Peripheral Soluble Immune Checkpoint-Related Proteins Were Associated with Survival and Treatment Efficacy of Osteosarcoma Patients, a Cohort Study.

BACKGROUND: The immune checkpoint blockade remains obscure in osteosarcoma (OS). We aim to explore the clinical significance of soluble immune checkpoint (ICK)-related proteins in OS. METHODS: We profiled 14 soluble ICK-related proteins (BTLA, GITR, HVEM, IDO, LAG-3, PD-1, PD-L1, PD-L2, TIM-3, CD28, CD80, CD137, CD27, and CTLA-4) in the plasma of 76 OS patients and matched controls. We evaluated the associations between the biomarkers and the risk of OS using unconditional multivariate logistic regression. The multivariate Cox model was utilized to develop the prediction model of OS. Immune subtypes were established from the identified biomarkers. Transcriptional data from GEO were analyzed to elucidate potential mechanisms. RESULTS: We found that sTIM3, sCD137, sIDO, and sCTLA4 were significantly correlated with OS risk (all p < 0.05). sBTLA, sPDL2, and sCD27 were significantly associated with the risk of lung metastasis, whereas sBTLA and sTIM3 were associated with the risk of disease progression. We also established an immune subtype based on sBTLA, sPD1, sTIM3, and sPDL2. Patients in the sICK-type2 subtype had significantly decreased progression-free survival (PFS) and lung metastasis-free survival (LMFS) than those in the sICK-type1 subtype (log-rank p = 2.8 × 10-2, 1.7 × 10-2, respectively). Interestingly, we found that the trend of LMFS and PFS in the subtypes of corresponding ICK genes' expression was opposite to the results in the blood (log-rank p = 2.6 × 10-4, 9.5 × 10-4, respectively). CONCLUSION: Four soluble ICK-related proteins were associated with the survival of OS patients. Soluble ICK-related proteins could be promising biomarkers for the outcomes and immunotherapy of OS patients, though more research is warranted.

Impaired lung function and lung cancer risk in 461 183 healthy individuals: a cohort study.

BACKGROUND: It has been known that smoking and various lung diseases including lung cancer can cause lung function impairment. However, the impact of different types of lung function impairments, such as preserved ratio impaired spirometry (PRISm) and airflow obstruction (AO), on the incidence and mortality of lung cancer in both general and never-smoker populations remains unclear. We wished to examine the effect of lung function impairments on lung cancer risks. METHODS: This was a retrospective cohort study (1 January 1994 to 31 December 2017) of individuals from a health surveillance programme in Taiwan who underwent baseline spirometry tests at the entry point. PRISm was defined as an FEV1/FVC (forced expiratory volume in 1 s/forced vital capacity) ratio >0.7 and FEV1 <0.8, while AO was defined as an FEV1/FVC ratio <0.7. Cox proportional hazards models and cubic spline curves were used to examine the associations between lung function impairments and lung cancer risks. RESULTS: The study included 461,183 individuals, of whom 14.3% had PRISm and 7.9% had AO. A total of 4038 cases of lung cancer and 3314 lung cancer-related deaths were identified during the 23 years of follow-up. Individuals with PRISm and AO exhibited a higher risk of lung cancer incidence and mortality compared with those with normal lung function. The adjusted HRs and 95% CIs were 1.14 (1.03 to 1.26) and 1.23 (1.10 to 1.37) in the overall cohort, and 1.08 (0.93 to 1.24), and 1.23 (1.05 to 1.45) in the never-smoker cohort. The risks of both developing and dying of lung cancer increased with the severity levels of lung function impairments and lower FEV1 values. CONCLUSION: Impaired lung function is associated with increased risks of developing lung cancer and subsequent mortality. The study highlights the importance of considering lung function in lung cancer screening for better candidate selection.

