NRI and SIRI are the optimal combinations for prognostic risk stratification in patients with non-small cell lung cancer after EGFR-TKI therapy.

BACKGROUND: Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have become the standard treatment for advanced non-small cell lung cancer (NSCLC) with EGFR mutations. However, NSCLC heterogeneity leads to differences in efficacy; thus, potential biomarkers need to be explored to predict the prognosis of patients. Recently, the prognostic importance of pre-treatment malnutrition and systemic inflammatory response in cancer patients has received increasing attention. METHODS: In this study, clinical information from 363 NSCLC patients receiving EGFR-TKI treatment at our clinical center was used for analysis. RESULTS: High nutritional risk index (NRI) and systemic inflammation response index (SIRI) were significantly associated with poor overall survival (OS) and progression-free survival (PFS) in NSCLC patients (P < 0.05). Importantly, NRI and SIRI were the best combination models for predicting clinical outcomes of NSCLC patients and independent OS and PFS predictors. Moreover, a nomogram model was constructed by combining NRI/SIRI, sex, smoking history, EGFR mutation, TNM stage, and surgery treatment to visually and personally predict the 1-, 2-, 3-, 4-, and 5-year OS of patients with NSCLC. Notably, risk stratification based on the nomogram model was better than that based on the TNM stage. CONCLUSION: NRI and SIRI were the best combination models for predicting clinical outcomes of NSCLC patients receiving EGFR-TKI treatment, which may be a novel biomarker for supplement risk stratification in NSCLC patients.

Prevalence and prognostic value of malnutrition in patients with IPF using three scoring systems.

BACKGROUND: To describe the nutritional status of IPF patients, report clinical associations and evaluate the prognostic value of them in IPF. METHODS: 264 IPF patients diagnosed with IPF at the Second Xiangya Hospital of Central South University between January 2011 and January 2021 were recruited. Three different scoring systems, including nutritional risk index (NRI), controlling nutritional status (CONUT) score, and prognostic nutritional index (PNI) were used to describe the nutritional status of IPF patients. RESULT: This study investigated the prevalence of malnutrition in 264 IPF patients, of which the percentage with malnutrition varied from 37.5 % with the NRI, to 47.4 % with the CONUT score, and to 6.4 % with the PNI. The moderate to severe malnutrition ranged from 10.2 % to 31.1 % across these indices, with PNI identifying only 4.9 % in this category. Worsening malnutrition status was associated with significantly higher incidence of all-cause mortality and IPF death regard of the malnutrition index as NRI (p < 0.05). When the normal nutrition of NRI was used as a reference, patients in the moderate to severe risk remained at a higher risk of all-cause death (HR = 2.06(1.25-3.41)) and IPF death(HR = 2.36(1.35-4.15)). The adjusted multivariate analysis, identified age(HR = 1.13(1.08-1.20)), DLCO <60, % predicted (HR = 3.31(1,24-9.42)) and the use of anti-fibrotic drugs (HR = 0.25(0.10-0.60)) as independent predictors of mortality. CONCLUSIONS: Malnutrition is common among patients with IPF and the baseline as diagnosis of IPF is strongly related to increased mortality.

Association of Nutritional Risk Index With Infection-Related Hospitalization and Death After Hospitalization in Patients Undergoing Maintenance Hemodialysis.

OBJECTIVE: Patients undergoing dialysis frequently experience hospitalization due to cardiovascular disease (CVD) and infection. This population is also at high risk of rehospitalization and subsequent death. In addition to serious outcomes, hospitalization incurs substantial medical cost. Prevention of hospitalization is accordingly an urgent matter. Here, we examined whether nutritional disorder was associated with hospitalization and subsequent death. METHODS: The study was conducted under a prospective design using data from the Japanese Dialysis Outcomes and Practice Pattern Study. The exposure was the Nutritional Risk Index for Japanese Hemodialysis (NRI-JH), through which patients were divided into low-, medium-, and high-risk groups, with the low-risk group as referent. The primary outcome was CVD-related or infection-related hospitalization. Secondary outcome was all-cause mortality. For exploratory analyses, the associations of baseline or latest NRI-JH just before hospitalization, with death after hospitalizations, were examined. RESULTS: Of 4021 patients, 566 patients had CVD-related hospitalization and 375 had infection-related hospitalization during a median follow-up of 2.6 years. NRI-JH at baseline was significantly associated with infection-related hospitalization but not with CVD-related hospitalization, in multivariable Cox models (hazard ratio [HR] 1.46, 95% confidential interval [CI]: 1.09 to 1.97, P = .012 for medium-risk vs. low-risk group) (HR 2.46, 95% CI: 1.81 to 3.35, P < .001 for high-risk vs. low-risk group). NRI-JH was also associated with all-cause mortality. In addition, the baseline and latest high-risk NRI-JH groups were significantly associated with death after both CVD-related and infection-related hospitalizations. CONCLUSIONS: A higher nutritional risk as evaluated by NRI-JH was associated with infection-related hospitalization but not with CVD-related hospitalization. However, NRI-JH was significantly associated with death after both CVD-related and infection-related hospitalizations, suggesting that nutritional risk may be separately involved in hospitalization or subsequent death. NRI-JH may be useful in the planning of individual care to improve outcomes.

