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Significance Statement Why are there so few biomarkers accepted by health authorities and implemented in clinical practice, despite the high and growing number of biomaker studies in medical research ? In this meta-epidemiological study, including 804 studies that were critically appraised by expert reviewers, the authors have identified all prognostic kidney transplant biomarkers and showed overall suboptimal study designs, methods, results, interpretation, reproducible research standards, and transparency. The authors also demonstrated for the first time that the limited number of studies challenged the added value of their candidate biomarkers against standard-of-care routine patient monitoring parameters. Most biomarker studies tended to be single-center, retrospective studies with a small number of patients and clinical events. Less than 5% of the studies performed an external validation. The authors also showed the poor transparency reporting and identified a data beautification phenomenon. These findings suggest that there is much wasted research effort in transplant biomarker medical research and highlight the need to produce more rigorous studies so that more biomarkers may be validated and successfully implemented in clinical practice. Background Despite the increasing number of biomarker studies published in the transplant literature over the past 20 years, demonstrations of their clinical benefit and their implementation in routine clinical practice are lacking. We hypothesized that suboptimal design, data, methodology, and reporting might contribute to this phenomenon. Methods We formed a consortium of experts in systematic reviews, nephrologists, methodologists, and epidemiologists. A systematic literature search was performed in PubMed, Embase, Scopus, Web of Science, and Cochrane Library between January 1, 2005, and November 12, 2022 (PROSPERO ID: CRD42020154747). All English language, original studies investigating the association between a biomarker and kidney allograft outcome were included. The final set of publications was assessed by expert reviewers. After data collection, two independent reviewers randomly evaluated the inconsistencies for 30% of the references for each reviewer. If more than 5% of inconsistencies were observed for one given reviewer, a re-evaluation was conducted for all the references of the reviewer. The biomarkers were categorized according to their type and the biological milieu from which they were measured. The study characteristics related to the design, methods, results, and their interpretation were assessed, as well as reproducible research practices and transparency indicators. Results A total of 7372 publications were screened and 804 studies met the inclusion criteria. A total of 1143 biomarkers were assessed among the included studies from blood ( n =821, 71.8%), intragraft ( n =169, 14.8%), or urine ( n =81, 7.1%) compartments. The number of studies significantly increased, with a median, yearly number of 31.5 studies (interquartile range [IQR], 23.8–35.5) between 2005 and 2012 and 57.5 (IQR, 53.3–59.8) between 2013 and 2022 ( P < 0.001). A total of 655 studies (81.5%) were retrospective, while 595 (74.0%) used data from a single center. The median number of patients included was 232 (IQR, 96–629) with a median follow-up post-transplant of 4.8 years (IQR, 3.0–6.2). Only 4.7% of studies were externally validated. A total of 346 studies (43.0%) did not adjust their biomarker for key prognostic factors, while only 3.1% of studies adjusted the biomarker for standard-of-care patient monitoring factors. Data sharing, code sharing, and registration occurred in 8.8%, 1.1%, and 4.6% of studies, respectively. A total of 158 studies (20.0%) emphasized the clinical relevance of the biomarker, despite the reported nonsignificant association of the biomarker with the outcome measure. A total of 288 studies assessed rejection as an outcome. We showed that these rejection studies shared the same characteristics as other studies. Conclusions Biomarker studies in kidney transplantation lack validation, rigorous design and methodology, accurate interpretation, and transparency. Higher standards are needed in biomarker research to prove the clinical utility and support clinical use.

