Apatinib Plus Toripalimab (Anti-PD1 Therapy) as Second-Line Therapy in Patients With Advanced Gastric or Esophagogastric Junction Cancer: Results From a Randomized, Open-Label Phase II Study.

BACKGROUND: This study aimed to assess the activity of apatinib plus toripalimab in the second line for patients with advanced gastric or esophagogastric junction cancer (GC/EGJC). METHODS: In this open-label, phase II, randomized trial, patients with advanced GC/EGJC who progressed after first-line chemotherapy were enrolled and received 250 mg apatinib per day plus 240 mg toripalimab on day 1 per 3 weeks (arm A) or physician's choice of chemotherapy (PC, arm B). The primary endpoint of this study was the 1-year survival rate. Progression-free survival (PFS), overall survival (OS), overall response rate (ORR), and safety were assessed as secondary endpoints. RESULTS: Twenty-five patients received apatinib plus toripalimab while 26 were enrolled in arm B. The 1-year survival rates of the 2 groups were 43.3% and 42.3%, respectively (P = .903). The PFS was 2.77 versus 2.33 months (P = .660). The OS was 8.30 versus 9.88 months (P = .539). An objective response was reported in 20.0% of patients in arm A compared to 26.9% in arm B (P = .368), respectively. A total of 6 (24.0%) patients experienced adverse events of grade ≥ 3 in arm A, while 9 (34.6%) patients suffered from adverse events of grade ≥ 3 in arm B. No drug-related deaths occurred in either group. CONCLUSION: Toripalimab plus apatinib treatment in second-line therapy of advanced GC/EGJC showed manageable toxicity but did not improve clinical outcomes relative to PC treatment (ClinicalTrials.gov Identifier: NCT04190745).

BHAFT: Bayesian heredity-constrained accelerated failure time models for detecting gene-environment interactions in survival analysis.

In addition to considering the main effects, understanding gene-environment (G × E) interactions is imperative for determining the etiology of diseases and the factors that affect their prognosis. In the existing statistical framework for censored survival outcomes, there are several challenges in detecting G × E interactions, such as handling high-dimensional omics data, diverse environmental factors, and algorithmic complications in survival analysis. The effect heredity principle has widely been used in studies involving interaction identification because it incorporates the dependence of the main and interaction effects. However, Bayesian survival models that incorporate the assumption of this principle have not been developed. Therefore, we propose Bayesian heredity-constrained accelerated failure time (BHAFT) models for identifying main and interaction (M-I) effects with novel spike-and-slab or regularized horseshoe priors to incorporate the assumption of effect heredity principle. The R package rstan was used to fit the proposed models. Extensive simulations demonstrated that BHAFT models had outperformed other existing models in terms of signal identification, coefficient estimation, and prognosis prediction. Biologically plausible G × E interactions associated with the prognosis of lung adenocarcinoma were identified using our proposed model. Notably, BHAFT models incorporating the effect heredity principle could identify both main and interaction effects, which are highly useful in exploring G × E interactions in high-dimensional survival analysis. The code and data used in our paper are available at https://github.com/SunNa-bayesian/BHAFT.

Visceral adiposity associated with incidence and development trajectory of cardiometabolic diseases: A prospective cohort study.