Diagnostic Value of Nutritional Risk Index and Other Indices for Predicting Sarcopenia in the Middle-Aged and Elderly Population of China Without Cancer: A ROC Curve Analysis.

Background: Emerging evidence suggests that systemic inflammatory and nutritional biomarkers, along with derived indices, could serve as predictors for sarcopenia in cancer population. This study aimed to compare these predictors, focusing on the nutritional risk index (NRI) and evaluate its diagnostic value, for sarcopenic patients without cancer. Methods: This cross-sectional retrospective study included 1674 participants. Sarcopenia is defined by skeletal muscle mass index (SMI). Laboratory data reflected the values of systemic inflammatory and nutritional biomarkers, from which the derived indices were calculated. Multiple logistic regression analysis, ROC curve analysis, and the Youden index were utilized to assess the association between these markers and sarcopenia and determine the cutoff value for predicting sarcopenia. Results: Among all participants (1110 men and 564 women, mean age 61.97 ± 9.83 years), 398 individuals were diagnosed with sarcopenia, indicating a prevalence of 23.78% in China's middle-aged and elderly population without cancer. Logistic regression analysis revealed significant associations between all biomarkers and derived indices with sarcopenia. Following adjustment for potential confounders, lower NRI values were significantly associated with a higher incidence of sarcopenia. For sarcopenia diagnosis, the area under the curve (AUC) for NRI was 0.769 ([95% CI, 0.742, 0.796], P < 0.001), with a cutoff value of 106.016, sensitivity of 75.6% and specificity of 66.1%. NRI demonstrated greater predictive advantage for sarcopenia incidence in men compared to women. Conclusion: A lower NRI value was associated with a higher prevalence of sarcopenia. NRI shows promise for early, rapid, and effective sarcopenia screening, particularly in China's middle-aged and elderly male population without cancer.

Maladaptive personality traits and older adult relationship satisfaction: A co-twin control approach to understanding associations.

OBJECTIVE: Maladaptive personality traits have been implicated in romantic relationship dissatisfaction, but the etiology of those links and the degree to which they extend to other types of relationships are unclear. The purpose of this study was to examine associations between maladaptive personality traits and satisfaction in various relationships using a co-twin control design to identify potential environmental contributions. METHOD: The sample consisted of 1340 older adult twin participants from the Minnesota Twin Registry (Mage = 70.3) that completed the Personality Inventory for DSM-5 Faceted Brief Form and Network of Relationships Inventory (Revised for Older Adults). RESULTS: Several maladaptive personality traits were phenotypically associated with relationship dissatisfaction, with detachment and negative affect having the largest effects. Further, within twin pair differences in detachment and negative affect were associated with greater relationship dissatisfaction, suggesting that observed associations were mediated partly by the unique environment, not solely the result of genetic and familial confounding. Both phenotypic and co-twin associations were strongest overall in the romantic partner relationship. CONCLUSION: These findings support the notion that maladaptive personality traits are implicated in interpersonal dysfunction across multiple domains.

Developing Dynamic Structure-Based Pharmacophore and ML-Trained QSAR Models for the Discovery of Novel Resistance-Free RET Tyrosine Kinase Inhibitors Through Extensive MD Trajectories and NRI Analysis.