OBJECTIVE Diabetes mellitus (DM) is a known risk factor for postsurgical and systemic complications after lumbar spinal surgery. Smaller studies have also demonstrated diminished improvements in patient-reported outcomes (PROs), with increased reoperation and readmission rates after lumbar surgery in patients with DM. The authors aimed to examine longer-term PROs in patients with DM undergoing lumbar decompression and/or arthrodesis for degenerative pathology. METHODS The Quality Outcomes Database was queried for patients undergoing elective lumbar decompression and/or arthrodesis for degenerative pathology. Patients were grouped into DM and non-DM groups and optimally matched in a 1:1 ratio on 31 baseline variables, including the number of operated levels. Outcomes of interest were readmissions and reoperations at 30 and 90 days after surgery in addition to improvements in Oswestry Disability Index, back pain, and leg pain scores and quality-adjusted life-years at 90 days after surgery. RESULTS The matched decompression cohort comprised 7836 patients (3236 [41.3] females) with a mean age of 63.5 ± 12.6 years, and the matched arthrodesis cohort comprised 7336 patients (3907 [53.3%] females) with a mean age of 64.8 ± 10.3 years. In patients undergoing lumbar decompression, no significant differences in nonroutine discharge, length of stay (LOS), readmissions, reoperations, and PROs were observed. In patients undergoing lumbar arthrodesis, nonroutine discharge (15.7% vs 13.4%, p < 0.01), LOS (3.2 ± 2.0 vs 3.0 ± 3.5 days, p < 0.01), 30-day (6.5% vs 4.4%, p < 0.01) and 90-day (9.1% vs 7.0%, p < 0.01) readmission rates, and the 90-day reoperation rate (4.3% vs 3.2%, p = 0.01) were all significantly higher in the DM group. For DM patients undergoing lumbar arthrodesis, subgroup analyses demonstrated a significantly higher risk of poor surgical outcomes with the open approach. CONCLUSIONS Patients with and without DM undergoing lumbar spinal decompression alone have comparable readmission and reoperation rates, while those undergoing arthrodesis procedures have a higher risk of poor surgical outcomes up to 90 days after surgery. Surgeons should target optimal DM control preoperatively, particularly for patients undergoing elective lumbar arthrodesis.

Background: The use of CAR-T cell therapy has transformed treatment paradigms in B-cell malignancies. Ciltacabtagene autoleucel (cilta-cel) was approved for use in RRMM after four or more prior lines of therapy in 2022. While the pivotal studies exclusively treated patients in an inpatient setting, robust infrastructure planning at some centers across US has fostered outpatient administration of the commercially available product. Outpatient administration of CAR-T is more desirable due to superior financial sustainability, lower healthcare resource utilization, and greater patient autonomy during the treatment. Hence, we conducted a qualitative study to evaluate clinical and administrative perspectives and trends in outpatient administration of commercialized cilta-cel with an aim to understand best practices from certified CAR-T centers in the USA. Methods: A targeted literature review was conducted to better understand current practices around outpatient administration of CAR-T, and inform the development of primary research materials for designing subsequent interviews. Next, two 60-minute exploratory interviews were conducted with multi-stakeholder participants (n=5) from two certified cilta-cel centers, each with significant volume of outpatient administration of cilta-cel. Following the qualitative analysis of interviews, two 90-minute panels were conducted with multi-stakeholder participants (n=14) from six certified cilta-cel centers, including centers from exploratory interviews, focusing on clinical and administrative topics across the patient journey. Results: Each center in the study treated approximately 15-30 patients with cilta-cel in the outpatient setting. Using Likert scales, participants from all centers ranked space/capacity as the most important factor in decision-making process for outpatient cilta-cel administration, and ranked reimbursement incentives as a highly (67% of participants) or a moderately (33%) important factor. All participants agreed that having a dedicated outpatient infrastructure (dedicated space such as bed availability and internal processes including standard operating procedures (SOPs)), 24/7 support, outpatient bone marrow transplant (BMT) or cell therapy experience, and robust multidisciplinary teams were key to setting-up successful outpatient centers for cilta-cel therapy. The participants agreed that cilta-cel can be administered safely in an outpatient setting due to generally predictable, delayed onset of potential AEs, except in patients with significant comorbidities or organ dysfunction. Participants also considered caregiver support and lodging availability as factors of importance for outpatient administration. Institutionally established AE monitoring protocols are critical for safe use of cilta-cel in an outpatient setting. Over 50% of the centers interviewed have recently started to administer tocilizumab to treat mild grade 1 cytokine release syndrome (CRS) in an outpatient setting. Based on the findings across the phases of research, the patient journey for