Clinical Subgroups Research Articles

A proliferation-inducing ligand (APRIL) level among risk factors of ocular involvement in patients with Behçet’s disease

IntroductionOcular involvement is quite common in Behçet’s disease (BD) and may cause crucial functional complications. Even though the mechanisms of BD remain unclear, advances in gene­tic and immunological fields have improved our understanding of the immunopathogenesis of BD ocular involvement. Little is known about the expression of a proliferation-inducing ligand (APRIL) in terms of ocular involvement in BD. The objective of this study was to determine whether serum APRIL concentrations are associated with ocular involvement in patients with BD.Material and methodsThe study included 60 patients diagnosed with BD matched by age and sex to 30 healthy individuals. Every patient underwent a clinical evaluation, and the Behçet’s Disease Current Activity Form (BDCAF) was utilized to quantify disease activity. All patients underwent a comprehensive ophthalmological assessment. Serum APRIL was assessed for patients as well as controls.ResultsOne or more ocular manifestations were found in 42 BD patients (70%), while 18 patients (30%) had no ocular involvement. The mean level of serum APRIL levels was markedly elevated in BD patients, particularly those with ocular involvement, compared to both BD patients without ocular involvement and healthy individuals. A statistically significant association was determined between high APRIL concentration and development of uveitis, cataract, and hypopyon. Cutaneous lesions and arthritis were strong independent predictors for ocular involvement in BD patients.ConclusionsOverexpression of APRIL in patients with BD, particularly in terms of uveitis, cataract, and hypopyon, lends credence to the idea that B cell activating factors have an important function in BD. These findings may indicate that serum APRIL concentrations can differentiate a clinical subgroup of BD patients with ocular disease. As a result, finding a new therapeutic strategy targeting the APRIL pathway might be beneficial in BD patients suffering from ocular involvement.

Formal Thought Disorders and Neurocognition in Treatment-Resistant Schizophrenia: Trouble du cours de la pensée et neurocognition dans la schizophrénie réfractaire.

Formal thought disorders (FTDs), a core feature of schizophrenia, have been subdivided into positive and negative types, and are clinically assessed by examining speech (objective) or patient introspection (subjective). Despite being associated with poorer treatment response and worse outcomes, FTDs have been understudied in patients with schizophrenia, in particular treatment-resistant schizophrenia (TRS) or schizoaffective disorder. We aimed to explore the relationship between the severity of positive and negative FTDs and neurocognition as well as social/occupational functioning in this clinical subgroup. This was a retrospective chart review conducted at the Clozapine Clinic at the Centre for Addiction and Mental Health, Toronto, Canada. We reviewed charted standardized assessment of FTDs using the Thought and Language Disorder (TALD) scale, neurocognition using the Brief Cognitive Assessment Tool for Schizophrenia (B-CATS), and functioning using the Social and Occupational Functioning Assessment Scale (SOFAS) between October 2022 and June 2023. Following the original factor structure of the TALD, we computed 4- factor scores that combined positive or negative and objective or subjective FTDs. We then explored the correlation between the scores from each TALD factor and the neurocognition and functioning scores. We analysed data for 23 outpatients on clozapine. After the Bonferroni adjustment, total TALD scores, indicating overall severity of FTDs, were strongly and inversely correlated with SOFAS scores (p < 0.001). A strong inverse correlation was found between the objective positive TALD factor and Letter-Number Span verbal working memory scores, r(21) = -0.63, p < 0.001. Our results demonstrate the strong relationship between FTDs, neurocognition, and social/occupational functioning in a sample of TRS outpatients. Within the cognitive domains assessed, verbal working memory impairment had the strongest correlation with positive FTDs, such as derailment or tangentiality. These findings highlight the value of employing standardized psychopathological scales for FTDs in clinical practice.

The R.O.A.D. to precision medicine

We propose a novel framework that addresses the deficiencies of Randomized clinical trial data subgroup analysis while it transforms ObservAtional Data to be used as if they were randomized, thus paving the road for precision medicine. Our approach counters the effects of unobserved confounding in observational data through a two-step process that adjusts predicted outcomes under treatment. These adjusted predictions train decision trees, optimizing treatment assignments for patient subgroups based on their characteristics, enabling intuitive treatment recommendations. Implementing this framework on gastrointestinal stromal tumors (GIST) data, including genetic sub-cohorts, showed that our tree recommendations outperformed current guidelines in an external cohort. Furthermore, we extended the application of this framework to RCT data from patients with extremity sarcomas. Despite initial trial indications of universal treatment necessity, our framework identified a subset of patients who may not require treatment. Once again, we successfully validated our recommendations in an external cohort.