Development and application of a deep learning-based comprehensive early diagnostic model for chronic obstructive pulmonary disease.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a frequently diagnosed yet treatable condition, provided it is identified early and managed effectively. This study aims to develop an advanced COPD diagnostic model by integrating deep learning and radiomics features. METHODS: We utilized a dataset comprising CT images from 2,983 participants, of which 2,317 participants also provided epidemiological data through questionnaires. Deep learning features were extracted using a Variational Autoencoder, and radiomics features were obtained using the PyRadiomics package. Multi-Layer Perceptrons were used to construct models based on deep learning and radiomics features independently, as well as a fusion model integrating both. Subsequently, epidemiological questionnaire data were incorporated to establish a more comprehensive model. The diagnostic performance of standalone models, the fusion model and the comprehensive model was evaluated and compared using metrics including accuracy, precision, recall, F1-score, Brier score, receiver operating characteristic curves, and area under the curve (AUC). RESULTS: The fusion model exhibited outstanding performance with an AUC of 0.952, surpassing the standalone models based solely on deep learning features (AUC = 0.844) or radiomics features (AUC = 0.944). Notably, the comprehensive model, incorporating deep learning features, radiomics features, and questionnaire variables demonstrated the highest diagnostic performance among all models, yielding an AUC of 0.971. CONCLUSION: We developed and implemented a data fusion strategy to construct a state-of-the-art COPD diagnostic model integrating deep learning features, radiomics features, and questionnaire variables. Our data fusion strategy proved effective, and the model can be easily deployed in clinical settings. TRIAL REGISTRATION: Not applicable. This study is NOT a clinical trial, it does not report the results of a health care intervention on human participants.

Genetic predisposition, modifiable lifestyles, and their joint effects on human lifespan: evidence from multiple cohort studies.

OBJECTIVE: To investigate the associations across genetic and lifestyle factors with lifespan. DESIGN: A longitudinal cohort study. SETTING: UK Biobank. PARTICIPANTS: 353 742 adults of European ancestry, who were recruited from 2006 to 2010 and were followed up until 2021. EXPOSURES: A polygenic risk score for lifespan with long (highest quintile) risk categories and a weighted healthy lifestyle score, including no current smoking, moderate alcohol consumption, regular physical activity, healthy body shape, adequate sleep duration, and a healthy diet, categorised into favourable, intermediate, and unfavourable lifestyles. MAIN OUTCOME MEASURES: Lifespan defined as the date of death or the censor date minus the date of birth. RESULTS: Of the included 353 742 participants of European ancestry with a median follow-up of 12.86 years, 24 239 death cases were identified. Participants were grouped into three genetically determined lifespan categories including long (20.1%), intermediate (60.1%), and short (19.8%), and into three lifestyle score categories including favourable (23.1%), intermediate (55.6%), and unfavourable (21.3%). The hazard ratio (HR) of death for individuals with a genetic predisposition to a short lifespan was 1.21 (95% CI 1.16 to 1.26) compared to those with a genetic predisposition to a long lifespan. The HR of death for individuals in the unfavourable lifestyle category was 1.78 (95% CI 1.71 to 1.85), compared with those in the favourable lifestyle category. Participants with a genetic predisposition to a short lifespan and an unfavourable lifestyle had 2.04 times (95% CI 1.87 to 2.22) higher rates of death compared with those with a genetic predisposition to a long lifespan and a favourable lifestyle. No multiplicative interaction was detected between the polygenic risk score of lifespan and the weighted healthy lifestyle score (p=0.10). The optimal combination of healthy lifestyles, including never smoking, regular physical activity, adequate sleep duration, and a healthy diet, was derived to decrease risk of premature death (death before 75 years). CONCLUSION: Genetic and lifestyle factors were independently associated with lifespan. Adherence to healthy lifestyles could largely attenuate the genetic risk of a shorter lifespan or premature death. The optimal combination of healthy lifestyles could convey better benefits for a longer lifespan, regardless of genetic background.

Validity, feasibility, and effectiveness of a voice-recognition based digital cognitive screener for dementia and mild cognitive impairment in community-dwelling older Chinese adults: A large-scale implementation study.

INTRODUCTION: We investigated the validity, feasibility, and effectiveness of a voice recognition-based digital cognitive screener (DCS), for detecting dementia and mild cognitive impairment (MCI) in a large-scale community of elderly participants. METHODS: Eligible participants completed demographic, cognitive, functional assessments and the DCS. Neuropsychological tests were used to assess domain-specific and global cognition, while the diagnosis of MCI and dementia relied on the Clinical Dementia Rating Scale. RESULTS: Among the 11,186 participants, the DCS showed high completion rates (97.5%) and a short administration time (5.9 min) across gender, age, and education groups. The DCS demonstrated areas under the receiver operating characteristics curve (AUCs) of 0.95 and 0.83 for dementia and MCI detection, respectively, among 328 participants in the validation phase. Furthermore, the DCS resulted in time savings of 16.2% to 36.0% compared to the Mini-Mental State Examination (MMSE) and Montral Cognitive Assessment (MoCA). DISCUSSION: This study suggests that the DCS is an effective and efficient tool for dementia and MCI case-finding in large-scale cognitive screening. HIGHLIGHTS: To our best knowledge, this is the first cognitive screening tool based on voice recognition and utilizing conversational AI that has been assessed in a large population of Chinese community-dwelling elderly. With the upgrading of a new multimodal understanding model, the DCS can accurately assess participants' responses, including different Chinese dialects, and provide automatic scores. The DCS not only exhibited good discriminant ability in detecting dementia and MCI cases, it also demonstrated a high completion rate and efficient administration regardless of gender, age, and education differences. The DCS is economically efficient, scalable, and had a better screening efficacy compared to the MMSE or MoCA, for wider implementation.

