Cox Survival Models Research Articles

Myocardial Histopathology in Patients With Obstructive Hypertrophic Cardiomyopathy

BackgroundHypertrophic cardiomyopathy (HCM) is characterized by multiple pathological features including myocyte hypertrophy, myocyte disarray, and interstitial fibrosis. ObjectivesThis study sought to correlate myocardial histopathology with clinical characteristics of patients with obstructive HCM and post-operative outcomes following septal myectomy. MethodsThe authors reviewed the pathological findings of the myocardial specimens from 1,836 patients with obstructive HCM who underwent septal myectomy from 2000 to 2016. Myocyte hypertrophy, myocyte disarray, interstitial fibrosis, and endocardial thickening were graded and analyzed. ResultsThe median age at operation was 54.2 years (43.5 to 64.3 years), and 1,067 (58.1%) were men. A weak negative correlation between myocyte disarray and age at surgery was identified (ρ = −0.22; p < 0.001). Myocyte hypertrophy (p < 0.001), myocyte disarray (p < 0.001), and interstitial fibrosis (p < 0.001) were positively associated with implantable cardioverter-defibrillator implantation. Interstitial fibrosis (p < 0.001) and endocardial thickening (p < 0.001) were associated with atrial fibrillation pre-operatively. In the Cox survival model, older age (p < 0.001), lower degree of myocyte hypertrophy (severe vs. mild hazard ratio: 0.41; 95% confidence interval: 0.19 to 0.86; p = 0.040), and lower degree of endocardial thickening (moderate vs. mild hazard ratio: 0.75; 95% confidence interval: 0.58 to 0.97; p = 0.019) were independently associated with worse post-myectomy survival. Among 256 patients who had genotype analysis, patients with pathogenic or likely pathogenic variants (n = 62) had a greater degree of myocyte disarray (42% vs. 15% vs. 20%; p = 0.022). Notably, 13 patients with pathogenic or likely pathogenic genetic variants of HCM had no myocyte disarray. ConclusionsHistopathology was associated with clinical manifestations including the age of disease onset and arrhythmias. Myocyte hypertrophy and endocardial thickening were negatively associated with post-myectomy mortality.

Follow-up of women screened for cervical cancer in São Paulo, Brazil: An analysis of the times to diagnostic investigation and treatment

BackgroundCervical cancer incidence and mortality rates are higher in Brazil than in western countries. Access to cytology-based screening has increased in the country in recent decades, but few studies have assessed the quality of the follow-up care of women with abnormal screening tests that require further investigation. MethodsA record-linkage cohort study was conducted in São Paulo state. Women aged 25+ years, who were screened in 2010, and whose test revealed a high-grade, or more severe, lesion were eligible. Follow-up information on diagnostic investigations, treatments and mortality was obtained through record-linkage of health databases. The Kaplan-Meier method was used to estimate median times between screening and diagnostic investigation, and diagnosis and treatment initiation. Cox survival models were used to identify correlates of the length of these time intervals. Results4300 women had a high-grade, or more severe, test result. Of these, 2788 (64.8 %) had a diagnostic investigation record, 1763 (41 %) a confirmed diagnosis of a precursor lesion or cancer, and 1247 (70.7 %) a treatment record. The median time to diagnosis was 190 days, with the probability of undergoing a diagnostic investigation within 30 days of the abnormal screening test being 7%. The median time to treatment was 81 days, with the probability of undergoing treatment within 60 days of a confirmed diagnosis being 44 %. Delays in diagnosis and treatment were associated with area-based healthcare indicators. ConclusionTimes to diagnosis and treatment were long, well above recommendations. Strategies to improve follow-up care must be prioritized to ensure screening reduces cervical cancer incidence and mortality.

