Citations

Gemcitabine plus docetaxel is an effective treatment regimen for advanced soft tissue sarcomas (STSs). However, the prognosis for patients remains poor, and thus there is an urgent medical need for novel and effective therapies to improve long-term outcomes. The aim of the ANNOUNCE 2 trial was to explore the addition of olaratumab (O) to gemcitabine (G) and docetaxel (D) for advanced STS. Adults with unresectable locally advanced/metastatic STS, ≤2 prior lines of systemic therapy, and ECOG PS 0–1 were eligible. In Phase 2, patients were randomized 1:1 from two cohorts (O-naïve and O-pretreated) to 21-day cycles of olaratumab (20 mg/kg Cycle 1 and 15 mg/kg other cycles, Days 1 and 8), gemcitabine (900 mg/m2, Days 1 and 8), and docetaxel (75 mg/m2, Day 8). The primary objective was overall survival (OS) in the O-naïve population (α level = 0.20). Secondary endpoints included OS (O-pretreated), other efficacy parameters, patient-reported outcomes, safety, pharmacokinetics, and immunogenicity. A total of 167 and 89 patients were enrolled in the O-naïve and O-pretreated cohorts, respectively. Baseline patient characteristics were well balanced. No statistically significant difference in OS was observed between the investigational vs. control arm for either cohort (O-naïve cohort: HR = 0.95 (95% CI: 0.64−1.40), p = 0.78, median OS, 16.8 vs. 18.0 months; O-pretreated cohort: HR = 0.67 (95% CI: 0.39−1.16), p = 0.15, median OS 19.8 vs. 17.3 months). Safety was manageable across treatment arms. There was no statistically significant difference in the primary endpoint of OS between the two arms in the O-naïve population, and therefore based on hierarchical evaluation no other outcomes in this study can be considered statistically significant. No new safety signals were observed.

Importance Transthyretin gene silencing is an emerging treatment strategy for hereditary transthyretin (ATTRv) amyloidosis. Objective To evaluate eplontersen, an investigational ligand-conjugated antisense oligonucleotide, in ATTRv polyneuropathy. Design, Setting, and Participants NEURO-TTRansform was an open-label, single-group, phase 3 trial conducted at 40 sites across 15 countries (December 2019-April 2023) in 168 adults with Coutinho stage 1 or 2 ATTRv polyneuropathy, Neuropathy Impairment Score 10-130, and a documented TTR variant. Patients treated with placebo from NEURO-TTR ( NCT01737398 ; March 2013–November 2017), an inotersen trial with similar eligibility criteria and end points, served as a historical placebo (“placebo”) group. Interventions Subcutaneous eplontersen (45 mg every 4 weeks; n = 144); a small reference group received subcutaneous inotersen (300 mg weekly; n = 24); subcutaneous placebo weekly (in NEURO-TTR; n = 60). Main Outcomes and Measures Primary efficacy end points at week 65/66 were changes from baseline in serum transthyretin concentration, modified Neuropathy Impairment Score +7 (mNIS+7) composite score (scoring range, –22.3 to 346.3; higher scores indicate poorer function), and Norfolk Quality of Life Questionnaire–Diabetic Neuropathy (Norfolk QoL-DN) total score (scoring range, –4 to 136; higher scores indicate poorer quality of life). Analyses of efficacy end points were based on a mixed-effects model with repeated measures adjusted by propensity score weights. Results Among 144 eplontersen-treated patients (mean age, 53.0 years; 69% male), 136 (94.4%) completed week-66 follow-up; among 60 placebo patients (mean age, 59.5 years; 68% male), 52 (86.7%) completed week-66 follow-up. At week 65, adjusted mean percentage reduction in serum transthyretin was −81.7% with eplontersen and −11.2% with placebo (difference, −70.4% [95% CI, −75.2% to −65.7%]; P < .001). Adjusted mean change from baseline to week 66 was lower (better) with eplontersen vs placebo for mNIS+7 composite score (0.3 vs 25.1; difference, −24.8 [95% CI, −31.0 to −18.6; P < .001) and for Norfolk QoL-DN (−5.5 vs 14.2; difference, −19.7 [95% CI, −25.6 to −13.8]; P < .001). Adverse events by week 66 that led to study drug discontinuation occurred in 6 patients (4%) in the eplontersen group vs 2 (3%) in the placebo group. Through week 66, there were 2 deaths in the eplontersen group consistent with known disease-related sequelae (cardiac arrhythmia; intracerebral hemorrhage); there were no deaths in the placebo group. Conclusions and Relevance In patients with ATTRv polyneuropathy, the eplontersen treatment group demonstrated changes consistent with significantly lowered serum transthyretin concentration, less neuropathy impairment, and better quality of life compared with a historical placebo. Trial Registration ClinicalTrials.gov Identifier: NCT04136184 ; EU Clinical Trials Register: EudraCT 2019-001698-10