Activation of RET tyrosine kinase plays a critical role in the pathogenesis of various cancers, including non-small cell lung cancer, papillary thyroid cancers, multiple endocrine neoplasia type 2A and 2B (MEN2A, MEN2B), and familial medullary thyroid cancer. Gene fusions and point mutations in the RET proto-oncogene result in constitutive activation of RET signaling pathways. Consequently, developing effective inhibitors to target RET is of utmost importance. Small molecules have shown promise as inhibitors by binding to the kinase domain of RET and blocking its enzymatic activity. However, the emergence of resistance due to single amino acid changes poses a significant challenge. In this study, a structure-based dynamic pharmacophore-driven approach using E-pharmacophore modeling from molecular dynamics trajectories is proposed to select low-energy favorable hypotheses, and ML-trained QSAR models to predict pIC50 values of compounds. For this aim, extensive small molecule libraries were screened using developed ligand-based models, and potent compounds that are capable of inhibiting RET activation were proposed.

A Comprehensive Model Based on Dynamic Contrast-Enhanced Magnetic Resonance Imaging Can Better Predict the Preoperative Histological Grade of Breast Cancer Than a Radiomics Model.

Background: Histological grade is an important prognostic factor for patients with breast cancer and can affect clinical decision-making. From a clinical perspective, developing an efficient and non-invasive method for evaluating histological grading is desirable, facilitating improved clinical decision-making by physicians. This study aimed to develop an integrated model based on radiomics and clinical imaging features for preoperative prediction of histological grade invasive breast cancer. Methods: In this retrospective study, we recruited 211 patients with invasive breast cancer and randomly assigned them to either a training group (n=147) or a validation group (n=64) with a 7:3 ratio. Patients were classified as having low-grade tumors, which included grade I and II tumors, or high-grade tumors, which included grade III tumors. Three models were constructed based on basic clinical features, radiomics features, and the sum of the two. To assess diagnostic performance of the radiomics models, we employed measures such as receiver operating characteristic (ROC) curve, decision curve analysis (DCA), accuracy, sensitivity, and specificity, and the predictive performance of the three models was compared using the DeLong test and net reclassification improvement (NRI). Results: The area under the curve (AUC) of the clinical model, radiomics model, and comprehensive model was 0.682, 0.833, and 0.882 in the training set and 0.741, 0.751, and 0.836 in the validation set, respectively. NRI analysis confirmed that the combined model was better than the other two models in predicting the histological grade of breast cancer (NRI=21.4% in the testing cohort). Conclusion: Compared with the other models, the comprehensive model based on the combination of basic clinical features and radiomics features exhibits more significant potential for predicting histological grade and can better assist clinicians in optimal decision-making.

Setting epidemiological cut-off values for Vibrio harveyi relevant to MIC data generated by a standardised microdilution method.

The lack of internationally harmonised criteria for interpreting the data generated by standardised susceptibility testing methods presents a serious obstacle for the development of prudent use of antimicrobials in aquaculture. The data required to set epidemiological cut-off values for minimum inhibitory concentrations for antibiotic agents against Vibrio harveyi was determined using a standard microdilution method that specified the use of cation-adjusted Mueller Hinton broth and incubation at 28°C for 24 to 28 h. In total, 120 observations were made in 4 independent laboratories from 109 unique isolates. The aggregated data from these laboratories were analysed by the normalised resistance method and by ECOFFinder to calculate epidemiological cut-off values. The data for chloramphenicol, meropenem and sulfamethoxazole were not considered as suitable for analysis. The data for ampicillin indicated that this species is innately resistant to this agent. No acceptable ranges for quality control strains have been set for ceftazidime and, therefore, only provisional cut-off values could be generated for this agent. The epidemiological cut-off values were, however, calculated for the other 6 agents. These values were ≤0.5 µg ml-1 for enrofloxacin, ≤1 µg ml-1 for florfenicol, oxolinic acid and oxytetracycline, ≤4 µg ml-1 for gentamicin and ≤0.5/9.5 µg ml-1 for trimethoprim/sulfamethoxazole. Evidence is presented demonstrating that the data for these 6 antimicrobial agents was of sufficient quantity and quality that they could be used by the relevant authorities to set internationally harmonised, consensus epidemiological cut-off values for V. harveyi.

Correlation of immune inflammatory indices and nutritional risk index with prognosis in patients with non-small cell lung cancer.