Toward understanding autism heterogeneity: Identifying clinical subgroups and neuroanatomical deviations.

Autism spectrum disorder ("autism") is a neurodevelopmental condition characterized by substantial behavioral and neuroanatomical heterogeneity. This poses significant challenges to understanding its neurobiological mechanisms and developing effective interventions. Identifying phenotypically more homogeneous subgroups and shifting the focus from average group differences to individuals is a promising approach to addressing heterogeneity. In the present study, we aimed to parse clinical and neuroanatomical heterogeneity in autism by combining clustering of clinical features with normative modeling based on neuroanatomical measures (cortical thickness [CT] and subcortical volume) within the Autism Brain Imaging Data Exchange data sets (N autism = 861, N nonautistic individuals [N NAI] = 886, age range = 5-64). First, model-based clustering was applied to autistic symptoms as measured by the Autism Diagnostic Observation Schedule to identify clinical subgroups of autism (N autism = 499). Next, we ran normative modeling on CT and subcortical parcellations (N autism = 690, N NAI = 744) and examined whether clinical subgrouping resulted in increased neurobiological homogeneity within the subgroups compared to the entire autism group by comparing their spatial overlap of neuroanatomical deviations. We further investigated whether the identified subgroups improved the accuracy of autism classification based on the neuroanatomical deviations using supervised machine learning with cross-validation. Results yielded two clinical subgroups primarily differing in restrictive and repetitive behaviors (RRBs). Both subgroups showed increased homogeneity in localized deviations with the high-RRB subgroup showing increased volume deviations in the cerebellum and the low-RRB subgroup showing decreased CT deviations predominantly in the postcentral gyrus and fusiform cortex. Nevertheless, substantial within-group heterogeneity remained highlighted by the lack of improvement of the classifier's performance when distinguishing between the subgroups and NAI. Future research should aim to further reduce heterogeneity incorporating additional neuroanatomical clustering in even larger samples. This will eventually pave the way for more tailored behavioral interventions and improving clinical outcomes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

HERC5: a comprehensive in silico analysis of its diagnostic, prognostic, and therapeutic potential in cancer.

HERC5, a vital protein in the HERC family, plays crucial roles in immune response, cancer progression, and antiviral defense. This bioinformatic study comprehensively assessed HERC5's significance across various malignancies by analyzing its gene expression, immune and molecular subtype expressions, target proteins, biological functions, and prognostic and diagnostic values in pan-cancer. We further examined its correlation with clinical features, co-expressed and differentially expressed genes, and prognosis in clinical subgroups, focusing on endometrial cancer (UCEC). Our findings showed that HERC5 RNA is expressed at low levels in most cancers and significantly differs across immune and molecular subtypes. HERC5 accurately predicts cancer and correlates with most cancer prognoses. In UCEC, HERC5 was significantly associated with age, hormonal status, clinical stage, treatment status, and metastasis. Elevated HERC5 expression was linked to worse progression-free interval, disease-specific survival, and overall survival in UCEC, particularly in diverse clinical subgroups. Significant differences in HERC5 expression were also observed in various human cancer cell line validations. In summary, HERC5 may be a critical biomarker for pan-cancer prognosis, progression, and diagnosis, as well as a promising new target for cancer therapy.

