NecroGlobalGCN: Integrating micronecrosis information in HCC prognosis prediction via graph convolutional neural networks.

BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma (HCC) ranks fourth in cancer mortality, underscoring the importance of accurate prognostic predictions to improve postoperative survival rates in patients. Although micronecrosis has been shown to have high prognostic value in HCC, its application in clinical prognosis prediction requires specialized knowledge and complex calculations, which poses challenges for clinicians. It would be of interest to develop a model to help clinicians make full use of micronecrosis to assess patient survival. METHODS: To address these challenges, we propose a HCC prognosis prediction model that integrates pathological micronecrosis information through Graph Convolutional Neural Networks (GCN). This approach enables GCN to utilize micronecrosis, which has been shown to be highly correlated with prognosis, thereby significantly enhancing prognostic stratification quality. We developed our model using 3622 slides from 752 patients with primary HCC from the FAH-ZJUMS dataset and conducted internal and external validations on the FAH-ZJUMS and TCGA-LIHC datasets, respectively. RESULTS: Our method outperformed the baseline by 8.18% in internal validation and 9.02% in external validations. Overall, this paper presents a deep learning research paradigm that integrates HCC micronecrosis, enhancing both the accuracy and interpretability of prognostic predictions, with potential applicability to other pathological prognostic markers. CONCLUSIONS: This study proposes a composite GCN prognostic model that integrates information on HCC micronecrosis, collecting large dataset of HCC histopathological images. This approach could assist clinicians in analyzing HCC patient survival and precisely locating and visualizing necrotic tissues that affect prognosis. Following the research paradigm outlined in this paper, other prognostic biomarker integration models with GCN could be developed, significantly enhancing the predictive performance and interpretability of prognostic model.

Housing Adaptations and Long-Term Care Facility Admissions Among Older Adults With Care Needs in Japan.

OBJECTIVES: Housing adaptations may contribute to aging in place for older adults with care needs by reducing the risk of long-term care facility (LTCF) admissions, but this association remains unclear. We examined the association between housing adaptations and LTCF admissions among older adults with care needs. DESIGN: Retrospective cohort study using data from a Japanese municipality. SETTING/PARTICIPANTS: Adults aged ≥65 years who were newly certified with care needs under the public long-term care insurance system between April 2014 and March 2016. METHODS: The study exposure was the implementation of insurance-covered housing adaptations (maximum covered cost: ∖200,000) during the 2 years after certification. Based on this exposure, participants were assigned to a non-implementation group (no housing adaptations), sub-maximum cost group (housing adaptations below the maximum cost), or maximum cost group (housing adaptations at the maximum cost). A Fine-Gray subdistribution hazards model was used to analyze the associations between the exposure groups and new LTCF admissions after adjusting for various risk factors. Death was regarded as a competing risk, and participants were followed until March 2022. RESULTS: Among 4610 participants, 1261 (27.3%) had implemented housing adaptations. Among these, 943 (74.8%) were in the sub-maximum cost group and 318 (25.2%) were in the maximum cost group. During the follow-up period (median: 51 months), the incidence of LTCF admission was 3.9/1000 person-months in the non-implementation group, 3.8/1000 person-months in the sub-maximum cost group, and 2.8/1000 person-months in the maximum cost group. The adjusted subdistribution hazard ratio of LTCF admission (reference: non-implementation) was 0.90 (95% CI: 0.75-1.08) for the sub-maximum cost group and 0.67 (0.49-0.93) for the maximum cost group. CONCLUSIONS AND IMPLICATIONS: Housing adaptations can support aging in place for older adults with care needs. Health care professionals and policymakers should consider the suitability of housing environments to reduce the risk of institutionalization.

Characteristics, efficacy, and prognosis analysis of newly diagnosed marginal zone lymphoma.