Time-varying prognostic effects of primary tumor sidedness and grade after curative liver resection for colorectal liver metastases

BackgroundThe veracity of the proportional hazards (PH) requirement is rarely scrutinized in most areas of cancer research, although fulfilment of this assumption underpins widely-used Cox survival models. We sought to critically appraise the existence of prognostic factors with time-dependent effects and to characterize their impact on survival among CLM patients. MethodsConsecutive patients who underwent liver resection with curative intent for CLM at the Singapore General Hospital were identified from a prospectively-maintained database. We evaluated PH of 55 candidate variables, and parameters which departed significantly from proportionality were included in Cox models that incorporated an interaction term to account for time-dependent effects. As sensitivity analyses, we fitted Weibull mixture ‘cure’ models to handle long plateaus in the tails of survival curves, and also analyzed the restricted mean survival time. Results318 consecutive patients who underwent curative liver resection for CLM between Jan 2000 and Nov 2016 were included in this analysis. Hazard ratios for tumor grade (poorly-versus well- and moderately-differentiated) were found to decrease from 3.135 (95% CI: 1.637–6.003) at 12 months to 2.048 (95% CI: 1.038–4.042) after 24 months, and ceased to be significant at 26 months. Compared to left-sided tumors, a right-sided tumor location was found to portend worse prognosis for the first 10 months after resection but subsequently confer a survival benefit due to a crossing of survival curves. Corroborating this observation, long-term cure fractions were estimated to be 25.5% (95% CI: 17.4%–33.6%) and 34.2% (95% CI: 17.4%–50.9%) among patients with left-sided and right-sided primary disease respectively. ConclusionPrimary tumor sidedness and grade appear to exert time-varying prognostic effects in CLM patients undergoing curative liver resection.

Utility of Total Cardiac and Right Ventricular Mass Ratios in Recipients with Pulmonary Hypertension: A UNOS Database Analysis

<h3>Purpose</h3> Cardiac mass ratio (CMR) is validated for donor-recipient sizing, and as a predictor of transplant outcomes. However, there is a lack of data reviewing the role CMR plays in transplant recipients with pulmonary hypertension (pHTN). In particular, the right ventricular (RV) mass ratio (RVMR) is a component of CMR not yet studied separately for this purpose. We aimed to review the relationship of CMR and RVMR with pHTN in terms of development of primary graft dysfunction (PGD) and overall survival. <h3>Methods</h3> The United Network for Organ Sharing (UNOS) database was queried for primary heart transplant patients from 1987 to 2020. Missing data was imputed using a Bayesian network. Left ventricular (LV), RV, total cardiac mass (CM), and their ratios were calculated for donors and recipients. Relevant hemodynamic variables were included in logistic regression and cox proportional-hazards models to evaluate a relationship to PGD and overall survival. A stepwise regression created parsimonious models. Covariates with statistically significant relationships to the outcomes were included in tensor product spline models. <h3>Results</h3> 62,169 patients were identified. A parsimonious logistic model for odds of PGD included RVMR (OR 0.99, p<0.001) and mean PAP (mPAP) (OR 1.00, p<0.001). A parsimonious cox model for survival included diastolic PAP (HR 1.01, p<0.001), systolic PAP (HR 1.01, p<0.001), mPAP (HR 0.98, p<0.001), transpulmonary gradient (TPG) (HR 1.01, p<0.001), and CMR (HR 0.76, p<0.001). A tensor product spline model evaluating PGD demonstrated increasing odds of PGD in patients with elevated mPAP and smaller RVMR (Figure, p<0.001). Comparable models evaluating overall survival demonstrated smaller CMR was associated with reduced survival at elevated mPAP (p<0.001) and TPG (p<0.001). <h3>Conclusion</h3> In patients with pHTN, RVMR is significantly associated with odds of developing PGD, and CMR is with overall survival. Some RV oversizing may be beneficial to mitigate the risk of PGD.

Cox Model Survival Analysis to Evaluate Treatment of Electro-Capacitive Cancer Therapy (ECCT) For Cancer Patients

Cancer is a disease caused by uncontrolled growth of abnormal cells in the body. Lung cancer, brain cancer and breast cancer are a deadly threat to sufferers. Cancer treatment using a therapy called Electro-Capacitive Cancer Therapy (ECCT) has received a lot of medical attention. Since 2012, the C-Tech Labs Edwar Technology Cancer Research Tangerang has applied ECCT to the therapeutic treatment more than 11,000 cancer patients. In this study, the Cox Proportional Hazard model was used to asses factors that affects survival of cancer patients. Some prognostic factors are evaluated included age of patient and type treatments such as herbs therapy, chemotherapy, radiotherapy and monitoring frequency of ECCT. The all three survival models (breast cancer, brain cancer, and lung cancer) identified the same prognostic factors. The study showed that monitoring frequency of ECCT is significant factor that influenced in cancer survival for all three survival models. Based on the Cox survival model, the hazard ratio (HR) value ranges from are 0.8 – 0.9. It means that each additional one time the frequency of monitoring, the risk of experiencing death decreased by 0.8 – 0.9 times.

