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Introduction: Neoadjuvant systemic therapy (NAST) is vital in the management of HER2-positive (HER2+) breast cancer. Nevertheless, the indications for NAST in tumors <2 cm remain controversial. Method: A total of 7961 patients were screened from the Surveillance, Epidemiology, and End Result database. Independent prognostic factors were identified using multivariate Cox analysis. Subgroup analyses and Kaplan–Meier analyses were used to simulate whether NAST would provide a survival benefit with different high-risk characteristics. Nomograms were constructed, and an internal validation cohort was employed. Results: Of the 7961 included patients, 1137 (14.3%) underwent NAST. In the total population, NAST was associated with poorer overall survival (OS) and breast cancer-specific survival (BCSS) (OS: P = 0.00093; BCSS: P < 0.0001). Multivariate Cox analysis confirmed that NAST markedly affected the prognosis of enrolled patients. Besides, a direct association between T, N, age, subtype, and prognosis was observed. Subgroup analyses yielded in these three subgroups, T1c, hormone receptor-negative, and 61–69 years of age, NAST and AST had comparable OS, while NAST possessed worse BCSS. Notably, even in the N3, we still did not observe any additional benefit of NAST. The calculated C-index of 0.72 and 0.73 confirmed the predictability of the nomograms. The AUCs exhibit consistency in the training and validation cohorts. Conclusion: Our findings suggest that NAST does not provide additional benefit to patients with T1 HER2+ breast cancer, even in the presence of lymph node metastasis, T1c, or hormone receptor negativity. This study facilitates the implementation of individualized management strategies. [ABSTRACT FROM AUTHOR]

Background: Estimated pulse wave velocity (ePWV), which measures vascular aging, is an independent predictor of cardiovascular death. Nevertheless, the relationship between ePWV and all-cause mortality among patients suffering from non-traumatic subarachnoid hemorrhages (NSAH) remains obscure. Consequently, the objective of this study is to ascertain whether ePWV exerts influence on the prognosis of individuals afflicted with NSAH. Methods: Through the Medical Information Mart for Intensive Care IV (MIMICIV) database, 644 eligible participants were included. The Kaplan-Meier survival curve method was employed to assess the disparity in survival status between the low and high ePWV cohorts. The Cox proportional hazard model was employed to investigate the association between ePWV and inpatient mortality among critically ill patients diagnosed with NSAH. The Restricted Cubic Spline (RCS) model was employed to examine the dose-response correlation. Subsequently, multivariate Cox regression analysis was performed to identify independent prognostic factors. Lastly, the impact of ePWV on inpatient mortality across various subgroups was evaluated through stratified analysis. Results: Participants were categorized into two groups, delineated by their ePWV levels: a low ePWV level group and a high ePWV level group. Survival analysis unveiled that individuals with high ePWV exhibited a diminished survival rate compared to their counterparts with low ePWV. Following adjustment, low ePWV was significantly linked with a reduced risk of inpatient mortality among patients with NSAH (HR = 0.54, 95% CI = 0.32-0.89, p = 0.016). Simultaneously, analysis employing the RCS model further substantiated a linear escalation in the risk of inpatient mortality with increasing ePWV values. Conclusion: Elevated ePWV levels have been identified as an independent risk factor for the rise in inpatient mortality among NSAH patients and as a significant predictor of the clinical outcome of NSAH. [ABSTRACT FROM AUTHOR]

Importance and objectives The current medical paradigm of evidence-based medicine relies on clinical guidelines derived from randomized clinical trials (RCTs), but these guidelines often overlook individual variations in treatment effects. Approaches have been proposed to develop models predicting the effects of individualized management, such as predictive allocation, individualizing treatment allocation. It is currently unknown whether widespread implementation of predictive allocation could result in better population-level outcomes over guideline-based therapy. We sought to simulate the potential effect of predictive allocation using data from previously conducted RCTs. Methods and results Data from 3 RCTs (positive trial, negative trial, trial stopped for futility) in pediatric cardiology were used in a computational simulation study to quantify the potential benefits of a personalized approach based on predictive allocation. Outcomes were compared when using a universal approach vs predictive allocation where each patient was allocated to the treatment associated with the lowest predicted probability of negative outcome. Compared to results from RCTs, predictive allocation yielded absolute risk reductions of 13.8% (95% confidence interval [CI] −1.9 to 29.5), 13.9% (95% CI 4.5-23.2), and 15.6% (95% CI 1.5-29.6), respectively, corresponding to a number needed to treat of 7.3, 7.2, and 6.4. The net benefit of predictive allocation was directly proportional to the performance of the prediction models and disappeared as model performance degraded below an area under the curve of 0.55. Discussion These findings highlight that predictive allocation could result in improved group-level outcomes, particularly when highly predictive models are available. These findings will need to be confirmed in simulations of other trials with varying conditions and eventually in RCTs of predictive vs guideline-based treatment allocation. [ABSTRACT FROM AUTHOR]

The growing popularity of data heterogeneity motivates people to identify homogeneous subgroups with identical parameters. Meanwhile, in many fields of recent data science for some applications, such as personalized education and personalized marketing, the massive data are usually recorded as categorical or ordinal variables, which highlights the importance of performing subgroup analysis on those ordinal outcomes. In this paper, we propose a cumulative link model with subject-specific intercepts to detect and identify homogeneous subgroups through concave pairwise fusion penalty for ordinal response, where heterogeneity arises from some unknown or unobserved latent factors. The concave fusion method can simultaneously determine the number of subgroups, identify the group membership, and estimate the regression coefficients. An alternating direction method of multipliers algorithm with concave penalties for the generalized linear regression model with logit link is developed and its convergence property is studied. We also establish the oracle property of the proposed penalized estimator under some mild conditions. Our simulation studies show that the proposed method could recover the heterogeneous subgroup structure effectively when the response of interest is ordinal. Further, the advantages of our method are illustrated by the analysis on a Mathematics Student Performance Data Set of two public schools from the Alentejo region of Portugal. [ABSTRACT FROM AUTHOR]

In the era of personalized medicine, there is an increasing interest in the identification of patients who may benefit from or be sensitive to a specific type of treatment. Recently a threshold linear mixed model was proposed to identify treatment-sensitive subgroups based on a continuous covariate when longitudinal measurements are the outcomes of the study. This model assumes, however, a normal distribution for these measurements. In some studies, the longitudinal measurements are restricted in an interval and subject to floor and ceiling effects caused by a portion of subjects with measurements on the boundaries of the interval, which would violate the normality assumption. In this paper, a threshold mixed-effects Tobit model is introduced to overcome this problem. The proposed models and inference procedures are assessed through simulation studies, as well as an application to the analysis of data from a randomized clinical trial. [ABSTRACT FROM AUTHOR]

ABSTRACT Stratification on important variables is a common practice in clinical trials, since ensuring cosmetic balance on known baseline covariates is often deemed to be a crucial requirement for the credibility of the experimental results. However, the actual benefits of stratification are still debated in the literature. Other authors have shown that it does not improve efficiency in large samples and improves it only negligibly in smaller samples. This paper investigates different subgroup analysis strategies, with a particular focus on the potential benefits in terms of inferential precision of prestratification versus both poststratification and post hoc regression adjustment. For each of these approaches, the pros and cons of population‐based versus randomization‐based inference are discussed. The effects of the presence of a treatment‐by‐covariate interaction and the variability in the patient responses are also taken into account. Our results show that, in general, prestratifying does not provide substantial benefit. On the contrary, it may be deleterious, in particular for randomization‐based procedures in the presence of a chronological bias. Even when there is treatment‐by‐covariate interaction, prestratification may backfire by considerably reducing the inferential precision. [ABSTRACT FROM AUTHOR]

BackgroundMethodsResultsConclusionsResearch exploring the link between dietary riboflavin intake and cognitive decline in this demographic is limited. Our aim was to examine the association between riboflavin intake levels and cognitive decline.The National Health and Nutrition Examination Survey (NHANES) data from 2011 to 2014 were utilized in this cross-sectional analysis. The Consortium to Establish a Registry for Alzheimer's Disease test Word Learning delayed recall trial (DR), Digit Symbol Substitution Test (DSST), Animal Fluency Test(AFT) and Z test were used to evaluate cognitive performance. Multivariate logistic regression, restricted cubic spline and subgroup analysis were performed to evaluate the associations between riboflavin intake and cognitive decline.The study included a total of 2255 patients, with 47.9% being male. The incidence of cognitive decline was 23.8%. After adjusting for all selected covariates, we found that high riboflavin intake was associated with a lower risk of cognitive impairment in adults in the United States. When riboflavin intake was used as a Categorical variable, compared to those with the lowest intake, the odds ratio (OR) of individuals with the highest riboflavin intake for DR test, AFT test, DSST test and Z test were 0.73 (95% CI: 0.53~1), 0.68(95% CI: 0.49–0.96),0.53(95% CI: 0.37–0.77) and 0.56(95% CI: 0.39–0.8). The study also found an L-shaped association between riboflavin intake and cognitive decline, with an inflection point at approximately 2.984 mg/d.Our cross-sectional study in a nationwide sample of American old adults suggests that dietary riboflavin intake was negative associated with cognitive decline. [ABSTRACT FROM AUTHOR]