OBJECTIVE: To investigate the relationship of lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and nutritional risk index (NRI) with the prognosis of non-small cell lung cancer (NSCLC). METHODS: The clinical data of 400 NSCLC patients undergoing surgery at Shaoxing Shangyu Hospital of Traditional Chinese Medicine from January 2019 to June 2022 were collected for this retrospective analysis. The optimal cutoff values for NLR, PLR, LMR and NRI were determined using receiver operating characteristic (ROC) curves. The patients were grouped according to the optimal cutoff values, and the clinicopathological characteristics were compared between groups. The Kaplan-Meier survival curve and Cox risk model were used to identify the independent risk factors affecting the prognosis of patients with NSCLC. A nomogram risk prediction model was constructed and its effectiveness was verified. RESULTS: ROC curve analysis revealed that the area under the curve (AUC) values for NLR, PLR, LMR and NRI in predicting overall survival of NSCLC patients were 0.827, 0.753, 0.719 and 0.770, respectively. The optimal cutoff values for NLR, PLR, LMR and NRI were 2.49, 126.32, 3.02 and 89, respectively. Survival analysis found that the survival time was shorter in patients with NLR>2.49, PLR>126.32, LMR>3.02 and NRI≤89. Results from Cox model indicated that TNM staging, NLR>2.49, LMR>3.02, NRI≤89, surgical method, intraoperative blood loss, postoperative complication, and adjuvant chemotherapy were risk factors affecting the prognosis of NSCLC patients. A nomogram was constructed based on the results of multivariate analysis. The AUC of the nomogram was 0.967 (95% CI: 0.943-0.992) and 0.948 (95% CI: 0.874-1) in the training set and the test set, respectively. The C-index was 0.90 and 0.89, respectively. The calibration curve demonstrated good agreement between the predicted values of the nomogram and the actual observed values. CONCLUSION: NLR, LMR and NRI are significant predictors of the prognosis of patients with NSCLC. NLR>2.49, LMR>3.02, and NRI≤89 are risk factors for the prognosis of NSCLC patients.

Tick-borne encephalitis epidemiology and surveillance in Poland, and comparison with selected European countries before and during the COVID-19 pandemic, 2008 to 2020.

BackgroundTick-borne encephalitis (TBE) is the most common viral central nervous system (CNS) infection in Poland. Previous research suggests that its incidence was underestimated in the pre-pandemic period. The COVID-19 pandemic caused a considerable burden on surveillance systems, which could further impact reporting.AimWe aimed to assess the completeness of reporting of TBE in the years 2008 to 2020 and explore the potential impact of the COVID-19 pandemic on reporting to the epidemiological surveillance system, compared with hospitalisations for TBEV and other viral neuro-infections.MethodsWe compared the Polish epidemiology of TBE and other viral infections of the CNS from national surveillance reports with data on hospitalisations from 2008 to 2020 and data from selected European countries.ResultsBetween 2008 and 2020, 3,016 TBE cases were reported to surveillance compared with 3,620 hospitalisations. There was an increasing trend in hospitalisations, while surveillance data demonstrated the opposite, with the largest discrepancy observed in the first pandemic year (354 hospitalisations vs 159 cases reported to surveillance). Serological testing for TBE was used more in the known endemic region of north-eastern Poland and less in non-endemic areas. Other European countries reported higher TBE case numbers and an increase during the COVID-19 pandemic, whereas Poland observed an opposite trend.ConclusionThe sensitivity of TBE surveillance in Poland requires improvement. There are considerable regional differences. Regions that test for TBE intensively report most cases. Policymakers should be made aware of the value of quality epidemiological data for planning prophylactic measures in risk areas.

AFP score and metroticket 2.0 perform similarly and could be used in a "within-ALL" clinical decision tool.