Comparing the educational gradients in three cardiovascular disease-specific health measures

Less-educated persons have worse cardiovascular health. We compare the educational gradients in three disease-specific health measures (biomarkers, self-reported doctors’ diagnoses and cause-specific mortality) in order to compare their relevance in different stages of the disease process. We study 14,102 people aged 50–89 from the US Health Retirement Study (HRS) in the period 2006–17. We use six CVD biomarkers (systolic/​diastolic blood pressure, ratio total/HDL cholesterol, C-reactive protein, body mass index, HbA1c) and two self-reported doctors’ diagnoses (stroke, heart attack). We estimate the gradient in biomarkers using log-binomial regression and the hazard of diagnoses and CVD mortality with Cox survival models. Among those without pre-diagnosed CVD conditions, the educational gradient in mortality is highest (RR 1.97), the gradient for those who receive a CVD diagnosis is in the middle (RR 1.46), and the gradient in biomarkers is lowest (RR 1.32). Among those with recent/​older diagnoses, the biomarker gradient is comparable to levels among the non-diagnosed, while the mortality gradient is much lower (RR 1.35). The gradients in diagnoses and mortality are only slightly explained by differences in biomarkers. The comparison of the three gradients and the mediation analysis suggest that in each of the steps to diagnosis and death there are social factors involved that increase the gradient and go beyond what biomarkers can predict. Having a CVD diagnosis leads to smaller mortality gradients, presumably because of the convergence of educational differences in behaviour and during treatment and monitoring. Our findings support prevention as a strategy against social inequalities in CVD.

Identifying Stage II Colorectal Cancer Recurrence Associated Genes by Microarray Meta-Analysis and Building Predictive Models with Machine Learning Algorithms.

Background Stage II colorectal cancer patients had heterogeneous prognosis, and patients with recurrent events had poor survival. In this study, we aimed to identify stage II colorectal cancer recurrence associated genes by microarray meta-analysis and build predictive models to stratify patients' recurrence-free survival. Methods We searched the GEO database to retrieve eligible microarray datasets. The microarray meta-analysis was used to identify universal recurrence associated genes. Total samples were randomly divided into the training set and the test set. Two survival models (lasso Cox model and random survival forest model) were trained in the training set, and AUC values of the time-dependent receiver operating characteristic (ROC) curves were calculated. Survival analysis was performed to determine whether there was significant difference between the predicted high and low risk groups in the test set. Results Six datasets containing 651 stage II colorectal cancer patients were included in this study. The microarray meta-analysis identified 479 recurrence associated genes. KEGG and GO enrichment analysis showed that G protein-coupled glutamate receptor binding and Hedgehog signaling were significantly enriched. AUC values of the lasso Cox model and the random survival forest model were 0.815 and 0.993 at 60 months, respectively. In addition, the random survival forest model demonstrated that the effects of gene expression on the recurrence-free survival probability were nonlinear. According to the risk scores computed by the random survival forest model, the high risk group had significantly higher recurrence risk than the low risk group (HR = 1.824, 95% CI: 1.079–3.084, p = 0.025). Conclusions We identified 479 stage II colorectal cancer recurrence associated genes by microarray meta-analysis. The random survival forest model which was based on the recurrence associated gene signature could strongly predict the recurrence risk of stage II colorectal cancer patients.

A deep survival interpretable radiomics model of hepatocellular carcinoma patients.