Clinical trials powered to detect subgroup effects provide the most reliable data on heterogeneity of treatment effect among different subpopulations. However, pre-specified subgroup analysis is not always practical and post hoc analysis results should be examined cautiously. Bayesian hierarchical modelling provides grounds for defining a controlled post hoc analysis plan that is developed after seeing outcome data for the population but before unblinding the outcome by subgroup. Using simulation based on the results from a tobacco cessation clinical trial conducted among the general population, we defined an analysis plan to assess treatment effect among American Indians and Alaska Natives (AI/AN) enrolled in the study. Patients were randomized into two arms using Bayesian adaptive design. For the opt-in arm, clinicians offered a cessation treatment plan after verifying that a patient was ready to quit. For the opt-out arm, clinicians provided all participants with free cessation medications and referred them to a Quitline. The study was powered to test a hypothesis of significantly higher quit rates for the opt-out arm at one-month post randomization. Overall, one-month abstinence rates were 15.9% and 21.5% (opt-in and opt-out arm, respectively). For AI/AN, one-month abstinence rates were 10.2% and 22.0% (opt-in and opt-out arm, respectively). The posterior probability that the abstinence rate in the treatment arm is higher is 0.96, indicating that AI/AN demonstrate response to treatment at almost the same probability as the whole population. [ABSTRACT FROM AUTHOR]

The effects of treatments may differ between persons with different characteristics. Addressing such treatment heterogeneity is crucial to investigate whether patients with specific characteristics are likely to benefit from a new treatment. The current paper presents a novel Bayesian method for superiority decision-making in the context of randomized controlled trials with multivariate binary responses and heterogeneous treatment effects. The framework is based on three elements: a) Bayesian multivariate logistic regression analysis with a Pólya-Gamma expansion; b) a transformation procedure to transfer obtained regression coefficients to a more intuitive multivariate probability scale (i.e., success probabilities and the differences between them); and c) a compatible decision procedure for treatment comparison with prespecified decision error rates. Procedures for a priori sample size estimation under a non-informative prior distribution are included. A numerical evaluation demonstrated that decisions based on a priori sample size estimation resulted in anticipated error rates among the trial population as well as subpopulations. Further, average and conditional treatment effect parameters could be estimated unbiasedly when the sample was large enough. Illustration with the International Stroke Trial dataset revealed a trend toward heterogeneous effects among stroke patients: Something that would have remained undetected when analyses were limited to average treatment effects. [ABSTRACT FROM AUTHOR]

We present the motivation, experience, and learnings from a data challenge conducted at a large pharmaceutical corporation on the topic of subgroup identification. The data challenge aimed at exploring approaches to subgroup identification for future clinical trials. To mimic a realistic setting, participants had access to 4 Phase III clinical trials to derive a subgroup and predict its treatment effect on a future study not accessible to challenge participants. A total of 30 teams registered for the challenge with around 100 participants, primarily from Biostatistics organization. We outline the motivation for running the challenge, the challenge rules, and logistics. Finally, we present the results of the challenge, the participant feedback as well as the learnings. We also present our view on the implications of the results on exploratory analyses related to treatment effect heterogeneity. [ABSTRACT FROM AUTHOR]

We give examples of three features in the design of randomized controlled clinical trials which can increase power and thus decrease sample size and costs. We consider an example multilevel trial with several levels of clustering. For a fixed number of independent sampling units, we show that power can vary widely with the choice of the level of randomization. We demonstrate that power and interpretability can improve by testing a multivariate outcome rather than an unweighted composite outcome. Finally, we show that using a pooled analytic approach, which analyzes data for all subgroups in a single model, improves power for testing the intervention effect compared to a stratified analysis, which analyzes data for each subgroup in a separate model. The power results are computed for a proposed prevention research study. The trial plans to randomize adults to either telehealth (intervention) or in-person treatment (control) to reduce cardiovascular risk factors. The trial outcomes will be measures of the Essential Eight, a set of scores for cardiovascular health developed by the American Heart Association which can be combined into a single composite score. The proposed trial is a multilevel study, with outcomes measured on participants, participants treated by the same provider, providers nested within clinics, and clinics nested within hospitals. Investigators suspect that the intervention effect will be greater in rural participants, who live farther from clinics than urban participants. The results use published, exact analytic methods for power calculations with continuous outcomes. We provide example code for power analyses using validated software. [ABSTRACT FROM AUTHOR]

Objectives: Women represent >50% of people with HIV globally but have historically been underrepresented in clinical trials. We evaluated the efficacy and safety of switching to dolutegravir/lamivudine (DTG/3TC) vs continuing their current antiretroviral regimen (CAR) by sex assigned at birth (female and male) in virologically suppressed adults with HIV‐1 without prior virological failure in a pooled analysis of two randomized controlled trials. Methods: This analysis included 48‐week data from the phase 3 TANGO and SALSA studies. Primary and key secondary endpoints included proportions of participants with HIV‐1 RNA ≥50 and <50 copies/mL at week 48, respectively. Safety was also assessed. Results: Of 1234 participants, 250 (DTG/3TC, n = 133; CAR, n = 117) were female at birth. Week 48 proportions of participants with Snapshot HIV‐1 RNA ≥50 copies/mL were similar regardless of sex at birth (DTG/3TC vs CAR: female, <1% [1/133] vs 2% [2/117]; male, <1% [1/482] vs <1% [3/502]). Proportions with HIV‐1 RNA <50 copies/mL were high across sexes and treatment groups (DTG/3TC vs CAR: female, 91% [121/133] vs 89% [104/117]; male, 94% [455/482] vs 94% [471/502]). Immunological response with DTG/3TC was slightly higher in female participants. Incidences of adverse events leading to withdrawal and serious adverse events were low and comparable between treatment groups and across sexes. Weight gain was higher with DTG/3TC than with CAR among female participants aged ≥50 years (treatment difference 2.08 kg [95% confidence interval 0.40–3.75]). Conclusions: Results confirm the robustness of DTG/3TC as a switch option in virologically suppressed females with HIV‐1, with outcomes similar to those in males. [ABSTRACT FROM AUTHOR]

Epilepsy is a common neurological disorder that significantly contributes to the worldwide disease burden. Restless legs syndrome is sleep-related movement disorder that causes uncomfortable sensations in the legs with an irresistible urge to move them. The aim of this study is to comprehensively assess the current evidence to estimate the prevalence of restless legs syndrome (RLS) in adults with epilepsy (AWE) and to compare it to healthy controls. PubMed, Medline, Scopus, and Web of Science databases were searched for observational studies reporting the prevalence of RLS in AWE. The modified Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the studies. Comprehensive Meta-Analysis software (version 3.0) was used to perform data analysis. The heterogeneity of the studies was assessed using the I2 index. The pooled prevalence of RLS in AWE and the odds ratio were calculated based on the random-effect model. Sensitivity analysis was assessed. A funnel plot and Egger's test were used to investigate publication bias. Subgroup analysis and univariate meta-regression analysis were done. Based on the analysis of 17 studies (2262 AWE patients), the prevalence of RLS was 14.9 % (95%CI, 10.4%–21 %). This rate was highest in the Americas (35.3 %; 95 % CI: 19.7-54.9 %) and lowest in Asian countries (11.6 %). The risk of RLS was significantly higher in AWE patients compared to health controls (12 studies, OR = 2.09; 95 % CI: 1.53-2.85, I2 = 91.69 %, P < 0.001). subgroup analysis showed Variations in RLS rates between studies depending on quality scores, methodology, and diagnostic criteria. The funnel plot and Egger's test suggest there was publication bias. Sensitivity analysis showed that none of the studies on their own significantly affected the results. This meta-analysis provides the first pooled estimate of RLS prevalence in AWE. RLS occurs in 15 out of every 100 AWE patients, and the risk is high compared to healthy controls. However, the findings need to be confirmed in future studies owing to limitations in the analysis and study design. • There is a higher prevalence of RLS among Adults with epilepsy as compared to healthy adults. • RLS prevalence is lower in Asian adults with epilepsy as compared to the non-Asian adults with epilepsy. • Factors studied for differences in RLS prevalence among adults with epilepsy showed no clear impact. [ABSTRACT FROM AUTHOR]

While the relationship between ESG disclosures and firm risk has been researched substantially, the results remain inconclusive, and contradictory, as of 2023. Through meta‐analysis, we investigate the effect of ESG disclosures measured by studies using E, S, G, or ESG disclosure on firm risk measured as total, systematic, or idiosyncratic risk with a sample of 76 papers published between 1991 and 2023. To the best of our knowledge, this is the pioneering attempt to investigate the impact of ESG disclosure on firm risk by adopting a meta‐analytical procedure to assess the significance of estimated mean effect size followed by meta‐regression analysis to test the effect of potential moderators. E, S, and G disclosures were found to be inversely related to firm risk as proposed by stakeholder and legitimacy theories. Further, the relationship between ESG disclosures and firm risk was found to be more pronounced for idiosyncratic risk rather than systematic risk. Results confirmed that firm size and female participation significantly moderated the relation between ESG disclosures and the level of firm risk. However, R&D, financial flexibility, disclosure index, and ROA had an insignificant but negative impact on the relationship. Our findings provide solace to managers and policymakers who may increasingly invest in ESG activities without worrying as ESG investing results in reducing firm risk. In addition, to manage risk, portfolio managers may include more stocks of environmentally as well as socially responsible firms in their portfolios. Future studies may suggest new moderators in the field of ESG disclosures and firm risk, thereby broadening the theoretical realm. Subsequent studies should examine the influence of specific environmental concerns such as carbon emissions, as well as social concerns such as gender equality and employee compensation, on stock returns. It contributes to the prevailing debate on ESG disclosures and firm risk nexus as well as attempts to shed light on pertinence of moderators affecting the relationship. [ABSTRACT FROM AUTHOR]