outpatient administration of cilta-cel was updated (Figure 1). While patients may be admitted for toxicity events, 100% of centers interviewed had 24-hour coverage and bed availability for these patients if needed. Conclusions: Overall, this study further supports the notion that centers can safely administer cilta-cel in an outpatient setting, if appropriate infrastructure is in place. Additional best practices for new outpatient sites include adequate infrastructure, SOPs, a well-trained and multidisciplinary team, and education of patients and caregivers (Table 1). Outpatient management and earlier intervention for low-grade AEs is currently evolving, with more real-world research required. Continued expert sharing of best practices can aid centers in implementing outpatient administration of CAR-T therapies. Funding: This analysis was supported by Janssen Research & Development, LLC and Legend Biotech USA, Inc

Introduction The advent of venetoclax (VEN) based chemotherapy has revolutionized the treatment of elderly acute myeloid leukemia (AML), with improvement in remission rates from historical 10%-20% to 60%-70%. However, remission duration is short-lived in patients (pts) with high-risk AML with consequent dismal outcome. As our knowledge of genomic landscape of AML expands and more immunotherapies become available, exploration of the immune tumor microenvironment (TME) of AML may allow identification of subsets of pts that may benefit from immune based therapy. We conducted an investigator initiated prospective study to evaluate TME of pts receiving VEN plus hypomethylating agent (HMA; azacitidine or decitabine) combination. We hypothesize that these pts will cluster into immune-infiltrated vs. immune-depleted sub-types by high-definition immune cell profiling. Methods In 26 newly diagnosed AML pts, who were planned to receive VEN plus HMA therapy, we isolated bone marrow (BM) and peripheral blood (PB) derived mononuclear cells (MC) by density gradient centrifugation and cryopreserved. We performed CyTOF (cytometry time-of-flight) analysis to study their immune signatures. Thawed cells were labeled with metal-conjugated antibodies that bind CD33, CD196, CD19, CD127, CD11b, CD4, IgD, CD11c, CD14, CD56, CD123, TCRgd, CD185/CXCR5, CD45RA, CD27, CD28, CD66b, CD183 (CXCR3), CD161, CD45RO, CD197 (CCR7), CD8a, CD25, CD3, CD20, CD38, HLA-DR, CD194 (CCR4), CD57, CD16 and CD45. We performed a Rphenograph clustering on 25 paired BMMC and PBMC samples (one patient only had PBMC) to create 35 unique clusters for each ( Figure 1). Then we broke down the distribution of cluster by two different groupings: pts with TP53 mutation (m) and those who achieve complete remission. Statistical significance of clusters calculated using t-test. We performed Pearson correlation test on the paired BMMC and PBMC samples to assess correlation between BMMC and PBMC samples. Results Baseline characteristics The median age of the pts was 74 years (range, 53-88), and 17 (65%) pts were male. Ten (37%) pts had secondary AML, and 12 (46%) pts had ELN adverse risk disease (n=6; TP53m). There was no significant difference in median age (p= &gt;0.99), proportion of pts with secondary AML (p= 0.64), acute myelomonocytic leukemia (p= 0.14) white blood cell count (WBC) ≥ 100 (10 9/L) (p= &gt;0.99), and frequency of commonly occurring co-mutations ( ASXL1 [p=0.35]), FLT3 ITD [p=0.54], splicing [p=0.29], IDH1/2 [p=0.28], DNMT3A [p=0.29], NPM1 [p=0.29], TET2 [p=0.35]) in TP53m and TP53 wild-type group. Response 12/20 (60%) evaluable pts achieved complete remission with or without count recovery (CR/CRi). There was no significant difference in median age (p= 0.06), proportion of pts with secondary AML (p= 0.16), therapy related AML (p= 0.60) WBC ≥ 100 (10 9/L) (p= 0.40), and frequency of commonly occurring mutations ( TP53 [p=0.60], ASXL1 [p &gt; 0.99]), FLT3 ITD [p=0.54], splicing [p &gt; 0.99], IDH1/2 [p=0.60], DNMT3A [p=&gt;0.99], NPM1 [p=0.61], TET2 [p &gt;0.99]) in CR/CRi and no-CR/CRi group. CyTOF analysis and Rphenograph clustering on 25 paired BMMC and PBMC samples We found significant clustering with high expression of B-cell activated (cluster 2; p= 0.005), NK cell rich (cluster 1; p= 0.005, cluster 35; p= 0.0009), CD8 T-cells (cluster 31; p= 0.01) and CD4 effector cells (cluster 17; p= 0.005) phenotype among TP53m AML ( Table 1). Among pts who achieved CR/CRi, significant clustering with low expression of B-cell activated (cluster 29; p= 0.01), CD8 cytotoxic (cluster 14; p= 0.01) CD4 activated (cluster 21; p= 0.03) phenotypes observed. Correlation between BMMC and PBMC clustering Among clusters which showed significance for a particular phenotype, we performed Pearson correlation (R 2) and observed strong correlation between BMMC and PBMC samples clustering in cluster 1 (R 2 = 0.99), cluster 2 (R 2 = 0.95), cluster 17 (R 2 = 0.96), cluster 21 (R 2 = 0.99) and cluster 29 (R 2 = 0.93). Conclusion In this single institutional study using CyTOF analysis we have identified novel clustering with immune- infiltrated phenotype among pts with TP53m AML and conversely immune-depleted phenotype among AML pts who responded to VEN plus HMA. Moreover, we found strong correlation in CyTOF analysis conducted from BMMC and PBMC samples. Future studies with larger sample size needed to validate our findings.