A biological age model based on physical examination data to predict mortality in a Chinese population.

Biological age could be reflective of an individual's health status and aging degree. Limited estimations of biological aging based on physical examination data in the Chinese population have been developed to quantify the rate of aging. We developed and validated a novel aging measure (Balanced-AGE) based on readily available physical health examination data. In this study, a repeated sub-sampling approach was applied to address the data imbalance issue, and this approach significantly improved the performance of biological age (Balanced-AGE) in predicting all-cause mortality with a 10-year time-dependent AUC of 0.908 for all-cause mortality. This mortality prediction tool was found to be effective across different subgroups by age, sex, smoking, and alcohol consumption status. Additionally, this study revealed that individuals who were underweight, smokers, or drinkers had a higher extent of age acceleration. The Balanced-AGE may serve as an effective and generally applicable tool for health assessment and management among the elderly population.

Combining Classic and Novel Neutrophil-Related Biomarkers to Identify Non-Small-Cell Lung Cancer.

BACKGROUND: Recent studies have revealed that neutrophils play a crucial role in cancer progression. This study aimed to explore the diagnostic value of neutrophil-related biomarkers for non-small-cell lung cancer (NSCLC). METHODS: We initially assessed the associations between classic neutrophil-related biomarkers (neutrophil-to-lymphocyte ratio (NLR), absolute neutrophil counts (NEU), absolute lymphocyte counts (LYM)) and NSCLC in 3942 cases and 6791 controls. Then, we measured 11 novel neutrophil-related biomarkers via Luminex Assays in 132 cases and 66 controls, individually matching on sex and age (±5 years), and evaluated their associations with NSCLC risk. We also developed the predictive models by sequentially adding variables of interest and assessed model improvement. RESULTS: Interleukin-6 (IL-6) (odds ratio (OR) = 10.687, 95% confidence interval (CI): 3.875, 29.473) and Interleukin 1 Receptor Antagonist (IL-1RA) (OR = 8.113, 95% CI: 3.182, 20.689) shows strong associations with NSCLC risk after adjusting for body mass index, smoking status, NLR, and carcinoembryonic antigen. Adding the two identified biomarkers to the predictive model significantly elevated the model performance from an area under the receiver operating characteristic curve of 0.716 to 0.851 with a net reclassification improvement of 97.73%. CONCLUSIONS: IL-6 and IL-1RA were recognized as independent risk factors for NSCLC, improving the predictive performance of the model in identifying disease.

Global, regional, and national burden and quality of care of multiple myeloma, 1990-2019.

Background: Multiple myeloma (MM) is the second most common haematologic malignancy, presenting a great disease burden on the general population; however, the quality of care of MM is overlooked. We therefore assessed gains and disparity in quality of care worldwide from 1990 to 2019 based on a novel summary indicator - the quality of care index (QCI) - and examined its potential for improvement. Methods: Using the Global Burden of Disease 2019 data set, we calculated the QCI of MM for 195 countries and territories. We used the principal component analysis to extract the first principal component of ratios with the combinations of mortality to incidence, prevalence to incidence, disability-adjusted life years to prevalence, and years of life lost to years lived with disability as QCI. We also conducted a series of descriptive and comparative analyses of QCI disparities with age, gender, period, geographies, and sociodemographic development, and compared the QCI among countries with similar socio-demographic index (SDI) through frontier analysis. Results: The age-standardised rates of MM were 1.92 (95% uncertainty interval (UI) = 1.68, 2.12) in incidence and 1.42 (95% UI = 1.24, 1.52) in deaths per 100 000 population in 2019, and were predicted to increase in the future. The global age-standardised QCI increased from 51.31 in 1990 to 64.28 in 2019. In 2019, New Zealand had the highest QCI at 99.29 and the Central African Republic had the lowest QCI at 10.74. The gender disparity of QCI was reduced over the years, with the largest being observed in the sub-Saharan region. Regarding age, QCI maintained a decreasing trend in patients aged >60 in SDI quintiles. Generally, QCI improved with the SDI increase. Results of frontier analysis suggested that there is a potential to improve the quality of care across all levels of development spectrum. Conclusions: Quality of care of MM improved during the past three decades, yet disparities in MM care remain across different countries, age groups, and genders. It is crucial to establish local objectives aimed at enhancing MM care and closing the gap in health care inequality.