Li Zuo,1,&ast; Wenhui Zhang,2,&ast; Ying Wang,3 Xin Qi1 1Department of Pulmonary and Critical Care Medicine, China Aerospace Science & Industry Corporation 731 Hospital, Beijing, 100074, People’s Republic of China; 2General Practice Clinic, Sijiqing Town Community Health Service Center of Haidian District, Beijing, 100097, People’s Republic of China; 3Department of Pharmacy, Wangtai Branch of Jincheng General Hospital, Jincheng, 048006, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xin Qi, Department of pulmonary and critical care medicine, China Aerospace Science & Industry Corporation 731 Hospital, No. 3, Zhen Gang Nan Li, Feng Tai District, Beijing, 100074, People’s Republic of China, Email xinqixq015@163.comObjective: To explore serum KL-6 level and investigate its diagnostic value in interstitial lung diseases (ILDs).Methods: Serum KL-6 level was measured using the chemiluminescent enzyme immunoassay. Statistical analysis was performed for determining the KL-6 concentration of each group.Results: KL-6 level (U/mL) in the ILD group was 1388.321 ± 1943.116, which was higher than that in the control group, showing a significant statistical difference. ROC curve analysis based on the receiver operating characteristic curve showed the optimal cut-off value of 402.5U/mL, sensitivity of 77.4%, specificity of 93.4%, and accuracy of 89.4%; through Chi-square test with the two groups, the positive rate of KL-6 in patients with ILD was proved to be significantly higher than that in the control group. KL-6 level was 1063.00± 504.757 in the idiopathic pulmonary fibrosis (IPF) group, 1346.892 ± 1827.252 in the connective tissue disease-associated interstitial lung disease (CTD-ILD) group, 467.889± 288.859 in the organizing pneumonia (OP) group, 8252.333± 6050.625 in the pulmonary alveolar proteinosis (PAP) group, and 359.200± 392.707 in the sarcoidosis group. The rank sum test showed that the differences were statistically significant. KL-6 level was the lowest in the sarcoidosis group, followed by that in the OP group.Conclusion: Serum KL-6 level was confirmed to be highly sensitive, specific, and accurate in the diagnosis of ILD. Subgroup analysis showed that the KL-6 level was the lowest in the sarcoidosis group, followed by that in the OP group.Keywords: ILD, KL-6, diagnostic value, subgroup analysis

In biomedical science, analyzing treatment effect heterogeneity plays an essential role in assisting personalized medicine. The main goals of analyzing treatment effect heterogeneity include estimating treatment effects in clinically relevant subgroups and predicting whether a patient subpopulation might benefit from a particular treatment. Conventional approaches often evaluate the subgroup treatment effects via parametric modeling and can thus be susceptible to model mis-specifications. In this paper, we take a model-free semiparametric perspective and aim to efficiently evaluate the heterogeneous treatment effects of multiple subgroups simultaneously under the one-step targeted maximum-likelihood estimation (TMLE) framework. When the number of subgroups is large, we further expand this path of research by looking at a variation of the one-step TMLE that is robust to the presence of small estimated propensity scores in finite samples. From our simulations, our method demonstrates substantial finite sample improvements compared to conventional methods. In a case study, our method unveils the potential treatment effect heterogeneity of rs12916-T allele (a proxy for statin usage) in decreasing Alzheimers disease risk.

Abstract Previous studies have reported that the significant association between serum calcium and mortality substantially in patients, especially among those with intensive care unit (ICU). And In diabetes mellitus, congestive heart failure (CHF) is a significant comorbidity. We aim to evaluate the association between serum calcium levels and in-hospital mortality among patients with diabetes and congestive heart failure. The participants in this study were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. To scrutinize potential associations between serum calcium levels and in-hospital mortality, a comprehensive analysis encompassing multivariate logistic regression, cubic spline function model, threshold effect analysis, and subgroup analysis was performed. This retrospective cohort study encompassed 7063 patients, among whom the in-hospital mortality stood at 12.2%. In the multivariate logistic regression, adjusted odds ratios (ORs) were contrasted with the reference category Q6 (8.8–9.1 mg/dL) for serum calcium levels and in-hospital mortality. The adjusted ORs for Q1 (≤ 7.7 mg/dL), Q2 (7.7–8 mg/dL), and Q7 (≥ 9.1 mg/dL) were 1.69 (95% CI 1.17–2.44, p = 0.005), 1.62 (95% CI 1.11–2.36, p = 0.013), and 1.57 (95% CI 1.1–2.24, p = 0.012) respectively. The dose–response analysis uncovered a U-shaped relationship between serum calcium levels and in-hospital mortality in diabetic patients with heart failure. Subgroup analyses confirmed result stability notwithstanding the influence of diverse factors. Our investigation revealed a U-shaped correlation between serum calcium levels and in-hospital mortality in diabetes patients with congestive heart failure, pinpointing a significant inflection point at 9.05 mg/dL.

Abstract Subgroup analysis aims to identify subgroups (usually defined by baseline/demographic characteristics), who would (or not) benefit from an intervention under specific conditions. Often performed post hoc (not pre-specified in the protocol), subgroup analyses are prone to elevated type I error due to multiple testing, inadequate power, and inappropriate statistical interpretation. Aside from the well-known Bonferroni correction, subgroup treatment interaction tests can provide useful information to support the hypothesis. Using data from a previously published randomized trial where a p value of 0.015 was found for the comparison between standard and Hemopatch® groups in (the subgroup of) 135 patients who had hand-sewn pancreatic stump closure we first sought to determine whether there was interaction between the number and proportion of the dependent event of interest (POPF) among the subgroup population (patients with hand-sewn stump closure and use of Hemopatch®), Next, we calculated the relative excess risk due to interaction (RERI) and the “attributable proportion” (AP). The p value of the interaction was p = 0.034, the RERI was − 0.77 (p = 0.0204) (the probability of POPF was 0.77 because of the interaction), the RERI was 13% (patients are 13% less likely to sustain POPF because of the interaction), and the AP was − 0.616 (61.6% of patients who did not develop POPF did so because of the interaction). Although no causality can be implied, Hemopatch® may potentially decrease the POPF after distal pancreatectomy when the stump is closed hand-sewn. The hypothesis generated by our subgroup analysis requires confirmation by a specific, randomized trial, including only patients undergoing hand-sewn closure of the pancreatic stump after distal pancreatectomy. Trial registration: INS-621000-0760.

Bingcong Zhao,1,2 Zhigang Li,3 Chuan Shi,4 Yan Liu,5 Yang Sun,3 Bin Li,1,2 Jie Zhang,6 Zhizhong Gong,7 Yuanzheng Wang,8 Xuehong Ma,9 Xinjing Yang,10 Huili Jiang,3 Yuanbo Fu,1,2 Xin Wang,1,2 Yang Li,6 Hengchia Liu,6 Tuya Bao,3 Yutong Fei11– 13 1Department of Acupuncture and Moxibustion, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, People’s Republic of China; 2Beijing Key Laboratory of Acupuncture Neuromodulation, Beijing, People’s Republic of China; 3School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, People’s Republic of China; 4Psychological Assessment Center, Peking University Sixth Hospital, Beijing, People’s Republic of China; 5Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, People’s Republic of China; 6Department of Psychosomatic Medicine, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, People’s Republic of China; 7Division of Medical Affairs, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, People’s Republic of China; 8Department of Integrative TCM and Western Medicine, Peking University First Hospital, Beijing, People’s Republic of China; 9Department of Acupuncture & Moxibustion, Dongfang Hospital, the Second Clinical Medical College of Beijing University of Chinese Medicine, Beijing, People’s Republic of China; 10Department of Traditional Chinese Medicine, South China Hospital of Shenzhen University, Shenzhen, People’s Republic of China; 11Centre for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, People’s Republic of China; 12Institute of Excellence in Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, People’s Republic of China; 13Beijing GRADE Centre, Beijing, People’s Republic of ChinaCorrespondence: Tuya Bao, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, No. 11, Bei San Huan Dong Lu, Chaoyang District, Beijing, 100029, People’s Republic of China, Email tuyab@263.net Yutong Fei, Centre for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, No. 11, Bei San Huan Dong Lu, Chaoyang District, Beijing, 100029, People’s Republic of China, Email feiyt@bucm.edu.cnPurpose: Anxious depression (AD) is a common, distinct depression subtype. This exploratory subgroup analysis aimed to explore the effects of acupuncture as an add-on therapy of selective serotonin reuptake inhibitors (SSRIs) for patients with AD or non-anxious depression (NAD).Patients and Methods: Four hundred and sixty-five patients with moderate-to-severe depression from the AcuSDep pragmatic trial were included in analysis. Patients were randomly assigned to receive MA+SSRIs, EA+SSRIs, or SSRIs alone (1:1:1) for six weeks. AD was defined by using dimensional criteria. The measurement instruments included 17-items Hamilton Depression Scale (HAMD-17), Self-Rating Depression Scale (SDS), Clinical Global Impression (CGI), Rating Scale for Side Effects (SERS), and WHO Quality of Life-BREF (WHOQOL-BREF). Comparison between AD and NAD subgroups and comparisons between groups within either AD or NAD subgroups were conducted.Results: Eighty percent of the patients met the criteria for AD. The AD subgroup had poorer clinical manifestations and treatment outcomes compared to those of the NAD subgroup. For AD patients, the HAMD response rate, remission rate, early onset rate, and the score changes on each scale at most measurement points on the two acupuncture groups were significantly better than the SSRIs group. For NAD patients, the HAMD early onset rates of the two acupuncture groups were significantly better than the SSRIs group.Conclusion: For AD subtype patients, either MA or EA add-on SSRIs showed comprehensive improvements, with small-to-medium effect sizes. For NAD subtype patients, both the add-on acupuncture could accelerate the response to SSRIs treatment. The study contributed to the existing literature by providing insights into the potential benefits of acupuncture in combination with SSRIs, especially for patients with AD subtypes. Due to its limited nature as a post hoc subgroup analysis, prospectively designed, high-quality trials are warranted.Clinical Trials Registration: ChiCTR-TRC-08000297.Keywords: anxious depression, non-anxious depression, acupuncture, SSRIs, subgroup analysis

