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Background ABBV-383 is an off-the-shelf, fully human B-cell maturation antigen (BMCA) X CD3 bispecific antibody with bivalent BCMA domain and low CD3 affinity that targets both BCMA-expressing multiple myeloma (MM) cells and CD3-expressing T cells. ABBV-383 has shown promising activity in an ongoing phase 1 study in patients (pts) with relapsed/refractory (RR) MM ( Voorhees et al. ASH 2022; Weisel et al. EHA 2023). Here, we report the safety and efficacy results from the ABBV-383 IV Q3W at 20 mg, 40 mg and 60 mg dose levels. Methods The phase 1 dose escalation (ESC) and expansion (EXP) study (NCT03933735) of ABBV-383 enrolled pts with RRMM with ≥3 prior lines of therapy (LOT), including a PI, IMiD, and an anti-CD38 mAb with no prior BCMA exposure. After exploring 14 dose levels in dose ESC, 3 dose levels were further explored in dose EXP including ABBV-383 Q3W IV 20 mg, 40 mg, and 60 mg, until disease progression/unacceptable toxicity. The primary objectives were to determine safety/tolerability, PK/PD, and RP2D. The secondary objective was to evaluate clinical activity. Responses were investigator assessed per IMWG 2016 criteria and adverse events (AEs) by CTCAE v5.0. Results As of 17May2023, 220 pts were treated with ABBV-383, 73 pts in the dose ESC and 147 in the dose EXP with 32 pts at 20 mg, 55 pts at 40 mg, and 61 pts at 60 mg Q3W. Median duration of follow up was 7.1 (0.8-36.9), 12.2 (1.3-34.4) and 24.2 (0.6-33.4) months (mo) in the 20 mg, 40 mg and 60 mg dose levels with 25%, 36% and 21% pts continuing treatment (tx), respectively. Median age for all pts was 68 yrs (range, 35-92 yrs), Median prior LOT was 5 (range, 3-23), and 80% were triple-class refractory. Baseline characteristics are summarized in Table 1 by dose level. Treatment-emergent (TE) AEs were reported in 97% (78% ≥G3) of pts at 20 mg, 100% (84% ≥G3) of pts at 40 mg, and 100% (82% ≥G3) of pts at 60 mg. CRS, the most common TEAE, occurred in 50% (34% G1/13% G2/3% G3) of pts at 20 mg, 71%(45% G1/25% G2/0% ≥G3) of pts at 40 mg, and 70%(51% G1/18% G2/2% G3) of pts at 60mg. At the 3 dose levels, CRS occurring after the first dose had median time to onset of 1 day (range, 1-2) and median duration was 2 days (range, 1-10). ICANS occurred in 3% (3% G1/0% ≥G2) of pts at 20 mg, 5% (2 % G1/4% G2/0% ≥G3) of pts at 40 mg, and 5% (3% G2/2% G3) of pts at 60 mg. No G4/5 CRS or ICANS occurred. Infections occurred in 56% (25% ≥G3) of pts at 20 mg, 71% (26% ≥G3) of pts at 40 mg, and 57% (34% ≥G3) of pts at 60 mg; most frequently (≥10%) reported were upper respiratory tract infections (15%, G3/4 1%), pneumonia (14%, G3/4 12%), urinary tract infections (12%, G3/4 3%), and COVID-19 (11%, G3/4 1%). At 20 mg, 40 mg, and 60 mg, the incidence of neutropenia was 41% (25% ≥G3), 42% (31% ≥G3), and 43% (34% ≥G3); anemia 50% (25% ≥G3), 55% (31% ≥G3), and 38% (13% ≥G3); thrombocytopenia 44% (28% ≥G3), 36% (16% ≥G3) and 26% (13% ≥G3), respectively. The tx discontinuation due to AEs was 6%, 11%, 10% in 20 mg, 40 mg and 60 mg, respectively, with no single PT reported in >2 pts. Clinical responses are shown in Figure 1. The median time to ≥VGPR was 0.7mo (0.7-5.8) at 20 mg, 1.0mo (0.7-10.4) at 40 mg, and 1.4 mo (0.7-7.8) at 60 mg. The median DOR was 9.7 mo (3.5-not reached (NR)) at 20 mg, and NR at 40 mg and 60 mg. The Kaplan-Meier (KM) estimates for DOR at 12 mo was 42% at 20 mg, 70% at 40 mg, 66% at 60 mg. The mPFS was 3.8 mo (2.4-7.9) at 20mg, 13.7mo (5.0-NR) at 40 mg, and 11.2 mo (4.8-NR) at 60 mg. The KM estimates for PFS at 12 mo was 19% at 20 mg, 51% at 40 mg, 49% at 60 mg. The median OS was 21.6 mo (7.9-NR) at 20 mg, and NR at 40 mg and 60 mg. ABBV-383 at 20 mg, 40 mg, and 60 mg led to rapid and transient production of key proinflammatory cytokines (IL-6, IL8, IFN-γ, and TNF-α), and