Nonlinear optimization for a low-emittance storage ring.

A multi-objective genetic algorithm (MOGA) is a powerful global optimization tool, but its results are considerably affected by the crossover parameter ηc. Finding an appropriate ηc demands too much computing time because MOGA needs be run several times in order to find a good ηc. In this paper, a self-adaptive crossover parameter is introduced in a strategy to adopt a new ηc for every generation while running MOGA. This new scheme has also been adopted for a multi-generation Gaussian process optimization (MGGPO) when producing trial solutions. Compared with the existing MGGPO and MOGA, the MGGPO and MOGA with the new strategy show better performance in nonlinear optimization for the design of low-emittance storage rings.

Discontinuation risk from adverse events: immunotherapy alone vs. combined with chemotherapy: a systematic review and network meta-analysis.

BACKGROUND: While immunotherapy combined with chemotherapy (Chemo-IO) is generally recognized for providing superior outcomes compared to monotherapy (mono-IO), it is associated with a higher incidence of treatment-related adverse events (TRAEs), which may lead to treatment discontinuation. In this study, we compared the rates of treatment discontinuation between mono-IO and Chemo-IO as first-line treatments for various solid tumors. METHODS: We systematically reviewed clinical trials from databases (PubMed, Embase, Cochrane Library, and an additional source) published from January 1, 2018, to July 10, 2023. We included phase III randomized controlled trials (RCTs) that utilized immunotherapy agents in at least one arm as first-line treatments for a variety of solid tumors. Data extraction followed the Preferred Reporting Items for Systematic Reviews (PRISMA) extension statement for network meta-analysis. A random effects model was used for the network meta-analysis, with the risk of bias assessed using the Cochrane risk-of-bias tool II. The primary outcomes encompassed treatment discontinuation rates due to TRAEs among patients who underwent immunotherapy, either alone or combined with chemotherapy, for various solid tumors. Pooled relative risks (RRs) with 95% confidence intervals (CIs) were calculated to compare between treatment groups. RESULTS: From 29 RCTs, a total of 21,677 patients and 5 types of treatment were analyzed. Compared to mono-IO, Chemo-IO showed a significantly higher rate of discontinuation due to TRAEs (RR 2.68, 95% CI 1.98-3.63). Subgroup analysis for non-small cell lung cancer (NSCLC) patients also exhibited a greater risk of discontinuation due to TRAEs with Chemo-IO compared to mono-IO (RR 2.93, 95% CI 1.67-5.14). Additional analyses evaluating discontinuation rates due to either treatment emergent adverse events (TEAEs) or AEs regardless of causality (any AEs) consistently revealed an elevated risk associated with Chemo-IO. CONCLUSIONS: Chemo-IO was associated with an elevated risk of treatment discontinuation not only due to TRAEs but also any AEs or TEAEs. Given that the treatment duration can impact clinical outcomes, a subset of patients might benefit more from mono-IO than combination therapy. Further research is imperative to identify and characterize this subset.

Congruent Concavity Restoration of the Reconstructed Glenoid After the Latarjet Procedure: Compensation for the Position of the Graft.

BACKGROUND: Few clinical studies have addressed concavity restoration by natural remodeling after a Latarjet procedure. This study investigated the fibrous tissue and osseous remodeling of the reconstructed glenoid and concavity restoration after a Latarjet procedure using postoperative computed tomographic arthrography (CTA). METHODS: This retrospective study included 31 patients who underwent immediate postoperative computed tomographic (CT) scanning followed by CTA at 6 months postoperatively. We investigated whether fibrous tissue was newly created over the graft, whether the created fibrous tissue restored the congruity of the articular surface and the osseous remodeling of the graft to the glenoid level (whether the osseous portion of the graft was remodeled flush to the glenoid level) and the concavity of the glenoid using the radius of a best-fit circle on the articular surface, and the relationship between the amount of created fibrous tissue and the position of the graft. RESULTS: In all patients, the fibrous tissue on the graft yielded a smooth articular surface, as revealed by the CTA. The mean radius of the entire glenoid, including the transferred graft, was significantly smaller (p = 0.010) at 33.2 ± 8.5 mm than that of the glenoid posterior to the osseous step-off at 37.6 ± 9.4 mm, which is presumed to be the glenoid before the surgical procedure. Despite the congruity of the articular surfaces due to fibrous tissue seen in the CTA, 14 (45%) of 31 patients showed a subchondral osseous step-off on either the medial side or the lateral side in the immediate postoperative CT scans. However, through osseous remodeling, 8 of the 10 grafts with a lateral step-off and 2 of the 4 grafts with a medial step-off converted to a flush position. The position of the step-off was correlated with the thickness of the fibrous tissue, with a tendency for thicker tissue in cases of a step-off on the medial side (p = 0.014). CONCLUSIONS: Fibrous tissue formation plus remodeling of the transferred graft resulted in the restoration of a congruent concavity after a Latarjet procedure by compensating for initially non-flush positioning of the graft. However, due to the small sample size in our study, clinical outcomes could not be correlated with radiographic findings, and our recommendation is to continue placing the graft as anatomically as possible. LEVEL OF EVIDENCE: Therapeutic Level IV . See Instructions for Authors for a complete description of levels of evidence.

