Phylogenetic Survival Analysis.

Going back in time through a phylogenetic tree makes it possible to evaluate ancestral genomes and assess their potential to acquire key polymorphisms of interest over evolutionary time. Knowledge of this kind may allow for the emergence of key traits to be predicted and pre-empted from currently circulating strains in the future. Here, we present a novel genome-wide survival analysis and use the emergence of drug resistance in Mycobacterium tuberculosis as an example to demonstrate the potential and utility of the technique.

Subjective cognitive concerns, APOE ε4, PTSD symptoms, and risk for dementia among older veterans.

BACKGROUND: Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are associated with self-reported problems with cognition as well as risk for Alzheimer's disease and related dementias (ADRD). Overlapping symptom profiles observed in cognitive disorders, psychiatric disorders, and environmental exposures (e.g., head injury) can complicate the detection of early signs of ADRD. The interplay between PTSD, head injury, subjective (self-reported) cognitive concerns and genetic risk for ADRD is also not well understood, particularly in diverse ancestry groups. METHODS: Using data from the U.S. Department of Veterans Affairs (VA) Million Veteran Program (MVP), we examined the relationship between dementia risk factors (APOE ε4, PTSD, TBI) and subjective cognitive concerns (SCC) measured in individuals of European (n = 140,921), African (n = 15,788), and Hispanic (n = 8,064) ancestry (EA, AA, and HA, respectively). We then used data from the VA electronic medical record to perform a retrospective survival analysis evaluating PTSD, TBI, APOE ε4, and SCC and their associations with risk of conversion to ADRD in Veterans aged 65 and older. RESULTS: PTSD symptoms (B = 0.50-0.52, p < 1E-250) and probable TBI (B = 0.05-0.19, p = 1.51E-07 - 0.002) were positively associated with SCC across all three ancestry groups. APOE ε4 was associated with greater SCC in EA Veterans aged 65 and older (B = 0.037, p = 1.88E-12). Results of Cox models indicated that PTSD symptoms (hazard ratio [HR] = 1.13-1.21), APOE ε4 (HR = 1.73-2.05) and SCC (HR = 1.18-1.37) were positively associated with risk for ADRD across all three ancestry groups. In the EA group, probable TBI also contributed to increased risk of ADRD (HR = 1.18). CONCLUSIONS: The findings underscore the value of SCC as an indicator of ADRD risk in Veterans 65 and older when considered in conjunction with other influential genetic, clinical, and demographic risk factors.

Prediction of lifespan and assessing risk factors of large-sample implant prostheses: a multicenter study.

PURPOSE: This study aimed to analyze factors influencing the success and failure of implant prostheses and to estimate the lifespan of prostheses using standardized evaluation criteria. An online survey platform was utilized to efficiently gather large samples from multiple institutions. MATERIALS AND METHODS: During the one-year period, patients visiting 16 institutions were assessed using standardized evaluation criteria (KAP criteria). Data from these institutions were collected through an online platform, and various statistical analyses were conducted. Risk factors were assessed using both the Cox proportional hazard model and Cox regression analysis. Survival analysis was conducted using Kaplan-Meier analysis and nomogram, and lifespan prediction was performed using principal component analysis. RESULTS: The number of patients involved in this study was 485, with a total of 841 prostheses evaluated. The median survival was estimated to be 16 years with a 95% confidence interval. Factors found to be significantly associated with implant prosthesis failure, characterized by higher hazard ratios, included the 'type of clinic', 'type of antagonist', and 'plaque index'. The lifespan of implant prostheses that did not fail was estimated to exceed the projected lifespan by approximately 1.34 years. CONCLUSION: To ensure the success of implant prostheses, maintaining good oral hygiene is crucial. The estimated lifespan of implant prostheses is often underestimated by approximately 1.34 years. Furthermore, standardized form, online platform, and visualization tool, such as nomogram, can be effectively utilized in future follow-up studies.

Comprehensive transcriptomic analysis identifies SLC25A4 as a key predictor of prognosis in osteosarcoma.