This work aims to identify a new radiomics signature using imaging phenotypes and clinical variables for risk prediction of overall survival (OS) in hepatocellular carcinoma (HCC) patients treated with stereotactic body radiation therapy (SBRT). 167 patients were retrospectively analyzed with repeated nested cross-validation to mitigate overfitting issues. 56 radiomic features were extracted from pre-treatment contrast-enhanced (CE) CT images. 37 clinical factors were obtained from patients' electronic records. Variational autoencoders (VAE) based survival models were designed for radiomics and clinical features and a convolutional neural network (CNN) survival model was used for the CECT. Finally, radiomics, clinical and raw image deep learning network (DNN) models were combined to predict the risk probability for OS. The final models yielded c-indices of 0.579 (95%CI: 0.544-0.621), 0.629 (95%CI: 0.601-0.643), 0.581 (95%CI: 0.553-0.613) and 0.650 (95%CI: 0.635-0.683) for radiomics, clinical, image input and combined models on nested cross validation scheme, respectively. Integrated gradients method was used to interpret the trained models. Our interpretability analysis of the DNN showed that the top ranked features were clinical liver function and liver exclusive of tumor radiomics features, which suggests a prominent role of side effects and toxicities in liver outside the tumor region in determining the survival rate of these patients. In summary, novel deep radiomic analysis provides improved performance for risk assessment of HCC prognosis compared with Cox survival models and may facilitate stratification of HCC patients and personalization of their treatment strategies. Liver function was found to contribute most to the OS for these HCC patients and radiomics can aid in their management.

Development of a Metastasis-Related Immune Prognostic Model of Metastatic Colorectal Cancer and Its Usefulness to Immunotherapy.

Background: Post-surgical recurrence of the metastatic colorectal cancer (mCRC) remains a challenge, even with adjuvant therapy. Moreover, patients show variable outcomes. Here, we set to identify gene models based on the perspectives of intrinsic cell activities and extrinsic immune microenvironment to predict the recurrence of mCRC and guide the adjuvant therapy.Methods: An RNA-based gene expression analysis of CRC samples (total = 998, including mCRCs = 344, non-mCRCs = 654) was performed. A metastasis-evaluation model (MEM) for mCRCs was developed using the Cox survival model based on the prognostic differentially expressed genes between mCRCs and non-mCRCs. This model separated the mCRC samples into high- and low-recurrence risk clusters that were tested using machine learning to predict recurrence. Further, an immune prognostic model (IPM) was built using the COX survival model with the prognostic differentially expressed immune-related genes between the two MEM risk clusters. The ability of MEM and IPM to predict prognosis was analyzed and validated. Moreover, the IPM was utilized to evaluate its relationship with the immune microenvironment and response to immuno-/chemotherapy. Finally, the dysregulation cause of IPM three genes was analyzed in bioinformatics.Results: A high post-operative recurrence risk was observed owing to the downregulation of the immune response, which was influenced by MEM genes (BAMBI, F13A1, LCN2) and their related IPM genes (SLIT2, CDKN2A, CLU). The MEM and IPM were developed and validated through mCRC samples to differentiate between low- and high-recurrence risk in a real-world cohort. The functional enrichment analysis suggested pathways related to immune response and immune system diseases as the major functional pathways related to the IPM genes. The IPM high-risk group (IPM-high) showed higher fractions of regulatory T cells (Tregs) and smaller fractions of resting memory CD4+ T cells than the IPM-low group. Moreover, the stroma and immune cells in the IPM-high samples were scant. Further, the IPM-high group showed downregulation of MHC class II molecules. Additionally, the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and GDSC analysis suggested the IPM-low as a promising responder to anti-CTLA-4 therapy and the common FDA-targeted drugs, while the IPM-high was non-responsive to these treatments. However, treatment using anti-CDKN2A agents, along with the activation of major histocompatibility complex (MHC) class-II response might sensitize this refractory mCRC subgroup. The dysfunction of MEIS1 might be the reason for the dysregulation of IPM genes.Conclusions: The IPM could identify subgroups of mCRC with a distinct risk of recurrence and stratify the patients sensitive to immuno-/chemotherapy. Further, for the first time, our study highlights the importance of MHC class-II molecules in the treatment of mCRCs using immunotherapy.

Conventional single-chamber pacemakers versus transcatheter pacing systems in a "real world" cohort of patients: A comparative prospective single-center study.