Integrated omics profiling reveals systemic dysregulation and potential biomarkers in the blood of patients with neuromyelitis optica spectrum disorders

BackgroundNeuromyelitis optica spectrum disorders (NMOSD) are autoimmune conditions that affect the central nervous system. The contribution of peripheral abnormalities to the disease's pathogenesis is not well understood.MethodsTo investigate this, we employed a multi-omics approach analyzing blood samples from 52 NMOSD patients and 46 healthy controls (HC). This included mass cytometry, cytokine arrays, and targeted metabolomics. We then analyzed the peripheral changes of NMOSD, and features related to NMOSD's disease severity. Furthermore, an integrative analysis was conducted to identify the distinguishing characteristics of NMOSD from HC. Additionally, we unveiled the variations in peripheral features among different clinical subgroups within NMOSD. An independent cohort of 40 individuals with NMOSD was utilized to assess the serum levels of fibroblast activation protein alpha (FAP).ResultsOur analysis revealed a distinct peripheral immune and metabolic signature in NMOSD patients. This signature is characterized by an increase in monocytes and a decrease in regulatory T cells, dendritic cells, natural killer cells, and various T cell subsets. Additionally, we found elevated levels of inflammatory cytokines and reduced levels of tissue-repair cytokines. Metabolic changes were also evident, with higher levels of bile acids, lactates, triglycerides, and lower levels of dehydroepiandrosterone sulfate, homoarginine, octadecadienoic acid (FA[18:2]), and sphingolipids. We identified distinctive biomarkers differentiating NMOSD from HC and found blood factors correlating with disease severity. Among these, fibroblast activation protein alpha (FAP) was a notable marker of disease progression.ConclusionsOur comprehensive blood profile analysis offers new insights into NMOSD pathophysiology, revealing significant peripheral immune and metabolic alterations. This work lays the groundwork for future biomarker identification and mechanistic studies in NMOSD, highlighting the potential of FAP as a marker of disease progression.

From deconstruction to reconstruction: A search for natural kinds in developmental psychopathology.

A "natural kind" is a specific classification that identifies some structure of truth and reality, a delimited entity. Psychiatric disorders are not natural kinds. As one moves from physics and chemistry to biology and medicine, natural kinds degrade, and the boundaries of differentiating phenomena become less clear. Within psychiatry, the categorization of psychopathology has further ontological challenges, especially across development. We suggest that to identify and isolate clinical subgroups, it is critical to integrate external validators in an iterative process, with the goal of linking classification to treatments with maximal clinical benefit. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Association between platelet-to-high-density lipoprotein cholesterol ratio and cognitive function in older americans: insights from a cross-sectional study

The main aim of this study was to explore the correlation between the platelet/high-density lipoprotein cholesterol ratio (PHR) and cognitive function in elderly individuals from the United States. This investigation leveraged data encompassing 2299 participants, all aged 60 years and above, from the National Health and Nutrition Examination Survey conducted from 2011 to 2014. Inclusion criteria were based on the availability of complete datasets for PHR and cognitive function assessments. The analytical approach incorporated multivariate logistic regression to discern the association between PHR and cognitive function. Additionally, the study employed restricted cubic splines (RCS) to explore potential non-linear relationships and subgroup analyses to identify variations in the observed associations across different demographic and clinical subgroups. In the fully adjusted model, an increment of 10 units in PHR was associated with a decline of 0.014 in cognitive scores (β=-0.014, 95% CI: -0.025, -0.002; P < 0.05). Compared to the lowest quartile, participants in the highest quartile exhibited a 38.4% increased prevalence of cognitive impairment per one-unit increase in PHR (OR = 1.384, 95% CI: 1.012, 1.893; P < 0.05). Subgroup analysis revealed consistent results regarding the relationship between PHR and cognitive impairment across all subgroups. A non-linear relationship between PHR and cognitive impairment was observed using RCS, indicating that an increase in PHR above 111.49 significantly elevated the incidence of cognitive impairment (P < 0.05). Our study demonstrates that a higher PHR is associated with a greater risk of cognitive decline in an older U.S. population, and although further validation is needed, this warrants consideration in clinical assessments and interventions.

The severity of metabolic derangement predicts survival of out-of-hospital cardiac arrest and the benefit of extracorporeal life support