Objective: To retrospectively analyze the characteristics of newly diagnosed marginal zone lymphoma (MZL) patients, evaluate the efficacy of different treatment regimens, and explore prognostic factors in the era of immunotherapy. Methods: We reviewed the clinical data of newly diagnosed MZL patients treated at the Department of Hematology, The First Hospital of Jilin University, from October 2013 to October 2023. Survival differences between groups were analyzed using the log-rank test, and prognostic factors were identified. Results: A total of 265 newly diagnosed MZL patients were included, with a median age of 59 years (range 22-90). The most common pathological type was mucosa-associated lymphoid tissue (MALT) lymphoma, accounting for 66.0% of cases. Among the 147 MZL patients included in the efficacy analysis, the median follow-up was 43.4 months. Both the median progression-free survival (PFS) and overall survival (OS) were not reached. The 5-year PFS and OS rates were 76.0% and 86.6%, respectively. Patients who achieved complete response (CR) after induction therapy had significantly better PFS (P=0.0045), OS (P<0.001), and time to next treatment (TTNT) (P=0.0045) compared to those who did not achieve CR. A subgroup analysis was conducted on 51 MZL patients with high tumor burden who received ≥4 cycles of treatment. It was found that the CR rate (CRR) in patients receiving obinutuzumab (G) ± chemotherapy was significantly higher than in those receiving rituximab (R) ± chemotherapy (93.8% vs. 48.6%, P=0.002). Multivariate analysis revealed that disease progression or death within 24 months of initial treatment (POD24) was an independent risk factor affecting OS (P<0.001). Patients who experienced POD24 had a median survival of only 19.7 months, with a 3-year OS rate of just 37.6%, whereas those without POD24 had a 3-year OS rate of 97.3%. Conclusion: MZL is predominantly seen in middle-aged and elderly patients and is a specific indolent B-cell lymphoma, with MALT lymphoma being the most common subtype. Achieving CR after induction therapy significantly prolongs survival in MZL patients. Compared to R ± chemotherapy, G ± chemotherapy achieves a higher CRR in high tumor burden MZL patients. In the era of immunotherapy, POD24 is an independent prognostic factor for MZL.

Testing for Sufficient Follow-Up in Censored Survival Data by Using Extremes.

In survival analysis, it often happens that some individuals, referred to as cured individuals, never experience the event of interest. When analyzing time-to-event data with a cure fraction, it is crucial to check the assumption of "sufficient follow-up," which means that the right extreme of the censoring time distribution is larger than that of the survival time distribution for the noncured individuals. However, the available methods to test this assumption are limited in the literature. In this article, we study the problem of testing whether follow-up is sufficient for light-tailed distributions and develop a simple novel test. The proposed test statistic compares an estimator of the noncure proportion under sufficient follow-up to one without the assumption of sufficient follow-up. A bootstrap procedure is employed to approximate the critical values of the test. We also carry out extensive simulations to evaluate the finite sample performance of the test and illustrate the practical use with applications to leukemia and breast cancer data sets.

Think before you pop: Outcomes of non-operative management of ureteroceles.

INTRODUCTION/BACKGROUND: Ureteroceles are often diagnosed antenatally and incidentally and treated in a minimally invasive fashion with endoscopic puncture. Recent literature suggests that observation, or non-operative management, is an effective and viable management option in select patients with ureteroceles and certain radiologic findings, however there is no consensus on how to best select patients for non-operative management. OBJECTIVE: To 1) determine if pediatric ureteroceles managed non-operatively require less or sooner secondary surgical intervention than those managed with up-front incision, 2) describe characteristics of success and failure in pediatric ureteroceles managed non-operatively, and 3) identify risk factors associated with receiving intervention and time to intervention. RESULTS: Of 287 ureteroceles, 65 (23%) were managed non-operatively and underwent secondary surgical intervention less frequently (9% vs. 34%, P < 0.01) and later (median age 40 vs. 20 months) than those managed with puncture. Successful non-operative management was associated with fewer comorbidities, smaller ureterocele size, absence of vesicoureteral reflux (VUR) and high-grade VUR, single collecting system, lesser degree of hydronephrosis, ipsilateral MCDK and intravesical location. For all ureteroceles, high-grade VUR, duplex system, and female sex were associated with shorter time to secondary intervention (intervention after initial management). DISCUSSION: In the largest retrospective review of ureterocele management, smaller ureterocele size, absence of high-grade VUR, single system, ipsilateral MCDK and minimal hydronephrosis were factors that increased the efficacy of non-operative management of select pediatric ureteroceles. Furthermore, time to event analysis showed that non-operative management did not predispose patients to sooner secondary intervention (Figure). Lack of a standardized protocol for ureterocele management is a limitation of this single institution retrospective study as it introduces selection bias to the results, however few patients with low risk characteristics underwent puncture and no high risk patients were observed. CONCLUSION: Smaller ureterocele size, absence of high-grade VUR, single system, ipsilateral MCDK and minimal hydronephrosis are factors that may increase the efficacy of non-operative management of select pediatric ureteroceles, which may delay or avoid secondary surgical intervention.