Background: Osteosarcoma (OS) is highly malignant and prone to local infiltration and distant metastasis. Due to the poor outcomes of OS patients, the study aimed to identify differentially expressed genes (DEGs) in OS and explore their role in the carcinogenesis and progression of OS. Methods: RNA sequencing was performed to identify DEGs in OS. The functions of the DEGs in OS were investigated using bioinformatics analysis, and DEG expression was verified using RT-qPCR and Western blotting. The role of SLC25A4 was evaluated using gene set enrichment analysis (GSEA) and then investigated using functional assays in OS cells. Results: In all, 8353 DEGs were screened. GO and KEGG enrichment analyses indicated these DEGs showed strong enrichment in the calcium signaling pathway and pathways in cancer. Moreover, the Kaplan-Meier survival analysis showed ten hub genes were related to the outcomes of OS patients. Both SLC25A4 transcript and protein expression were significantly reduced in OS, and GSEA suggested that SLC25A4 was associated with cell cycle, apoptosis and inflammation. SLC25A4-overexpressing OS cells exhibited suppressed proliferation, migration, invasion and enhanced apoptosis. Conclusion: SLC25A4 was found to be significantly downregulated in OS patients, which was associated with poor prognosis. Modulation of SLC25A4 expression levels may be beneficial in OS treatment.

Application of Mixture and Non-mixture Cure Models in Survival Analysis of Patients With COVID-19.

Background Due to the emergence of new COVID-19 mutations and an increase in re-infection rates, it has become an important priority for the medical community to identify the factors affecting the short- and long-term survival of patients. This study aimed to determine the risk factors of short- and long-term survival in patients with COVID-19 based on mixture and non-mixture cure models. Methodology In this study, the data of 880 patients with COVID-19 confirmed with polymerase chain reaction in Fereydunshahr city (Isfahan, Iran) from February 20, 2020, to December 21, 2021, were gathered, and the vital status of these patients was followed for at least one year. Due to the high rate of censoring, mixture and non-mixture cure models were applied to estimate the survival. Akaike information criterion values were used to evaluate the fit of the models. Results In this study, the mean age of the patients was 48.9 ± 21.23 years, and the estimated survival rates on the first day, the fourth day, the first week, the first month, and at one year were 0.997, 0.982, 0.973, 0.936, and 0.928, respectively. Among the parametric models, the log-logistic mixed cure model with the logit link, which showed the lowest Akaike information criterion value, demonstrated the best fit. The variables of age and prescribed medication type were significant predictors of long-term survival, while occupation was influential in the short-term survival of patients. Conclusions According to the results of this study, it can be concluded that elderly patients should observe health protocols more strictly and consider receiving booster vaccine doses. The log-logistic cure model with a logit link can be used for survival analysis in COVID-19 patients, a fraction of whom have long-term survival.

Reproductive potential and implant loss in female hamadryas baboons (Papio hamadryas) previously contracepted with melengestrol acetate contraceptive implants at AZA institutions.

Melengestrol acetate (MGA) implants are a progestin-based reversible contraceptive used to manage fertility in animals. MGA implants are recommended for replacement every 2 years; however, reproduction may be suppressed longer if implants are not removed. In this study, we investigated whether the probability of reproducing (pR) differed among nonimplanted females, females with MGA implants removed, and females whose implants were not removed. In addition, since implant loss in hamadryas baboons is a concern, we explored whether female age, institution, implant placement year, implant location, or implant placement type (intramuscular vs. subcutaneous) differed for females whose implants were lost compared to those that were not. The pR differed significantly across all three treatment conditions with the nonimplanted group having the highest pR. The pR plateaued at 63% after 40 months for the implant-removed group compared to 96% after 84 months in the nonimplanted group. There was no reproduction after contraception if implants were not removed (7.83-45.53 months). In the nonimplanted group, pR was significantly higher for older and parous females. In terms of implant loss, we found that implant placement type was significantly associated with implant loss, such that there were fewer losses when implants were placed intramuscularly (IM) as compared to subcutaneously. Our results suggest that placing MGA implants IM is likely to reduce loss. When loss is prevented, MGA implants are an effective form of contraception and are reliably reversibly in most individuals when removed. However, if not removed, they can prevent reproduction longer than 2 years.

Making Sense of Censored Covariates: Statistical Methods for Studies of Huntington's Disease.