Abstract Aims This study aimed to develop Metabolic Derangement score and validate its prognostic performance in patients with out-of-Hospital Cardiac Arrest (OHCA) and also its discriminative performance in guiding the application of extracorporeal life support (ECLS). Methods and Results From 5,100 patients (average age 67 years, 69% male), Metabolic Derangement score was developed to predict primary outcome (death or poor neurologic outcome, cerebral performance category ≥ 3 at day 30) from initial blood laboratory test including pH, PaCO2, PaO2, potassium, haemoglobin, lactate, and creatinine. It was created using machine learning algorithms and a training set (60%), and validated with a test set (40%). The risk of primary outcome consistently increased from 34% to 100% as the Metabolic Derangement score ranged from 0 to 7. Patients with Metabolic Derangement score ≤ 2 showed no difference in the primary outcome risk between those with or without ECLS. Conversely, those with a Metabolic Derangement score ≥3 had a lower risk with ECLS (difference of restricted mean survival time=6.5 days, 95% CI=3.3-9.6 days, ratio of restricted mean time lost=0.76, 95%CI=0.65-0.88, all p&amp;lt;0.001). Clinical subgroup analyses showed generally consistent results. Metabolic Derangement score also outperformed OHCA-, CAHP-, and NULL-PLEASE-scores in prediction the primary outcome (p&amp;lt;0.05, all). Conclusions The severity of metabolic derangement predicted the clinical outcome of OHCA, and could also identify patients likely to benefit from ECLS.Metabolic Derangement score

Modeling a biofluid-derived extracellular vesicle surface signature to differentiate pediatric idiopathic nephrotic syndrome clinical subgroups

Idiopathic Nephrotic Syndrome (INS) is a common childhood glomerular disease requiring intense immunosuppressive drug treatments. Prediction of treatment response and the occurrence of relapses remains challenging. Biofluid-derived extracellular vesicles (EVs) may serve as novel liquid biopsies for INS classification and monitoring. Our cohort was composed of 105 INS children at different clinical time points (onset, relapse, and persistent proteinuria, remission, respectively), and 19 healthy controls. The expression of 37 surface EV surface markers was evaluated by flow cytometry in serum (n = 83) and urine (n = 74) from INS children (mean age = 10.1, 58% males) at different time points. Urine EVs (n = 7) and serum EVs (n = 11) from age-matched healthy children (mean age = 7.8, 94% males) were also analyzed. Tetraspanin expression in urine EVs was enhanced during active disease phase in respect to the remission group and positively correlates with proteinuria levels. Unsupervised clustering analysis identified an INS signature of 8 markers related to immunity and angiogenesis/adhesion processes. The CD41b, CD29, and CD105 showed the best diagnostic scores separating the INS active phase from the healthy condition. Interestingly, combining urinary and serum EV markers from the same patient improved the precision of clinical staging separation. Three urinary biomarkers (CD19, CD44, and CD8) were able to classify INS based on steroid sensitivity. Biofluid EVs offer a non-invasive tool for INS clinical subclassification and “personalized” interventions.

Identification of Severe Acute Exacerbations of Chronic Obstructive Pulmonary Disease Subgroups by Machine Learning Implementation in Electronic Health Records.

Acute exacerbations of COPD (AECOPD) are heterogeneous. Machine learning (ML) has previously been used to dissect some of the heterogeneity in COPD. The widespread adoption of electronic health records (EHRs) has led to the rapid accumulation of large amounts of patient data as part of routine clinical care. However, it is unclear whether the implementation of ML in EHR-derived data has the potential to identify subgroups of AECOPD. Determine whether ML implementation using EHR data from severe AECOPD requiring hospitalization identifies relevant subgroups. This study used two retrospective cohorts of patients with AECOPD (non-COVID-19 and COVID-19) treated at Yale-New Haven Hospital (YNHHS). K-means clustering was used to identify patient subgroups. We identified three subgroups in the non-COVID cohort (n=1,736). Each subgroup had distinct clinical characteristics. The reference subgroup was the largest (n=904), followed by cardio-renal (n = 548) and eosinophilic (n=284). The eosinophilic subgroup had milder severity of AECOPD, including a shorter hospital stay (p<0.01). The cardio-renal subgroup had the highest mortality during (5%) and in the year after hospitalization (30%). Validation of the severe AECOPD classifier in the COVID-19 cohort recapitulated the characteristics seen in the non-COVID cohort. AECOPD subgroups in the COVID-19 cohort had different IL-1 beta, IL-2R, and IL-8 levels (FDR ≤ 0.05. These specific leukocyte and cytokine profiles resulted in inflammatory differences between the AECOPD subgroups based on C-reactive protein levels. Incorporating ML with EHR-data allows the identification of specific clinical and biological subgroups for severe AECOPD.