reduction of soluble BCMA levels over time that were associated with disease response. ABBV-383 also promoted T-cell activation and proliferation with upregulation of CD69 and KI67 markers on peripheral CD4 and CD8 T cells in evaluable pts. Conclusions ABBV-383 showed a manageable safety profile at dosages of 20 mg, 40 mg, and 60 mg IV Q3W, with low incidence of TEAEs leading to discontinuation. Also, extended Q3W dosing interval with no step-up dosing schedule of ABBV-383 may provide enhanced convenience. However, 20 mg yielded numerically lower responses when compared to 40 mg and 60 mg. At 40 mg and 60 mg, ABBV-383 monotherapy yielded deep and durable responses with mPFS of 13.7 mo and 11.2 mo, and 12-month DOR of 70% and 66% (mDOR NR in pts with ≥CR), respectively. These results in heavily pretreated RRMM pts support further clinical evaluation.

Introduction Newly-diagnosed multiple myeloma (MM) patients often share tumor genetic abnormalities associated with a high risk of progression and poor survival. We hypothesized that single-cell transcriptomic characterization of the tumor immune microenvironment (TIME) may be combined with tumor-based risk stratification to uncover novel disease biology mechanisms associated with clinical outcomes and improve risk stratification. Methods We performed single-cell RNA sequencing of 361 CD138 negative sorted bone marrow mononuclear cells (BMMCs) samples from 263 MM patients enrolled at time of diagnosis in the Multiple Myeloma Research Foundation CoMMpass study (NCT01454297). Specimens were analyzed at baseline (n=263) across a network of five collaborating academic research centers following assay harmonization. Genetic factors that determine risk were defined as one or more of the following gain- or loss-of-function events derived from baseline genomic sequencing data: del17p14, translocations of the Ig locus with the MAF/A/B or WHSC1/MMSET/NSD2 loci, and gain of chromosome 1q21. Statistical modeling strategies were used to assess single-cell populations or RNA signatures associations with known risk factors or disease progression (FDR<0.05). Results The study generated high-quality single-cell profiles of 731,643 cells from 123 high-risk and 107 standard-risk MM patients based on genetics. Based on distinct transcriptome profiles, BMMCs formed 106 clusters corresponding to 5 major compartments: NK and T cells, B cells, erythrocytes, myeloid cells, and plasma cells. Our preliminary differential abundance analysis comparing high- vs standard-risk patients at baseline uncovered significant differences in the TIME associated with genetic risk. The high-risk group was identified as enriched in effector CD8+, and CD4+ T cells. In contrast, the high-risk group exhibited depletion of naive CD8+ and interferon-associated CD4+ and CD8+ T as compared to the standard-risk group. Within subclusters in the T and NK cells compartment, a higher cytotoxicity signature was observed in high-risk patients, characterized by the expression of granzymes and perforin. Finally, our preliminary survival and progression analysis associated a higher frequency of IDO1-expressing macrophages in worst progression patients, while better outcomes were associated with CD8+ T and B cells expressing androgen response and IL6/STAT3/EMT programs, respectively. Conclusions Current approaches for risk stratification are based on bulk measurements of tumor's genetic or epigenetics features, which do not capture the diversity and dynamics of the TIME. Through single-cell transcriptomics, we were able to capture, in high granularity, the TIME and correlate specific immune cell populations and phenotypes with relapse risk and poor prognostic outcomes. These results suggest that immune subpopulations may be an essential novel aspect for improving current risk stratification models.