Abstract Background Native vertebral osteomyelitis (NVO) caused by Staphylococcus aureus is associated with high risk of treatment failure and increased morbidity. The role of rifampin-based therapy for the treatment of this condition is controversial. The goal of this systematic review and meta-analysis is to explore the efficacy and safety of rifampin-based therapy for the treatment of S. aureus NVO. Methods We searched Cochrane, Embase, Medline, Scopus, and Web of Science databases for studies published up to May 2023, focusing on adults with NVO treated with or without rifampin-containing regimens. A random-effects model meta-analysis estimated relative risks and risk difference with 95% confidence intervals (CI). Results Thirteen studies (2 randomized controlled trials and 11 comparative cohort studies), comprising 244 patients with S. aureus NVO who received rifampin and 435 who did not, were analyzed. Meta-analysis showed that rifampin-based regimens were associated with lower risk of clinical failure (risk difference, −14%; 95% CI, −19% to −8%; P < .001; I 2 = 0%; relative risk, 0.58; 95% CI, .37–.92, P = .02, I 2 = 21%). Only 1 study reported on adverse events. All studies had a high or uncertain risk of bias, and the certainty of evidence was rated as very low. Conclusions Adjunctive rifampin therapy might be associated with lower risk of S. aureus NVO treatment failure; however, the low certainty of evidence precludes drawing definitive conclusions that would alter clinical practice. A randomized trial is necessary to corroborate these findings.

ABSTRACT Aims Takotsubo syndrome (TTS) is associated with a substantial rate of adverse events. We sought to design a machine learning (ML)-based model to predict the risk of in-hospital death and to perform a clustering of TTS patients to identify different risk profiles. Methods and results A ridge logistic regression-based ML model for predicting in-hospital death was developed on 3482 TTS patients from the International Takotsubo (InterTAK) Registry, randomly split in a train and an internal validation cohort (75% and 25% of the sample size, respectively) and evaluated in an external validation cohort (1037 patients). Thirty-one clinically relevant variables were included in the prediction model. Model performance represented the primary endpoint and was assessed according to area under the curve (AUC), sensitivity and specificity. As secondary endpoint, a K-medoids clustering algorithm was designed to stratify patients into phenotypic groups based on the 10 most relevant features emerging from the main model. The overall incidence of in-hospital death was 5.2%. The InterTAK-ML model showed an AUC of 0.89 (0.85–0.92), a sensitivity of 0.85 (0.78–0.95) and a specificity of 0.76 (0.74–0.79) in the internal validation cohort and an AUC of 0.82 (0.73–0.91), a sensitivity of 0.74 (0.61–0.87) and a specificity of 0.79 (0.77–0.81) in the external cohort for in-hospital death prediction. By exploiting the 10 variables showing the highest feature importance, TTS patients were clustered into six groups associated with different risks of in-hospital death (28.8% vs. 15.5% vs. 5.4% vs. 1.0.8% vs. 0.5%) which were consistent also in the external cohort. Conclusion A ML-based approach for the identification of TTS patients at risk of adverse short-term prognosis is feasible and effective. The InterTAK-ML model showed unprecedented discriminative capability for the prediction of in-hospital death.

PURPOSE The investigation of multiple molecular targets with next-generation sequencing (NGS) has entered clinical practice in oncology, yielding to a paradigm shift from the histology-centric approach to the mutational model for personalized treatment. Accordingly, most of the drugs recently approved in oncology are coupled to specific biomarkers. One potential tool for implementing the mutational model of precision oncology in daily practice is represented by the Molecular Tumor Board (MTB), a multidisciplinary team whereby molecular pathologists, biologists, bioinformaticians, geneticists, medical oncologists, and pharmacists cooperate to generate, interpret, and match molecular data with personalized treatments. PATIENTS AND METHODS Since May 2020, the institutional MTB set at Fondazione IRCCS Istituto Nazionale Tumori of Milan met weekly via teleconference to discuss molecular data and potential therapeutic options for patients with advanced/metastatic solid tumors. RESULTS Up to October 2021, among 1,996 patients evaluated, we identified >10,000 variants, 43.2% of which were functionally relevant (pathogenic or likely pathogenic). On the basis of functionally relevant variants, 711 patients (35.6%) were potentially eligible to targeted therapy according to European Society of Medical Oncology Scale for Clinical Actionability of Molecular Targets tiers, and 9.4% received a personalized treatment. Overall, larger NGS panels (containing >50 genes) significantly outperformed small panels (up to 50 genes) in detecting actionable gene targets across different tumor types. CONCLUSION Our real-world data provide evidence that MTB is a valuable tool for matching NGS data with targeted treatments, eventually implementing precision oncology in clinical practice.