ABSTRACT Subgroup analysis may be used to investigate treatment effect heterogeneity among subsets of the study population defined by baseline characteristics. Several methodologies have been proposed in recent years and with these, statistical issues such as multiplicity, complexity, and selection bias have been widely discussed. Some methods adjust for one or more of these issues; however, few of them discuss or consider the stability of the subgroup assignments. We propose exploring the stability of subgroups as a sensitivity analysis step for stratified medicine to assess the robustness of the identified subgroups besides identifying possible factors that may drive this instability. After applying Bayesian credible subgroups, a nonparametric bootstrap can be used to assess stability at subgroup‐level and patient‐level. Our findings illustrate that when the treatment effect is small or not so evident, patients are more likely to switch to different subgroups (jumpers) across bootstrap resamples. In contrast, when the treatment effect is large or extremely convincing, patients generally remain in the same subgroup. While the proposed subgroup stability method is illustrated through Bayesian credible subgroups method on time–to–event data, this general approach can be used with other subgroup identification methods and endpoints. [ABSTRACT FROM AUTHOR]

Background: There is limited evidence regarding the correlation between prostate-specific antigen (PSA) kinetics and clinical outcomes. Therefore, after regulating other covariates, we studied patients with castration-resistant prostate cancer who received abiraterone acetate as the first-line treatment. In this study, we investigated whether time to PSA nadir was independently associated with PSA progression-free survival (PFS). Methods: As a retrospective cohort study, this study contained a total of 77 castration-resistant prostate cancer patients who received abiraterone acetate from October 2015 to April 2021 in a Chinese hospital. The dependent variable was PSA-PFS. The objective independent variable was time to PSA nadir (TTPN). Covariates involved in this study included age, duration of androgen deprivation therapy (ADT), PSA level at baseline, time of 50% PSA decline, time of PSA decline to nadir, Gleason score, bone metastasis, previous treatment, PSA decline <50% in 3 months, PSA to nadir in 3 months, PSA decline <90%, PSA decline <0.2 ng/ mL, and PSA flare. Results: For the 77 subjects, their mean age was 72.70 ± 8.08 years. Fully calibrated linear regression findings indicated that PSA decline and kinetics were positively associated with PFS (months) after adjusting confounders (ß = 0.77, 95% CI: 0.11-1.44). A non-linear relationship was not detected between PSA decline or PSA kinetics and progression-free survival. Conclusion: According to the data of this study, there was a correlation between early PSA changes and patients treated with abiraterone acetate. [ABSTRACT FROM AUTHOR]

Precision medicine aims to identify specific patient subgroups that may benefit the most from a particular treatment than the whole population. Existing definitions for the best subgroup in subgroup analysis are based on a single outcome and do not consider multiple outcomes; specifically, outcomes of different types. In this article, we introduce a definition for the best subgroup under a multiple‐outcome setting with continuous, binary, and censored time‐to‐event outcomes. Our definition provides a trade‐off between the subgroup size and the conditional average treatment effects (CATE) in the subgroup with respect to each of the outcomes while taking the relative contribution of the outcomes into account. We conduct simulations to illustrate the proposed definition. By examining the outcomes of urinary tract infection and renal scarring in the RIVUR clinical trial, we identify a subgroup of children that would benefit the most from long‐term antimicrobial prophylaxis. [ABSTRACT FROM AUTHOR]

Previous studies have reported that the significant association between serum calcium and mortality substantially in patients, especially among those with intensive care unit (ICU). And In diabetes mellitus, congestive heart failure (CHF) is a significant comorbidity. We aim to evaluate the association between serum calcium levels and in-hospital mortality among patients with diabetes and congestive heart failure. The participants in this study were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. To scrutinize potential associations between serum calcium levels and in-hospital mortality, a comprehensive analysis encompassing multivariate logistic regression, cubic spline function model, threshold effect analysis, and subgroup analysis was performed. This retrospective cohort study encompassed 7063 patients, among whom the in-hospital mortality stood at 12.2%. In the multivariate logistic regression, adjusted odds ratios (ORs) were contrasted with the reference category Q6 (8.8–9.1 mg/dL) for serum calcium levels and in-hospital mortality. The adjusted ORs for Q1 (≤ 7.7 mg/dL), Q2 (7.7–8 mg/dL), and Q7 (≥ 9.1 mg/dL) were 1.69 (95% CI 1.17–2.44, p = 0.005), 1.62 (95% CI 1.11–2.36, p = 0.013), and 1.57 (95% CI 1.1–2.24, p = 0.012) respectively. The dose–response analysis uncovered a U-shaped relationship between serum calcium levels and in-hospital mortality in diabetic patients with heart failure. Subgroup analyses confirmed result stability notwithstanding the influence of diverse factors. Our investigation revealed a U-shaped correlation between serum calcium levels and in-hospital mortality in diabetes patients with congestive heart failure, pinpointing a significant inflection point at 9.05 mg/dL. [ABSTRACT FROM AUTHOR]

Subgroup analysis aims to identify subgroups (usually defined by baseline/demographic characteristics), who would (or not) benefit from an intervention under specific conditions. Often performed post hoc (not pre-specified in the protocol), subgroup analyses are prone to elevated type I error due to multiple testing, inadequate power, and inappropriate statistical interpretation. Aside from the well-known Bonferroni correction, subgroup treatment interaction tests can provide useful information to support the hypothesis. Using data from a previously published randomized trial where a p value of 0.015 was found for the comparison between standard and Hemopatch® groups in (the subgroup of) 135 patients who had hand-sewn pancreatic stump closure we first sought to determine whether there was interaction between the number and proportion of the dependent event of interest (POPF) among the subgroup population (patients with hand-sewn stump closure and use of Hemopatch®), Next, we calculated the relative excess risk due to interaction (RERI) and the "attributable proportion" (AP). The p value of the interaction was p = 0.034, the RERI was − 0.77 (p = 0.0204) (the probability of POPF was 0.77 because of the interaction), the RERI was 13% (patients are 13% less likely to sustain POPF because of the interaction), and the AP was − 0.616 (61.6% of patients who did not develop POPF did so because of the interaction). Although no causality can be implied, Hemopatch® may potentially decrease the POPF after distal pancreatectomy when the stump is closed hand-sewn. The hypothesis generated by our subgroup analysis requires confirmation by a specific, randomized trial, including only patients undergoing hand-sewn closure of the pancreatic stump after distal pancreatectomy. Trial registration: INS-621000-0760. [ABSTRACT FROM AUTHOR]

The effect of weekend catch-up sleep (WCS) on depressive symptoms is inconsistent among different populations, with limited evidence in Americans. Therefore, we aimed to investigate the association between WCS and depressive symptoms in American adults. We recruited 7719 participants from the National Health and Nutrition Examination Survey (NHANES) 2017–2020. Information on sleep duration and depressive symptoms were assessed by several self-reported questions and Patient Health Questionnaire-9 (PHQ-9), respectively. Then, WCS duration was calculated as weekend sleep duration minus weekday sleep duration, and WCS was further defined as WCS duration >0 h. Survey designed regression analyses were used to assess the association of WCS and depressive symptoms. In fully adjusted multivariate logistic regression models, the odds ratio (95 % confidence interval) for depressive symptoms and the β (95 % confidence interval) for PHQ-9 score in response to WCS were 0.746 (0.462, 1.204; P = 0.218) and −0.429 (−0.900, 0.042; P = 0.073), respectively. Besides, the smooth relationship presented L-shaped, and only WCS duration of 0–2 h was statistically significantly associated with depressive symptoms or PHQ-9 score. Subgroup analyses showed that the negative associations were stronger among men, adults younger than 65 years, and those with short weekday sleep duration (P for interaction <0.05). Limitations. The cross-sectional design limits the capability for causal relationship between WCS and depressive symptoms. This study suggests that moderate WCS is associated with reduced odds of depressive symptoms, which provides additional epidemiological evidence for the effects of sleep on depressive symptoms. • We firstly explored the effects of WCS on depressive symptoms in American adults. • WCS duration of 0–2 h was related to decreased odds of depressive symptoms. • Continuous WCS duration showed a non-linear association with depressive symptoms. • Specific subgroups were more sensitive to the benefits of WCS. • Our findings offer more evidence to help alleviate depressive symptoms in Americans. [ABSTRACT FROM AUTHOR]