Purpose: Advances in targeted therapeutics for histiocytic neoplasms have led to a growing survivor population, especially for Erdheim-Chester disease (ECD), Langerhans cell histiocytosis (LCH), and Rosai-Dorfman disease (RDD). This growing population is at risk of adverse health-related quality of life (HRQoL) as a result of the disease or treatments received. Patient-reported outcomes in this population remain understudied, and we aim to define their HRQoL using a validated tool. Methods: We enrolled patients from 2 histiocytosis centers and an international conference from Aug 2022-April 2023 to complete the PROMIS © (Patient-Reported Outcomes [PROs] Measurement Information System) 29+2 profile v2.1, which captures 8 domains of physical/mental health and functioning. Domains are reported as T-scores, with 50 being the general population mean. We calculated summary T-scores for Physical Health (PH) and Mental Health (MH), and differences of 3 from general population were considered clinically meaningful. We then used these T-scores to calculate each patient's PROMIS-Preference (PROPr) score, which is a health-utility score that measures overall HRQoL. A mean PROPr score difference of 0.4 from the US population mean of 0.52 was considered meaningful. We ran independent-samples t-tests to examine differences in PH/MH summary scores and PROPr between sub-cohorts. Finally, we performed a multinomial logistic regression analysis to identify factors associated with worse scores, and calculated odds ratios (OR) for each factor. Results: We included a total of 77 participants. Specific diagnoses included ECD (n=33, 42.9%), LCH (n=21, 27.3%), RDD (n=19, 24.7%), and other/unknown (n=4, 5.2%). Median age at diagnosis was 50y (9-79) and at survey was 54y (18-82), with a median 4 year difference between diagnosis and survey completion. Racial demographics included white (n=64, 83.1%), Black (n=12, 15.6%), and Asian (n=1, 1.3%). 4 patients (5.2%) identified as having a Hispanic ethnicity. Disease extent included unifocal (n=13, 16.9%), single system multifocal (ss-M, n=8, 10.4%), single system lung LCH (ss-L, n=3, 3.9%), or multisystem (n=53, 68.8%) disease. The most commonly involved organs included bone (n=44, 57.1%), kidney (n=24, 31.2%), skin (n=24, 31.2%), CNS (n=24, 31.2%), and pituitary (n=19, 24.7%). PH and MH summary scores were lower in various diagnostic categories as compared with the US population, and PROPr scores were reduced in all diagnostic categories. Bone involvement was associated with worse PH (-6.16, 95%CI -10.81, -1.52, [p=0.005]), MH (-7.96, 95%CI -12.48, -3.44, [p=<0.001]), and PROPr (-0.184, 95%CI -0.313, -0.056, [p=0.003]) scores. CNS involvement was associated with worse PH (-4.78, 95%CI -9.14, -0.42, [p=0.016]). We initially constructed a multinomial regression model using diagnosis, race, age at survey completion, and CNS and bone involvement. This model was not statistically significant, and in particular, diagnosis and age did not significantly contribute to the model. We then removed diagnosis and age and constructed a new model using the remaining variables, which was statistically significant for all 3 scores (p<0.05). We found that factors associated with worse PH score were disease involvement of bone (OR=6.19, 95%CI 1.88, 20.43 [p=0.003]) and CNS (OR=10.36, 95%CI 2.01, 53.39 [p=0.005] Figure 2). Factors associated with worse MH scores included female sex (OR=4.12, 95%CI 1.24, 13.66 [p=0.021]) and CNS involvement (OR=10.74, 95%CI 2.47, 46.79 [p=0.002]). Having race/ethnic group other than white/Non-Hispanic or Black was associated with improved MH. However, as this group had only 4 members, the significance of this is uncertain. Finally, CNS involvement was found to be associated with worse odds of having a low PROPr score (OR=10.46, 95%CI 2.17, 50.37 [p=0.003]). Conclusions: Several PROs were worse in patients with histiocytic neoplasms as compared with the general population. We further found that CNS involvement was independently associated with worse HRQoL, regardless of the diagnosis type. Additionally, female sex was associated with worse MH scores, and bone involvement with worse PH scores. PROPr score was particularly low among patients with ECD. Future research is warranted to assess the impact of treatments on HRQoL, as well as the economic loss resulting from loss of productivity as highlighted by low PROPr scores.