The landscape of survival analysis is constantly being revolutionized to answer biomedical challenges, most recently the statistical challenge of censored covariates rather than outcomes. There are many promising strategies to tackle censored covariates, including weighting, imputation, maximum likelihood, and Bayesian methods. Still, this is a relatively fresh area of research, different from the areas of censored outcomes (i.e., survival analysis) or missing covariates. In this review, we discuss the unique statistical challenges encountered when handling censored covariates and provide an in-depth review of existing methods designed to address those challenges. We emphasize each method's relative strengths and weaknesses, providing recommendations to help investigators pinpoint the best approach to handling censored covariates in their data.

Survival among people with HIV and their families in Denmark 1995-2021: a nationwide population-based cohort study.

Background: Survival among people with HIV (PWH) has vastly improved globally over the last few decades but remains lower than among the general population. We aimed to estimate time trends of survival among PWH and their families from 1995 to 2021. Methods: We conducted a registry-based, nationwide, population-based, matched cohort study. We included all Danish-born PWH from 1995 to 2021 who had been on antiretroviral therapy for 90 days, did not report intravenous drug use, and were not co-infected with hepatitis C (n = 4168). We matched population controls from the general population 10:1 to PWH by date of birth and sex (n = 41,680). For family cohorts, we identified siblings, mothers, and fathers of PWH and population controls. From Kaplan-Meier tables with age as time scale, we estimated survival from age 25. We compared PWH with population controls and families of PWH with families of population controls to calculate mortality rate ratios adjusted for sex, age, comorbidities, and education (aMRR). Findings: The median age of death among PWH increased from 27.5 years in 1995-1997 to 73.9 years (2010-2014), but thereafter survival increased only marginally. From 2015 to 2021, mortality was increased among PWH (aMRR 1.87 (95% CI: 1.65-2.11)) and siblings (aMRR: 1.25 (95% CI: 1.07-1.47)), mothers (aMRR: 1.30 (95% CI: 1.17-1.43)), and fathers (aMRR: 1.15 (95% CI: 1.03-1.29)) of PWH compared to their respective control cohorts. Mortality among siblings of PWH who reported heterosexual route of HIV transmission (aMRR: 1.51 (95% CI: 1.16-1.96)) was higher than for siblings of PWH who reported men who have sex with men as route of HIV transmission (aMRR 1.19 (95% CI: 0.98-1.46)). Interpretation: Survival among PWH improved substantially until 2010, after which it increased only marginally. This may partly be due to social and behavioural factors as PWH families also had higher mortality. Funding: Preben and Anna Simonsen's Foundation and Independent Research Fund Denmark.

Survival Analysis of Patients with Severe Acute Malnutrition Admitted at the In-patient Therapeutic Care of the Bicol Regional Training and Teaching Hospital.

Background: Severe acute malnutrition (SAM) in children under five years remains a major global health concern. It carries a burden to the overall health of a child, contributes to mortality, and adds financial strain to the family and the hospital. The Philippine Integrated Management of Acute Malnutrition was established to address acute malnutrition in Filipino children. Objective: This study aimed to determine the factors affecting survival of patients admitted at Bicol Regional Training and Teaching Hospital (BRTTH) In-patient Therapeutic Care (ITC). Methods: This is a retrospective cohort study design utilizing survival analysis. Accrual period was from January 1, 2018 to December 31, 2018. Follow-up ended on March 31, 2019. There were 154 admissions and excluded 17 missing charts. Survival analysis was done utilizing STATA 14. Results: The prevalence of SAM requiring ITC admission was 3.0 percent. Majority belonged to 6-59 months of age (63%), with equal predilection for both sexes (1:1) and 71% came from the home province, Albay. Most of patients' caretakers had middle educational attainment. Sixty-eight percent (68%) were new patients, 16% readmitted, 15% transferred from the Out-patient Therapeutic Care (OTC) and <1% relapsed. The top three most common complications and co-morbidities include: pneumonia, low electrolytes, and fever. Sixty-three percent (63%) of patients at the ITC had a desirable treatment outcome, of which, 8% were cured and 55% transferred to OTC. Undesirable outcomes accounted for 37% of the cases which included non-cured, defaulter, and died at 12%, 8%, and 17%, respectively. The risk of dying was higher in SAM patients with parents having middle and low educational attainment as compared to those with high educational attainment (2-5 folds to 100-200 folds). SAM patients presenting with hypovolemic shock were likely to die by 1.5-19 times (1.5-19x) as compared to those without. SAM patients with malignancy were more likely to die 4-44 folds as compared to patients without malignancy. Conclusion and Recommendations: Educational attainment of parents, malignancy, and hypovolemic shock were significant predictors of mortality. We recommend prompt intervention by educating families, strengthen policies targeting socio-economic determinants, capacitate medical staff, refine current clinical practice guidelines and treatment pathways to reduce the number of children who die from severe acute malnutrition.