Background & Aims: Two recently developed composite models, the alpha-fetoprotein (AFP) score and Metroticket 2.0, could be used to select patients with hepatocellular carcinoma (HCC) who are candidates for liver transplantation (LT). The aim of this study was to compare the predictive performance of both models and to evaluate the net risk reclassification of post-LT recurrence between them using each model's original thresholds. Methods: This multicenter cohort study included 2,444 adult patients who underwent LT for HCC in 47 centers from Europe and Latin America. A competing risk regression analysis estimating sub-distribution hazard ratios (SHRs) and 95% CIs for recurrence was used (Fine and Gray method). Harrell's adapted c-statistics were estimated. The net reclassification index for recurrence was compared based on each model's original thresholds. Results: During a median follow-up of 3.8 years, there were 310 recurrences and 496 competing events (20.3%). Both models predicted recurrence, HCC survival and survival better than Milan criteria (p <0.0001). At last tumor reassessment before LT, c-statistics did not significantly differ between the two composite models, either as original or threshold versions, for recurrence (0.72 vs. 0.68; p = 0.06), HCC survival, and overall survival after LT. We observed predictive gaps and overlaps between the model's thresholds, and no significant gain on reclassification. Patients meeting both models ("within-ALL") at last tumor reassessment presented the lowest 5-year cumulative incidence of HCC recurrence (7.7%; 95% CI 5.1-11.5) and higher 5-year post-LT survival (70.0%; 95% CI 64.9-74.6). Conclusions: In this multicenter cohort, Metroticket 2.0 and the AFP score demonstrated a similar ability to predict HCC recurrence post-LT. The combination of these composite models might be a promising clinical approach. Impact and implications: Composite models were recently proposed for the selection of liver transplant (LT) candidates among individuals with hepatocellular carcinoma (HCC). We found that both the AFP score and Metroticket 2.0 predicted post-LT HCC recurrence and survival better than Milan criteria; the Metroticket 2.0 did not result in better reclassification for transplant selection compared to the AFP score, with predictive gaps and overlaps between the two models; patients who met low-risk thresholds for both models had the lowest 5-year recurrence rate. We propose prospectively testing the combination of both models, to further optimize the LT selection process for candidates with HCC.

Prognostic value of the nutritional risk index in patients with newly diagnosed multiple myeloma.

The nutritional risk index (NRI), which is based on weight and albumin levels, is closely associated with the prognosis of many cancers. However, its prognostic value has not been investigated in patients with newly diagnosed multiple myeloma (NDMM). We aimed to assess the association between the NRI and survival outcomes in patients with NDMM. We retrospectively collected and analyzed clinical and laboratory data from patients with NDMM between 2005 and 2019 at our center. Patients were stratified into the high NRI (> 89) and low NRI (≤ 89) groups for prognostic analysis. The NRI and other variables were also explored to evaluate their prognostic value for overall survival (OS). A total of 638 patients diagnosed with NDMM were retrospectively included. Patients in the high NRI group had a significantly better median OS than those in the low NRI group (64 months vs 43 months, p < 0.001). In the multivariate analysis, a high NRI was shown to be an independent prognostic factor for OS (hazard ratio, 0.758; 95% confidence interval, 0.587-0.977; p = 0.033). Age, performance status, transplant status, and lactate dehydrogenase level were also independent prognostic factors for OS. In conclusion, our study demonstrates that the NRI is a simple and useful predictor of survival outcomes in patients with NDMM.

MRI-based radiomics to predict neoadjuvant chemoradiotherapy outcomes in locally advanced rectal cancer: A multicenter study.

Background and purpose: Predicting tumour response would be useful for selecting patients with locally advanced rectal cancer (LARC) for organ preservation strategies. We aimed to develop and validate a prediction model for T downstaging (ypT0-2) in LARC patients after neoadjuvant chemoradiotherapy and to identify those who may benefit from consolidation chemotherapy. Materials and methods: cT3-4 LARC patients at three tertiary medical centers from January 2012 to January 2019 were retrospectively included, while a prospective cohort was recruited from June 2021 to March 2022. Eight filter (principal component analysis, least absolute shrinkage and selection operator, partial least-squares discriminant analysis, random forest)-classifier (support vector machine, logistic regression) models were established to select radiomic features. A nomogram combining radiomics and significant clinical features was developed and validated by calibration curve and decision curve analysis. Interaction test was conducted to investigate the consolidation chemotherapy benefits. Results: A total of 634 patients were included (426 in training cohort, 174 in testing cohort and 34 in prospective cohort). A radiomic prediction model using partial least-squares discriminant analysis and a support vector machine showed the best performance (AUC: 0.832 [training]; 0.763 [testing]). A nomogram combining radiomics and clinical features showed significantly better prognostic performance (AUC: 0.842 [training]; 0.809 [testing]) than the radiomic model. The model was also tested in the prospective cohort with AUC 0.727. High-probability group (score > 81.82) may have potential benefits from ≥ 4 cycles consolidation chemotherapy (OR: 4.173, 95 % CI: 0.953-18.276, p = 0.058, pinteraction = 0.021). Conclusion: We identified and validated a model based on multicenter pre-treatment radiomics to predict ypT0-2 in cT3-4 LARC patients, which may facilitate individualised treatment decision-making for organ-preservation strategies and consolidation chemotherapy.