PurposeDespite the developments in conventional transvenous pacemakers (VVI-PM), the procedure is still associated with significant complications. Although there are no prospective clinical trials that compared VVI-PM with transcatheter pacemaker systems (TPS).MethodsThis is a prospective, observational, single-center study that included all patients with an indication for a single-chamber pacemaker implant within a 4-year period. All clinical, ECG and echocardiographic characteristics at implant, electrical parameters, associated complications and mortality were analyzed. A Cox survival model and a Bayesian cohort analysis were performed for differences in complication rates between groups.ResultsThere were 443 patients included (198 TPS and 245 VVI-PM). The mean age was 81.5 years (TPS group, 79.2 ± 6.6 years; VVI-PM group, 83.5 ± 8.9 years). There was a male predominance in TPS group (123, 62.1% vs. 67, 27.3%; p < 0.001). The presence of systolic dysfunction and renal insufficiency were more frequent in VVI-PM group than in TPS patients. Mean follow-up was 22.3 ± 15.9 months. In a multivariable paired data the TPS group presented fewer complications than VVI-PM group (HR = 0.39 [0.15–0.98], p-value 0.013), but major complications were not different (6, 3% vs 14, 5.6% respectively, p = 0.1761). There was no difference in the mortality rate between the groups. The TPS group had less risk than VVI-PM group to have a complication, with a 96% of probability.ConclusionsTPS patients had a lower overall complication rate than VVI-PM patients including matched-pair samples using a Bayesian analysis. These results confirm the safety profile of TPS in clinical practice.

Prognostic gene profiles in the tumor microenvironment of ovarian serous adenocarcinoma.

Ovarian serous adenocarcinoma is one of the most common and fatal malignancies among women worldwide. The tumor microenvironment plays a critical role in tumor initiation, proliferation, and metastasis. Immune scores and stromal scores of the tumor microenvironment were determined using the ESTIMATE. Immune cell infiltration was assessed using TIMER and differentially expressed genes (DEGs) were determined using the R/Bioconductor package of edgeR. Survival analysis was carried out using a univariate Cox model and Kaplan-Meier survival, and gene functional information was obtained through Gene Ontology and KEGG pathway analysis. Survival analysis revealed 39 DEGs that significantly influenced the prognosis of ovarian serous adenocarcinoma patients and were correlated with immune cell abundance. Functional enrichment and protein-protein interaction network analyses further indicated that these genes are primarily involved in immune-related responses. Finally, we verified the prognostic value of these genes via GEO. The present results reveal the genes associated with the tumor microenvironment of ovarian adenocarcinoma, potentially providing prognostic information.

Effect of physician prescribed information on hospital readmission and death after discharge among patients with health failure: A randomized controlled trial.

In order to understand if a physician prescribed medical information changes, the number of hospital readmission, and death among the heart failure patients. A 12-month randomized controlled trial was conducted (December 2013-2014). Totally, 120 patients were randomly allocated into two groups of intervention (n = 60) and control (n = 60). Accordingly, the control group was given the routine oral information by the nurse or physician, and the intervention group received the Information Prescription (IP) prescribed by the physician as well as the routine oral information. The data was collected via telephone interviews with the follow-up intervals of 6 and 12 months, and also for 1 year after the discharge. The patients with the median age of (IQR) 69.5 years old (19.8) death upon adjusting a Cox survival model, [RR = 0.67, 95%CI: 0.46-0.97]. Few patients died during 1 year in the intervention group compared to the controls (7 vs 15) [RR = 0.47, 95%CI: 0.20-1.06]. During a period of 6-month follow-up there was not statistically significant on death and readmission between two groups. Physician prescribed information was clinically and statistically effective on the reduction of death and hospital readmission rates among the HF patients in long term follow-up.

A Bayesian Survival Model Approach for Business Distress Prediction

The early warning signals of corporate distress and failure have been a major area of concern for shareholders, policy makers and academicians alike. Numerous approaches have been applied to examine firm insolvency ranging from the famous Altman’s Z-score, traditional econometrics, financial ratio analysis to the more contemporary tools of Artificial Intelligence and Machine Learning. The Cox proportional survival hazard model is a commonly applied technique not only in the field of medical sciences for estimating occurrences of a specific event but also in failure prediction of private firms. The study investigates distress prediction of firms in context of emerging nation like India where otherwise the application of Bayesian survival models is limited. A rich panel of firms spanning over ten years and representing varied sectors like manufacturing, services, mining and construction is compiled for the purpose. The study contributes by developing hazard (survival) modelling using Bayesian perspective. The advantage of Bayesian method lies in dealing effectively with censored and small samples over usual frequentist methods. Both standard Cox survival model for censored failure time and Bayesian estimation have been performed to assess and compare their performance. It is found that prediction accuracy of Bayesian Cox model is significantly higher than of the classical Cox model. The study contributes by providing useful insights in detecting early signs of distress in Indian corporate sector that is otherwise scant in literature.