Background: To be useful across the broadest range of patients and clinical settings, clinical prediction models should be externally validated in different data sets and clinical settings and refined over time. In 2022, the HoLISTIC Consortium (www.hodgkinconsortium.org) developed and validated the A-HIPI model via TRIPOD guidelines for adults 18-65 with advanced stage classic Hodgkin Lymphoma (AS-HL) (Rodday et al., JCO 2023). The A-HIPI model, based on individual patient (pt) data from more than 5000 patients (pts) from North America, Europe, and Australia, predicts progression-free survival and overall survival within the first 5 years (PFS5 and OS5) based on pre-treatment pt and disease characteristics (www.qxmd.com/calculate/calculator_869/a-hipi). In collaboration with Brazilian clinical experts and researchers, we describe the performance of the A-HIPI in the Brazilian Prospective HL registry. Methods: The Brazilian Prospective HL registry (NCT02589548) was originally established in 2009 with the goal of evaluating risk factors, treatment, and disease outcomes. By 2022, 1357 pts with classic HL were registered with a median follow-up of 5 years for surviving patients (Biasoli I. HemaSphere 2022). 5-year PFS and OS were calculated using the Kaplan-Meier method. Using the methodology for validation and calibration outlined in by Rodday et al., calculated risk scores were calculated for PFS5 and OS5. Harrell c-statistic and the Uno c-statistic were calculated to evaluate discrimination (i.e., differentiation of those at higher risk of having an event from those at lower risk) and plots of deciles of predicted vs. observed outcomes were created to assess calibration (i.e., how similar the predicted absolute risk of the model is to the true (observed) risk in an external cohort). In the primary A-HIPI analysis, laboratory values outside of permitted range were excluded and not imputed. This was checked in sensitivity analysis using multiple imputation for missing values; no substantial differences were noted. Thus, in the current validation, out-of-range lab values were excluded. There were no exclusions in the current analysis for early death, defined as deaths that occurred from the onset of first treatment until 30 days after its end. Pts with HIV were excluded from the assembled cohort. Results: 694 patients with AS-HL with the inclusion criteria of the original study were included in the present study. The median age was 30.9 years (range, 18-65) at diagnosis with 46% of the pts being female. 230 (33%) patients were classified as Stage IIB, 190 with Stage III (27.4%), and 274 (39.5%) with Stage IV. Bulky disease (>10 cm) was present in 226 patients (33%). Median hemoglobin was 11.6 g/dL (8-16.3), median albumin 3.63 g/dL (1.41-5.46), and median lymphocyte count was 1.5 x 10 3 µL (0.10-4.76). The 5-y PFS (PFS5) in the A-HIPI Brazilian validation dataset was 68.4% (95% CI: 64.7-71.9%) and the 5-y OS (OS5) was 86.0% (95% CI: 82.8-88.6).Harrell c-statistics for the A-HIPI model were 0.60 (95% CI, .56-.64) for 5-year PFS and 0.69 (95%CI, .64-.74) for 5-year OS and Uno c-statistics for the A-HIPI model were 0.63 (95% CI, .58-.68) for 5-year PFS and 0.72 (95%CI, .65-.78) for 5-year OS. Calibration plots (see figures) show the predicted A-HIPI model estimates were well calibrated with the observed outcomes in the Brazilian HL registry. Conclusions: Despite important differences between the original development cohort for A-HIPI and the Brazilian registry in patient and clinical characteristics (e.g., younger age at diagnosis, greater proportion of Stage IV disease) and the well characterized impact of income maldistribution and socio-economic status on clinical outcomes (Biasoli et al., Int J Cancer 2018), the A-HIPI clinical prediction tool performed well in the Brazilian Prospective Registry. This included evidence of adequate discrimination and calibration. Future studies are planned, including the impact of treatment selection and response, use of interim imaging, and supportive care may underscore important differences in outcomes among adults with AS-HL.