A deep learning approach for overall survival prediction in lung cancer with missing values.

BACKGROUND AND OBJECTIVE: In the field of lung cancer research, particularly in the analysis of overall survival (OS), artificial intelligence (AI) serves crucial roles with specific aims. Given the prevalent issue of missing data in the medical domain, our primary objective is to develop an AI model capable of dynamically handling this missing data. Additionally, we aim to leverage all accessible data, effectively analyzing both uncensored patients who have experienced the event of interest and censored patients who have not, by embedding a specialized technique within our AI model, not commonly utilized in other AI tasks. Through the realization of these objectives, our model aims to provide precise OS predictions for non-small cell lung cancer (NSCLC) patients, thus overcoming these significant challenges. METHODS: We present a novel approach to survival analysis with missing values in the context of NSCLC, which exploits the strengths of the transformer architecture to account only for available features without requiring any imputation strategy. More specifically, this model tailors the transformer architecture to tabular data by adapting its feature embedding and masked self-attention to mask missing data and fully exploit the available ones. By making use of ad-hoc designed losses for OS, it is able to account for both censored and uncensored patients, as well as changes in risks over time. RESULTS: We compared our method with state-of-the-art models for survival analysis coupled with different imputation strategies. We evaluated the results obtained over a period of 6 years using different time granularities obtaining a Ct-index, a time-dependent variant of the C-index, of 71.97, 77.58 and 80.72 for time units of 1 month, 1 year and 2 years, respectively, outperforming all state-of-the-art methods regardless of the imputation method used. CONCLUSIONS: The results show that our model not only outperforms the state-of-the-art's performance but also simplifies the analysis in the presence of missing data, by effectively eliminating the need to identify the most appropriate imputation strategy for predicting OS in NSCLC patients.

Dual-stream multi-dependency graph neural network enables precise cancer survival analysis.

Histopathology image-based survival prediction aims to provide a precise assessment of cancer prognosis and can inform personalized treatment decision-making in order to improve patient outcomes. However, existing methods cannot automatically model the complex correlations between numerous morphologically diverse patches in each whole slide image (WSI), thereby preventing them from achieving a more profound understanding and inference of the patient status. To address this, here we propose a novel deep learning framework, termed dual-stream multi-dependency graph neural network (DM-GNN), to enable precise cancer patient survival analysis. Specifically, DM-GNN is structured with the feature updating and global analysis branches to better model each WSI as two graphs based on morphological affinity and global co-activating dependencies. As these two dependencies depict each WSI from distinct but complementary perspectives, the two designed branches of DM-GNN can jointly achieve the multi-view modeling of complex correlations between the patches. Moreover, DM-GNN is also capable of boosting the utilization of dependency information during graph construction by introducing the affinity-guided attention recalibration module as the readout function. This novel module offers increased robustness against feature perturbation, thereby ensuring more reliable and stable predictions. Extensive benchmarking experiments on five TCGA datasets demonstrate that DM-GNN outperforms other state-of-the-art methods and offers interpretable prediction insights based on the morphological depiction of high-attention patches. Overall, DM-GNN represents a powerful and auxiliary tool for personalized cancer prognosis from histopathology images and has great potential to assist clinicians in making personalized treatment decisions and improving patient outcomes.

Prognostic effect of microscopically negative but close resection margin in gastric cancer.