Big data and artificial intelligence in cancer research.

The field of oncology has witnessed an extraordinary surge in the application of big data and artificial intelligence (AI). AI development has made multiscale and multimodal data fusion and analysis possible. A new era of extracting information from complex big data is rapidly evolving. However, challenges related to efficient data curation, in-depth analysis, and utilization remain. We provide a comprehensive overview of the current state of the art in big data and computational analysis, highlighting key applications, challenges, and future opportunities in cancer research. By sketching the current landscape, we seek to foster a deeper understanding and facilitate the advancement of big data utilization in oncology, call for interdisciplinary collaborations, ultimately contributing to improved patient outcomes and a profound understanding of cancer.

Urinary miRNAs Predict Metastasis in Patients With Clinically Localized Clear Cell Renal Cell Carcinoma Treated With Nephrectomy.

PURPOSE: Patients with clear cell renal cell carcinoma (ccRCC) might develop metastasis after surgery with curative intent. We aimed to characterize the expression levels of microRNAs in the urine (UmiRNAs) of patients before and after nephrectomy to determine the impact of UmiRNAs expression in the emergence of metastases. METHODS: We prospectively collected pre- and post-nephrectomy urine samples from 117 patients with clinically localized and locally advanced ccRCC. UmiRNAs were extracted, purified, and measured using RT-PCR. Relative quantifications (RQ) of 137 UmiRNAs were calculated through 2-∆∆ method. The post-surgery/pre-surgery RQs ratio represented the magnitude of the expression levels of the UmiRNAs. The association of UmiRNA expression and the development of distant metastases was tested with Cox regression model. RESULTS: Five UmiRNAs (miR-191-5p, miR-324-3p, miR-186-5p, miR-93-5p, miR-30b-5p) levels were upregulated before nephrectomy (p < .05). This conferred a 2- to 4-fold increased risk of metastasis, with miR-191-5p showing the most significant association with this endpoint (HR = 4.16, 95% CI = 1.38-12.58, p = .011). In a multivariate model stratified with stage and Fuhrman grade, we found that miR-191-5p, miR-324-3p, and miR-186-5p exhibited a strong association with metastasis development in patients with pathological T3 (pT3) tumors. Enrichment analysis with the most differentially expressed UmiRNAs showed that these UmiRNAs targeted genes that regulate cell survival and proliferation. CONCLUSION: Our study indicated UmiR-191-5p, UmiR-324-3p, and UmiR-186-5p are potential markers to predict the development of metastasis, particularly in pT3 patients. PATIENT SUMMARY: We compared changes of UmiRNAs expression detected pre- and postnephrectomy of patients with ccRCC. Our findings suggest that UmiRNA expression likely reflects tumor-specific changes that can be promising to predict the metastasis development, particularly in patients with non-metastatic locally advanced ccRCC. If confirmed, these findings may be useful for surveillance protocols for adjuvant therapy protocols.

Beneficial associations between outdoor visible greenness at the workplace and metabolic syndrome in Chinese adults.

BACKGROUND: Greenness surrounding residential places has been found to significantly reduce the risk of diseases such as hypertension, obesity, and metabolic syndrome (MetS). However, it is unclear whether visible greenness exposure at the workplace has any impact on the risk of MetS. METHODS: Visible greenness exposure was assessed using a Green View Index (GVI) based on street view images through a convolutional neural network model. We utilized logistic regression to examine the cross-sectional association between GVI and MetS as well as its components among 51,552 adults aged 18-60 in the city of Hangzhou, China, from January 2018 to December 2021. Stratified analyses were conducted by age and sex groups. Furthermore, a scenario analysis was conducted to investigate the risks of having MetS among adults in different GVI scenarios. RESULTS: The mean age of the participants was 40.1, and 38.5% were women. We found a statistically significant association between GVI and having MetS. Compared to the lowest quartile of GVI, participants in the highest quartile of GVI had a 17% (95% CI: 11-23%) lower odds of having MetS. The protective association was stronger in the males, but we did not observe such differences in different age groups. Furthermore, we found inverse associations between GVI and the odds of hypertension, low high-density lipoprotein cholesterol, obesity, and high levels of FPG. CONCLUSIONS: Higher exposure to outdoor visible greenness in the workplace environment might have a protective effect against MetS.

Association of fat mass and fat-free mass with all-cause and cause-specific mortality in Asian individuals: A prospective cohort study.