Machine learning for post-liver transplant survival: Bridging the gap for long-term outcomes through temporal variation features.

BACKGROUND: The long-term survival of liver transplant (LT) recipients is essential for optimizing organ allocation and estimating mortality outcomes. While models like the Model-for-End-Stage-Liver-Disease (MELD) predict 90-day mortality on the waiting list, they do not predict post-LT survival accurately. There is a need for predictive models that can forecast post-LT survival beyond the immediate period after transplantation. METHOD: This study introduces new temporal variation features for predicting post-LT survival during the waiting list period. Cox Proportional-Hazards regression (CoxPH), Random Survival Forest (RSF), and Extreme Gradient Boosting (XGB) models are utilized, along with patient demographics and waiting list duration. Data from 716 LT patients from the University of Minnesota CTSI (2011-2021) are used to develop, evaluate, and compare post-LT survival prediction models. RESULTS: The temporal variation features, particularly when combined with the RSF model, proved most effective in predicting post-LT survival, with a C-index of 0.71 and an IBS of 0.151. This outperformed the predictive capability of the most recent MELD score, which had a C-index of <0.51 in the same cohort. CONCLUSIONS: Incorporating temporal variation features with the RSF model enhances long-term post-LT survival predictions. These insights can assist clinicians and patients in making more informed decisions about organ allocation and understanding the utility of LT, ultimately leading to improved patient outcomes.

Overall Survival and Treatment Patterns Among Patients With Warm Autoimmune Hemolytic Anemia in Sweden: A Nationwide Population-based Study.

OBJECTIVES: Warm autoimmune hemolytic anemia (wAIHA) is a rare autoantibody-mediated disorder, and first-line treatment primarily relies on corticosteroids. This study assessed overall survival (OS) and treatment patterns of wAIHA in Sweden. METHODS: Adults with ≥ 1 primary diagnosis code for wAIHA (or AIHA plus oral corticosteroids (OCS)/immunosuppressants as sensitivity analyses) between 2011 and 2022 were identified from five Swedish national registers and linked through each patient's unique identity number. Kaplan-Meier curves with log-rank tests and Cox regressions were performed to assess OS for patients with primary versus secondary wAIHA and patients with wAIHA and long-term versus short-term (≥ 3 vs. < 3 months) OCS users. RESULTS: The main analysis included 292 patients; 1791 patients were included in the sensitivity analysis. At a median 3.7-year follow-up, a median OS in primary wAIHA was not reached versus 6.0 years for secondary wAIHA (log-rank test: p = 0.003). Subgroup analyses showed no significant difference in risk of death between long-term and short-term OCS users; however, in the sensitivity analysis, long-term OCS users showed significantly higher risk of death (adjusted hazard ratio: 1.45; 95% confidence interval: 1.180, 1.781; p < 0.001) versus short-term OCS users. CONCLUSION: Secondary wAIHA or long-term OCS use was associated with lower OS, underscoring the disease burden and unmet need for efficacious wAIHA treatments.

Association of Pre-Existing Type 2 Diabetes on Kidney Transplant Outcomes and Factors Correlating With Survival: A Single-Center Analysis.

INTRODUCTION: Kidney transplantation (KT) is the treatment of choice for end-stage renal disease. Diabetes mellitus is the most common indication for KT, with most recipients having type 2 diabetes mellitus (T2DM). Previous studies have shown inferior patient survival in T2DM KT recipients. This single-center study aimed to understand the individual factors associated with negative long-term outcomes. METHODS: This is a single-center retrospective analysis of adult KT recipients, with and without T2DM from 2012 to 2017 with a follow-up through December 2022. Primary Outcomes were graft loss and patient survival. Univariate, Multivariate Cox regression, and Kaplan-Meier analyses were used to assess KT outcomes. RESULTS: We analyzed 1185 patients, 288 (24.3%) with T2DM. T2DM patients tended to be older, 56.6 ± 9.8 versus 47.1 ± 13.7 y. (P < 0.01), male (66.3% versus 58.2% P < 0.001) had a higher body mass index, 31.3 ± 5.4 versus 27.4 ± 5.7 P < 0.01) and less likely to get a living donor transplant (46.5% versus 58.4%, P < 0.01). T2DM patients after KT had a 50% higher risk for graft loss (hazard ratio 1.509, 95% CI 1.15-1.95, P < 0.001) and a 106% higher risk of death (hazard ratio 2.06 (95% CI 1.48-2.87, P < 0.0001). Among the T2DM patients, the most common cause of death was infection (39.9%). The average HbA1c at 1 y after transplant was 7.8%. CONCLUSIONS: The present study shows that T2DM is strongly associated with an increased risk of graft loss and death after KT, particularly in older recipients of deceased donor transplants with longer cold ischemia time that experience delayed graft function. This underscores the importance of avoiding delayed graft function in older, type 2 diabetic kidney transplant recipients and prioritizing living donors.