Effectiveness of COVID-19 Vaccines in Preventing Hospitalizations and Deaths in Colombia: A Pair-Matched, National-Wide Cohort Study in Older Adults

Background: Currently, Colombia is carrying out the National Vaccination Plan against COVID-19. Clinical trials of vaccines used in the country have a high efficacy and safety, but information on effectiveness is needed. We assessed the real-world effectiveness of the highly diversified portfolio of vaccines acquired by Colombia in fully vaccinated individuals 60 years and above.Methods: We carried out a population-based cohort study in 3,346,826 people 60 years and older, matched 1:1 by sex, age, health system affiliation regime, presence of comorbidities, and municipality of residence. The exposed cohort consisted of older adults fully vaccinated with Ad26.COV2.S (Janssen), BNT162b2 (Pfizer), ChAdOx1 nCoV-19 (Oxford/AstraZeneca), or CoronaVac (Sinovac) without history of Sars-CoV-2 infection. The follow-up was made between March 11th and August 11th, 2021. To estimate effectiveness, we constructed cause-specific Cox survival models in presence of competitive risks (hospitalization vs death due to COVID-19), adjusted for main potential confounders.Findings: The overall effectiveness of vaccines to prevent hospitalization was 69·9% (95% CI 65·5% - 73·7%), to prevent post-hospitalization death, 79·4% (95% CI 77·2 % - 81·4%) and to prevent death without hospitalization, 74·5% (95% CI 71·1% - 77·5%). The effectiveness of vaccines to prevent death after hospitalisation for Covid-19 was 27·7 percentage points less in adults 80 and older compared with adults between 60 and 69 years old (69·0% vs. 96·7%). Effectiveness of vaccines decreased with increasing age. We did not find a statistically significant difference in effectiveness between vaccines used in preventing hospitalisation or death.Interpretation: The Ad26.COV2.S, BNT162b2, ChAdOx1 nCoV-19, and CoronaVac vaccines are effective in preventing hospitalization and death caused by COVID-19 in adults 60 years and older fully vaccinated. Effectiveness decreases with increasing age, regardless of the type of vaccine used in the primary scheme. An additional dose seems the best alternative for increase protection in population 70 and above.

Estimating the Risk of Poverty Transitions at Old Age in the United States: A Survival Analysis Focused on the Hispanic Population

Many Americans work well past the Social Security full retirement age. Moreover, the high labor participation rate of aged workers does not translate into better living conditions and decreased poverty at old age. According to the OECD’s relative poverty threshold, the poverty rate at old age is 23.1% (14 points higher than the absolute measure), showing important increases as age progresses. In the context of financial pressure faced by SS, understanding the factors that could help people ensure themselves against poverty is crucial at old age, especially for groups such as Hispanics. Hispanics tend to rely mostly on SS, and tend to retire earlier than non-Hispanics due to limited working opportunities. Using data drawn from the Health and Retirement Study (2008-2016), cox survival models, were conducted to estimate the risk of transitioning into poverty during retirement on determinants of long-term accumulation of disadvantages over the life course (i.e.: wealth accumulation, medical care access, unemployment history). Results suggest that being foreign born and Hispanic are strongly associated with an increase on the probability of experiencing poverty at old age, conditional on health, education and employment status. Furthermore, delaying claims of SS by one year reduces the probability of falling into poverty by 3%, supporting that socioeconomic conditions faced by older adults, especially, the interactions between such factors and ethnicity are key in explaining poverty at old age. This would help policy makers to implement policies could be targeting those factors earlier on, beneficiating the individuals and society as a whole

Retinal vascular occlusions are associated with increased risk for vascular dementia in APOE ε4 carriers in a community‐based cohort