Analysis and validation of clinical subgroups of Kawasaki disease in children in China: a retrospective study

ObjectiveAlthough Kawasaki disease (KD) is commonly regarded as a single disease entity, clinical subgroups have recently been described. We aimed to validate previous research on clinical subgroups and establish a...

Comparative Risk of Neuropsychiatric Adverse Events Associated With Leukotriene-Receptor Antagonists Versus Inhaled Corticosteroids

Leukotriene-receptor antagonists (LTRA) and inhaled corticosteroids (ICS) are common controller medications for asthma, but limited studies examine their comparative risks on neuropsychiatric adverse events (NAEs) in asthma patients. To investigate the comparative risks of LTRA versus ICS on seven distinct categories of NAEs in asthma patients at a nationwide level. We conducted a nationwide cohort study during 2010-2021. Incident NAEs and its clinical subgroups (e.g., psychotic disorders, anxiety disorders, movement disorders, behavioral and emotional disorders, mood disorders, sleep-related disorders, and personality disorders) were assessed. Cox proportional hazards regressions were employed to quantify the comparative risks. There were 1,249,897 asthma patients aged 6-64 years. Incidence rates for NAEs were 25.10 per 1000 person-years among patients treated with LTRA, and 23.46 per 1000 person-years among those treated with ICS. The incidence rate difference was 1.64 [95%CI: 0.30-2.98] per 1000 person-years. Positive associations of NAEs and three clinical subgroups were found in patients treated with LTRA compared to ICS (hazard ratios (HR): 1.06 [95%CI: 1.00-1.12] for NAEs; HR: 1.88 [95%CI: 1.24-2.84] for psychotic disorders; HR: 1.10 [95%CI: 1.01-1.20] for anxiety disorders; and HR: 1.27 [95%CI: 1.02-1.58] for behavioral and emotional disorders), but not for movement disorders, mood disorders, sleep-related disorders, and personality disorders. This nationwide cohort study identified heightened risks, ranging from 6% to 88%, of NAEs and three clinical subgroups in asthma patients treated with LTRA compared to ICS. These findings underscore the necessity for clinicians to communicate with patients regarding potential neuropsychiatric harms when prescribing LTRA.

Association of PCSK9 inhibitors with mortality: insights from a retrospective cohort analysis.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors are effective in reducing cardiovascular events, but their impact on all-cause mortality and medical utilization compared to statins is unclear. This study investigated PCSK9 inhibitor use and its impact on mortality and medical utilization vs. statins, using TriNetX database data with up to 9 years of follow-up. This retrospective cohort study analysed TriNetX data spanning 1 July 2015, to 31 December 2023, including 79194 PCSK9 inhibitor users (alirocumab, evolocumab, inclisiran) and 5437513 statin users with hyperlipidaemia. The primary outcomes were all-cause mortality and medical utilization, including hospital inpatient services, emergency department visits, critical care, and mechanical ventilation. Propensity score matching showed that PCSK9 inhibitor use was associated with a 28.3% lower risk of all-cause mortality [adjusted hazard ratio (aHR) 0.717, 95% confidence interval (CI): 0.673-0.763] and significant reductions in medical utilization (hospital inpatient services usage: aHR 0.692, 95% CI: 0.664-0.721; emergency department services: aHR 0.756, 95% CI: 0.726-0.788; critical care services: aHR 0.619, 95% CI: 0.578-0.664; and mechanical ventilation: aHR 0.537, 95% CI: 0.484-0.596) compared to statins. These findings were consistent across various demographics and clinical subgroups. The sensitivity analyses supported the robustness of the findings. PCSK9 inhibitors significantly reduced all-cause mortality and medical utilization compared to statins, suggesting their important role in dyslipidaemia management, particularly for statin-naïve or intolerant patients. Further research, including randomized controlled trials, is needed to confirm these findings and explore the underlying mechanisms.