T cell exhaustion methylation signature drives differential immune responses in glioblastoma.

BACKGROUND: Methylation-related signatures play crucial roles in tumorigenesis and progression. However, their roles in the immune response in primary glioblastoma (GBM) remains unclear. METHODS: We analyzed the differential expression of specific members of T cell exhaustion-related pathways in GBM from the perspective of T cell exhaustion. We further screened for significantly negatively correlated methylation sites as candidate methylation markers for T cell exhaustion. Using consensus clustering, we divided the samples into two categories with significant differences in overall survival (OS). We then performed univariate and multivariate Cox regression analyses to construct the T Cell Exhaustion Methylation (TEXM) signature. Finally, we confirmed that this signature served as an independent prognostic factor, and further characterized it in terms of drug resistance and immunotherapy. RESULTS: We identified 95 significantly differentially expressed T cell exhaustion-related genes and 51 methylation markers associated with T cell exhaustion. The cancer samples were classified according to methylation site markers, thus indicating two subtypes with significant differences in OS: subtype A and subtype B. Tumor scores, stromal scores, tumor purity, and ESTIMATE scores all showed significant differences between subtypes (P < 0.05). Univariate Cox regression analysis identified five methylation sites significantly associated with OS, and multivariate Cox regression analysis was used to construct the TEXM signature model by using these five methylation sites. Significant differences in OS were found between the groups with high and low TEXM signature scores, on the basis of calculation of the TEXM signature scores of tumor samples and using the median score to divide them into high and low score groups. Survival analysis revealed that the high score group had poorer OS and DFS than the low score group in the validation set. Notably, we observed a significant difference in drug sensitivity between the high and low TEXM signature score groups, with the high score group showing higher drug resistance and poorer prognosis. The tumor immune state, as predicted with Tracking Tumor Immunophenotype (TIP), revealed significant differences in antitumor immune scores between the high and low TEXM signature score groups. Finally, we identified 43 significantly differentially regulated metabolism-associated biological processes. CONCLUSION: The epigenetic methylation-related TEXM signature plays a key role in driving differential immune responses in GBM.

Prognostic factors for premature cardiovascular disease mortality in Malaysia: a modelling approach using semi-parametric and parametric survival analysis with national health and morbidity survey linked mortality data.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of premature mortality worldwide. Despite existing research on CVD risk factors, the study of premature CVD mortality in Malaysia remains limited. This study employs survival analysis to model modifiable risk factors associated with premature CVD mortality among Malaysian adults. METHOD: We utilised data from Malaysia's National Health and Morbidity Survey (NHMS) conducted in 2006, 2011, and 2015, linked with mortality records. The cohort comprised individuals aged 18 to 70 during the NHMS interview. Follow-up extended to 2021, focusing on CVD-related premature mortality between ages 30 and 70. We employed six survival models: a semi-parametric Cox proportional hazard (PH) and five parametric survival models, which were Exponential, Weibull, Gompertz, log-normal and log-logistic distributions using R software. The age standardized incidence rate (ASIR) of premature CVD mortality was calculated per 1000 person-years. RESULTS: Among 63,722 participants, 886 (1.4%) experienced premature CVD mortality, with an ASIR of 1.80 per 1000 person-years. The best-fit models (based on AIC value) were the stratified Cox model by age (semi-parametric) and the log-normal accelerated failure time (AFT) model (parametric). Males had higher risk (Hazard Ratio, HR = 2.68) and experienced 49% shorter survival time (Event Time Ratio, ETR = 0.51) compared to females. Compared to Chinese ethnicity, Indians, Malays, and other Bumiputera had higher HR and lower survival times. Rural residents and those with lower education also faced increased HRs and reduced survival times. Diabetes (diagnosed: HR = 3.26, ETR = 0.37; undiagnosed: HR = 1.63, ETR = 0.63), hypertension (diagnosed: HR = 1.84, ETR = 0.53; undiagnosed: HR = 1.46, ETR = 0.68), and undiagnosed hypercholesterolemia (HR = 1.31, ETR = 0.80) increased risk and decreased survival times. Additionally, current smoking and abdominal obesity elevated risk (HR = 1.38, 1.60) and shortened survival (ETR = 0.81, 0.71). CONCLUSION: The semi-parametric and parametric survival models both highlight the considerable impact of socioeconomic status and modifiable risk factors on premature CVD mortality, underscoring the imperative for targeted interventions to effectively mitigate these effects.