AbstractBackgroundWe previously reported that several eye conditions were associated with increased risks of developing Alzheimer’s disease (AD). Retinal vascular occlusions (RVO, i.e. retinal vein and artery occlusions) are one of the leading sight‐threatening retinal vascular disorders. In this study, we sought to determine whether RVO are associated with increased risks of AD and other types of dementia. A few previous studies suggest that APOE is associated with RVO and vascular dementia.MethodParticipants aged ≥ 65 and dementia‐free were recruited in a prospective, observational cohort (Adult Changes in Thought [ACT] study). Self‐reported smoking history, hypertension, congestive heart failure, diabetes, and history of cardiovascular or cerebrovascular disease were obtained at study visits, and APOE genotype was obtained from consenting participants. Cognition was evaluated every two years with extensive neurological and neuropsychological testing when cognitive scores fell below normal range. All data were reviewed at consensus conferences for diagnosis of AD and various types of dementia such as vascular dementia (VasD). Eye diagnoses were obtained using ICD‐9/10 codes. We used adjusted Cox survival models to compute hazard ratios (HR) for developing dementia.ResultA total of 4,743 participants had 1,037 incident cases of AD. 439 (9.3%) participants had retinal vascular occlusions. In participants with any APOE ε4 alleles, the HR of developing VasD was 3.03 (95%CI 1.37, 6.71, p‐value=0.0064) in participants diagnosed with retinal vascular occlusions compared to those without [Figure, Table 2]. This strong relationship persisted after further adjustment for diabetes, hypertension, and cardiovascular disease. No significant association was found between retinal vascular occlusions and VasD in participants (HR=1.05 95% CI 0.54, 2.03 , p= 0.89) who were negative for APOE ε4. No associations were found between RVO and AD or all‐cause dementia.ConclusionIncreased risk of vascular dementia was found in participants diagnosed with RVO in participants who are APOE ε4 carriers. Further research about the relationship between APOE, dementia, and eye conditions is warranted.

Does Prolonged Education Causally Affect Dementia Risk When Adult Socioeconomic Status Is Not Altered? A Swedish Natural Experiment in 1.3 Million Individuals.

Intervening on modifiable risk factors to prevent dementia is of key importance, since progress-modifying treatments are not currently available. Education is inversely associated with dementia risk, but causality and mechanistic pathways remain unclear. We aimed to examine the causality of this relationship in Sweden using, as a natural experiment, data on a compulsory schooling reform that extended primary education by 1 year for 70% of the population between 1936 and 1949. The reform introduced substantial exogenous variation in education that was unrelated to pupils' characteristics. We followed 18 birth cohorts (n=1,341,842) from 1985 to 2016 (up to ages 79-96 years) for a dementia diagnosis in the National Inpatient and Cause of Death registers and fitted Cox survival models with stratified baseline hazards at the school-district level, chronological age as the time scale, and cohort indicators. Analyses indicated very small or negligible causal effects of education on dementia risk (main hazard ratio=1.01, 95% confidence interval: 0.98, 1.04). Multiple sensitivity checks considering only compliers, the pre-/post- design, differences in health-care-seeking behavior, and the impact of exposure misclassification left the results essentially unaltered. The reform had limited effects on further adult socioeconomic outcomes, such as income. Our findings suggest that without mediation through adult socioeconomic position, education cannot be uncritically considered a modifiable risk factor for dementia.

Updating the International IgA Nephropathy Prediction Tool for use in children

Although IgA nephropathy (IgAN) is a common cause of glomerulonephritis in children, the absence of a method to predict disease progression limits personalized risk-based treatment decisions. The adult International IgAN Prediction Tool comprises two validated Cox survival models that predict a 50% decline in estimated glomerular filtration rate (eGFR) or end stage kidney disease (ESKD) using clinical risk factors and Oxford MEST histology scores. Here, we updated the Prediction Tool for use in children using a multiethnic international cohort of 1,060 children with IgAN followed into adulthood. The updated pediatric Prediction Tool had better model fit than the original adult tool with lower Akaike Information Criterion, higher R2D and similar C-statistics. However, calibration showed very poor agreement between predicted and observed risks likely due to the observed disease trajectory in children. Therefore, the Tool was updated using a secondary outcome of a 30% reduction in eGFR or ESKD, resulting in better R2D (30.3%/22.2%) and similar C-statistics (0.74/0.68) compared to the adult tool but with good calibration. The trajectory of eGFR over time in children differed from adults being highly non-linear with an increase until 18 years old followed by a linear decline similar to that of adults. A higher predicted risk was associated with a smaller increase in eGFR followed by a more rapid decline, suggesting that children at risk of a 30% decrease in eGFR will eventually experience a larger 50% decrease in eGFR when followed into adulthood. As such, these two outcomes are analogous between pediatric and adult Prediction Tools. Thus, our pediatric Prediction Tool can accurately predict the risk of a 30% decline in eGFR or ESKD in children with IgAN.

