Recently, we reported the real-world effectiveness of palbociclib plus endocrine therapy (ET) in HR+/HER2– advanced breast cancer (ABC) in Japan (NCT05399329). However, median overall survival (OS) was not reached because of limited follow-up (36 months). Here, we present follow-up data from this study, including real-world clinical outcomes and treatment patterns. The P-BRIDGE study was a multi-center, observational study evaluating the real-world effectiveness and treatment patterns of patients diagnosed with HR+/HER2– ABC who received palbociclib plus ET in first (1L) or second line (2L) in Japan. The primary endpoint was real-world progression-free survival (rwPFS); secondary endpoints included OS and chemotherapy-free survival (CFS). Of the 693 eligible patients, 426 and 267 patients received palbociclib with ET as 1L and 2L treatment, respectively. After a median follow-up of 48.1 months, the median rwPFS (95
Idiopathic pulmonary fibrosis (IPF) is an intractable lung disease that belongs to idiopathic interstitial pneumonia (IIP) with limited therapeutic options. Conventional patient stratification approaches often fail to integrate diverse data modalities, particularly heterogeneous electronic medical records (EMR) containing mixed discrete and continuous values, with omics data, or fail to extract the interpretable many-to-many relationships crucial for precision medicine. We introduce subset binding (SB), a novel unsupervised algorithm that extends fuzzy association rule mining to robustly integrate heterogeneous clinical data (EMR) and omics data. This framework is uniquely designed to identify clinically meaningful patient subgroup patterns and discover associated molecular signatures based on observable symptoms rather than relying on ambiguous conventional diagnostic categories, such as IIPs. Applying SB to a dataset including 602 samples (from 403 IIPs including IPF patients and 39 healthy controls), we successfully identified 20 proteins linked with key IPF clinical features. Network-based pathway analysis nominated tyrosine kinases as critical drug target candidates, leading to the proposal of ponatinib, a multi-kinase inhibitor, as a candidate therapeutic. Functional validation using a TGF-β-induced epithelial-mesenchymal transition (EMT) model confirmed ponatinib's ability to at least partially suppress TGF-β-induced EMT. This inhibitory effect is consistent with the anti-fibrotic mechanism of the existing IPF drug, nintedanib, and reinforces prior evidence supporting ponatinib's anti-fibrotic property. This study demonstrates that SB enables transparent, reproducible, and robust, molecularly defined patient stratification from multimodal patient data. By establishing a data-driven framework that focuses on observation-based rules, this work lays the critical foundation for future prognostic validation and tailored treatment strategies, offering clinically actionable insights and therapeutic discovery in diagnostically ambiguous diseases like IPF, with ponatinib emerging as a compelling repurposing candidate. Significance statement Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with limited therapeutic options. IPF is classified as idiopathic interstitial pneumonia (IIP), but distinguishing it from other similar diseases in IIP is not straightforward. The ambiguities in distinguishing IPF from other IIPs necessitate the identification of molecules associated with specific clinical features, rather than relying on solely on diagnosis. Existing methods for multi-omics data analysis often fail to effectively integrate heterogeneous data - such as EMR (containing mixed discrete and continuous values) and omics - or to extract many-to-many molecular-phenotypic relationships. We developed subset binding (SB), a novel, interpretable unsupervised machine learning method to specifically address these technical limitations by integrating EMR and omics data. Our approach successfully detected proteins in serum extracellular vesicles associated with IPF-related features, highlighted several tyrosine kinases as potential drug targets, and proposed the multi-kinase inhibitor ponatinib as a compelling candidate for drug repurposing. This data-driven framework establishes a scalable and interpretable foundation for biomarker and drug target discovery for intractable diseases whose mechanisms are not fully understood.
INTRODUCTION:The severity of haemophilia A is classified by the degree of factor VIII (FVIII) deficiency, rather than by clinical manifestations. However, FVIII activity alone does not necessarily accurately reflect clinical severity such as bleeding tendency, and patients with mild-to-moderate haemophilia A can experience significant disease burden. AIM:This narrative review explores the clinical relevance of non-severe haemophilia A (focusing on moderate disease), and examines the profile of patients with, and the evidence supporting the use of prophylaxis to manage, this disease form. METHODS:A PubMed search was conducted (no language/date limits), using terms including 'hemophilia' or 'haemophilia', and 'moderate', 'nonsevere' or 'non-severe', with the names of prophylactic agents. RESULTS:Some patients with moderate haemophilia A experience significant disease burden (in terms of bleeding frequency and joint damage), diminished health-related quality of life and marked economic impact. In addition, variation in bleeding phenotype across disease severity levels has been recognised, such that patients with moderate disease may have a severe phenotype and experience more frequent spontaneous bleeds than those with a mild phenotype. Few studies have specifically assessed outcomes associated with prophylaxis in patients with moderate haemophilia A. However, available data suggest that prophylaxis with FVIII concentrates and non-factor treatments (i.e. emicizumab) provides beneficial effects in terms of bleeding frequency and joint health. CONCLUSION:Severity classification alone is insufficient to predict bleeding tendency, and joint bleeding and joint injury are observed in patients with moderate disease. As such, routine prophylaxis may be recommended for some patients with moderate haemophilia A.