BACKGROUND AND AIMS: There is a lack of literature concerning the effects of visceral adipose on the development of first cardiometabolic disease (FCMD) and its subsequent progression to cardiometabolic multimorbidity (CMM) and mortality. METHODS AND RESULTS: 423,934 participants from the UK Biobank with different baseline disease conditions were included in the analysis. CMM was defined as the simultaneous presence of coronary heart disease, T2D, and stroke. Visceral adiposity was estimated by calculating the visceral adiposity index (VAI). Multistate models were used to assess the effect of visceral adiposity on the development of CMM. During a median follow-up of 13.5 years, 50,589 patients had at least one CMD, 6131 were diagnosed with CMM, whereas 24,634 patients died. We observed distinct roles of VAI with respect to different disease transitions of CMM. HRs (95 % CIs) of high VAI were 2.35 (2.29-2.42) and 1.64 (1.50-1.79) for transitions from healthy to FCMD and from FCMD to CMM, and 0.97 (0.93-1.02) for all-cause mortality risk from healthy, FCMD and CMM, respectively. CONCLUSIONS: Our study provides the first evidence that visceral adipose may contribute to the development of FCMD and CMM in healthy participants. However, visceral adipose may confer resistance to all-cause mortality in participants with existing CMD or CMM. A better understanding of the relationship between visceral adipose and CMM can focalize further investigations on patients with CMD with high levels of visceral fat and help take targeted preventive measures to reduce the medical burden on individual patients and society.

Trajectories of quality of life and cognition in different multimorbidity patterns: Evidence from SHARE.

OBJECTIVES: The study aimed to observe the trajectory of quality of life (QoL) and cognition, and to a analyze the bidirectional association between cognition and QoL for diverse multimorbidity patterns. METHODS: In total, 16,153 older participants age ≥50 years were included from the Survey of Health, Ageing and Retirement in Europe (SHARE). We used latent class analysis (LCA) to identify multimorbidity patterns in the baseline population. We used linear mixed models (LMM) to examine the trajectory of cognition and QoL in different multimorbidity patterns. A cross-lagged model was employed to analyze the bidirectional association between cognition and QoL in diverse multimorbidity patterns. RESULTS: Latent class analysis identified four multimorbidity patterns: high and low comorbidity burden (HC and LC), cardiometabolic (CA), and osteoarthrosis (OS). The HC group had the poorest cognitive function and QoL (p for trend < 0.001). Delayed and immediate episodic memory in the OS group declined at a highest rate (p for trend < 0.001). Additionally, a bidirectional association between cognition and QoL was observed. The effect of cognitive function on QoL was relatively stronger than the reverse in the CA and LC groups. CONCLUSIONS: The rate of decline in cognition and QoL over the time differs in diverse multimorbidity patterns, and patients with four or more chronic diseases should be specially considered. Notably, early monitoring of cognitive function and can help break the vicious cycle between cognitive deterioration and poor QoL in patients with OS or CA diseases.

Association of healthy lifestyle factors and genetic liability with bipolar disorder: Findings from the UK Biobank.

BACKGROUND: The interplay between genetic and lifestyle factors in the development of bipolar disorder (BD) remains unclear. METHODS: A cohort study was carried out on 365,517 participants from the UK Biobank. Lifestyle scores, based on smoking, physical activity, diet, alcohol consumption, sedentary behavior, sleep duration, and social contact, were grouped as favorable (scores 6-7), intermediate (scores 4-5), or unfavorable (scores 0-3). The BD polygenic risk score (PRS) was also categorized into high, intermediate, and low-risk groups using PRS tertiles. Cox regression models determined hazard ratios (HRs) and 95 % confidence intervals (CIs) for BD. RESULTS: During the 12.9-year follow-up, 529 individuals developed BD. Comparing those with favorable lifestyles to those with unfavorable participants, the HR of developing BD was 3.28 (95 % CI, 2.76-3.89). Similarly, individuals with a high PRS had a risk of 3.20 (95 % CI, 2.83-3.63) compared to those with a low PRS. Notably, individuals with both a high PRS and an unfavorable lifestyle had a significantly higher risk of BD (HR = 6.31, 95 % CI, 4.14-9.63) compared to those with a low PRS and a favorable lifestyle. Additionally, the interaction between PRS and lifestyle contributed an additional risk, with a relative excess risk of 1.74 (95 % CI, 0.40-3.07) and an attributable proportion due to the interaction of 0.37 (95 % CI, 0.16-0.58). CONCLUSIONS: Our findings suggest that genetic liability for BD, measured as PRS, and lifestyle have an additive effect on the risk of developing BD. A favorable lifestyle was associated with a reduced risk of developing BD.