[Impact of HPV status on nutritional status during radio chemotherapy for oropharyngeal cancer]. / Impact du statut HPV sur l'évolution nutritionnelle au cours de la chimioradiothérapie des patients atteints d'un cancer de l'oropharynx.

PURPOSE: Patients with oropharyngeal cancer are at high nutritional risk before and during treatment. Little is known about the influence of human papillomavirus (HPV) infection on nutritional status and its evolution during treatment. MATERIALS AND METHODS: A single-center retrospective study was conducted between August 2017 and December 2020 including 48 patients (14 HPV-induced: HPV+ and 34 non-HPV-induced: HPV-) with oropharyngeal squamous cell carcinoma treated by radiotherapy±chemotherapy (RT/CT). Nutritional risk at the time of tumor assessment (TA) was assessed by weight loss, swallowing ability, and the presence of digestive disorders in 4 stages of increasing severity. Nutritional status was assessed by weight and nutrition risk index (NRI) at the time of TA, before the start and at 3 months from the end of RT±CT. During RT±CT, the NRI and the systemic inflammatory response index (SIRI=neutrophils * monocytes/lymphocytes) were assessed weekly. RESULTS: HPV+patients were at lower nutritional risk at TA (50% grade ≥2 vs 85%, P=0.02), lost more weight (6% of their body weight vs 3%, P=0.05), and increased their SIRI by 7.5 points more than HPV- patients (P=0.04) during RT/CT. CONCLUSION: HPV+ oropharyngeal cancer patients are at high nutritional risk even in the absence of undernutrition at the outset of management.

Association between plaque localization in proximal coronary segments and MACE outcomes in patients with mild CAC: Results from the EISNER study.

Objective: Coronary artery calcium score (CAC) is a validated tool to predict and reclassify cardiovascular risk. Additional metrics such as regional distribution and extent of CAC over Agatston CAC score may allow further risk stratification. In this study, we evaluate the prognostic significance of proximal CAC involvement in asymptomatic population from the prospective EISNER (Early-Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) registry, focusing on patients with mild CAC (score 1-99). Methods: This study included a total of 2,047 adult asymptomatic subject who underwent baseline CAC scan and 14-year follow-up for MACE, defined as myocardial infarction, late revascularization, or cardiac death. Proximal involvement was defined as presence of CAC in the LM, proximal LAD, LCX or RCA. CAC was categorized as 0, 1-99, and ≥100. Results: 1,090 (53.2%) subjects had no CAC, 576 (28.1%) had CAC 1-99, and 381 (18.7%) had CAC ≥100. Proximal involvement was seen in 67.2% of subjects with CAC 1-99 and 97.3% of subjects with CAC ≥100. In the CAC 1-99 category, the presence of proximal CAC was associated with increased MACE risk after adjustment for CAC score, CAC extent and conventional risk factors compared to those without proximal CAC (HR: 2.84 95% CI: 1.29-6.25, p=0.009). Conclusion: In asymptomatic subjects with CAC scores of 1-99, the presence and extent of proximal CAC plaques provides strong independent prognostic information in predicting MACE.

Abdominal aortic calcification on lateral spine images captured during bone density testing and late-life dementia risk in older women: A prospective cohort study.

Background: Dementia after the age of 80 years (late-life) is increasingly common due to vascular and non-vascular risk factors. Identifying individuals at higher risk of late-life dementia remains a global priority. Methods: In prospective study of 958 ambulant community-dwelling older women (≥70 years), lateral spine images (LSI) captured in 1998 (baseline) from a bone density machine were used to assess abdominal aortic calcification (AAC). AAC was classified into established categories (low, moderate and extensive). Cardiovascular risk factors and apolipoprotein E (APOE) genotyping were evaluated. Incident 14.5-year late-life dementia was identified from linked hospital and mortality records. Findings: At baseline women were 75.0 ± 2.6 years, 44.7% had low AAC, 36.4% had moderate AAC and 18.9% had extensive AAC. Over 14.5- years, 150 (15.7%) women had a late-life dementia hospitalisation (n = 132) and/or death (n = 58). Compared to those with low AAC, women with moderate and extensive AAC were more likely to suffer late-life dementia hospitalisations (9.3%, 15.5%, 18.3%, respectively) and deaths (2.8%, 8.3%, 9.4%, respectively). After adjustment for cardiovascular risk factors and APOE, women with moderate and extensive AAC had twice the relative hazards of late-life dementia (moderate, aHR 2.03 95%CI 1.38-2.97; extensive, aHR 2.10 95%CI 1.33-3.32), compared to women with low AAC. Interpretation: In community-dwelling older women, those with more advanced AAC had higher risk of late-life dementia, independent of cardiovascular risk factors and APOE genotype. Given the widespread use of bone density testing, simultaneously capturing AAC information may be a novel, non-invasive, scalable approach to identify older women at risk of late-life dementia. Funding: Kidney Health Australia, Healthway Health Promotion Foundation of Western Australia, Sir Charles Gairdner Hospital Research Advisory Committee Grant, National Health and Medical Research Council of Australia.