INTRODUCTION: Microscopically positive resection margin (RM) following curative surgery has been linked to disease recurrence in gastric cancer (GC), but the impact of microscopically negative but close RM (CRM) remains unclear. This study aimed to evaluate the prognostic implications of a CRM of ≤0.5 cm in GC patients. METHODS: A retrospective review of the institutional GC database identified 1958 patients who underwent curative gastrectomy for pathologically proven GC between January 2011 and December 2015. The patients were categorized into CRM (RM ≤0.5 cm) and sufficient RM (SRM, RM >0.5 cm) groups. The impact of CRM on recurrence-free survival (RFS) and overall survival (OS) was analyzed compared to the SRM group. RESULTS: The cohort comprised 1264 patients with early GC (EGC, 64.6%) and 694 with advanced GC (AGC, 35.4%). Forty-four patients (2.2%) had RM of ≤0.5 cm. CRM was associated with worse RFS in AGC (5-year RFS in the CRM vs. SRM groups; 41.6% vs. 68.7%, p = 0.011); however, the effect on OS was not significant (p = 0.159). Multivariate analysis revealed that CRM was an independent prognostic factor for RFS (hazard ratio [HR] 2.035, 95% confidence interval [CI] 1.097-3.776). In AGC, the locoregional recurrence rate was significantly higher in the CRM group than in the SRM group (15.4% vs. 4.9%, p = 0.044). CONCLUSION: CRM of ≤0.5 cm was a significant prognostic factor for RFS in GC patients and was associated with a significant increase in locoregional recurrence in AGC.

Impact of reproductive traits on productive life in Iranian Holstein dairy cows.

Enhancing reproductive performance is a key strategy to mitigate involuntary culling rates, thereby extending productive life (PL) and ultimately improving profitability in dairy cattle herds. A piecewise Weibull proportional hazards model was used to investigate the effect of several important reproductive traits on PL in Holstein dairy cows. Data comprised 200,747 lactation records from 82,505 cows sired by 1952 bulls across 36 dairy herds. PL was defined as the number of days from the first calving to the last milk record or censoring. The statistical model accounted for the time-dependent fixed effects of changes in herd size, year-season, milk production, fat and protein contents, and the time-independent fixed effect of age at first calving. Herd-year and sire effects were also included as random effects. Reproductive traits include calving traits such as calving ease (CE), calf size (CZ), and calf survival (CS), as well as female fertility traits such as number of inseminations per conception (NI), days from calving to first service (CFS), days from first service to conception (FSC), and days open (DO). All reproductive traits had a significant effect on PL (p < 0.001). Each reproductive trait was analysed separately. The relative risk (RR) of being culled increased as the severity of calving difficulties increased in both primiparous and multiparous cows. Cows that calved small or large calves showed a higher risk of being culled compared with those that calved medium size calves. The increased RR of culling was observed only for primiparous cows that gave birth to dead calves. In addition, cows that required more NI, a longer CFS, FSC, and DO had shorter longevity. These insights can deepen our comprehension of the factors affecting PL and provide information for refining management and breeding strategies, which could lead to increased profitability and sustainability in Iranian dairy farming.

Impact of Social Vulnerability Index on the Development of Severe Visual Impairment or Blindness from Glaucoma.