Objective: This study aims at establishing benchmark values for best achievable outcomes following open major anatomic hepatectomy for liver tumors of all dignities. Background: Outcomes after open major hepatectomies vary widely lacking reference values for comparisons among centers, indications, types of resections, and minimally invasive procedures. Methods: A standard benchmark methodology was used covering consecutive patients, who underwent open major anatomic hepatectomy from 44 high-volume liver centers from 5 continents over a 5-year period (2016–2020). Benchmark cases were low-risk non-cirrhotic patients without significant comorbidities treated in high-volume centers (≥30 major liver resections/year). Benchmark values were set at the 75th percentile of median values of all centers. Minimum follow-up period was 1 year in each patient. Results: Of 8044 patients, 2908 (36%) qualified as benchmark (low-risk) cases. Benchmark cutoffs for all indications include R0 resection ≥78%; liver failure (grade B/C) ≤10%; bile leak (grade B/C) ≤18%; complications ≥grade 3 and CCI ® ≤46% and ≤9 at 3 months, respectively. Benchmark values differed significantly between malignant and benign conditions so that reference values must be adjusted accordingly. Extended right hepatectomy (H1, 4-8 or H4-8) disclosed a higher cutoff for liver failure, while extended left (H1-5,8 or H2-5,8) were associated with higher cutoffs for bile leaks, but had superior oncologic outcomes, when compared to formal left hepatectomy (H1-4 or H2-4). The minimal follow-up for a conclusive outcome evaluation following open anatomic major resection must be 3 months. Conclusion: These new benchmark cutoffs for open major hepatectomy provide a powerful tool to convincingly evaluate other approaches including parenchymal-sparing procedures, laparoscopic/robotic approaches, and alternative treatments, such as ablation therapy, irradiation, or novel chemotherapy regimens.

Abstract Purpose: Microsatellite instability (MSI) is currently the only predictive biomarker of efficacy of immune checkpoint inhibitors (ICI) in metastatic colorectal cancers (mCRC). However, 10% to 40% of patients with MSI mCRC will experience a primary resistance to ICI. Experimental Design: In two cohorts of patients with MSI mCRC treated with ICI (exploratory, N = 103; validation, N = 35), 3′ RNA sequencing was performed from primary tumors. Previously described single-cell transcriptomic signatures of tumor microenvironment (TME) were analyzed. Results: In the exploratory cohort, the unsupervised clustering allowed the identification of three clusters of tumors with distinct transcriptional profiles: cluster A (“stromalHIGH-proliferationLOW”), cluster B (“stromalHIGH-proliferationMED”), and cluster C (“stromalLOW-proliferationHIGH”), with an enrichment of patients progressing at first disease assessment under ICI in cluster A (30% vs. 12% in cluster B and 8.1% in cluster C; P = 0.074). Progression-free survival (PFS) was also significantly shorter in patients belonging to cluster A, compared with clusters B or C (P < 0.001) with 2-year PFS rates of 33.5%, 80.5%, and 78.3%, respectively. In multivariate analysis, PFS was still significantly longer in patients belonging to cluster B [HR, 0.19; 95% confidence interval (CI), 0.08–0.45; P < 0.001] and cluster C (HR, 0.25; 95% CI, 0.10–0.59; P = 0.02), compared with patients belonging to cluster A. The association of this clustering with PFS under ICI was confirmed in the validation cohort. PFS related to non–ICI-based regimens was not significantly different according to cluster. Conclusions: This unsupervised transcriptomic classification identified three groups of MSI mCRCs with different compositions of TME cells and proliferative capacities of TME/tumor cells. The “stromalHIGH-proliferationLOW” cluster is associated with a poorer prognosis with ICI treatment.