Introduction: SystemicAL amyloidosis is a progressive and often fatal disease caused by misfolded light chains that aggregate into amyloid fibrils and deposit in vital organs, leading to organ dysfunction. Current standard of care (SoC) therapies for AL amyloidosis target the plasma cell clone to reduce or eliminate light chain production, but do not remove soluble toxic light chain aggregates or insoluble amyloid deposits. Early mortality remains high for patients with advanced disease (e.g., Mayo 2012 Stage IV disease, median overall survival <6 months). Birtamimab - a humanized monoclonal antibody that neutralizes soluble, toxic light chain aggregates and depletes insoluble amyloid deposits by inducing phagocytosis - is under investigation for the treatment of AL amyloidosis. Here, we present a pooled safety analysis from previous Phase 1-3 clinical trials, with a focus on the 2 double-blind randomized controlled trials (RCTs): PRONTO (NCT02632786) and VITAL (NCT02312206). Methods: Patients with AL amyloidosis were treated with intravenous birtamimab up to 24 mg/kg every 28 daysin the non-placebo-controlled Phase 1/2 open-label trial (NCT01707264) with open-label extension (OLE; NCT02613182) and 2 RCTs (Phase 2 PRONTO with OLE [NCT03154047] and Phase 3 VITAL). In PRONTO, patients had received ≥1 previous systemic therapy with at least a partial hematologic response and persistent cardiac dysfunction, and received birtamimab or placebo. In VITAL, newly diagnosed treatment-naïve patients with cardiac involvement received birtamimab + SoC or placebo + SoC (where SoC was a bortezomib-containing chemotherapy regimen). The analysis included all patients who received ≥1 dose of birtamimab. Pooled median exposure times were calculated, and baseline characteristics and demographics were summarized. For VITAL and PRONTO, pooled rates and severity of treatment-emergent adverse events (TEAEs) with birtamimab were compared with rates in the placebo arms. In addition, safety data from the non-placebo-controlled studies were summarized. Results: The median (range) exposure to birtamimab among 302 patients pooled from the Phase 1-3 trials was 12.24 (0.03-57.72) months. Of the 302 patients exposed to birtamimab, 295 received at least one 24-mg/kg infusion, up to 2500 mg. Analysis of the 2 randomized, placebo-controlled trials included data from 196 patients treated with birtamimab from the PRONTO (n=66) and VITAL (n=130) trials and 193 patients who received placebo (PRONTO, n=63; VITAL, n=130). Both trials had comparable treatment durations overall. The rates of TEAEs, serious and grade ≥3 TEAEs were similar between birtamimab and placebo arms within each trial and between treatment arms in the placebo-controlled pooled analysis set (PRONTO and VITAL; Table 1). Higher rates of treatment-related, serious, and grade ≥3 TEAEs were reported in VITAL compared with PRONTO, presumably due to the treatment-naïve population and receipt of concomitant SoC therapy in VITAL. In the pooled analysis set, the most common TEAEs that occurred with greater frequency in the birtamimab vs placebo arms in either trial were, respectively, fatigue (36.2%, 34.2%), diarrhea (33.2%, 33.7%), nausea (31.6%, 30.1%), constipation (31.1%, 31.6%), and dyspnea (25.0%, 24.9%). The most commonly reported (≥5%) serious and grade ≥3 TEAEs were primarily cardiac disorders (cardiac failure, syncope, cardiac arrest), consistent with the underlying disease. Infusion-associated TEAE rates were low in the pooled birtamimab and placebo arms (5.1% vs 3.6%, respectively) and were generally mild to moderate. The safety profile observed in the non-placebo-controlled Phase 1/2 trial plus OLE and PRONTO OLE (n=106) was consistent with the safety data reported in the placebo-controlled studies. Conclusions: Birtamimab was well tolerated in patients with AL amyloidosis when administered as monotherapy and did not demonstrate additive toxicity when given with SoC chemotherapy. Rates of TEAEs in the birtamimab arm were similar to rates in the placebo arm in the PRONTO and VITAL trials. The safety and efficacy of birtamimab is being further investigated in an ongoing confirmatory Phase 3 double-blind RCT in patients with Mayo Stage IV AL amyloidosis (AFFIRM-AL; NCT04973137), which is currently enrolling.