Introduction Indolent systemic mastocytosis (ISM) is a rare clonal mast cell disease driven by the KIT D816V mutation in nearly all patients. Patients with ISM can present with debilitating acute and chronic cutaneous, gastrointestinal, neurocognitive, and systemic symptoms caused by the release of inflammatory mediators from abnormal mast cells. In some patients, symptoms are not adequately controlled with best supportive care (BSC) medications. Elenestinib (BLU-263) is a novel, investigational, oral, next-generation tyrosine kinase inhibitor that potently and selectively inhibits KIT D816V with limited central nervous system penetration and pharmacokinetics (PK) that support once daily dosing. HARBOR (NCT04910685) is a randomized, double-blind, placebo-controlled, phase 2/3 study assessing efficacy and safety of elenestinib in patients with ISM. Methods Eligible adult patients with ISM, confirmed following central review of bone marrow (BM) pathology, clinical, and laboratory findings per World Health Organization criteria and a moderate-to-severe symptom score based on minimum mean total symptom score (TSS) of the ISM-Symptom Assessment Form (ISM-SAF©2018), were stratified by baseline serum tryptase (&lt;20 ng/mL vs ≥20 ng/mL) and randomly assigned 3:1 to elenestinib 25 mg, 50 mg, or 100 mg once daily + BSC (“elenestinib”) or placebo + BSC (“placebo”). The primary objective of Part 1 was to determine the recommended dose based on safety, PK, and pharmacodynamics. Secondary endpoints included changes in biomarkers of disease burden (serum tryptase, KIT D816V variant allele fraction [VAF], and BM mast cells) and ISM-SAF TSS. Three additional open-label PK groups enrolled patients at 50 mg, 75 mg, and 100 mg to further characterize PK and safety. Results As of data cutoff on July 3, 2023, a total of 122 patients with ISM have received their assigned treatment in Part 1 of the study; 39 were blinded and randomized to elenestinib or placebo, and 83 were treated with open-label elenestinib in the PK groups (21 patients at 50 mg, 34 patients at 75 mg, and 28 patients at 100 mg). Baseline demographics were similar to those reported for the general ISM population. After 12 weeks of therapy, symptom improvement was observed for all dose cohorts, and symptom reduction by TSS was greater for patients on elenestinib versus placebo in the blinded portion of Part 1. Patients receiving elenestinib at 25 mg, 50 mg, and 100 mg doses showed reduction (mean percent) from baseline for tryptase (-15.4%, -50.9%, and -68.4% vs 3.3%, respectively) and KIT D816VVAF (-37.5%, -70.3%, and -77.0% vs -2.5%, respectively) as compared to placebo. Similar reductions in TSS and disease-related biomarkers were observed in the open-label PK cohorts. After a median treatment duration of 35.3 weeks, elenestinib was well-tolerated at all dose levels. There were no treatment-related serious adverse events and no treatment-related adverse events that led to drug discontinuation. Conclusion Elenestinib at all tested doses demonstrated beneficial effects on disease-related symptoms and biomarkers of mast cell burden in this large and maturing cohort of patients with ISM with a moderate-to-severe symptom burden. Elenestinib was well tolerated across all dose levels with a promising early benefit-risk profile in ISM. These preliminary findings will inform dosing for the planned Part 2 of HARBOR, which will examine elenestinib versus placebo in a randomized, blinded, placebo-controlled setting.