Survival analysis of primary molars following pulpectomy performed under dental general anesthesia: a five-year retrospective study.

BACKGROUND: Currently, the indications for pulpectomy of primary molars performed under dental general anesthesia vary across countries. Therefore, we retrospectively investigated the five-year survival rate of primary molars following pulpectomy performed under dental general anesthesia and the impact of this treatment on permanent successors, assessed the risk factors related to overall survival and clarified the indications for pulpectomy. METHODS: The medical records of children receiving pulpectomy of primary molars under dental general anesthesia from August 1, 2013, to November 30, 2023, were reviewed. Potential risk factors, including gender, age, general health, tooth type, tooth location, endodontic diagnosis and quality of root filling, were assessed via univariate and multivariate Cox proportional hazards regression models, and the survival rate was examined via the Kaplan‒Meier technique. Moreover, the rate of resorption of the root canal filling materials, degree of resorption of the overfilled/over-extended root canal filling materials and development of permanent successors were assessed by clinical and radiographic examination. RESULTS: The study included 320 teeth from 161 children (86 boys and 75 girls). The overall five-year survival rate was 38.2%, and the mean overall survival time was 54.2 months. Endodontic diagnosis was considered a significant risk factor (P < 0.05). In the first, second and third years, 57.4%, 81.8%, and 94.8%, respectively, of obturation materials in the root canals were resorbed at a faster rate than the roots. There was an altered eruption direction in 7 permanent teeth, and 4 permanent teeth were diagnosed with enamel hypoplasia. CONCLUSIONS: In this study, the 60-month survival rate of primary molars treated by pulpectomy under dental general anesthesia was 38.32%. Operators should have an accurate assessment of the status of the pulp, have a strict grasp of the preoperative indications and select the appropriate treatment method according to the guidelines. Individual cases suggest overfilling, overextension and periapical periodontitis in primary molars have an impact on enamel hypoplasia and altered eruption direction in permanent teeth.

Long-term Outcomes and Prognostic Factors of Gastric MALT Lymphoma.

PURPOSE: This study aimed to evaluate the long-term prognosis of patients with gastric mucosa-associated lymphoid tissue (MALT) lymphoma, including overall survival (OS), remission, and factors associated with an aggressive disease course. MATERIALS AND METHODS: Medical records of 153 patients diagnosed with gastric MALT lymphoma between 2013 and 2020 were retrospectively reviewed. Patients experiencing relapse, progression, high-grade transformation, or residual diseasewere included in the aggressive group and were compared with those in the indolent group. Additionally, the endoscopic findings of Helicobacter pylori-negative patients were reviewed. RESULTS: Patient characteristics were as follows: mean age (56.9±11.2 years), sex (male, 51.0%), H. pylori infection (positive, 79.7%), endoscopic location (distal, 89.5%), endoscopic feature (superficial, 89.5%), clinical stage (stage I, 92.8%), invasion depth by endoscopic ultrasound (mucosa, n=115, 75.7%), and bone marrow result (no involvement, n=77, 100.0%). The median follow-up period was 59 months (mean, 61; range, 36-124) and the continuous remission period (n=149) was 51 months (mean, 50; range, 3-112). The 5-year survival rate was 97.7% while the 5-year continuous remission was 88.3%. Factors associated with the patients in the aggressive group were old age, sex(male), and clinical stage II or higher. H. pylori-negative patients' endoscopy revealed a high incidence of atrophic gastritis in the antrum. CONCLUSIONS: The long-term prognosis of gastric MALT lymphoma appears indolent and is indicated by the 5-year OS and continuous remission rates. Aggressive disease courses are associated with old age, sex (male), and clinical stage II or higher, but are not related to OS.