Background: Oral decitabine/cedazuridine (ASTX727) is a fixed dose combination of decitabine (35 mg) and the cytidine deaminase inhibitor cedazuridine (100 mg) given once daily X 5 days on a 28-day cycle producing pharmacokinetic (PK) exposure equivalent to the standard intravenous (IV) decitabine regimen of 20 mg/m 2 daily X 5 days on a 28-day cycle. This was demonstrated in the pivotal ASCERTAIN study (Garcia-Manero, et al, ASH 2019) as it provided a PK bridge to existing decitabine data and demonstrated median OS was 31.7 mo. (Savona,et al. Intl. MDSF International Congress on MDS, 2021). Subjects were initially classified by the International Prognosis Scoring System (IPSS) for historical reasons, however IPSS-R and IPSS-M are enhancements to IPSS that provide dynamic risk assessment for predicting clinical outcomes in MDS. Here, the objective was to re-classify the MDS subjects enrolled on the ASCERTAIN study by IPSS-R and IPSS-M and measure the impact of informing patient outcomes based on re-calculated risk assessment. Methods: One hundred thirty-three subjects with MDS/CMML (chronic myelomonocytic leukemia) were enrolled in ASCERTAIN and were randomly assigned either IV decitabine for cycle 1 and oral decitabine/cedazuridine for cycle 2 or the opposite treatment sequence. All subjects continuing beyond cycle 2 received oral decitabine/cedazuridine for all subsequent cycles until treatment discontinuation for disease progression, toxicity, patient's decision, or HSCT. Whole blood collected prior to treatment was used for DNA isolation and molecular abnormalities identified using next-generation sequencing (NGS) hematologic malignancy panel of 179 genes including all genes commonly mutated in MDS. In the initial analysis of clinical outcomes, subjects were classified by IPSS with response assessment by IWG 2006 IPSS low and Int-1 risk levels were categorized as lower-risk MDS (LR-MDS), whereas IPSS Int-2 and high-risk categories were categorized as higher-risk MDS (HR-MDS). Subjects with sufficient data based on (e.g., available heme parameters, cytogenetics, NGS etc.) were reclassified by IPSS-R and IPSS-M. Subjects with IPSS-R score of ≤3.5 or IPSS-M of either very low, low, or moderate low were categorized as LR-MDS. Similarly subjects with IPSS-R score of >3.5 or an IPSS-M categorization of either moderate high, high, or very high were categorized as HR-MDS. Reclassified subjects were reassessed for CR (Complete Response), OS, and LFS and Harrell's concordance index (c-index) was used to describe the level of agreement between each scale and outcomes. Results: Based on the available data, the number of MDS subjects in the different risk classifications were the following: IPSS: 117, IPSS-R: 104, and IPSS-M: 105. Thirteen and 12 subjects on the IPSS could not be reclassified in the IPSS-R and IPSS-M, respectively, including 5 Int-1 and 2 low-risk MDS cases. CMML subjects were excluded from these analyses. Re-classification generally resulted in the upgrade of the subjects from LR-MDS to HR-MDS (Fig. 1). Thirty-one (26.5%) subjects from IPSS were reallocated in the IPSS-R to different risk categories; 3 (9.7%) were downgraded and 28 (90.3%) were upgraded. Similarly on reclassification with IPSS-M 34 (32.4%) of the patients reclassified; 5 (14.8%) were downgraded and 29 (85.3%) were upgraded. For IPSS LR-MDS, 23.2% of patients achieved CR, and 22.9% in the IPSS HR-MDS. Similarly, 21.6% patients achieved CR in the IPSS-R LR-MDS, and 23.9% in the IPSS-R HR-MDS; 26.3% patients achieved CR in the IPSS-M LR-MDS, and 20.9% in the