Reduced toxicity (FluBu3) versus myeloablative (BuCy) conditioning in acute myeloid leukemia patients who received first allogeneic hematopoietic stem cell transplantation in measurable residual disease-negative CR1.

In the present study, reduced toxicity (FluBu3) and myeloablative (BuCy) conditioning were compared in patients with AML who received first allogeneic HSCT in MRD-negative CR1. The study included 124 adult patients who underwent HSCT from an HLA-matched (8/8) sibling, unrelated, or 1-locus mismatched (7/8) unrelated donor (MMUD). The median age was 45 years and intermediate cytogenetics comprised majority (71.8%). The 2-year OS, RFS, CIR and NRM for BuCy (n = 78, 62.9%) and FluBu3 (n = 46, 37.1%) groups were 78.3% and 84.5% (p = 0.358), 78.0% and 76.3% (p = 0.806), 7.7% and 21.5% (p = 0.074) and 14.3% and 2.2% (p = 0.032), respectively. At the time of data cut-off, relapse and NRM were the main causes of HSCT failure in each of the FluBu3 and BuCy arms. Among patients, 75% of relapsed FluBu3 patients had high-risk features of either poor cytogenetics or FLT3-ITD mutation compared with 16.7% of BuCy patients. The majority of NRM in the BuCy group was due to GVHD (73%), half of whom received MMUD transplantation. To conclude, the FluBu3 reduced toxicity conditioning showed comparable post-transplant OS and RFS to BuCy and was associated with significantly reduced NRM that was offset by a trend towards higher risk of relapse even in MRD-negative CR1 population.

Inflamed immune phenotype predicts favorable clinical outcomes of immune checkpoint inhibitor therapy across multiple cancer types.

BACKGROUND: The inflamed immune phenotype (IIP), defined by enrichment of tumor-infiltrating lymphocytes (TILs) within intratumoral areas, is a promising tumor-agnostic biomarker of response to immune checkpoint inhibitor (ICI) therapy. However, it is challenging to define the IIP in an objective and reproducible manner during manual histopathologic examination. Here, we investigate artificial intelligence (AI)-based immune phenotypes capable of predicting ICI clinical outcomes in multiple solid tumor types. METHODS: Lunit SCOPE IO is a deep learning model which determines the immune phenotype of the tumor microenvironment based on TIL analysis. We evaluated the correlation between the IIP and ICI treatment outcomes in terms of objective response rates (ORR), progression-free survival (PFS), and overall survival (OS) in a cohort of 1,806 ICI-treated patients representing over 27 solid tumor types retrospectively collected from multiple institutions. RESULTS: We observed an overall IIP prevalence of 35.2% and significantly more favorable ORRs (26.3% vs 15.8%), PFS (median 5.3 vs 3.1 months, HR 0.68, 95% CI 0.61 to 0.76), and OS (median 25.3 vs 13.6 months, HR 0.66, 95% CI 0.57 to 0.75) after ICI therapy in IIP compared with non-IIP patients, respectively (p<0.001 for all comparisons). On subgroup analysis, the IIP was generally prognostic of favorable PFS across major patient subgroups, with the exception of the microsatellite unstable/mismatch repair deficient subgroup. CONCLUSION: The AI-based IIP may represent a practical, affordable, clinically actionable, and tumor-agnostic biomarker prognostic of ICI therapy response across diverse tumor types.