Objective: The objective of our study was to integrate the efficacy results of post-nephrectomy adjuvant therapies in renal cell carcinoma (RCC) patients with risk of recurrence, and attempt to determine the optimal intervention choice. Methods: We performed standard meta-analysis procedures in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The PubMed, Embase, and Cochrane Library databases were searched from inception to 22 September 2022. Randomized controlled trials reporting overall survival (OS) or disease-free survival (DFS) of adjuvant therapies, including immune checkpoint inhibitors (ICIs) and targeted therapies, in adult post-nephrectomy RCC patients were eligible for inclusion. Results: Seven studies involving 7548 participants were included in our analyses. In contrast with placebo, DFS benefit with ICIs was only observed in female RCC patients and RCC patients with high programmed death-ligand 1 (PD-L1) expression (≥ 1%), sarcomatoid features, and M0 intermediate–high risk. Network meta-analyses demonstrated that pembrolizumab exhibited both DFS and OS benefit compared with placebo, sunitinib, sorafenib, and girentuximab, and only DFS benefit compared with atezolizumab and nivolumab plus ipilimumab. Conclusions: Our results suggest that post-nephrectomy RCC patients with sarcomatoid differentiation and high PD-L1 expression were more responsive to ICIs. Furthermore, pembrolizumab monotherapy exhibited superior DFS and OS results over other adjuvant therapies. [ABSTRACT FROM AUTHOR]

Parent vessel occlusion (PVO) is a time-honored treatment for unclippable or uncoilable intracranial aneurysms. Flow diversion (FD) is a recent endovascular alternative that can occlude the aneurysm and spare the parent blood vessel. Our aim was to compare outcomes of FD with endovascular PVO. This is a prespecified treatment subgroup analysis of the Flow diversion in Intracranial Aneurysms trial (FIAT). FIAT was an investigator-led parallel-group all-inclusive pragmatic randomized trial. For each patient, clinicians had to prespecify an alternative management option to FD before stratified randomization. We report all patients for whom PVO was selected as the best alternative treatment to FD. The primary outcome was a composite of core-lab determined angiographic occlusion or near-occlusion at 3–12 months combined with an independent clinical outcome (mRS<3). Primary analyses were intent-to-treat. There was no blinding. There were 45 patients (16.2% of the 278 FIAT patients randomized between 2011 and 2020 in 3 centers): 22 were randomly allocated to FD and 23 to PVO. Aneurysms were mainly large or giant (mean 22 mm) anterior circulation (mainly carotid) aneurysms. A poor primary outcome was reached in 11/22 FD (50.0%) compared to 9/23 PVO patients (39.1%) (RR: 1.28, 95% CI [0.66–2.47]; P = 0.466). Morbidity (mRS >2) at 1 year occurred in 4/22 FD and 6/23 PVO patients. Angiographic results and serious adverse events were similar. The comparison between PVO and FD was inconclusive. More randomized trials are needed to better determine the role of FD in large aneurysms eligible for PVO. [ABSTRACT FROM AUTHOR]

Recent years have seen increasing attention to improving depressive symptoms through dietary intakes, yet the association between thiamine intake and depression remains unclear. The present study aimed to explore this association using data from an American cross-sectional study. We explored the association of covariates, exposure, and outcome with logistic regression equations. Multivariable regression models were performed to further exclude confounding factors. To investigate nonlinear relationships, we employed restricted cubic splines. Recursive algorithms were utilized to identify inflection points. Additionally, we conducted stratified analyses by age and sex to uncover differences among subgroups. When all covariates were adjusted, the association between thiamine intake and depression was not statistically significant [0.93 (0.82, 1.07)]. In the linear trend test using Q1 as the reference, the ORs (95%CI) for Q2, Q3, and Q4 were 0.87 (0.73, 1.04), 0.83 (0.68, 1.00), and 0.92 (0.73, 1.16), which suggested that the association might be nonlinear. We then confirmed this nonlinear relationship with a restricted cubic spline, and the inflection point of 1.35 mg/day was calculated. Before the inflection point, the effect value of the relationship was 0.68 (0.53, 0.89). After the inflection point, no significant association was found [1.10 (0.92, 1.31)]. Stratified analyses revealed that this nonlinear relationship was consistent among women and individuals aged <60 years. In this cross-sectional study among American general adults, we found a nonlinear association between thiamine intake and depression and further observed differences by age and sex. • Our study highlighted a nonlinear association between thiamine intake and depression among American general adults. • This association was statistically significant only before the inflection point of 1.35 mg/day. • This study may provide a reference for the prevention of depression through dietary intake. [ABSTRACT FROM AUTHOR]

Missing data problems arise in randomized trials, which complicates the inference of causal effects if the missing mechanism is non-ignorable. We tackle the challenge of identifying and estimating the complier average causal effect parameters under non-ignorable missingness by increasing the covariates to mitigate the sensitivity to the violation of specific identification assumptions. The missing data mechanism is assumed to follow a logistic model, wherein the absence of the outcome is explained by the outcome itself, the treatment received, and the covariates. We establish the identifiability of the models under mild conditions by assuming that the outcome follows a normal distribution. We develop a computational method to estimate model parameters through a two-step likelihood estimation approach, employing subgroup analysis. The bootstrap method is employed for variance estimation, and the effectiveness of our approach is confirmed through simulation. We applied the proposed method to analyze the household income dataset from the Chinese Household Income Project Survey 2013. [ABSTRACT FROM AUTHOR]

Background: Vadadustat is an oral hypoxia-inducible factor prolyl hydroxylase inhibitor developed for treating anemia in chronic kidney disease (CKD). The purpose of this post-hoc analysis was to investigate the factors affecting the responsiveness to vadadustat in anemia patients with nondialysis-dependent (NDD) or hemodialysis-dependent (HDD) CKD in two Japanese phase 3 studies. Methods: Of 151 and 162 patients enrolled in NDD-CKD and HDD-CKD studies, 136 and 140 patients, respectively, were included and divided into subgroups for the analysis. To assess vadadustat responsiveness, the resistance index was defined as the mean body weight-adjusted dose of vadadustat (mg/kg) at weeks 20–24 divided by the mean hemoglobin (g/dL) at weeks 20–24. Multivariate analysis was performed to identify the variables affecting the resistance index. Results: Independent factors identified as determinants for better response to vadadustat were as follows: high baseline hemoglobin, low baseline eGFR, high week-20–24 ferritin, and CKD not caused by autoimmune disease/glomerulonephritis/vasculitis in NDD-CKD; and male sex, high baseline C-reactive protein, and low baseline erythropoiesis-stimulating agent resistance index (ERI) in HDD-CKD. Conclusions: In this post-hoc analysis, several factors were identified as affecting the response to vadadustat. These results may provide useful information leading to an appropriate dose modification for vadadustat. Clinical trial registration: NCT03329196 (MT-6548-J01) and NCT03439137 (MT-6548-J03). [ABSTRACT FROM AUTHOR]

Background and purpose: In 2016, we concluded a randomized controlled trial testing 1 mg rasagiline per day add‐on to standard therapy in 252 amyotrophic lateral sclerosis (ALS) patients. This article aims at better characterizing ALS patients who could possibly benefit from rasagiline by reporting new subgroup analysis and genetic data. Methods: We performed further exploratory in‐depth analyses of the study population and investigated the relevance of single nucleotide polymorphisms (SNPs) related to the dopaminergic system. Results: Placebo‐treated patients with very slow disease progression (loss of Amyotrophic Lateral Sclerosis Functional Rating Scale–Revised [ALSFRS‐R] per month before randomization of ≤0.328 points) showed a per se survival probability after 24 months of 0.85 (95% confidence interval = 0.65–0.94). The large group of intermediate to fast progressing ALS patients showed a prolonged survival in the rasagiline group compared to placebo after 6 and 12 months (p = 0.02, p = 0.04), and a reduced decline of ALSFRS‐R after 18 months (p = 0.049). SNP genotypes in the MAOB gene and DRD2 gene did not show clear associations with rasagiline treatment effects. Conclusions: These results underline the need to consider individual disease progression at baseline in future ALS studies. Very slow disease progressors compromise the statistical power of studies with treatment durations of 12–18 months using clinical endpoints. Analysis of MAOB and DRD2 SNPs revealed no clear relationship to any outcome parameter. More insights are expected from future studies elucidating whether patients with DRD2CC genotype (Rs2283265) show a pronounced benefit from treatment with rasagiline, pointing to the opportunities precision medicine could open up for ALS patients in the future. [ABSTRACT FROM AUTHOR]

The DEXamethasone twice for pain treatment after Total Knee Arthroplasty (DEX‐2‐TKA) trial showed that adding one and two doses of 24 mg intravenous dexamethasone to paracetamol, ibuprofen and local infiltration analgesia, reduced morphine consumption (primary outcome) within 48 h after TKA. We aimed to explore the differences in the effect of dexamethasone on morphine consumption in different subgroups. Quantile regression adjusted for site was used to test for significant interaction between the predefined dichotomised subgroups and treatment group. The subgroups were defined based on baseline data: sex (male/female), age (≤65 years/>65 years), American Society of Anaesthesiologists (ASA)‐score (ASA I + II/III), visual analogue score of preoperative pain at rest (≤30 mm/>30 mm), pain during mobilisation (≤30 mm/>30 mm), type of anaesthesia (spinal anaesthesia/general anaesthesia and spinal converted to general anaesthesia), and prior daily use of analgesics (either paracetamol and/or NSAID/neither). These analyses were supplemented with post hoc multivariate linear regression analyses. Test of interaction comparing sex in the pairwise comparison between DX2 (dexamethasone [24 mg] + dexamethasone [24 mg]) versus placebo (p =.02), showed a larger effect of dexamethasone on morphine consumption in male patients compared to females. Test of interaction comparing age in the pairwise comparison between DX1 (dexamethasone [24 mg] + placebo) versus placebo (p =.04), showed a larger effect of dexamethasone on morphine consumption in younger patients (≤65 years) compared to older. All remaining subgroup analyses showed no evidence of a difference. The supplemental multivariate analyses did not support any significant interaction for sex (p =.256) or age (p =.730) but supported a significant interaction with the type of anaesthesia (p <.001). Our results from the quantile regression analyses indicate that the male sex and younger age (≤65 years) may be associated with a larger analgesic effect of dexamethasone than the effects in other types of patients. However, this is not supported by post‐hoc multivariate linear regression analyses. The two types of analyses both supported a possible interaction with the type of anaesthesia. [ABSTRACT FROM AUTHOR]

