Citations

Abstract Introduction: Brentuximab vedotin (BV) was approved by the US FDA for relapsed/refractory (R/R) classical Hodgkin lymphoma (cHL) in 2011 and for previously untreated advanced stage cHL in 2018. The immune checkpoint inhibitors (ICIs) nivolumab and pembrolizumab were approved for R/R cHL in 2016 and 2017, respectively. These novel agents have significantly changed the landscape of cHL management in recent years. In this study, we analyzed data from the National Cancer Database (NCDB) to investigate whether survival outcomes have improved in the novel agent era (2011 and beyond) for patients with cHL in the US. Methods: Patients diagnosed with cHL between 2004 and 2020 were identified in the NCDB. Those with missing survival data were excluded. Three treatment eras were defined based on the timing of FDA approval of novel agents: Chemo era (2004–2010), BV era (2011–2015), and ICI era (2016–2020). Patient and disease characteristics were compared using the Chi-square test. Survival analyses were conducted using the Kaplan-Meier method and Cox proportional hazards model. Results: A total of 85,488 patients with newly diagnosed cHL were identified: 36,150 in the Chemo era, 27,058 in the BV era, and 22,280 in the ICI era. Compared to the chemo era, the BV and/or ICI eras included slightly more patients aged ≥66 (17.3% vs 17.8% vs 19.5%), male (53.6% vs 54.6% vs 53.8%, p=0.042), Black (11.3% vs 12.9% vs 12.5%), Hispanic (9.0% vs 9.9% vs 10.9%), with Charlson-Deyo score ≥1 (14.2% vs 16.1% vs 17.2%), B symptoms (44.1% vs 46.9% vs 46.9%), treated at academic centers (32.4% vs 35.9% vs 36.4%), on Medicaid (9.5% vs 12.2% vs 13.7%) or Medicare (19.3% vs 20.3% vs 21.7%), and with higher income (≥4th quartile by 2008-2012 standard; 34.5% vs 34.3% vs 36.3%) (all p<0.001 except for sex, noted above). Ann Arbor stage data were not available in the ICI era. There were slightly more patients with advanced-stage disease in the BV era compared to the Chemo era (45.4% vs 40.3%, p<0.001). IPS scores were available for only 2,344 patients, with a similar distribution (0–2 vs 3–7) across the three eras (p=0.957). The median follow-up was 6.9 years (95% CI 6.9-7.0). Overall survival (OS) significantly improved in the novel agent eras: the 5-year OS rate was 79.8% (95% CI, 79.4%–81.2%) for patients diagnosed in the Chemo era, 81.9% (95% CI, 81.9%–82.4%) in the BV era, and 84.1% (95% CI, 83.5%–84.8%) in the ICI era (p<0.001). Statistically significant OS improvements were observed across all subgroups, including age (≤40: 92.8% vs 94.9% vs 96.5%, 41-65: 80.5% vs 81.8% vs 84.4%, ≥66: 41.4% vs 46.6% vs 52.7%), sex (male: 78.0% vs 80.0% vs 81.9%, female: 81.9% vs 84.1% vs 86.7%), race (White: 79.9% vs 81.6% vs 83.7%, Black: 77.2% vs 81.2% vs 84.6%, others: 84.5% vs 87.0% vs 89.3%), ethnicity (Hispanic 79.7% vs 82.3% vs 85.1%, Non-Hispanic 80.0% vs 81.9% vs 84.1%), Charlson-Deyo score (0: 83.5% vs 85.4% vs 87.9%, 1: 62.8% vs 68.2% vs 73.2%, 2: 42.5% vs 52.6% vs 58.3%, 3+: 49.0% vs 54.4% vs 51.7%), B symptoms (yes: 74.7% vs 78.9% vs 81.5%, no: 84.3% vs 85.1% vs 87.5%), treatment facility type (academic: 69.8% vs 74.0% vs 77.1%, non-academic: 66.4% vs 67.6% vs 70.2%, unknown: 92.9% vs 95.0% vs 96.5%), insurance type (private: 89.9% vs 91.2% vs 93.4%, Medicare: 46.5% vs 52.3% vs 57.2%, Medicaid: 79.1% vs 84.5% vs 87.7%) and income level (Q1: 74.1% vs 77.1% vs 81.1%, Q2 77.7% vs 80.1% vs 81.3%, Q3 79.8% vs 81.6% vs 85.2%, Q4: 82.8% vs 84.9% vs 87.0%) (all p<0.001). In multivariate Cox regression analysis adjusting for age, sex, race, ethnicity, Charlson-Deyo score, B symptoms, treatment facility type, insurance type, and income level, diagnosis in the BV era (HR = 0.856; 95% CI, 0.827–0.885; p<0.001) and ICI era (HR = 0.666; 95% CI, 0.636–0.698; p<0.001) was independently associated with improved OS compared to the Chemo era. Conclusions: In this large NCDB-based analysis, survival outcomes for patients with cHL significantly improved in the BV and ICI eras compared to the Chemo era. OS improvement was consistent across all subgroups and remained independent of age, sex, race, ethnicity, Charlson-Deyo score, B symptoms, treatment facility type, insurance type, and income level in multivariate analysis. These findings may reflect the positive impact of BV and ICIs on survival in patients with cHL.