BIOM-13. DNA METHYLATION MARKS GLUCOCORTICOID PATHWAY RESPONSE IN DEXAMETHASONE-TREATED BRAIN TUMOR PATIENTS

Abstract Dexamethasone (DEX) is routinely prescribed in brain tumor patients to limit vasogenic edema but may also exacerbate immunosuppression and adversely affect survival. The wide spectrum of dosing and individual variation in glucocorticoid (GC) response makes it difficult to assess the impact of DEX exposures. A potential marker of steroid pathway activation and GC load affecting the immune system are induced changes in chromatin structure marked by DNA methylation. We identified DEX-responsive DNA methylation sites in blood leukocytes from glioma patients treated with the drug at various doses and times during the course of their disease. Using weighted co-methylation network analysis, we show that DEX-induced hypomethylation includes well-known regulators of GC receptor (GR) sensitivity (e.g., FK506 binding protein 51: FKBP5) and inflammation (e.g., myeloperoxidase: MPO) and is enriched at genomic locations containing glucocorticoid receptor (GR) binding sites. Elastic net regression modeling was used to train a multilocus GC methylation index (GCMI) that discriminates current DEX users and non-users. GCMI scores showed wide interindividual variation among cases and DEX naïve control subjects. Using independent samples of DEX naïve and exposed glioma patients we show that the GCMI is a sensitive and specific indicator of DEX exposure. GCMI measured in non-glioma controls indicated sensitivity to non-DEX steroid treatments (e.g. prednisolone, fluticasone). Subjects with elevated neutrophil and decreased lymphocyte counts demonstrated high GCMI scores, reflecting the clinically relevant in vivo impact of this marker. Among 195 IDH wildtype and hTERT non-mutant glioma subjects, the GCMI was associated with a HR of 1.11 (95% CI 1.06–1.17) p&amp;lt; 0.0001 in Cox survival models that included age and tumor grade. We conclude that epigenetic remodeling in the peripheral immune compartment in response to DEX exposures is a rich source of potentially powerful markers of individual response to GC pathway activation and associated alterations in the immune response.

Nutritional risk index is an independent predictor of one-year mortality after primary angioplasty for ST-segment elevation myocardial infarction, regardless of age, frailty and clinical severity

Abstract Background Undernutrition is a common feature of elderly and hospitalized patients with cardiovascular diseases and is associated with adverse events. Purpose Assess the impact of nutritional risk index (NRI) in one-year mortality in ST-segment elevation myocardial infarction (STEMI) patients following primary angioplasty (PA). Methods Cohort of 319 consecutive patients (64.4 years [54.3–75.2]; 21.9% women) admitted to a general ICU after a PA for STEMI. NRI was calculated as 1.519 × serum albumin (g/L) + 41.7 × (actual body weight [kg]/ideal weight [kg]). Patients were dichotomized in no to mild (NRI ≥97.5) and moderate to severe (NRI &amp;lt;97.5) nutritional risk. We used Kaplan-Meier and Cox survival models. Results Patients with NRI &amp;lt;97.5 were older, mainly women, had a higher GRACE 2.0 and required more inotropic agents (P=0.001) and mechanical ventilation (P=0.002) during admission. They had lower CK and higher BNP levels, despite the lack of differences in LVEF and MI location (P=0.164) (Table 1). One-year mortality rate was higher in patients with NRI &amp;lt;97.5 (P&amp;lt;0.001), mainly from cardiogenic shock (P&amp;lt;0.001) (Table). After Cox regression analysis, moderate to severe nutritional risk showed a 3.10-fold higher risk of one-year mortality (95% confidence interval [CI], 1.21 to 7.90, P=0.018), independently of age, female gender, frailty (Clinical Frailty Scale ≥4), GRACE 2.0 and LVEF (Figure 1). Conclusion Moderate to severe NRI was associated with one-year all-cause mortality in patients undergoing PA for STEMI, regardless of age, female gender, frailty and clinical severity. The prognostic impact of NRI in mortality suggests the need to include its assessment in clinical examination of STEMI patients. Figure 1. Kaplan-Meier and Cox survival curves Funding Acknowledgement Type of funding source: None