IPSS-M HR-MDS. The c-index for the IPSS was .64 (OS) and .67 (LFS), IPSS-R was .70 (OS) and .71 (LFS), and .75 (OS) and .78 (LFS) for the IPSS-M (Table1). Conclusion: Reclassification from IPSS to IPSS-R or IPSS-M upgraded multiple subjects from a LR to a HR category, describing the ASCERTAIN patient population as a majority higher risk population with worse prognosis than previously assumed based on the IPSS. The efficacy as measured by the CR rates did not change when the LR and HR categories were defined by the different risk stratification systems. In contrast, the c-index improves with migration from IPSS to IPSS-R to IPSS-M, indicating an increased discriminatory ability of IPSS-M score in comparison to IPSS and IPSS-R, to predict patient outcomes.

Abstract Background Context Surgical decompression is the definitive treatment for managing symptomatic lumbar spinal stenosis; however, select patients are poor surgical candidates. Consequently, minimally invasive procedures have gained popularity, but there exists the potential for failure of therapy necessitating eventual surgical decompression. Purpose To evaluate the incidence and characteristics of patients who require surgical decompression following minimally invasive procedures to treat lumbar spinal stenosis. Study Design/Setting Retrospective review. Patient Sample Patients who underwent minimally invasive procedures for lumbar spinal stenosis (Percutaneous Image‐guided Lumbar Decompression [PILD] or interspinous spacer device [ISD]) and progressed to subsequent surgical decompression within 5 years. Outcome Measures The primary outcome was the rate of surgical decompression within 5 years following the minimally invasive approach. Secondary outcomes included demographic and comorbid factors associated with increased odds of requiring subsequent surgery. Methods Patient data were collected using the PearlDiver‐Mariner database. The rate of subsequent decompression was described as a percentage while univariable and multivariable regression analysis was used for the analysis of predictors. Results A total of 5278 patients were included, of which 3222 (61.04%) underwent PILD, 1959 (37.12%) underwent ISD placement, and 97 (1.84%) had claims for both procedures. Overall, the incidence of subsequent surgical decompression within 5 years was 6.56% (346 of 5278 patients). Variables associated with a significantly greater odds ratio (OR) [95% confidence interval (CI)] of requiring subsequent surgical decompression included male gender and a prior history of surgical decompression by 1.42 ([1.14, 1.77], p = 0.002) and 2.10 times ([1.39, 3.17], p < 0.001), respectively. In contrast, age 65 years and above, a diagnosis of obesity, and a Charlson Comorbidity Index score of three or greater were associated with a significantly reduced OR [95% CI] by 0.64 ([0.50, 0.81], p < 0.001), 0.62 ([0.48, 0.81], p < 0.001), and 0.71 times ([0.56, 0.91], p = 0.007), respectively. Conclusions Minimally invasive procedures may provide an additional option to treat symptomatic lumbar spinal stenosis in patients who are poor surgical candidates or who do not desire open decompression; however, there still exists a subset of patients who will require subsequent surgical decompression. Factors such as gender and prior surgical decompression increase the likelihood of subsequent surgery, while older age, obesity, and a higher Charlson Comorbidity Index score reduce it. These findings aid in selecting suitable surgical candidates for better outcomes in the elderly population with lumbar spinal stenosis.