Explore genetic susceptibility association between viral infections and Guillain-Barré syndrome risk using two-sample Mendelian randomization

BackgroundNumerous observational studies have indicated that patients with Guillain-Barré syndrome (GBS) frequently had infections with various pathogens before the onset of the disease, particularly several viral infections. Some of these infections are linked to specific clinical and immunological subgroups of GBS, suggesting a potential correlation between viral infections and the development of GBS. However, observational studies have several limitations, including the presence of confounding factors.MethodWe explored the potential correlation between HIV, SARS-CoV-2, varicella-zoster virus, herpes simplex virus, Epstein-Barr virus, hepatitis B virus, and influenza virus with GBS using a two-sample Mendelian randomization approach. The data was derived from published summary statistics from genome-wide association studies (GWAS). After removing linkage disequilibrium, selecting strong instrumental variables and addressing confounding factors, we would conduct a two-sample Mendelian randomization analysis along with sensitivity testing and the MR-Steiger directional test.ResultHIV may have a causal association with GBS (IVW: p = 0.010, OR [95% CI] 1.240 [1.052–1.463]), while no such relationship exists with COVID-19 (IVW: p = 0.275, OR [95% CI] 0.831[0.596–1.159]), varicella (IVW: p = 0.543, OR [95% CI] 0.919 [0.701–1.206]), herpes zoster (IVW: p = 0.563, OR [95% CI] 0.941 [0.766–1.156]), HSV (IVW: p = 0.280, OR [95% CI] 1.244 [0.837–1.851]), EBV (IVW: p = 0.218, OR [95% CI] 0.883 [0.724–1.076]), HBV (IVW: p = 0.179, OR [95% CI] 1.072 [0.969–1.187]), or influenza virus (IVW: p = 0.917, OR [95% CI] 0.971 [0.553–1.703]). We did not find any abnormal SNPs, pleiotropy, or heterogeneity, nor is there any reverse causation.ConclusionOur study results indicate a causal relationship between HIV and GBS, providing new research directions for the etiology of GBS.

Patterns of pain medication usage and self-reported pain in older Irish adults with osteoarthritis: A latent class analysis of data from the Irish Longitudinal Study on Ageing

BackgroundThis study aimed to identify and describe links between pain medication use and self-reported pain among people aged ≥ 50 years with osteoarthritis (OA) in an Irish population, and to examine the relationships between pain, medication usage and socioeconomic and clinical characteristics.MethodsSecondary data analysis of wave 1 cross-sectional data from The Irish Longitudinal Study on Ageing (TILDA) was undertaken of 1042 people with self-reported doctor-diagnosed OA. We examined use of medications typically included in OA clinical guidelines, including non-opioid analgesics (e.g. paracetamol), topical and oral non-steroidal anti-inflammatory drugs (NSAIDs), opioids and nutraceuticals. Latent Class Analysis (LCA) was used to identify underlying clinical subgroups based on medication usage patterns, and self-reported pain severity. Multinomial logistic regression was used to explore sociodemographic and clinical characteristic links to latent class membership.ResultsA total of 358 (34.4%) of the 1042 people in this analysis were taking pain medications including oral NSAIDs (17.5%), analgesics (11.4%) and opioids (8.7%). Nutraceutical (glucosamine/chondroitin) use was reported by 8.6% and topical NSAID use reported by 1.4%. Three latent classes were identified: (1) Low medication use/no pain (n = 382, 37%), (2) low medication use/moderate pain (n = 523, 50%) and (3) moderate medication use/high pain (n = 137, 13%). Poorer self-rated health and greater sleep disturbance were associated with classes 2 and 3; depressive symptoms and female gender were associated with class 2, and retirement associated with class 3.ConclusionsWhilst pain medication use varied with pain severity, different medication types reported broadly aligned with OA guidelines. The two subgroups exhibiting higher pain levels demonstrated poorer self-rated health and greater sleep disturbance.

Elacestrant in ER+, HER2- Metastatic Breast Cancer with ESR1-Mutated Tumors: Subgroup Analyses from the Phase III EMERALD Trial by Prior Duration of Endocrine Therapy plus CDK4/6 Inhibitor and in Clinical Subgroups.