OBJECTIVE: The study's objective was to investigate the association of fat mass index (FMI) and fat-free mass index (FFMI) with all-cause mortality and cause-specific mortality in the Chinese population. METHODS: A total of 422,430 participants (48.1% men and 51.9% women) from the Taiwan MJ Cohort with an average follow-up of 9 years were included. RESULTS: The lowest (Q1) and highest (Q5) quintiles of FMI and FFMI were associated with increased all-cause mortality. Compared with those in the third quintile (Q3) group of FMI, participants in Q1 and Q5 groups of FMI had hazard ratios and 95% CI of 1.32 (1.24-1.40) and 1.13 (1.06-1.20), respectively. Similarly, compared with those in Q3 group of FFMI, people in Q1 and Q5 groups of FFMI had hazard ratios of 1.14 (1.06-1.23) and 1.16 (1.10-1.23), respectively. In the restricted cubic spline models, both FMI and FFMI showed a J-shaped association with all-cause mortality. People in Q5 group of FFMI had a hazard ratio of 0.72 (0.58-0.89) for respiratory disease. CONCLUSIONS: The mortality risk increases in those with excessively high or low FMI and FFMI, yet the associations between FMI, FFMI, and the risk of death varied across subgroups and causes of death.

6-Year trajectory of fasting plasma glucose (FPG) and mortality risk among individuals with normal FPG at baseline: a prospective cohort study.

BACKGROUND: Higher fasting plasma glucose (FPG) levels were associated with an increased risk of all-cause mortality; however, the associations between long-term FPG trajectory groups and mortality were unclear, especially among individuals with a normal FPG level at the beginning. The aims of this study were to examine the associations of FPG trajectories with the risk of mortality and identify modifiable lifestyle factors related to these trajectories. METHODS: We enrolled 50,919 individuals aged ≥ 20 years old, who were free of diabetes at baseline, in the prospective MJ cohort. All participants completed at least four FPG measurements within 6 years after enrollment and were followed until December 2011. FPG trajectories were identified by group-based trajectory modeling. We used Cox proportional hazards models to examine the associations of FPG trajectories with mortality, adjusting for age, sex, marital status, education level, occupation, smoking, drinking, physical activity, body mass index, baseline FPG, hypertension, dyslipidemia, cardiovascular disease or stroke, and cancer. Associations between baseline lifestyle factors and FPG trajectories were evaluated using multinomial logistic regression. RESULTS: We identified three FPG trajectories as stable (n = 32,481), low-increasing (n = 17,164), and high-increasing (n = 1274). Compared to the stable group, both the low-increasing and high-increasing groups had higher risks of all-cause mortality (hazard ratio (HR) = 1.18 (95% CI 0.99-1.40) and 1.52 (95% CI 1.09-2.13), respectively), especially among those with hypertension. Compared to participants with 0 to 1 healthy lifestyle factor, those with 6 healthy lifestyle factors were more likely to be in the stable group (ORlow-increasing = 0.61, 95% CI 0.51-0.73; ORhigh-increasing = 0.20, 95% CI 0.13-0.32). CONCLUSIONS: Individuals with longitudinally increasing FPG had a higher risk of mortality even if they had a normal FPG at baseline. Adopting healthy lifestyles may prevent individuals from transitioning into increasing trajectories.

Association between plant-based dietary pattern and biological aging trajectory in a large prospective cohort.

BACKGROUND: Aging is a dynamic and heterogeneous process that may better be captured by trajectories of aging biomarkers. Biological age has been advocated as a better biomarker of aging than chronological age, and plant-based dietary patterns have been found to be linked to aging. However, the associations of biological age trajectories with mortality and plant-based dietary patterns remained unclear. METHODS: Using group-based trajectory modeling approach, we identified distinctive aging trajectory groups among 12,784 participants based on a recently developed biological aging measure acquired at four-time points within an 8-year period. We then examined associations between aging trajectories and quintiles of plant-based dietary patterns assessed by overall plant-based diet index (PDI), healthful PDI (hPDI), and unhealthful PDI (uPDI) among 10,191 participants who had complete data on dietary intake, using multivariable multinomial logistics regression adjusting for sociodemographic and lifestyles factors. Cox proportional hazards regression models were applied to investigate the association between aging trajectories and all-cause mortality. RESULTS: We identified three latent classes of accelerated aging trajectories: slow aging, medium-degree, and high-degree accelerated aging trajectories. Participants who had higher PDI or hPDI had lower odds of being in medium-degree (OR = 0.75, 95% CI: 0.65, 0.86 for PDI; OR = 0.73, 95% CI: 0.62, 0.85 for hPDI) or high-degree (OR = 0.63, 95% CI: 0.46, 0.86 for PDI; OR = 0.62, 95% CI: 0.44, 0.88 for hPDI) accelerated aging trajectories. Participants in the highest quintile of uPDI were more likely to be in medium-degree (OR = 1.72, 95% CI: 1.48, 1.99) or high-degree (OR = 1.70, 95% CI: 1.21, 2.38) accelerated aging trajectories. With a mean follow-up time of 8.40 years and 803 (6.28%) participants died by the end of follow-up, we found that participants in medium-degree (HR = 1.56, 95% CI: 1.29, 1.89) or high-degree (HR = 3.72, 95% CI: 2.73, 5.08) accelerated aging trajectory groups had higher risks of death than those in the slow aging trajectory. CONCLUSIONS: We identified three distinctive aging trajectories in a large Asian cohort and found that adopting a plant-based dietary pattern, especially when rich in healthful plant foods, was associated with substantially lowered pace of aging.

Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins.

Background: Immune checkpoint inhibition holds promise as a novel treatment for pancreatic ductal adenocarcinoma (PDAC). The clinical significance of soluble immune checkpoint (ICK) related proteins have not yet fully explored in PDAC. Methods: We comprehensively profiled 14 soluble ICK-related proteins in plasma in 70 PDAC patients and 70 matched healthy controls. Epidemiological data of all subjects were obtained through structured interviews, and patients' clinical data were retrieved from electronical health records. We evaluated the associations between the biomarkers with the risk of PDAC using unconditional multivariate logistic regression. Consensus clustering (k-means algorithm) with significant biomarkers was performed to identify immune subtypes in PDAC patients. Prediction models for overall survival (OS) in PDAC patients were developed using multivariate Cox proportional hazards regression. Harrell's concordance index (C-index), time-dependent receiver operating characteristic (ROC) curve and calibration curve were utilized to evaluate performance of prediction models. Gene expressions of the identified ICK-related proteins in tumors from TCGA were analyzed to provide insight into underlying mechanisms. Results: Soluble BTLA, CD28, CD137, GITR and LAG-3 were significantly upregulated in PDAC patients (all q < 0.05), and elevation of each of them was correlated with PDAC increased risk (all p < 0.05). PDAC patients were classified into soluble immune-high and soluble immune-low subtypes, using these 5 biomarkers. Patients in soluble immune-high subtype had significantly poorer OS than those in soluble immune-low subtype (log-rank p = 9.7E-03). The model with clinical variables and soluble immune subtypes had excellent predictive power (C-index = 0.809) for the OS of PDAC patients. Furthermore, the immune subtypes identified with corresponding genes' expression in PDAC tumor samples in TCGA showed an opposite correlation with OS to that of immune subtypes based on blood soluble ICK-related proteins (log-rank p =0.02). The immune-high subtype tumors displayed higher cytolytic activity (CYT) score than immune-low subtype tumors (p < 2E-16). Conclusion: Five soluble ICK-related proteins were identified to be significantly associated with the risk and prognosis of PDAC. Patients who were classified as soluble immune-low subtype based on these biomarkers had better overall survival than those of the soluble immune-high subtype.

Risk of Death Associated With Reversion From Prediabetes to Normoglycemia and the Role of Modifiable Risk Factors.

Importance: Individuals with prediabetes have a higher risk of death than healthy individuals. However, previous findings have suggested that individuals with reversion from prediabetes to normoglycemia may not have a lower risk of death compared with individuals with persistent prediabetes. Objectives: To investigate the associations between changes in prediabetes status and risk of death and to elucidate the roles of modifiable risk factors in these associations. Design, Setting, and Participants: This population-based prospective cohort study used data from 45 782 participants with prediabetes from the Taiwan MJ Cohort Study who were recruited between January 1, 1996, and December 31, 2007. Participants were followed up from the second clinical visit to December 31, 2011, with a median (IQR) follow-up of 8 (5-12) years. Participants were categorized into 3 groups according to changes in their prediabetes status within a 3-year period after initial enrollment: reversion to normoglycemia, persistent prediabetes, and progression to diabetes. Cox proportional hazards regression models were used to examine the associations between changes in prediabetes status at baseline (ie, the second clinical visit) and risk of death. Data analysis was performed between September 18, 2021, and October 24, 2022. Main Outcomes and Measures: All-cause mortality, cardiovascular disease (CVD)-related mortality, and cancer-related mortality. Results: Of 45 782 participants with prediabetes (62.9% male; 100% Asian; mean [SD] age, 44.6 [12.8] years), 1786 (3.9%) developed diabetes and 17 021 (37.2%) reverted to normoglycemia. Progression from prediabetes to diabetes within a 3-year period was associated with higher risks of all-cause death (hazard ratio [HR], 1.50; 95% CI, 1.25-1.79) and CVD-related death (HR, 1.61; 95% CI, 1.12-2.33) compared with persistent prediabetes, while reversion to normoglycemia was not associated with a lower risk of all-cause death (HR, 0.99; 95% CI, 0.88-1.10), cancer-related death (HR, 0.91; 95% CI, 0.77-1.08), or CVD-related death (HR, 0.97; 95% CI, 0.75-1.25). Among individuals who were physically active, reversion to normoglycemia was associated with a lower risk of all-cause death (HR, 0.72; 95% CI, 0.59-0.87) compared with those with persistent prediabetes who were physically inactive. Among individuals with obesity, risk of death varied between those who experienced reversion to normoglycemia (HR, 1.10; 95% CI, 0.82-1.49) and those who had persistent prediabetes (HR, 1.33; 95% CI, 1.10-1.62). Conclusions and Relevance: In this cohort study, although reversion from prediabetes to normoglycemia within a 3-year period did not mitigate the overall risk of death compared with persistent prediabetes, risk of death associated with reversion to normoglycemia varied based on whether individuals were physically active or had obesity. These findings highlight the importance of lifestyle modification among those with prediabetes status.