Background: We previously reported that treatment with the anti-CD30 antibody-drug conjugate brentuximab vedotin (BV) in combination with the checkpoint inhibitors targeting CTLA-4 and/or PD-1 (ipilimumab (I) and nivolumab (N)) led to high overall response rates (ORR) and complete response (CR) rates in relapsed/refractory (R/R) Hodgkin's lymphoma patients in a Phase 1 ECOG-ACRIN sponsored clinical trial. As previously presented in the Phase 1 component of NCT01896999 (E4412), the ORR for the treatment arms were: BV+I 76%, BV+N 89%, and BV+I+N 82%, with CR rates of 57%, 61%, and 73% across the groups, respectively. This suggested that not all patients who responded derived equal benefit. Moreover, with a median follow-up of 2.24 years, the PFS of 1.1 year, NR, and 2.49 years across the groups suggest that even some patients who achieved CR progressed on or subsequent to treatment. Currently biomarkers have no ability to predict which patients will maximally benefit from these therapies. We investigated blood-based immune biomarkers mechanistically across all cohorts which may explain differential responses and guide future treatment decisions for R/R HL patients. Methods: Peripheral blood plasma for 54 of 61 (89%) patients evaluable for response was collected at up to 4 time points and tested for 92 immuno-oncology soluble analytes with Olink proximity extension assay and for antibody titers to 20 known tumor antigens by ELISA. Matching peripheral blood mononuclear cells (PBMC) were analyzed by CyTOF mass cytometry for major immune cell subsets and marker surface expression, and for T cell receptor diversity by Immunoseq®. Mixed effect linear models were used to identify significantly associated changes (P&lt;0.05) related to treatment longitudinally within groups and to ORR between groups. Results: Analysis of plasma demonstrated durable increase in soluble plasma PD-1 and decreases in CCL17, ANGPT2, MMP12, IL13, and CXCL13 in N-containing regimens, and higher GZMA and CAIX in BV+I (P&lt;0.05). Despite baseline heterogeneity in PBMC composition, we found durable increases in plasmacytoid dendritic cells (pDC) after N-containing treatments, and transient increases in plasmablasts and memory B cells, as well as early decreases in naïve CD4+ T cells and neutrophils across treatments. Treatment with BV+I+N demonstrated late increases in neutrophils, and changes in memory B cell markers. Clinical benefit analyses revealed that elevated soluble CD5, ADA, CXCL13, and CCL17 at baseline or after two treatment cycles were associated with worse ORR (P&lt;0.05), and that a module of co-regulated soluble analytes at baseline, including MUC16, was associated with worse progression free survival (PFS) (P&lt;0.05). NY-ESO-1 autoantibodies were more frequent in non-responders, and the top 10% of expanded TCR clonotypes were increased in responders after one treatment cycle (P&lt;0.05). Conclusion: This data reveals differential immune activation based on treatment modality for patients with R/R HL receiving checkpoint-based regimens in combination with an ADC. Our data highlights potential tumor- and immune-derived predictive and pharmacodynamic biomarker candidates of response and resistance. These novel findings have relevance for R/R HL patients receiving immunotherapy and other immunotherapy combinations such as immuno-chemotherapy platforms. Prospective evaluation of these biomarkers in the Phase II component of this study, a randomized comparison of BV+N vs. BV+N+I which has completed adult accrual, is planned. Figure Legend Clinical responders and non-responder patient samples were analyzed using ELISA (auto antibodies), CyTOF (Cell populations), TCRseq (T cell clonality) and Olink (proteomics). The results showed that pDCs, Neutrophils and B-Plasmablasts increased with specific drug combinations independently of clinical response. While T Cell expansion was associated with clinical response, the increase of auto antibodies against NY-ESO-1 and circulating proteins CD5, ADA, MUC16, CXCL13, CXCL9 and CCL17 were associated with worse prognosis