Deep Neural Network-Based Accelerated Failure Time Models Using Rank Loss.

An accelerated failure time (AFT) model assumes a log-linear relationship between failure times and a set of covariates. In contrast to other popular survival models that work on hazard functions, the effects of covariates are directly on failure times, the interpretation of which is intuitive. The semiparametric AFT model that does not specify the error distribution is sufficiently flexible and robust to depart from the distributional assumption. Owing to its desirable features, this class of model has been considered a promising alternative to the popular Cox model in the analysis of censored failure time data. However, in these AFT models, a linear predictor for the mean is typically assumed. Little research has addressed the non-linearity of predictors when modeling the mean. Deep neural networks (DNNs) have received much attention over the past few decades and have achieved remarkable success in a variety of fields. DNNs have a number of notable advantages and have been shown to be particularly useful in addressing non-linearity. Here, we propose applying a DNN to fit AFT models using Gehan-type loss combined with a sub-sampling technique. Finite sample properties of the proposed DNN and rank-based AFT model (DeepR-AFT) were investigated via an extensive simulation study. The DeepR-AFT model showed superior performance over its parametric and semiparametric counterparts when the predictor was nonlinear. For linear predictors, DeepR-AFT performed better when the dimensions of the covariates were large. The superior performance of the proposed DeepR-AFT was demonstrated using three real datasets.

Joint modeling of longitudinal and survival data for the evaluation of the impact of irrigation systems on the time until the occurrence of phoma leaf spot in Arabica coffee plants.

BACKGROUND: The coffee crop is prominent in Brazilian agriculture, making the country a global power in this area. One of the main concerns in the coffee sector is disease, which can affect coffee productivity and quality. Thus, it is important to evaluate the factors that may affect coffee quality and thus enhance the development of strategies to reduce coffee losses and costs and optimize production. This study evaluated the influence of the type of irrigation (self-propelled, drip, and center pivot) on the time until the occurrence of phoma leaf spot on Arabica coffee plants, considering the intensity of the disease. Additionally, the association between longitudinal incidence and the time until an event of interest was assessed based on the joint modeling of longitudinal and survival data. RESULTS: The results of this study identify the effectiveness of drip irrigation system compared with other systems; the use of such systems was associated with an ~46.5% reduction in the risk of leaf spot disease compared with the use of a self-propelled irrigation system. The use of a center pivot system increased the risk of disease progression compared with a self-propelled system. An association between the longitudinal and survival processes was also observed. CONCLUSION: The findings demonstrate the superior performance of the drip irrigation system in controlling phoma leaf spot disease in Arabica coffee plants compared with self-propelled and center pivot systems. This research highlights the potential of using drip irrigation to establish more effective agricultural practices in coffee cultivation, contributing to better disease management and improved crop quality. © 2024 Society of Chemical Industry.

Evaluating time-to-event surrogates for time-to-event true endpoints: an information-theoretic approach based on causal inference.

Putative surrogate endpoints must undergo a rigorous statistical evaluation before they can be used in clinical trials. Numerous frameworks have been introduced for this purpose. In this study, we extend the scope of the information-theoretic causal-inference approach to encompass scenarios where both outcomes are time-to-event endpoints, using the flexibility provided by D-vine copulas. We evaluate the quality of the putative surrogate using the individual causal association (ICA)-a measure based on the mutual information between the individual causal treatment effects. However, in spite of its appealing mathematical properties, the ICA may be ill defined for composite endpoints. Therefore, we also propose an alternative rank-based metric for assessing the ICA. Due to the fundamental problem of causal inference, the joint distribution of all potential outcomes is only partially identifiable and, consequently, the ICA cannot be estimated without strong unverifiable assumptions. This is addressed by a formal sensitivity analysis that is summarized by the so-called intervals of ignorance and uncertainty. The frequentist properties of these intervals are discussed in detail. Finally, the proposed methods are illustrated with an analysis of pooled data from two advanced colorectal cancer trials. The newly developed techniques have been implemented in the R package Surrogate.

Incident cardiovascular disease risk among older Asian, Native Hawaiian and Pacific Islander liver cancer survivors.