PURPOSE: To evaluate whether geocoded social risk factor data predict the development of severe visual impairment or blindness due to glaucoma during follow-up using a large electronic health record (EHR) database. DESIGN: Cohort study. METHODS: Patients diagnosed with open-angle glaucoma (OAG) at a tertiary care institution. All eyes had glaucomatous visual field defects at baseline. Sociodemographic and ocular data were extracted from EHR, including age, gender, self-reported race and ethnicity, insurance status, OAG type, prior glaucoma laser or surgery, baseline disease severity using Hodapp-Anderson-Parrish criteria, mean intraocular pressure (IOP) during follow-up, and central corneal thickness. Social vulnerability index (SVIndex) data at the census tract level were obtained using geocoded patient residences. Mixed-effects Cox proportional hazard models were completed to assess for the development of severe visual impairment or blindness during follow-up, defined as BCVA ≤20/200 at the last two clinic visits or standard automated perimetry (SAP) mean deviation (MD) ≤-22dB confirmed on two tests. RESULTS: A total of 4,046 eyes from 2,826 patients met inclusion criteria and were followed for an average of 4.3±2.2 years. Severe visual impairment or blindness developed in 79 eyes (2.0%) from 76 patients (2.7%) after an average of 3.4±1.8 years, leading to an incidence rate of severe visual impairment or blindness of 0.5% per year. Older age (adjusted hazards ratio (HR) 1.36 per decade, p=0.007), residence in areas with higher SVIndex (HR 1.56 per 25% increase, p<0.001), higher IOP during follow-up (HR 3.01 per 5 mmHg increase, p<0.001), and moderate or severe glaucoma at baseline (HR 7.31 and 26.87, p<0.001) were risk factors for developing severe visual impairment or blindness. Concordance index of the model was 0.87. Socioeconomic, minority status/language, and housing type/transportation SVIndex themes were key contributors to developing severe visual impairment or blindness. CONCLUSIONS: Risk factors for developing glaucoma-related severe visual impairment or blindness included older age, elevated IOP during follow-up, moderate or severe disease at baseline, and residence in areas associated with greater social vulnerability. In addition to ocular risk factors, geocoded EHR data regarding social risk factors could help identify patients at high risk of developing glaucoma-related visual impairment.

Cross-substance Effects of Adolescent Exposure to Alcohol Content in Popular Movies on Cannabis Initiation.

Objective: Alcohol is the most frequently depicted substance in the media, and adolescent exposure to alcohol in the media predicts alcohol use. There is relatively little research on exposure to cannabis in the media, but exposure to alcohol content may exert cross-substance effects on cannabis use. Given the social and health risks associated with early cannabis use, the present study aims to assess the cross-substance effects of exposure to alcohol media content on age of cannabis initiation. Method: A sample of 830 middle school students (53% female) reported on movie alcohol exposure and cannabis initiation longitudinally until high school completion. Discrete-time survival models examined whether movie alcohol exposure predicted subsequent initiation among students who were cannabis-naïve at baseline, controlling for demographic, social, and behavioral covariates. The interaction between sex and movie alcohol exposure was also explored. Results: One third (33%) of participants reported cannabis initiation with a mean of 5.57 estimated hours (SD = 4.29) of movie alcohol exposure. A 1-hour increase in movie exposure predicted a significant 16% increased probability of cannabis initiation in models adjusted for demographic variables and a significant 14% increase in models adjusted for demographic, behavioral, and social variables. No differences were observed across sex. Conclusions: Greater adolescent exposure to alcohol content in the media was associated with earlier cannabis initiation above and beyond other etiologically relevant demographic, behavioral, and social variables. The influence of cross-substance media exposures warrants further exploration and should be taken into consideration in the development of preventive interventions for youth substance use.

Brain natriuretic peptide is a long-term cardiovascular predictor in carotid endarterectomy.

BACKGROUND: In noncardiac surgery, several biomarkers are known to play a role in predicting long-term complications, such as major adverse cardiovascular events (MACE), myocardial infarction, or death. Carotid endarterectomy (CEA) is considered a low to medium-risk surgery for carotid stenosis aimed at preventing stroke events. Brain natriuretic peptide (BNP) is a biomarker with potential prognostic value regarding MACE. Since its role in patients undergoing CEA is unknown, this study aims to assess the potential role of BNP as a short and long-term predictor of all-cause mortality and MACE in patients undergoing CEA. METHODS: From a prospective database, patients who underwent CEA under regional anesthesia (RA) at a tertiary hospital center were enrolled, and a post hoc analysis was conducted. Patients on which BNP levels were measured up to fifteen days before surgery, and two groups based on the BNP threshold (200 pg/mL) were defined and compared. Kaplan Meier survival curves and adjusted hazard ratios (aHR) were assessed by multivariable Cox regression. The primary outcome was the incidence of long-term MACE and all-cause mortality. Secondary outcomes included the incidence of AMI and AHF. RESULTS: A total of 89 patients were evaluated. The mean age of the cohort was 71.2 ± 8.7 years, with 71 (79.8%) males, and presented a median follow-up of 30 [13.5-46.4] months. BNP > 200 pg/mL has demonstrated positive predictive value for MACE (aHR: 5.569, confidence interval (CI): 2.441-12.7, p < 0.001) and all-cause mortality (aHR: 3.469, CI: 1.315-9.150, p = 0.018). CONCLUSION: BNP has been demonstrated to independently predict long-term all-cause mortality, MACE and AMI following CEA. It serves as a low-cost, ready-to-use biomarker, although further studies are necessary.