Background: Scoliosis has various etiologies, ranging from idiopathic, congenital, to those with spinal cord abnormalities. Advanced imaging is not always feasible and limited by cost, low-yield, and anesthesia risks in children. Given artificial intelligence's potential, we hypothesize that a deep learning (DL)–based image classifier will demonstrate superior performance in radiographic classification of scoliosis etiology compared witht experienced spine surgeons based on spine radiographs. Methods: One thousand thirty-six pediatric patients from single institution with scoliosis diagnosis and paired anterior-posterior - lateral images were included. Patients were manually classified based on their scoliosis etiology from chart review, including previous spine imaging studies when available. Categories included idiopathic, congenital, and spinal cord pathology. Images were randomized and assigned for training, validation, and testing. A DL-classifier using EfficientNet B4 architecture was trained on the radiographs. Accuracy and positive predictive value as defined by precision, recall, and F1-score were calculated to assess final performance metrics. Results: The trained classifier performed well at identifying correct etiologies, with F1-Score (harmonic mean of precision-recall) of 0.97. Model precision was 0.99 for adolescent idiopathic scoliosis, 0.89 for congenital, and 0.78 for spinal cord pathology. Performance was higher on more common classes, with lower performance observed in class with fewer images. The algorithm has highest overall precision (0.96), recall (0.96), and F1 (0.96), while Surgeons 1 and 2 have lower accuracies (precision 0.80, recall 0.79, and F1 0.79 and precision 0.76, recall 0.67, and F10.71, respectively). There was no clear pattern identified regarding the surgeons' errors and poor agreement on which X-rays corresponded to underlying spinal cord pathology. Conclusion: A DL-convolutional-neural-network classifier has been trained to high degree of accuracy to distinguish between 3 scoliosis etiologies on pediatric spine radiographs. This model could provide a novel tool to clinicians to decide when to refer for axial imaging. It had superior diagnostic performance compared with experienced spine surgeons. After further validation and refinement, a clinician could put a patient's X-rays into the predictive tool for analysis and use the results to discuss with the family the risk of finding spinal cord pathology, helping them determine together the best timing for an MRI. Level of Evidence: Level III . See Instructions for Authors for a complete description of levels of evidence.

ABSTRACT Background Chronic myelomonocytic leukemia (CMML) is largely a disease of individuals older than 50 years; its occurrence in patients aged 50 years and younger is rare. The authors sought to characterize the clinicopathologic features and genetic profile of young‐onset (age 50 years and younger) CMML (y‐CMML) compared with older onset (older than 50 years) CMML (o‐CMML). Methods The authors conducted a multi‐institutional study of 32 patients with y‐CMML and 119 patients with o‐CMML, analyzing clinical, morphologic, cytogenetic, and molecular data. Results Patients who had y‐CMML frequently presented with splenomegaly (59% vs. 11%; p < .001) and hepatomegaly (25% vs. 2%; p < .001) compared with those who had o‐CMML. Although the overall incidence of cytogenetic abnormalities was similar, patients who had y‐CMML exhibited distinct mutational patterns. PTPN11 mutations were significantly more common in y‐CMML (13% vs. 3%; p = .034) than in o‐CMML, whereas TET2 (6% vs. 57%; p < .001) and SRSF2 (16% vs. 46%; p = .002) mutations were significantly less frequent. In addition, multi‐hit TET2 (6% vs. 34%; p = .002) and TET2‐SRSF2 (3% vs. 29%; p = .003) co‐mutations were rare in y‐CMML. However, the molecular differences did not affect the CMML‐specific risk‐stratification categories because the clinical outcomes, including overall survival and leukemia‐free survival, did not differ between the two groups. Conclusions CMML in patients aged 50 years and younger is rare and presents with unique clinical and mutational features, suggesting a distinct pathogenesis.