Background: Upfront autologous stem cell transplant (ASCT) is the standard-of-care for newly diagnosed multiple myeloma (MM) patients. However, relapse and the development of therapy-related myeloid neoplasms (t-MN) post ASCT results in considerable morbidity and mortality. We hypothesized that enrichment of abnormal myeloid progenitors and immune effector cells (IEC) in peripheral blood stem cells (PBSCs) of patients with MM is associated with a higher risk of relapse and development of t-MN. Methods: After institutional review board approval, we screened patients with active MM that were evaluated at Mayo Clinic, Rochester, MN between 01/01/2003 and 12/31/2020. Patients that underwent an ASCT and had cryopreserved PBSC product available for research were included. Using mass cytometry, we performed a comprehensive immunophenotyping of mobilized cryopreserved PBSCs from 54 MM patients undergoing 1 st ASCT, using validated antibody panel of 37 lymphoid- and myeloid-based markers each. Flow cytometry standard files were normalized and concatenated using the Fluidigm acquisition software. Flow cytometry standard files were uploaded to the OMIQ software from Dotmatics (www.omiq.ai, www.dotmatics.com), where transformation and cleaning (doublets, debris) were performed. To correct for between-sample technical variations (“batch effects”), we used fdaNorm within the omiq.ai platform. Clustering and visualization of normalized and concatenaded flowcytometry files were performed within the omiq.ai platform using PhenoGraph and UMAP, respectively. We performed principal component analysis (PCA) to identify major immunomic drivers of variability across patients. We explored the associations between immune subsets and the dichotomized clinical outcomes of interest: progression-free (PFS), myeloid neoplasm-free (MNFS) and overall survival (OS) from ASCT. A 2-sided false discovery rate adjusted P-value of &lt;0.05 was considered significant when multiple comparisons were performed; otherwise, a P-value of &lt;0.05 was considered significant. Results: The most abundant cell populations were T-cells (49% of the CD45 +) and myeloid cells (43% of the CD45 + cells). Clustering on the CD45 + cells revealed 30 unique lymphoid clusters and 27 unique myeloid clusters. Subclustering on NK-cells identified an additional 16 NK-cell clusters. On PCA, principal components-1 (PC-1) and 2 (PC-2) explained 15.2% and 12.5% of the variability in the data, respectively. A high PC-2 score was associated with inferior median PFS (20 vs. 52 months; P=0.005, Figure 1A), MNFS (52 vs. 85 months, P=0.03, Figure 1B) and OS (64 vs. 106 months, P=0.01) from ASCT. Immune subsets enriched in the high PC-2 cohort included the ‘NKT-like’ (CD56 +) T-cell subset which expressed the inhibitory CD159a receptor and TIGIT; a terminally differentiated (CD27/CD28 -, CD57/KLRG1 +) and exhausted (TIGIT/PD-1 +) T cell subset, 2 exhausted (TIGIT/PD-1 +) T cell subsets; an immunosenescent (CD27/CD28 -, CD57/KLRG1 +) T cell subset as well as a terminally exhausted (C27/C28 -, KLRG1/PD-1/TIGIT +) TCRgamma-delta subset. Immune subsets with high loadings within PC-1 (associated with improved clinical outcomes) consisted exclusively of CD4 + cells with early memory phenotypes (CD27/CD28/CD127 +). Abnormal expression of CD7 and HLA-DR expression on myeloid progenitor cell subsets was associated with an inferior PFS, MNFS, and OS. A NK-cell subcluster, characterized by an immature (CD56 high), inhibitory (CD159a +, NKG2A) phenotype, was enriched in patients developing t-MN (0.33% vs. 0.17%, P=0.006). Conclusion: We identify abnormal myeloid and immune effector cells in the PBSCs of patients with MM, even prior to ASCT. Patients with a PBSC product that is enriched in immunosuppressive T and myeloid cell subsets, and with a lower proportion of antigen presenting cells, progenitor populations, and anti-tumor macrophages have a shorter PFS and MNFS. This suggests that the predisposition to t-MN and inferior outcomes for MM are possibly determined early in the disease course. These findings need external validation and have the potential to guide sequencing of future treatment modalities.