Elacestrant significantly prolonged progression-free survival (PFS) with manageable safety versus standard-of-care (SOC) endocrine therapy (ET) in patients with estrogen receptor-positive (ER+), HER2- metastatic breast cancer and tumors harboring estrogen receptor 1 (ESR1) mutation following ET plus a cyclin-dependent kinase 4/6 inhibitor (ET+CDK4/6i). In patients with ESR1-mutated tumors, we evaluated the efficacy and safety of elacestrant versus SOC based on prior ET+CDK4/6i duration and in clinical subgroups with prior ET+CDK4/6i ≥12 months. EMERALD, an open-label phase III trial, randomly assigned patients with ER+, HER2- metastatic breast cancer who had received 1-2 prior lines of ET, mandatory CDK4/6i, and ≤1 chemotherapy to elacestrant (345 mg daily) or SOC (aromatase inhibitor or fulvestrant). PFS was assessed across subgroups in post hoc exploratory analyses without adjustment for multiple testing. In patients with ESR1-mutated tumors and prior ET+CDK4/6i ≥12 months, the median PFS for elacestrant versus SOC was 8.6 versus 1.9 months (HR, 0.41; 95% confidence interval, 0.26-0.63). In this population, the median PFS (in months) for elacestrant versus SOC was 9.1 versus 1.9 (bone metastases), 7.3 versus 1.9 (liver and/or lung metastases), 9.0 versus 1.9 (<3 metastatic sites), 10.8 versus 1.8 (≥3 metastatic sites), 5.5 versus 1.9 (PIK3 catalytic subunit α mutation), 8.6 versus 1.9 (tumor protein p53 gene mutation), 9.0 versus 1.9 (HER2-low), 9.0 versus 1.9 (ESR1D538G-mutated tumors), and 9.0 versus 1.9 (ESR1Y537S/N-mutated tumors). Subgroup safety was consistent with the overall population. The duration of prior ET+CDK4/6i ≥12 months in metastatic breast cancer was associated with a clinically meaningful improvement in PFS for elacestrant compared with SOC and was consistent across all subgroups evaluated in patients with ER+, HER2-, ESR1-mutated tumors.

Association of county-level medical debt and survival among individuals newly diagnosed with cancer in the United States.

156 Background: Individuals diagnosed with cancer often bear significant health care costs and productivity loss, with over half incurring cancer-related medical debt. Medical debt is increasingly recognized as a social determinant of health care and health outcomes. Using newly available nationwide county-level medical debt information from 2011 to 2019 linked with national cancer registry data, we examined the association of county-level medical debt with survival among individuals newly diagnosed with cancer in the US. Methods: Individuals aged ≥18 years with newly diagnosed first primary cancer in 2011-2019 were identified from the National Cancer Database, which was linked with credit bureau data on county-level percentage of adults with medical debt in collections based on patients’ year of diagnosis. Patients were followed from diagnosis through December 31, 2019. Hazard Ratios (HR) and were derived from Cox proportional hazard models to estimate the associations of county-level medical debt quartiles with overall survival, adjusting for year of diagnosis, age, sex, race and ethnicity, insurance status, comorbidity score, metropolitan status, county-level social deprivation index and medically underserved area designation, and state of residency. Stratified analyses were conducted by cancer type and sociodemographic and clinical factors. Results: A total of 7,558,658 individuals newly diagnosed with cancer were identified, with a median county-level medical debt of 18%, ranging from 0% to 56%. County-level medical debt decreased since 2015. The highest percentage of county-level medical debts was found among patients racialized as non-Hispanic Black, uninsured, and living in medically underserved areas. In adjusted analyses, patients living in counties with the highest quartile of medical debt had 17% increased risks of death compared with those living in counties with the lowest quartile of medical debt (HR=1.17, 95%CI=1.16-1.18), with a statistically significant dose-response relationship for the higher quartiles (P-trend&lt;.0001). The pattern was consistently seen across cancer types as well as socioeconomic and clinical groups. Conclusions: County-level medical debt was strongly associated with worse survival among individuals newly diagnosed with cancer, consistent across socioeconomics and clinical subgroups. Policies preventing and relieving medical debt maybe effective ways to improve cancer outcomes at population level. Hazard ratios for risk of death associated with county-level medical debt by cancer site and stage at diagnosis. County-Level Share of Population with Medical Debt Q1 Q2 Q3 Q4 All cancers 1 1.08 1.13 1.17 Female breast 1 1.10 1.13 1.16 Prostate 1 1.06 1.11 1.13 Lung 1 1.06 1.10 1.12 Colon and rectum 1 1.07 1.11 1.14 Stage I-III 1 1.09 1.14 1.19 Stage IV 1 1.07 1.11 1.13 All P for trend &lt;.0001.