Importance Total pancreatectomy (TP) is indicated for advanced pancreatic cancer or multifocal tumors. Furthermore, TP may be performed to avoid the risk of pancreatic fistula in selected patients to improve the perioperative risk profile. Objective To define reference values for TP based on a low-risk cohort treated at expert centers. Design, Setting, and Participants This multicenter study analyzed outcomes from patients undergoing primary TP for malignant or benign lesions from 25 international expert centers from January 2017 to November 2023. Low-risk patients undergoing TP (LR-TP) were without vascular resections or significant comorbidities. Exposures TP. Main Outcomes and Measures Twenty reference values were derived from the 75th or the 25th percentile of the median values of all centers. Outcomes of LR-TP were compared with a cohort of TP with vascular resection, TP due to high-risk pancreatic anastomosis, and the benchmark values for low-risk pancreatoduodenectomy. Results Of 994 patients, 333 (33.5%; median [IQR] age, 66 [58-72] years; 171 male [51.4%]) qualified as the LR-TP cohort. Reference values included blood loss (≤1000 mL), major complications (≤37%), 3-month postoperative mortality (&amp;lt;6%), and retrieved lymph nodes (≥29). Compared with TP with vascular resections, reference cutoffs were not met for major complications (51% vs LR-TP ≤37%) and 90-day mortality (11% vs LR-TP ≤6%). For TP due to high-risk anastomosis, failure to rescue rate (38% vs ≤6%) and 90-day mortality (11% vs LR-TP ≤6%) were not met. Compared with pancreatoduodenectomy, reference values for postoperative mortality were 3 times higher for LR-TP (≤2% vs ≤6%) and less for resected lymph nodes (≥16 vs ≥29). Conclusions and Relevance This case-control study provided global reference values for TP, indicating significantly higher postoperative morbidity and mortality compared with pancreatoduodenectomy. Perioperative morbidity of TP was especially increased in patients with vascular resections. These reference values can serve for quality control of pancreatic surgery.

Abstract BACKGROUND Mirdametinib is the first FDA-approved MEK1/2 inhibitor for both adults and children ≥2 years with NF1 who have symptomatic PN not amenable to complete resection. We report results from the phase 2b ReNeu trial (NCT03962543), including the LTFU. METHODS In ReNeu, mirdametinib was administered in 3-weeks-on/1-week-off 28-day cycles. Following the 24-cycle treatment phase, patients could continue mirdametinib in an optional LTFU. We report results through June 12, 2024, approximately 9 months from the previous data cutoff. RESULTS Fifty-eight adults and 56 children received mirdametinib. Median (range) duration of treatment was 21.8 (0.4, 54.4) months in adults and 25.4 (1.6, 48.5) months in children. Among LTFU-eligible patients, 26/31 (84%) adults and 32/37 (86%) children entered LTFU. Confirmed objective response rate (ORR, treatment+LTFU phases) was 47% (27/58; 95%CI, 33%, 60%) in adults and 55% (31/56; 95%CI, 42%, 69%) in children. Among confirmed responders, 18 adults and 19 children achieved a deep response (best target PN volume reduction from baseline of &gt;50%). Median (range) best percentage change from baseline in target PN volume was –41% (–90%, 13%) in adults and –43% (–98%, 48%) in children. Median duration of response (DoR) was not reached for either age cohort. Treatment-related adverse events (TRAEs) in ≥25% of patients were dermatitis acneiform, diarrhea, nausea, and vomiting in adults; and diarrhea, dermatitis acneiform, and paronychia in children. Grade ≥3 TRAEs occurred in 17% of adults and 25% of children. Dose interruptions, dose reductions, and discontinuations due to TRAEs occurred in 9%, 17%, and 22%, respectively, of adults, and 14%, 14%, and 9%, respectively, of children. CONCLUSIONS Improved confirmed ORR was observed with longer duration of mirdametinib, with additional deep responses achieved in both adults and children. Mirdametinib continued to be well tolerated with a manageable safety profile and no new safety signals in the LTFU.