School-based, universal social and emotional learning (SEL) has been widely practiced and promoted as a promising approach to prevent youth mental, emotional, and behavioral problems. Although prior research has accumulated robust evidence of the average effects of universal SEL, it remains unclear whether it works similarly or differentially across diverse sociocultural subgroups of students. Investigating subgroup effects has implications for understanding the impact of universal SEL on possible subgroup disparities in student social-emotional competence (SEC). This study examined whether the effects of a universal SEL program on student SEC development differed across diverse student subgroups classified by gender, race, ethnicity, socioeconomic status, disability status, and English learner status. Data came from student SEC progress monitoring collected during a 1-year quasi-experimental study of a universal SEL program (N = 1592; Grades K-2). The results of multigroup latent growth modeling suggest that (a) the intervention effects were slightly larger for Black students, compared to White or other racial-ethnic subgroups, and (b) the effects were not different across other examined subgroups. This study also found that in the comparison condition, the SEC disparities between Black and White students tended to widen throughout the year, whereas in the intervention condition, Black students showed a similar rate of growth as their White peers. Findings suggest that universal SEL may be similarly beneficial across many diverse student subgroups, while it may yield larger benefits among some racially marginalized subgroups, preventing racial disparities from further widening. Yet the benefits of SEL may not be sufficient to reduce existing subgroup disparities. These findings suggest a need for more studies to examine differential effects of universal preventive programs by diverse subgroups to better inform practices that enhance equity in youth outcomes.

BackgroundIn recent years, septic shock remains a common fatal disease in the intensive care unit (ICU). After sufficient fluid resuscitation, some patients still experience tachycardia, which may lead to adverse effects on cardiac function. However, the use of β-blockers in the treatment of septic shock remains controversial. Thus, the purpose of this study is to evaluate the efficacy of β-blockers in the treatment of patients with septic shock and explore the most appropriate patient subgroups for this treatment.MethodsThis retrospective observational study enrolled septic shock patients from the Medical Information Mart for Intensive Care (MIMIC)-IV and used propensity score matching (PSM) to balance some baseline differences between patients with and without β-blockers treatment. The primary outcome was the 28-day mortality. Length of stay (LOS) in the ICU and hospital, and the degree of support for organs such as circulatory, respiratory and renal systems were also assessed. Subgroup analysis and multivariate logistic regression were performed to determine the relationship between β-blockers therapy and 28-day mortality in different patient groups.ResultsA total of 4,860 septic shock patients were enrolled in this study and 619 pairs were finally matched after PSM. Our analysis revealed that β-blocker therapy was associated with a significant improvement in 28-day mortality (21.5% vs. 27.1%; P = 0.020) and led to a prolonged LOS in both the ICU and hospital. Subgroup analysis indicated that there was an interaction between cardiovascular diseases and β-blocker therapy in patients with septic shock. Patients with pre-existing heart disease or atrial arrhythmias were more likely to derive benefits from β-blocker treatment.ConclusionWe found β-blockers therapy was effective to improve 28-day mortality in patients with septic shock. Patients in the subgroup with cardiovascular diseases were more likely to benefit from β-blockers in mortality.

BackgroundLimited data are available regarding the association between serum transferrin saturation (TSAT) levels and heart failure (HF).MethodsWe utilized data from National Health and Nutrition Examination Survey (NHANES) 2017- 2020.03 for analysis. Data on TAST, HF and covariates were extracted and analyzed. Weighted logistic regression and subgroup analysis were used to explore the independent association between TSAT and HF. Furthermore, interaction tests were also carried out to evaluate the strata differences. We subsequently assessed whether there was a non-linear relationship between the 2 using Restricted cubic spline (RCS) and threshold effect models.ResultA total of 282 (3.87%) participants were identified to have HF. Among the total population, participants with HF had significantly lower TSAT levels compared to those without HF (24.63 vs. 27.95, P = 0.001). After fully adjusting for potential confounders, weighted multiple logistic regression models revealed a 2.6% reduced in the risk of HF when each unit of TSAT increased. There was also a negative association between elevated TSAT and developed risk of HF in the quartile groups (Q1 OR:1.00; Q2 OR: 0.924 [95%CI:0.593,1.440]; Q3 OR: 0.515 [95%CI:0.298,0.891]; Q4 OR:0.411 [95%CI:0.201,0.839]). The subgroup analysis results remained consistent across strata, with a strong negative correlation between TSAT and HF. Interaction tests showed no dependence on gender, age, Body Mass Index, race, diabetes, hypertension, hyperlipidemia, ratio of family income to poverty and education for this negative association between TSAT and HF (all p for interaction >0.05). The RCS and threshold effect models indicated a linear negative correlation between TSAT and HF, which was more pronounced when TSAT under 40%.ConclusionOverall, these findings suggest a consistent and negative association between TSAT levels and the presence of HF among middle-aged and older adults in the United States.

Black soldier fly (BSF) meal possesses a balanced nutritional profile, making it a promising substitute for fishmeal. Several studies have been conducted to investigate the effects of replacing fishmeal with BSF meal on fish immune response and antioxidant capacity. However, considering the varying effects of BSF meal on different fish species demonstrated in earlier studies, a meta-analysis study was imperative to determine the efficacy of BSF meal in aquafeed. This meta-analysis examined 38 studies on finfish. Subgroup analysis and meta-regression were conducted to investigate the source of heterogeneity in the immunostimulant and antioxidant efficacy of BSF meal. Categorical variables used in subgroup analysis included the BSF development stage (larvae versus prepupae or pupae), BSF processing method (full-fat versus defatted), and fish dietary habits. Two continuous variables were evaluated for meta-regression analysis: dietary BSF inclusion level and treatment duration. The datasets were assessed for publication bias using funnel plots and Egger's test with the Pustejovsky–Rodgers Approach. The results revealed that BSF meal influences immune performance and antioxidant ability. Subgroup analysis indicated that different BSF development stages significantly influence the immunostimulant and antioxidant efficacy of BSF meals, with BSF prepupae or pupae outperforming BSF larvae. In terms of processing, full-fat BSF was superior to defatted BSF. Furthermore, BSF meal demonstrated the highest efficacy in omnivorous fishes. Meta-regression outcomes revealed that a higher concentration of BSF meal may inhibit immune response and antioxidant ability and that treatment duration exerts little impact. In conclusion, the present meta-analysis demonstrated that BSF is a promising ingredient in aquafeed to improve fish immune response and antioxidant capacity.

Background: Prior pulmonary tuberculosis (PTB) might be associated with the development of chronic obstructive pulmonary disease (COPD). However, the impact of prior PTB on the risk of incident COPD has not been studied in a large prospective cohort study of the European population. Objectives: This study aimed to investigate the association of prior PTB with the risk of COPD. Design: Prospective cohort study. Methods: A multivariable Cox proportional model was used to estimate the hazard ratio (HR) and 95% confidence interval (95% CI) for the association of prior PTB with COPD. Subgroup analyses were further conducted among individuals stratified by age, sex, body mass index, smoking status, drinking status, physical activity, and polygenic risk score (PRS). Results: The study involved a total of 216,130 participants, with a median follow-up period of 12.6 years and 2788 incident cases of COPD. Individuals with a prior history of PTB at baseline had an 87% higher risk of developing incident COPD compared to those without such history [adjusted hazard ratio (aHR) = 1.87; 95% confidence interval (CI): 1.26–2.77; p = 0.002]. Subgroup analysis revealed that individuals having prior PTB history presented a higher risk of incident COPD among individuals who were aged from 50 to 59 years with aHR of 2.47 (1.02–5.95, p = 0.044), older than 59 years with aHR of 1.81 (1.16–2.81, p = 0.008), male with aHR of 2.37 (1.47–3.83, p < 0.001), obesity with aHR of 3.35 (2.16–5.82, p < 0.001), previous smoking with aHR of 2.27 (1.39–3.72, p < 0.001), current drinking with aHR of 1.98 (1.47–3.83, p < 0.001), low physical activity with aHR of 2.62 (1.30–5.26, p = 0.007), and low PRS with aHR of 3.24 (1.61–6.53, p < 0.001), as well as high PRS with aHR of 2.43 (1.15–5.14, p = 0.019). Conclusion: A history of PTB is an important independent risk factor for COPD. Clinical staff should be aware of this risk factor in patients with prior PTB, particularly in countries or regions with high burdens of PTB. Plain language summary: Associations of prior pulmonary tuberculosis with the incident COPD Prior pulmonary tuberculosis (PTB) indicates that an individual has a history of PTB. The impact of prior PTB on the risk of incident chronic obstructive pulmonary disease (COPD) has not been studied in a large prospective cohort study of European population. Here, we investigated the association between prior PTB and risk of COPD in 216,130 participants from the UK biobank (a large biomedical database). After a median follow up of more than 12 years, 2,788 incident COPD cases were recorded. Individuals with prior PTB at baseline had an 87% higher risk of developing incident COPD compared to those without history of PTB. Specifically, individuals with prior PTB presented with a higher risk of incident COPD among those who were older than 50 years, male, obese, had a previous history of smoking, are currently drinking, have low physical activity, and have a low and high genetic predicted lung function. This study suggested prior PTB as an important and independent risk factor for COPD. Clinical staff should be aware of this risk factor in patients with prior PTB, particularly in countries or regions with high burdens of PTB. [ABSTRACT FROM AUTHOR]