Validation Assessment of Privacy-Preserving Synthetic Electronic Health Record Data: Comparison of Original Versus Synthetic Data on Real-World COVID-19 Vaccine Effectiveness.

To assess the validity of privacy-preserving synthetic data by comparing results from synthetic versus original EHR data analysis. A published retrospective cohort study on real-world effectiveness of COVID-19 vaccines by Maccabi Healthcare Services in Israel was replicated using synthetic data generated from the same source, and the results were compared between synthetic versus original datasets. The endpoints included COVID-19 infection, symptomatic COVID-19 infection and hospitalization due to infection and were also assessed in several demographic and clinical subgroups. In comparing synthetic versus original data estimates, several metrices were utilized: standardized mean differences (SMD), decision agreement, estimate agreement, confidence interval overlap, and Wald test. Synthetic data were generated five times to assess the stability of results. The distribution of demographic and clinical characteristics demonstrated very small difference (< 0.01 SMD). In the comparison of vaccine effectiveness assessed in relative risk reduction between synthetic versus original data, there was a 100% decision agreement, 100% estimate agreement, and a high level of confidence interval overlap (88.7%-99.7%) in all five replicates across all subgroups. Similar findings were achieved in the assessment of vaccine effectiveness against symptomatic COVID-19 Infection. In the comparison of hazard ratios for COVID 19-related hospitalization and odds ratio for symptomatic COVID-19 Infection, the Wald tests suggested no significant difference between respective effect estimates in all five replicates for all patient subgroups but there were disagreements in estimate and decision metrices in some subgroups and replicates. Overall, comparison of synthetic versus original real-world data demonstrated good validity and reliability. Transparency on the process to generate high fidelity synthetic data and assurances of patient privacy are warranted.

Characterizing Treatment Credibility, Treatment Expectancy, and Symptom Expectancy in Patients Before Nonoperative Treatment for Degenerative Meniscal Tears.

The role of nonspecific factors, such as treatment credibility, treatment expectancy, and symptom expectancy, may shape the outcomes of the nonoperative treatment of degenerative meniscal tears (DMTs). The purpose of this study was to characterize treatment credibility and expectancy, symptom expectancy, and patient and clinical correlates of these factors among participants before undergoing 4 nonoperative treatment programs for DMTs. It was hypothesized that (1) treatment credibility scores would be similar across patient and baseline clinical subgroups and (2) treatment expectancy and symptom expectancy scores would be lower in older patients and among those reporting a longer pain duration or greater pain intensity. Cohort study; Level of evidence, 3. In 126 participants, validated scales were administered before treatment to assess the credibility of the assigned treatment (possible score of 1-9) as well as the expectations of treatment outcomes (0-100) and symptom improvement (1-5). Patient and clinical characteristics associated with these variables were examined. On average, participants (mean age, 58 years [range, 45-75 years]; 51% female; 94% White) expected the treatment to improve their symptoms by a mean of 68% and expected their symptoms to be "very likely" to improve. Participants with a body mass index (BMI) ≥30 kg/m2 had lower mean treatment credibility (6.09 ± 1.81) and treatment expectancy (64.53 ± 25.16) scores on bivariate analyses than those with a BMI <30 kg/m2 (6.73 ± 1.69 [P = .045] and 72.86 ± 19.20 [P = .039], respectively). Participants reporting a pain duration ≥3 months also had lower mean treatment expectancy (63.85 ± 23.83) and symptom expectancy (3.70 ± 0.85) scores compared to those reporting a pain duration <3 months (75.52 ± 18.93 [P = .003] and 4.16 ± 0.67 [P = .001], respectively). Most patients about to undergo physical therapy for DMTs considered it to be between "somewhat" and "very" credible and believed that their symptoms, on average, were "very likely" to improve. Although not supported by most evidence, patients with a BMI ≥30 kg/m2 believed physical therapy to be less credible and had lower treatment and symptom expectations, and those with symptoms present for ≥3 months had lower treatment and symptom expectations as well. Whether these nonspecific factors influence outcomes should be considered for further research.