Combined Charlson comorbidity/C-Reactive Protein Index Is a Novel Predictor in Renal Cell Carcinoma: Analysis of the International Marker Consortium for Renal Cancer (INMARC) Registry.

OBJECTIVE: To evaluate predictive ability of a novel combined index, Charlson comorbidity index and C-reactive protein (CCI-CRP), for outcomes in renal cell carcinoma (RCC), and compare predictive outcomes with of CCI-CRP to its separate components and to the UCLA integrated staging system (UISS). PATIENTS AND METHODS: We retrospectively analyzed INMARC registry of RCC patients. Receiver Operator Characteristics (ROC) analysis was fitted to identify threshold defining low-CRP (LCRP) and high-CRP (HCRP). Patients were stratified according to CCI [low-CCI ≤ 3 (LCCI); intermediate-CCI 4-6 (ICCI); high-CCI > 6 (HCCI)] and CRP level. Kaplan-Meier analysis (KMA) was conducted for overall (OS) and cancer-specific survival (CSS). Based on survival analysis distribution we proposed a new stratification: CCI-CRP. Model performance was assessed with ROC/area under the curve (AUC) analysis and compared to CCI and CRP alone, and UISS. RESULTS: We analyzed 2,890 patients (median follow-up 30 months). ROC identified maximum product sensitivity and specificity for CRP at 3.5 mg/L. KMA revealed 5-year OS of 95.6% for LCRP/LCCI, 83% LCRP/ICCI, 73.3% LCRP/HCCI, 62.6% HCRP/LCCI, 51.6% HCRP/ICCI and 40.5% HCRP/HCCI (P < .001). From this distribution, new CCI-CRP is proposed: low CCI-CRP (LCRP/LCCI and LCRP/ICCI), intermediate CCI-CRP (LCRP/HCCI and HCRP/LCCI), and high CCI-CRP (HCRP/ICCI and HCRP/HCCI). AUC for CCI-CRP showed improved performance for predicting OS/CSS vs. CCI alone (0.73 vs. 0.63/0.77 vs. 0.60), CRP alone (0.73 vs. 0.71/0.77 vs. 0.74) and UISS (0.73 vs 0.67/0.77 vs 0.73). CONCLUSIONS: CCI-CRP, exhibits increased prognostic performance for survival outcomes in RCC compared to CCI and CRP alone, and UISS. Further investigation is requisite.

Nocturnal Hypoxemic Burden in Patients with Heart Failure: Emerging Prognostic Role of Its Non-Specific Component.

BACKGROUND: Nocturnal hypoxemic burden has been shown to be a robust, independent predictor of all-cause mortality in patients with heart failure and reduced ejection fraction (HFrEF) and to occur in a severe form even in patients with low or negligible frequency of respiratory events (apneas/hypopneas). This suggests the existence of two components of hypoxemic burden: one unrelated to respiratory events and the other related. The aim of this study was to characterize these two components and to evaluate their prognostic value. METHODS: Nocturnal hypoxemic burden was assessed in a cohort of 280 patients with HFrEF by measuring the percentage of sleep with an oxygen saturation (SpO2) <90% (T90), and the area of the SpO2 curve below 90% (Area90). Both indices were also recalculated within the sleep segments associated with respiratory events (event-related component: T90Eve, Area90Eve) and outside these segments (non-specific component: T90Nspec, Area90Nspec). The outcome of the survival analysis (Cox regression) was all-cause mortality. RESULTS: During a median follow-up of 60 months, 87 patients died. T90, Area90, and their components were significant in univariate analysis (p<0.05 all). However, when these indices were adjusted for known risk factors, T90, T90Nspec, Area90, and Area90Nspec remained statistically significant (p=0.018, hazard ratio (HR)=1.12, 95%CI=(1.02, 1.23); p=0.007, HR=1.20, 95%CI=(1.05, 1.37); p=0.020, HR=1.05, 95%CI=(1.01, 1.10); p=0.0006, HR=1.15, 95%CI=(1.06, 1.25)), whereas T90Eve and Area90Eve did not (p=0.27, p=0.28). These results were internally validated using bootstrap resampling. CONCLUSIONS: By demonstrating a significant independent association of non-specific hypoxemic burden with all-cause mortality, this study suggests that this component of total nocturnal hypoxemic burden may play an important prognostic role in patients with HFrEF.