Abstract BACKGROUND Mirdametinib is the first FDA-approved MEK1/2 inhibitor for both adults and children (≥2y) with symptomatic NF1-PN. In ReNeu, symptomatic improvement and PN volume reductions were observed at the earliest assessments (~91 and ~152 days, respectively) and were sustained. This analysis evaluated time to first onset and resolution of commonly reported TRAEs in the ReNeu trial. METHODS Data cutoff (DCO) was September 20, 2023. Median time to first onset and resolution (days) for common TRAEs (≥15%) were evaluated for prepubescents (≥2 to &lt;12y, n=32), postpubescents (≥12 to &lt;18y, n=24), younger adults (≥18 to ≤50y, n=48), and older adults (&gt;50y, n=10). RESULTS Common TRAEs were mostly grades 1 to 2 (83%). In prepubescents, median day (range) of onset was 32 (14, 263) for vomiting, 71 (19, 386) for dermatitis acneiform, 123 (1, 663) for diarrhea, 124 (52, 775) for paronychia, and 127 (2, 663) for nausea. For postpubescents, median day (range) of onset was 8 (1, 438) for diarrhea, 8 (2, 574) for nausea, 12 (1, 252) for dermatitis acneiform, 28 (2, 354) for vomiting, and 110 (43, 245) for paronychia. In younger adults, median day (range) of onset was 5 (1, 352) for nausea, 8 (2, 15) for dermatitis acneiform, 9 (2, 73) for diarrhea, and 29 (1, 264) for vomiting. For older adults, median day (range) of onset was 4 (1, 286) for diarrhea, 9 (2, 15) for nausea, and 13 (2, 38) for dermatitis acneiform. Time to resolution was variable between TRAEs and among patients in all age groups; 90% resolved completely by DCO. Among all patients, 18 had a TRAE of asymptomatic ejection fraction decrease, with all but one resolving by DCO. CONCLUSIONS Overall, common TRAEs arose before treatment benefits and were generally resoluble by DCO. Proactively managing TRAEs may improve treatment experience and adherence.

Background: Tricuspid regurgitation (TR) is associated with significant morbidity, but individualized treatment and timing of intervention are yet to be defined. We previously proposed and validated artificial intelligence electrocardiography (AI-ECG) scores for various diseases. Whether incorporating AI-ECG information adds to risk stratification above and beyond classical clinical parameters is unknown. Objectives: To identify AI-ECG scores independently associated with all-cause mortality in chronic TR and to create a composite AI-ECG risk score. Methods: Patients with a first echocardiographic diagnosis of ≥moderate TR between 2005-2016 and an ECG within ±15 days were included. The Tricuspid Regurgitation Impact on Outcome (TRIO) score was calculated as previously described based on 8 simple parameters (age, sex, severe TR, heart failure, lung disease, heart rate, creatinine and AST). AI-ECG probabilities of low ejection fraction, aortic stenosis, amyloid, cirrhosis, atrial fibrillation and hypertrophic cardiomyopathy were estimated by existing algorithms; the first 4 were associated with all-cause mortality and a composite AI-ECG risk score was calculated (0-4; 1 point for each AI-ECG above specific threshold). Results: A total of 12,377 pts were included (age 72±13 yrs, 55% women). Over a median follow-up of 1.3 yrs (IQR 0.1 to 4.4), 7,121 pts (58%) died. Mortality risk increased significantly with higher composite AI-ECG risk score (Fig. 1A). On multivariable analysis (proportional hazards method), the composite AI-ECG risk score remained independently associated with death, even after adjusting for age, sex, high NT-proBNP levels (>2,500 pg/mL), right ventricular systolic pressure (RVSP), diuretic use and TRIO risk score category (Fig. 1B). Conclusions: Patients with ≥moderate TR show progressively worse survival with increasing composite AI-ECG risk score. Incorporating AI-derived information from a simple and inexpensive ECG may identify patients with the highest risk of mortality beyond clinical risk scores as TRIO or classical clinical, laboratory and echocardiographic parameters. Prospective validation of this approach needs to be tested in future trials.