Abstract Methylation profiling of brain tumors has revealed novel clusters whose biological and clinical significance is unknown. These include three entities termed by the 12.5 version of the Heidelberg methylation classifier as adult-type diffuse high grade glioma, IDH-wildtype, subtype B (HGG_B), subtype E (HGG_E), and subtype F (HGG_F). We have identified 75 cases belonging to these groups: HGG_B (25 cases, 32% female), HGG_E (40 cases, 42% female), and HGG_F (18 cases, 33% female). Although originally characterized as “adult-type,” we find that 70% of HGG_E cases are pediatric, with a median age at diagnosis of 11 years. HGG_B cases are predominantly seen in young adults, and HGG_F in older adults. The histology varies among methylation classes, with HGG_B cases demonstrating high-grade, predominantly astrocytic, morphology, while HGG_E cases demonstrate high-grade glial histology with distinct nuclear features, and HGG_F cases show highly infiltrative but lower grade glial morphology. Patient outcome data obtained to date shows a collective median survival exceeding 5 years, suggesting re-consideration of the proposed grading for these tumors. MGMT promoter methylation differs across the HGG_B (0%), HGG_E (12%), and HGG_F (0%) subtypes. Mutational analyses show enrichment of TERT promoter mutations in the HGG_F group, while HGG_E samples are enriched for tumors with POLE mutations and elevated tumor mutation burden. HGG_E tumors show epigenetic similarity to pediatric high-grade diffuse gliomas (pedHGG_RTK1A); we therefore propose that HGG_E be considered a pediatric-type HGG. HGG_B tumors show demographic and genomic similarities to high-grade astrocytomas with piloid features, including a subset of cases with CDKN2A/2B loss and ATRX mutation. HGG_F separate into two groups dictated by brain location, and despite the presence of TERT promoter mutations, appear distinct from GBMs. Overall, our work represents an initial effort to understand the morphologic, genomic and clinical characteristics of these previously uncharacterized subtypes of gliomas.

Comprehensive resources exist on how to plan a systematic review and meta-analysis. The objective of this article is to provide guidance to authors preparing their systematic review protocol in the fields of regional anesthesia and pain medicine. The focus is on systematic reviews of healthcare interventions, with or without an aggregate data meta-analysis. We describe and discuss elements of the systematic review methodology that review authors should prespecify, plan, and document in their protocol before commencing the review. Importantly, authors should explain their rationale for planning their systematic review and describe the PICO framework—participants (P), interventions (I),comparators (C), outcomes (O)—and related elements central to constructing their clinical question, framing an informative review title, determining the scope of the review, designing the search strategy, specifying the eligibility criteria, and identifying potential sources of heterogeneity. We highlight the importance of authors defining and prioritizing the primary outcome, defining eligibility criteria for selecting studies, and documenting sources of information and search strategies. The review protocol should also document methods used to evaluate risk of bias, quality (certainty) of the evidence, and heterogeneity of results. Furthermore, the authors should describe their plans for managing key data elements, the statistical construct used to estimate the intervention effect, methods of evidence synthesis and meta-analysis, and conditions when meta-analysis may not be possible, including the provision of practical solutions. Authors should provide enough detail in their protocol so that the readers could conduct the study themselves.

In Part I of this series, we provide guidance for preparing a systematic review protocol. In this article, we highlight important steps and supplement with exemplars on conducting and reporting the results of a systematic review. We suggest how authors can manage protocol violations, multiplicity of outcomes and analyses, and heterogeneity. The quality (certainty) of the evidence and strength of recommendations should follow the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. It is our goal that Part II of this series provides valid guidance to authors and peer reviewers who conduct systematic reviews to adhere to important constructs of transparency, structure, reproducibility, and accountability. This will likely result in more rigorous systematic reviews being submitted for publication to the journals like Regional Anesthesia & Pain Medicine and Anesthesia & Analgesia.