MYBL2 is a Novel Independent Prognostic Biomarker and Correlated with TMB in pancreatic cancer.

Background: Pancreatic cancer continues to pose a significant threat due to its high mortality rate. While MYB family genes have been identified as oncogenes in certain cancer types, their role in pancreatic cancer remains largely unexplored. Methods: The mRNA and protein expression of MYB family genes in pancreatic cancer samples was analyzed using TNMplot, HPA, and TISBID online bioinformatics tools, sourced from the TCGA and GETx databases. The relationship between MYB family gene expression and survival time was assessed through Kaplan-Meier analysis, while the prognostic impact of MYB family gene expression was evaluated using the Cox proportional hazards model. Additionally, Spearman's correlation analysis was employed to investigate the correlation between MYB family genes and TMB/MSI. Results: The integration of data from various databases demonstrated that all MYB family genes exhibited dysregulated expression in pancreatic cancer. However, only the expression of the MYBL2 gene displayed a notable association with the grade and stage of pancreatic cancer. Furthermore, the MYBL2 gene exhibited significant variations in both univariate and multivariate factor analyses.Subsequent functional analyses revealed a significant correlation between MYBL2 expression in pancreatic cancers and various biological processes, such as DNA replication, tumor proliferation, G2M checkpoint regulation, pyrimidine metabolism, and the P53 pathway. Additionally, a notable positive association was observed between MYBL2 expression and tumor mutational burden (TMB), a predictive indicator for response to PD1 antibody treatment. Conclusion: MYBL2 may be a double marker for independent diagnosis and PD1 antibody response prediction of pancreatic cancer patients.

Impact of pre-operative abdominal MRI on survival for patients with resected pancreatic carcinoma: a population-based study.

Background: This study determined the impact of pre-operative abdominal MRI on all-cause mortality for patients with resected PDAC. Methods: All adult (≥18 years) PDAC patients who underwent pancreatectomy between January 2011 and December 2022 in Ontario, Canada, were identified for this population-based cohort study (ICD-O-3 codes: C250, C251, C252, C253, C257, C258). Patient demographics, comorbidities, PDAC stage, medical and surgical management, and survival data were sourced from multiple linked provincial administrative databases at ICES. All-cause mortality was compared between patients with and without a pre-operative abdominal MRI after controlling for multiple covariates. Findings: A cohort of 4579 patients consisted of 2432 men (53.1%) and 2147 women (46.9%) with a mean age of 65.2 years (standard deviation: 11.2 years); 2998 (65.5%) died while 1581 (34.5%) survived. Median follow-up duration post-resection was 22.4 months (interquartile range: 10.8-48.8 months), and median survival post-pancreatectomy was 25.9 months (95% confidence interval [95% CI]: 24.8, 27.5). Patients who underwent a pre-operative abdominal MRI had a median survival of 33.1 months (95% CI: 30.7, 37.2) compared to 21.1 months (95% CI: 19.8, 22.6) for all others. A total of 2354/4579 (51.4%) patients underwent a pre-operative abdominal MRI, which was associated with a 17.2% (95% CI: 11.0, 23.1) decrease in the rate of all-cause mortality, with an adjusted hazard ratio (aHR) of 0.828 (95% CI: 0.769, 0.890). Interpretation: Pre-operative abdominal MRI was associated with improved overall survival for PDAC patients who underwent pancreatectomy, possibly due to better detection of liver metastases than CT. Funding: Northern Ontario Academic Medicine Association (NOAMA) Clinical Innovation Fund.