BACKGROUND: Cardiovascular disease (CVD) is a significant global health concern, particularly among Asian, Native Hawaiian, and Pacific Islander (ANHPI) communities that face unique health challenges. Liver cancer disproportionately affects ANHPI populations and has intricate associations with CVD risks due to shared pathophysiological mechanisms and metabolic disturbances. However, the specific CVD risk profile of ANHPI liver cancer patients remains poorly understood. METHODS: Using Surveillance, Epidemiology, and End Results (SEER)-Medicare data, we identified and matched 1150 ANHPI and 2070 Non-Hispanic White (NHW) liver cancer patients diagnosed between 2000 and 2017. We used the Fine-Gray sub-distribution hazard model to estimate hazard ratios (HRs) and 95 % confidence intervals (95 % CIs) for CVD risks, including ischemic heart disease (IHD), heart failure, and stroke, among ANHPI liver cancer patients compared to NHW counterparts and among ANHPI subgroups. RESULTS: ANHPI liver cancer patients demonstrated a lower risk of IHD compared to NHW counterparts (HR, 0.65, 95 % CI, 0.50, 0.86), aligning with broader trends. Subgroup analysis revealed notable heterogeneity within ANHPI populations, with Southeast Asian (HR, 0.65, 95 % CI, 0.42, 1.00) and Chinese patients (HR, 0.53, 95 % CI, 0.33-0.83) exhibiting lower IHD risks compared to their NHW counterparts. However, Native Hawaiian and Pacific Islander liver cancer patients showed elevated risks of heart failure (HR, 3.16, 95 % CI, 1.35-7.39) and IHD (HR, 5.64, 95 % CI, 2.19-14.53) compared to their Chinese counterparts. CONCLUSION: Our study highlights the complexity of CVD risks among ANHPI liver cancer patients. Addressing these disparities is crucial for improving cardiovascular outcomes and reducing the burden of CVD among ANHPI liver cancer patients.

Pairwise Accelerated Failure Time Regression Models for Infectious Disease Transmission in Close-Contact Groups With External Sources of Infection.

Many important questions in infectious disease epidemiology involve associations between covariates (e.g., age or vaccination status) and infectiousness or susceptibility. Because disease transmission produces dependent outcomes, these questions are difficult or impossible to address using standard regression models from biostatistics. Pairwise survival analysis handles dependent outcomes by calculating likelihoods in terms of contact interval distributions in ordered pairs of individuals. The contact interval in the ordered pair i j $$ ij $$ is the time from the onset of infectiousness in i $$ i $$ to infectious contact from i $$ i $$ to j $$ j $$ , where an infectious contact is sufficient to infect j $$ j $$ if they are susceptible. Here, we introduce a pairwise accelerated failure time regression model for infectious disease transmission that allows the rate parameter of the contact interval distribution to depend on individual-level infectiousness covariates for i $$ i $$ , individual-level susceptibility covariates for j $$ j $$ , and pair-level covariates (e.g., type of relationship). This model can simultaneously handle internal infections (caused by transmission between individuals under observation) and external infections (caused by environmental or community sources of infection). We show that this model produces consistent and asymptotically normal parameter estimates. In a simulation study, we evaluate bias and confidence interval coverage probabilities, explore the role of epidemiologic study design, and investigate the effects of model misspecification. We use this regression model to analyze household data from Los Angeles County during the 2009 influenza A (H1N1) pandemic, where we find that the ability to account for external sources of infection increases the statistical power to estimate the effect of antiviral prophylaxis.

CT-based body composition analysis and pulmonary fat attenuation volume as biomarkers to predict overall survival in patients with non-specific interstitial pneumonia.