Abstract Objective This study aimed to evaluate whether the preoperative FAN score—composed of the fibrosis‐4 (Fib‐4) index, albumin–bilirubin (ALBI) score and neutrophil–lymphocyte ratio (NLR)—predicts recurrence‐free, cancer‐specific and overall survival after radical cystectomy for bladder cancer. Patients and Methods We retrospectively analysed 1121 patients who underwent radical cystectomy at 13 institutions between April 2010 and March 2024. Associations between the FAN score and recurrence‐free survival (RFS), cancer‐specific survival (CSS) and overall survival (OS) were evaluated. Prognostic performance was assessed in an independent cohort of 296 patients from three institutions. Results FAN score distribution was 0 (n = 600, 53.5%), 1 (n = 409, 36.5%) and ≥2 (n = 112, 10.0%). Patients with a FAN score ≥2 had significantly worse RFS (median: not reached vs 12.3 months; p < 0.0001), CSS (not reached vs 22.8 months; p < 0.0001) and OS (112.5 vs 16.1 months; p < 0.0001) than those with a FAN score ≤1. On multivariable analysis, a FAN score ≥2 was an independent predictor of poorer RFS (HR 2.12, 95% CI 1.55–2.91; p < 0.0001), CSS (HR 2.80, 95% CI 2.00–3.92; p < 0.0001) and OS (HR 2.70, 95% CI 2.03–3.59; p < 0.0001). These associations were consistently observed in an independent cohort of 296 patients. Conclusions The FAN score is an independent prognostic marker of adverse outcomes after radical cystectomy for bladder cancer and may help stratify patients for perioperative management and follow‐up.
Abstract Background and aims Nonvalvular atrial fibrillation (NVAF) and Atherosclerotic cardiovascular disease (ASCVD) often coexist, yet whether clinical outcomes differ by sex in this population remains unclear. We evaluated sex differences in a post hoc analysis of ATIS-NVAF (Optimal Antithrombotic Therapy in Ischemic Stroke patients with Nonvalvular Atrial Fibrillation and atherothrombosis), a randomized trial of patients with recent ischemic stroke or transient ischemic attack (TIA), NVAF, and concomitant ASCVD. Methods We compared baseline characteristics and clinical outcomes by sex in a post hoc analysis of ATIS-NVAF. The primary outcome was the composite of cardiovascular death, ischemic stroke, myocardial infarction, systemic embolism, urgent revascularization for ischemia, or major bleeding within 2 years. Secondary outcomes were ischemic cardiovascular events; safety outcomes were major and clinically relevant non-major bleeding. We constructed a logistic regression model to estimate adjusted odds ratios (aORs) for women versus men. Results Of 222 patients, most were men (74.8%). Women were significantly older than men (median age, 79 [IQR 73.3–84] vs. 77 [71–81]; P=0.01). Regarding atherosclerotic disease, carotid artery stenosis was significantly less common in women (5/56 (8.9%) vs. 43/166 (25.9%); P=0.008), whereas intracranial artery stenosis was more frequent (24/56 (42.9%) vs. 47/166 (28.3%); P=0.04). The primary outcome was not significantly different between women and men (16.1% vs. 21.1%; aOR, 0.42; 95% CI, 0.16–1.10). There were no statistically significant differences in secondary outcomes or in safety outcomes. Conclusions There were no significant sex differences in the 2-year composite of cardiovascular and bleeding events. Conflict of interest Dr Uchida reports lecture fees from Daiichi Sankyo, Johnson & Johnson, Kaneka, Medtronic, Stryker, and Tokai Medical Products outside the submitted work. Dr. Yoshimura reports grants from Medico’s Hirata, Medtronic, and Terumo and lecture fees from Medtronic, Kaneka, Stryker, Daiichi Sankyo, Bristol-Meyers Squibb, and Johnson & Johnson outside the submitted work. Dr Koga reports lecture fees from Bayer Yakuhin, Boehringer Ingelheim, and Daiichi Sankyo and research funding from Boehringer Ingelheim and Daiichi Sankyo outside the submitted work. Dr Ihara reports lecturer fees from Daiichi Sankyo and Eisai and grant support from Panasonic, GE Precision Healthcare LLC, Bristol-Myers Squibb, and Shimadzu Corporation. Dr Yoshimoto reports personal fees from Eli Lilly, Daiichi Sankyo, Medico’s Hirata, Nippon Boehringer Ingelheim, Stryker, Takeda Pharmaceutical, and Tonbridge Medical. Dr Hirano reports lecture fees from Daiichi Sankyo and honoraria from Bayer Yakuhin outside the submitted work. Dr Toyoda reports personal fees from Janssen Pharmaceuticals, Otsuka Pharmaceutical, and SoftBank group outside the submitted work. Dr Sakai reports personal fees from Asahi Intecc, Kaneka, Medtronic, Stryker, and Terumo outside the submitted work. Dr Yamagami reported grants from Bristol Myers Squibb during the conduct of the study; lecture fees from Abbott Medical Japan, Boston Scientific Japan, Bristol Myers Squibb, Daiichi Sankyo, Medtronic, Otsuka Pharmaceutical, and Stryker outside the submitted work. No other disclosures were reported. Funding: Bristol Myers Squibb