Association of frailty with the incidence risk of cardiovascular disease and type 2 diabetes mellitus in long-term cancer survivors: a prospective cohort study.

BACKGROUND: Comorbidities among cancer survivors remain a serious healthcare burden and require appropriate management. Using two widely used frailty indicators, this study aimed to evaluate whether frailty was associated with the incidence risk of cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) among long-term cancer survivors. METHODS: We included 13,388 long-term cancer survivors (diagnosed with cancer over 5 years before enrolment) free of CVD and 6101 long-term cancer survivors free of T2DM, at the time of recruitment (aged 40-69 years), from the UK Biobank. Frailty was assessed by the frailty phenotype (FP_Frailty, range: 0-5) and the frailty index (FI_Frailty, range: 0-1) at baseline. The incident CVD and T2DM were ascertained through linked hospital data and primary care data, respectively. The associations were examined using Cox proportional hazards regression models. RESULTS: Compared with non-frail participants, those with pre-frailty (FP_Frailty [met 1-2 of the components]: hazard ratio [HR]=1.18, 95% confidence interval [CI]: 1.05, 1.32; FI_Frailty [0.10< FI ≤0.21]: HR=1.51, 95% CI: 1.32, 1.74) and frailty (FP_Frailty [met ≥3 of the components]: HR=2.12, 95% CI: 1.73, 2.60; FI_Frailty [FI >0.21]: HR=2.19, 95% CI: 1.85, 2.59) had a significantly higher risk of CVD in the multivariable-adjusted model. A similar association of FI_Frailty with the risk of incident T2DM was observed. We failed to find such an association for FP_Frailty. Notably, the very early stage of frailty (1 for FP_Frailty and 0.1-0.2 for FI_Frailty) was also positively associated with the risk of CVD and T2DM (FI_Frailty only). A series of sensitivity analyses confirmed the robustness of the findings. CONCLUSIONS: Frailty, even in the very early stage, was positively associated with the incidence risk of CVD and T2DM among long-term cancer survivors, although discrepancies existed between frailty indicators. While the validation of these findings is required, they suggest that routine monitoring, prevention, and interventive programs of frailty among cancer survivors may help to prevent late comorbidities and, eventually, improve their quality of life. Especially, interventions are recommended to target those at an early stage of frailty when healthcare resources are limited.

Development of a Novel Multidimensional Measure of Aging to Predict Mortality and Morbidity in the Prospective MJ Cohort.