This study applied a meta-analysis to evaluate the effects of adding Bacillus subtilis to the diet on the growth performance of broiler chickens, providing a theoretical basis for the application of Bacillus subtilis in poultry production. Relevant literature on the effects of Bacillus subtilis on the growth performance of broiler chickens published between January 1, 2017 and April 1, 2023 was retrieved and collected from databases such as CNKI, Wanfang, Web of Science, and PubMed.The meta-data analysis, subgroup analysis, and sensitivity analysis were conducted using Review Manager 5.4 and Stata 17, and related figures were drawn. The results showed that adding Bacillus subtilis to the diet can significantly increase the average daily gain (ADG) of broiler chickens [SMD=2.02, 95% CI (1.49, 2.55), P<0.000 01], the average daily feed intake (ADFI) [SMD=0.57, 95% CI (0.08, 1.06), P= 0.02<0.05], and decrease the feed conversion ratio (F/G) [SMD=-1.40, 95% CI (-2.05, -0.75), P<0.000 1]. To sum up, adding Bacillus subtilis to the diet can improve the ADG, ADFI, and F/G of broiler chickens, and enhance their growth performance. [ABSTRACT FROM AUTHOR]

OBJECTIVE: The rabbit model of steroid-induced osteonecrosis of femoral head is the most commonly used animal model of femoral head necrosis. The pathological changes of the femoral head are close to clinical practice, however, the conditions, methods and evaluation standards of animal models reported in and outside China are not uniform, which leads to the low scientific value of animal models and is difficult to popularize. This study aimed to clarify the influence of different mold-making conditions on the establishment of steroid-induced osteonecrosis of femoral head rabbit model and analyze the appropriate conditions for the successful model establishment. METHODS: We searched the CNKI, WanFang, VIP, CBM, WoS, PubMed and EMbsae databases for the literature on the modeling of steroid-induced osteonecrosis of femoral head rabbits up to April 1, 2022, completed the screening of the literature according to the inclusion and exclusion criteria and literature quality evaluation, and extracted the outcome index data in the literature. RevMan Stata and ADDIS statistical software were used to conduct a metaanalysis of the included data. RESULTS: (1) A total of 82 articles with 1 366 rabbits were included in the study. The steroid-induced osteonecrosis of femoral head modeling methods were divided into three types: steroid-alone method, steroid combined lipopolysaccharide method and steroid combined serum method. Among these, 33 articles used steroid-alone method; 20 articles used steroid combined lipopolysaccharide method; 29 articles used steroid combined serum method. (2) Meta-analysis results showed that the three modeling methods significantly increased the rate of empty bone lacunae in the femoral head of steroid-induced osteonecrosis of femoral head rabbits (P < 0.001), and significantly decreased the ratio of the trabecular bone area in the femoral head of steroid-induced osteonecrosis of femoral head rabbits (P < 0.001). The order of empty bone lacunae rate of each modeling method was: steroid combined with lipopolysaccharide method > steroid-alone method > steroid combined with serum method > normal group, and the order of trabecular bone area rate of each modeling method was: normal group > steroid combined with serum method > steroid-alone method > steroid combined with lipopolysaccharide method. (3) The results of subgroup analysis suggested that the rate of empty bone lacunae in the rabbit model induced by steroid alone might be related to the rabbit variety and the type of steroid used for modeling (difference between groups P < 0.05), in which the combined effect amount of New Zealand white rabbits was higher than that of Chinese white rabbits (P < 0.05) and Japanese white rabbits, and the combined effect amount of dexamethasone was higher than that of other steroids. The rate of empty bone lacunae induced by steroid combined with lipopolysaccharide was related to the administration mode of lipopolysaccharide and the type of steroid (P < 0.05), among which the combined effect of methylprednisolone sodium succinate was significantly higher than that of other steroids (P < 0.05), and the combined effect of prednisolone was significantly lower than that of other steroids (P < 0.05). The combined effect of lipopolysaccharide 100 μg/kg × twice was significantly lower than 10 μg/kg × twice and 50 μg/kg × twice (P < 0.05). The rate of empty bone lacunae in the model induced by steroid combined with serum was related to serum dose and steroid type (P < 0.05), among which the combined effect amount of dexamethasone sodium phosphate was significantly higher than other steroid types (P < 0.05), and the combined effect amount of dexamethasone was significantly lower than other steroid types (P < 0.05); the combined effect amount of serum “10 mL/kg+6 mL/kg” combined dose was lower than other serum doses (P < 0.05). CONCLUSION: (1) With the rate of empty bone lacunae and the ratio of trabecular bone area as the judgment standard for the successful establishment of the model, the three modeling methods can successfully construct the rabbit steroid-induced osteonecrosis of femoral head model, of which the steroid combined with lipopolysaccharide method is the best. (2) New Zealand white rabbits and dexamethasone are recommended when selecting the steroid-alone method. Methylprednisolone sodium succinate and low-dose lipopolysaccharide are recommended when selecting the steroid combined with lipopolysaccharide method. Dexamethasone sodium phosphate is recommended when selecting the steroid combined with serum modeling method. [ABSTRACT FROM AUTHOR]

Over the past three decades, a plethora of academic research has examined the impact of debt capital providers, proxied by leverage, on firms' sustainability reporting (SR) practices, indicating its relevance as a major determinant. Since the empirical literature remains inconclusive, we carried out the first comprehensive firm-level meta-analysis to reconcile the conflicting results from 112 studies involving 180 effect sizes across 32,953 firms spanning from 1989 to 2022. This provides a timely and up-to-date evaluation of the magnitude and nature of the engagement and influence of this significant stakeholder group on SR. Further, the study provides granular insights by dividing the overall effect on SR into three reporting dimensions—adoption, extent, and quality of reporting—to understand the impact of leverage on each and detail plausible reasons cited in the literature underpinning the positive or negative impact of debt providers on SR. The results show a positive significant impact of debt capital providers on SR, specifically, the adoption and extent of SR, but insignificant influence on SR quality, consistent with the findings of legitimacy theory. Debt capital providers' sustainability information needs remain limited to the "act" and "extent" of disclosure and concern for SR has not percolated to "ask for quality," indicative of a rather surface-level care for SR practices of firms. Regarding the strength of this stakeholder group and its funding power, greater activism, advocacy, and informational sensitivity are required to encourage firms to engage in meaningful SR practices. Subgroup analysis and meta-regression techniques were used to account for potential conceptual and study-based moderators. Significant discrepancies were observed due to differences in content of reported issues, type of firm, leverage proxies, the sample period, and publication quality. The study emphasizes the need for proactive measures among debt capital providers to counteract the limited positive impact of leverage on sustainability reporting. By identifying research gaps and exploring implications for debt providers and companies, this study highlights how ESG-sensitive lenders can potentially steer firms towards quality SR practices. It offers valuable insights that could inform policy changes, foster collaboration, and advance the practice of sustainability-oriented lending. [ABSTRACT FROM AUTHOR]

Objective: The necessity of postmastectomy radiotherapy(PMRT) for patients with HR+/HER2 T1-2 N1M0 breast cancer remains controversial. We want to use explainable machine learning to learn the feature importance of the patients and identify the subgroup of the patients who may benefit from the PMRT. Additionally, develop tools to provide guidance to the doctors. Methods: In this study, we trained and validated 2 machine learning survival models: deep learning neural network and Cox proportional hazard model. The training dataset consisted of 35,347 patients with HR+/HER2- T1-2 N1M0 breast cancer who received mastectomies from the SEER database from 2013 to 2018. The performance of survival models were assessed using a concordance index (c-index). Then we did subgroup analysis to identify the subgroup who could benefit from PMRT. We also analyzed the global feature importance for the model and individual feature importance for individual survival prediction. Finally, we developed a Cloud-based recommendation system for PMRT to visualize the survival curve of each treatment plan and deployed it on the Internet. Results: A total of 35,347 patients were included in this study. We identified that radiotherapy improved the OS in patients with tumor size >14mm and age older than 54: 5-year OS rates of 91.9 versus 87.2% (radio vs. nonradio, P <0.001) and cohort with tumor size >14mm and grade worse than well-differentiated, 5-year OS rates of 90.8 versus 82.3% (radio vs. nonradio, P <0.001). The deep learning network performed more stably and accurately in predicting patients survival than the random survival forest and Cox proportional hazard model on the internal test dataset (C-index=0.776 vs 0.641) and in the external validation(Cindex= 0.769 vs 0.650). Besides, the deep learning model identified several key factors that significantly influence patient survival, including tumor size, examined regional nodes, age at 45-49 years old and positive regional nodes (PRN). Conclusion: Patients with tumor size >14mm and age older than 54 and cohort with tumor size >14mm and grade worse than well-differentiated could benefit from the PMRT. The deep learning network performed more stably and accurately in predicting patients survival than Cox proportional hazard model on the internal test. Besides, tumor size, examined regional nodes, age at 45-49 years old and PRN are the most significant factors to the overall survival (OS). [ABSTRACT FROM AUTHOR]