BACKGROUND: Non-specific interstitial pneumonia (NSIP) is an interstitial lung disease that can result in end-stage fibrosis. We investigated the influence of body composition and pulmonary fat attenuation volume (CTpfav) on overall survival (OS) in NSIP patients. METHODS: In this retrospective single-center study, 71 NSIP patients with a median age of 65 years (interquartile range 21.5), 39 females (55%), who had a computed tomography from August 2009 to February 2018, were included, of whom 38 (54%) died during follow-up. Body composition analysis was performed using an open-source nnU-Net-based framework. Features were combined into: Sarcopenia (muscle/bone); Fat (total adipose tissue/bone); Myosteatosis (inter-/intra-muscular adipose tissue/total adipose tissue); Mediastinal (mediastinal adipose tissue/bone); and Pulmonary fat index (CTpfav/lung volume). Kaplan-Meier analysis with a log-rank test and multivariate Cox regression were used for survival analyses. RESULTS: Patients with a higher (> median) Sarcopenia and lower (< median) Mediastinal Fat index had a significantly better survival probability (2-year survival rate: 83% versus 71% for high versus low Sarcopenia index, p = 0.023; 83% versus 72% for low versus high Mediastinal fat index, p = 0.006). In univariate analysis, individuals with a higher Pulmonary fat index exhibited significantly worse survival probability (2-year survival rate: 61% versus 94% for high versus low, p = 0.003). Additionally, it was an independent risk predictor for death (hazard ratio 2.37, 95% confidence interval 1.03-5.48, p = 0.043). CONCLUSION: Fully automated body composition analysis offers interesting perspectives in patients with NSIP. Pulmonary fat index was an independent predictor of OS. RELEVANCE STATEMENT: The Pulmonary fat index is an independent predictor of OS in patients with NSIP and demonstrates the potential of fully automated, deep-learning-driven body composition analysis as a biomarker for prognosis estimation. KEY POINTS: This is the first study assessing the potential of CT-based body composition analysis in patients with non-specific interstitial pneumonia (NSIP). A single-center analysis of 71 patients with board-certified diagnosis of NSIP is presented Indices related to muscle, mediastinal fat, and pulmonary fat attenuation volume were significantly associated with survival at univariate analysis. CT pulmonary fat attenuation volume, normalized by lung volume, resulted as an independent predictor for death.

Factors associated with rod fracture following surgery for adult spinal deformity: a single-center retrospective study.

PURPOSE: Adult spinal deformity (ASD) has a significant impact on trunk balance and quality of life in the elderly. Postoperative rod fractures pose significant challenges, but the mechanisms of their occurrence are underexplored compared to other complications such as proximal junctional kyphosis. This study investigated factors associated with rod fracture in patients with ASD. METHODS: A retrospective single-center study analyzed 110 adult patients who underwent spinal deformity correction between 2012 and 2020. Comparative analysis and univariate and multivariate Cox regression analyses were employed to identify factors associated with rod fracture. RESULTS: In this study, rod fracture occurred in 14.5% of patients. The rod fracture group exhibited a larger change in lumbar lordosis (LL), a higher proportion of patients with pre-operatively existing (pre-existing) vertebral fractures, and a greater percentage of patients with a rod diameter of 6 mm or less compared to the non-rod fracture group. Univariate Cox regression analysis revealed that rod fracture was associated with pre-existing vertebral fracture, LL change, preoperative sagittal vertical axis, and preoperative pelvic tilt. Multivariate Cox regression analysis identified pre-existing vertebral fractures and the amount of LL change as independent factors associated with rod fractures. CONCLUSION: Pre-existing vertebral fractures and the magnitude of lumbar lordosis correction are independent risk factors for rod fracture following ASD surgery. Surgeons should consider these factors during preoperative planning to reduce the risk of postoperative rod fracture. LEVEL OF EVIDENCE: IV.

Elevated SH3 and Multiple Ankyrin Repeat Domains 2 Expression Correlates With Improved Glioma Prognosis.

This study investigates the prognostic significance of SH3 and multiple ankyrin repeat domains 2 (SHANK2) gene expression in glioma patients, using data from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) project, and the Gene Expression Omnibus (GEO). Through comprehensive analysis, we found a significant association between higher SHANK2 expression and improved survival outcomes across various glioma subtypes. To further validate the clinical relevance of SHANK2, we conducted cellular experiments involving siRNA-mediated knockdown of SHANK2 in U87 and A172 glioma cell lines. Quantitative real-time PCR (qPCR) and Western blot analyses confirmed the successful knockdown of SHANK2, and subsequent MTT assays revealed that silencing SHANK2 significantly promoted glioma cell proliferation. These findings underscore the potential role of SHANK2 as a tumor suppressor in glioma. The study also introduces a multivariate prognostic model incorporating SHANK2, providing a novel perspective on glioma prognosis. While the retrospective nature of the study presents limitations, our results suggest that SHANK2 expression could serve as a valuable biomarker for glioma prognosis and inform future therapeutic strategies.