BACKGROUND: Although biological aging has been proposed as a more accurate measure of aging, few biological aging measures have been developed for Asians, especially for young adults. METHODS: A total of 521 656 participants were enrolled in the MJ cohort (1996-2011) and were followed until death, loss-to-follow-up, or December 31, 2011, whichever came first. We selected 14 clinical biomarkers, including chronological age, using a random forest algorithm, and developed a multidimensional aging measure (MDAge). Model performance was assessed by area under the curve (AUC) and internal calibration. We evaluated the associations of MDAge and residuals from regressing MDAge on chronological age (MDAgeAccel) with mortality and morbidity, and assessed the robustness of our findings. RESULTS: MDAge achieved an excellent AUC of 0.892 in predicting all-cause mortality (95% confidence interval [CI]: 0.889-0.894). Participants with higher MDAge at baseline were at a higher risk of death (per 5 years, hazard ration [HR] = 1.671, 95% CI: 1.662-1.680), and the association remained after controlling for other variables and in different subgroups. Furthermore, participants with higher MDAgeAccel were associated with shortened life expectancy. For instance, compared to men who were biologically younger (MDAgeAccel ≤ 0) at baseline, men in the highest tertiles of MDAgeAccel had shortened life expectancy by 17.23 years. In addition, higher MDAgeAccel was associated with having chronic disease either cross-sectionally (per 1-standard deviation [SD], odds ratio [OR] = 1.564, 95% CI: 1.552-1.575) or longitudinally (per 1-SD, OR = 1.218, 95% CI: 1.199-1.238). CONCLUSION: MDAge accurately predicted mortality and morbidity, which has great potential in the early identification of individuals at higher risk and therefore promoting early intervention.

Body mass index and survival after cancer diagnosis: A pan-cancer cohort study of 114 430 patients with cancer.

The recommendation encouraging patients with cancer to keep a normal body mass index (BMI) is largely extrapolated from data on risk of developing cancer. We tested the prospective association between peri-diagnostic (within 1 year post-diagnosis) BMI and all-cause mortality in patients with incident cancers. During 7.2 years of follow-up, 42% (48,340) of the 114 430 patients with cancer died. Spline analysis revealed that compared with a BMI of 22.5, a BMI lower than 22.5 was associated with increased risk of all-cause mortality across 24 cancer types. A BMI higher than 22.5 was associated with reduced all-cause mortality, while a non-linear association was observed; the lowest risk was found at a BMI of 29.6-34.2, and the risk started to return to and above unity at very high BMI values. The reduced mortality risk of high BMI was observed in 23 of 24 cancer types and maintained after attempts to remove potential selection bias, confounding by smoking and comorbidities, and reserve causality. Compared with a normal BMI of 18.5-24.9, the hazard ratios were 0.85 (95% confidence interval [CI], 0.83-0.87) for an overweight BMI (25-29.9) and 0.82 (0.80-0.85) for an obese BMI (≥30), and the associations were generally consistent across cancer types and various subgroups. Obese BMI was associated with increased life expectancy, up to 6 years among men and 3 years among women. In conclusion, while overweight/obese BMI increases the risk of developing cancer in the general population, overweight/obese peri-diagnostic BMI was associated with longer survival in cancer patients.

Diagnostic Value of Peripheral Blood Lymphocytes for Primary Immune Thrombocytopenia.

The purpose of this study was to investigate the absolute value of peripheral blood lymphocytes in patients with primary immune thrombocytopenia and the diagnostic effect on patients with primary immune thrombocytopenia. From January 2020 to June 2021, 76 patients with primary immune thrombocytopenia and 80 healthy check-ups admitted to our hospital were selected as study subjects and divided into a control group (80 patients, healthy check-ups) and an observation group (76 patients, primary immune thrombocytopenia), according to the health status of the organism. Early morning fasting venous blood was collected from both groups, and the absolute value of peripheral blood lymphocytes was measured and compared using a fully automated hematology analyzer to investigate the diagnostic value of absolute peripheral blood lymphocytes in primary immune thrombocytopenia. The CD3+, CD3+CD4+, CD4+/CD8+, and CD16+CD56+ assay values in the observation group were lower than those in the control group, and the CD3+CD8+, CD19+, and ALC assay values were higher than those in the control group (P < 0.05). The CD3+CD8+ detection values of newly diagnosed patients were similar to those of relapsed refractory patients (P > 0.05); CD3+, CD3+CD4+, CD4+/CD8+, and CD16+CD56+ detection values of newly diagnosed patients were lower than those of relapsed refractory patients, and CD19+ and ALC detection values were higher than those of relapsed refractory patients; CD3+, CD3+CD4+, CD4+, CD4+/CD8+, and CD16+CD56+ detection values of mild patients were lower than those of relapsed refractory patients; CD3+, CD3+CD4+, CD4+/CD8+, and CD16+CD56+ detection values were higher in mild patients than in severe patients, and CD3+CD8+, CD19+, and ALC detection values were lower than in severe patients (P < 0.05). The absolute lymphocyte values were of high diagnostic value in primary immune thrombocytopenia, with a sensitivity and specificity of 93.42% and 90.00%. The application of absolute peripheral blood lymphocyte value in the clinical diagnosis of primary immune thrombocytopenia can achieve a better detection and diagnosis effect, which has a positive impact on the early diagnosis rate and can help patients to obtain more timely, effective and targeted treatment, and is worthy of promotion.