N=271, 40.3%) or Ph-neg ALL (N=319, 47.4%). Patients with Ph-like ALL were younger (median age 40 years vs 48 and 46 years for Ph-pos and Ph-neg ALL, respectively, p=0.01), more likely to be of Hispanic ethnicity (69% vs 32% and 48% for Ph-pos and Ph-neg ALL respectively, p&lt;0.001). Patients with Ph-like ALL were also more likely to have induction failure (24% vs 2% and 11% for Ph-pos and Ph-neg ALL, respectively, p=0.001). A summary of pts characteristics for each subgroup can be found in Table 1. The median follow-up was 30, 52 and 48 months for patients with Ph-like, Ph-pos and Ph-neg ALL, respectively. In univariate analysis, 3-yr OS and PFS did not differ significantly (66% and 59% vs 59% and 54%, p=0.1) between patients with Ph-like and Ph-neg ALL, respectively. Similarly, the cumulative incidence of relapse was comparable between patients with Ph-like and Ph-neg ALL (22% vs 20%, respectively, p=0.7). In contrast, the 3-yr OS (75%, p&lt;0.001) and PFS (70%, p=0.001) were significantly higher and relapse rate significantly lower (12%, p=0.003) in pts with Ph-pos ALL compared with Ph-like or Ph-neg ALL (Figure 1). The inferior survival in patients with Ph-like and Ph-neg ALL was likely attributable to higher relapse rates (22% and 20% vs 12%, respectively, p=0.003) compared to Ph-pos ALL. Finally, the 3-yr NRM rate in patients with Ph-like ALL was comparable (20% vs 18% and 23%, respectively, p&gt;0.1) to Ph-pos and Ph-neg ALL. We confirmed that the relapse rate in patients with Ph-like ALL was comparable to the rate in pts with Ph-neg ALL (HR=1.02, 95% CI 0.6-1.8, p=0.9) on multivariate analysis (MVA). Ph-pos ALL was associated with a significantly lower relapse rate compared with Ph-neg ALL (HR=0.4, 95% CI 0.3-0.7, p&lt;0.001). MRD positivity prior to allo-HCT was the only additional significant predictor for relapse on MVA (HR=2.9, 95% CI 1.8-4.7, p&lt;0.001). Conclusions: HCT appears to overcome the poor prognosis of patients with Ph-like ALL. Despite higher induction failure rates, patients with Ph-like ALL undergoing HCT in CR1 had similar outcomes to other Ph-neg ALL subsets. The impact of effective salvage therapy leading to MRD-negativity in CR1 in this group is under investigation and will be reported. Further studies are needed to assess the impact of different Ph-like alterations on HCT outcomes. Outcomes for patients with Ph-pos ALL are significantly better than other groups, likely due to the use of TKIs pre- and post-HCT.