To characterize sleep duration and investigate its association with quality of life among Parkinson's Disease (PD) patients. In this multicenter cross-sectional study, 970 PD patients were divided into five groups based on self-reported sleep duration: <5, ≥5 to <6, ≥6 to <7, ≥7 to ≤8, and >8 h. The quality of life was evaluated using the 39-Item Parkinson's Disease Questionnaire (PDQ-39). Multivariable linear regression analysis, subgroup analysis, and mediation analysis were conducted to examine the association between sleep duration and quality of life. In multivariable linear regression model, patients with sleep duration (<5 h) had significantly higher PDQ-39 scores (β = 8.132, 95 % CI: 3.99 to 12.266), especially in mobility, activities of daily living, emotional well-being, stigma, social support, cognition, communication, and bodily discomfort (p < 0.05). The association between sleep duration (<5 h) and worse quality of life was more pronounced in patients with higher HY stage, longer disease duration, and sleep disorders. Moreover, a significant indirect effect of sleep duration (<5 h) on quality of life was observed, with UPDRS I, UPDRS II, and UPDRS IV scores acting as mediators. Short sleep duration (<5 h) is associated with worse quality of life among PD patients. This association was stronger among patients with advanced PD and sleep disorders, while non-motor symptoms and motor complications were identified as significant mediators in this association. These findings highlight the significance of adequate sleep duration and suitable interventions for sleep may help improve quality of life. • There is a high prevalence of short sleep duration among PD patients. • There is a significant association between short sleep duration (<5 h) and a decline in quality of life. • Non-motor symptoms and motor complications were identified as significant mediators in this association. [ABSTRACT FROM AUTHOR]

Background: There is an ongoing debate over the prognostic value of the number of examined lymph nodes (ELNs) in cases of gastric signet-ring cell cancer (GSRCC). In this study, we sought to evaluate the correlation between the number of ELNs and the prognosis of GSRCC and identify the optimal number of ELNs. Methods: A total of 1020 patients diagnosed with GSRCC between 2011 and 2018 in the National Cancer Center database were identified. Clinicopathological characteristics were retrospectively collected, and optimal cutoff values of ELNs were calculated by using X-tile. The impact of different ELNs on overall survival (OS) was compared by using Kaplan–Meier curves. We used univariate and multivariate Cox and subgroup analyses to explore the relationship between ELNs and OS. Furthermore, nonlinear correlations were investigated by using restricted cubic splines (RCSs). Results: X-tile showed that the optimal cutoff value of ELNs was 22. The 5-year OS was higher for patients with ELNs > 22 (vs. ELNs ≤ 22, 66.9% vs. 74.9%, P = 0.026). Multivariate Cox analyses showed that high ELNs were associated with superior OS (hazard ratio = 0.56, 95% confidence interval 0.43–0.74, P < 0.001). In subgroup analyses, the significant association between tumor size > 4 cm, and TNM III stage was still observed. The RCS regression model showed a U-shaped dose–response nonlinear relationship between ELNs and OS; the inflection point, as well as the lowest risk points, corresponded to 44–52 ELNs. Conclusions: A U-shaped, nonlinear correlation with inflection points of 44–52 ELNs between ELNs and prognosis in GSRCC was identified. [ABSTRACT FROM AUTHOR]

Introduction: Current guidelines recommendations regarding chemotherapy in small (T1b and T1c), node-negative triple-negative breast cancer (TNBC) differ due to lack of high-quality data. Our study aimed to assess the benefit of adjuvant chemotherapy in patients with T1bN0M0 and T1cN0M0 TNBC. Methods: We obtained data from the Surveillance, Epidemiology, and End Results database for patients with node-negative, T1b/T1c TNBC diagnosed between 2010 and 2020. Logistic regresion models assessed variables associated with chemotherapy administration. We evaluated the effect of chemotherapy on overall survival (OS) and breast cancer specific survival (BCSS) with Kaplan-Meier methods and Cox proportional hazards methods. Results: We included 11,510 patients: 3,388 with T1b and 8,122 with T1c TNBC. During a median follow-up of 66 months, 305 patients with T1b and 995 with T1c died. After adjusting for clinicopathological, demographic and treatment factors, adjuvant chemotherapy improved OS in T1b TNBC (HR, 0.52; 95% CI, 0.41–0.68 p < 0.001) but did not improve BCSS (HR, 0.70; 95% CI, 0.45–1.07; p = 0.10); the association between chemotherapy and BCSS was not statistically significant in any subgroup. In T1c TNBC, adjuvant chemotherapy improved OS (HR, 0.54; 95% CI, 0.47–0.62; p < 0.001) and BCSS (HR, 0.79; 95% CI, 0.63–0.99; p = 0.043); the benefit of chemotherapy in OS varied by age (Pinteraction=0.024); moreover, the benefit in BCSS was similar in all subgroups. Conclusions: Our study results support the use of adjuvant chemotherapy in patients with node-negative, T1c TNBC. Patients with node-negative, T1b TNBC had excellent long-term outcomes; furthermore, chemotherapy was not associated with improved BCSS in these patients. [ABSTRACT FROM AUTHOR]

Methods for extending—generalizing or transporting—inferences from a randomized trial to a target population involve conditioning on a large set of covariates that is sufficient for rendering the randomized and nonrandomized groups exchangeable. Yet, decision makers are often interested in examining treatment effects in subgroups of the target population defined in terms of only a few discrete covariates. Here, we propose methods for estimating subgroup-specific potential outcome means and average treatment effects in generalizability and transportability analyses, using outcome model--based (g-formula), weighting, and augmented weighting estimators. We consider estimating subgroup-specific average treatment effects in the target population and its nonrandomized subset, and we provide methods that are appropriate both for nested and non-nested trial designs. As an illustration, we apply the methods to data from the Coronary Artery Surgery Study (North America, 1975–1996) to compare the effect of surgery plus medical therapy versus medical therapy alone for chronic coronary artery disease in subgroups defined by history of myocardial infarction. [ABSTRACT FROM AUTHOR]

The identification and estimation of heterogeneous treatment effects in biomedical clinical trials are challenging, because trials are typically planned to assess the treatment effect in the overall trial population. Nevertheless, the identification of how the treatment effect may vary across subgroups is of major importance for drug development. In this work, we review some existing simulation work and perform a simulation study to evaluate recent methods for identifying and estimating the heterogeneous treatments effects using various metrics and scenarios relevant for drug development. Our focus is not only on a comparison of the methods in general, but on how well these methods perform in simulation scenarios that reflect real clinical trials. We provide the R package benchtm that can be used to simulate synthetic biomarker distributions based on real clinical trial data and to create interpretable scenarios to benchmark methods for identification and estimation of treatment effect heterogeneity. [ABSTRACT FROM AUTHOR]

Background: Previously, overall comparable outcomes were seen for balloon-expandable (BE) or self-expanding (SE) transfemoral transcatheter aortic valve replacement (TAVR). However, subgroup analyses based on large case numbers are still needed. Methods: German national data of all BE and SE transfemoral TAVR treating aortic valve stenosis in 2019 and 2020 were analysed. We then compared different outcomes and performed a subgroup analysis for the endpoint in-hospital mortality. Results: Overall, 46,243 TAVR were analysed, 19,910 BE, and 26,333 SE. Patients in the SE group had a significantly higher logistic EuroSCORE (13.61 vs 12.66%, p < 0.001), age (81.55 vs 79.99a, p < 0.001), and proportion of women (54.82 vs 40.06%, p < 0.001). Both groups showed a similar in-hospital mortality with 2.37% in BE and 2.35% in SE (p = 0.916). In-hospital mortality also did not differ significantly after risk adjustment (OR = 0.98 [0.86, 1.13], p = 0.799). Patients in the SE group had a significantly lower risk of major bleeding (OR = 0.83 [0.73, 0.95], p = 0.006), but a significantly higher risk of stroke (OR = 1.38 [1.19, 1.59], p < 0.001), delirium (OR = 1.15 [1.06, 1.24], p = 0.001), and permanent pacemaker implantation (OR = 1.29 [1.21, 1.37], p < 0.001). In the subgroup analysis of in-hospital mortality, there were no significant differences in any of the observed subgroups (age < 75/75–79/80–84/ ≥ 85a, logistic EuroSCORE < 4/4– < 9/ ≥ 9, gender, NYHA III/IV, previous CABG, peripheral vascular disease, COPD, pulmonary hypertension, renal disease GFR < 30 ml/min, and diabetes mellitus). Conclusion: In the direct comparison of balloon-expandable and self-expanding TAVR, there are no differences for in-hospital mortality in subgroups. [ABSTRACT FROM AUTHOR]

This paper addresses patient heterogeneity associated with prediction problems in biomedical applications. We propose a systematic hypothesis testing approach to determine the existence of patient subgroup structure and the number of subgroups in patient population if subgroups exist. A mixture of generalized linear models is considered to model the relationship between the disease outcome and patient characteristics and clinical factors, including targeted biomarker profiles. We construct a test statistic based on expectation maximization (EM) algorithm and derive its asymptotic distribution under the null hypothesis. An important computational advantage of the test is that the involved parameter estimates under the complex alternative hypothesis can be obtained through a small number of EM iterations, rather than optimizing the objective function. We demonstrate the finite sample performance of the proposed test in terms of type-I error rate and power, using extensive simulation studies. The applicability of the proposed method is illustrated through an application to a multicenter prostate cancer study.