Spleen volume-based non-invasive tool for predicting hepatic decompensation in people with compensated cirrhosis (CHESS1701).

Background & Aims: Non-invasive stratification of the liver decompensation risk remains unmet in people with compensated cirrhosis. This study aimed to develop a non-invasive tool (NIT) to predict hepatic decompensation. Methods: This retrospective study recruited 689 people with compensated cirrhosis (median age, 54 years; 441 men) from 5 centres from January 2016 to June 2020. Baseline abdominal computed tomography (CT), clinical features, and liver stiffness were collected, and then the first decompensation was registered during the follow-up. The spleen-based model was designed for predicting decompensation based on a deep learning segmentation network to generate the spleen volume and least absolute shrinkage and selection operator (LASSO)-Cox. The spleen-based model was trained on the training cohort of 282 individuals (Institutions I-III) and was validated in 2 external validation cohorts (97 and 310 individuals from Institutions IV and V, respectively) and compared with the conventional serum-based models and the Baveno VII criteria. Results: The decompensation rate at 3 years was 23%, with a 37.6-month median (IQR 21.1-52.1 months) follow-up. The proposed model showed good performance in predicting decompensation (C-index ≥0.84) and outperformed the serum-based models (C-index comparison test p <0.05) in both the training and validation cohorts. The hazard ratio (HR) for decompensation in individuals with high risk was 7.3 (95% CI 4.2-12.8) in the training and 5.8 (95% CI 3.9-8.6) in the validation (log-rank test, p <0.05) cohorts. The low-risk group had a negligible 3-year decompensation risk (≤1%), and the model had a competitive performance compared with the Baveno VII criteria. Conclusions: This spleen-based model provides a non-invasive and user-friendly method to help predict decompensation in people with compensated cirrhosis in diverse healthcare settings where liver stiffness is not available. Lay summary: People with compensated cirrhosis with larger spleen volume would have a higher risk of decompensation. We developed a spleen-based model and validated it in external validation cohorts. The proposed model might help predict hepatic decompensation in people with compensated cirrhosis when invasive tools are unavailable.

A Prognostic Model Based on Nutritional Risk Index in Operative Breast Cancer.

BACKGROUND: The nutritional risk index (NRI) is an independent prognostic factor for overall survival in various cancers, but its prognostic value in breast cancer remains unclear. This study aimed to explore the relationship between the NRI and overall survival (OS) in breast cancer and to develop a predictive nomogram. METHODS: We retrospectively enrolled 1347 breast cancer patients who underwent mastectomy or lumpectomy between January 2011 and November 2012. Using a cutoff value of 110.59, patients were divided into a high-NRI group and a low-NRI group. OS was compared between the two groups. Clinicopathological factors independently associated with survival were used to construct a predictive nomogram. RESULTS: Of the 1347 patients, 534 patients were classified as high NRI and 813 as low NRI. OS was significantly shorter in low-NRI patients. The 3- and 5-year OS rates were 87.3% and 73.4%, respectively, in the high-NRI group whereas they were 83.0% and 67.2%, respectively, in the low-NRI group. Cox regression analysis found that histopathological type, tumor size, lymph node status, progesterone receptor (PR) status, Ki-67, and NRI were independently associated with OS. CONCLUSIONS: NRI is an independent prognostic factor of OS in breast cancer patients. The proposed nomogram model may be a useful tool for individualized survival prediction.

A long-term nutritional assessment of maxillary cancer patients undergoing prosthodontic rehabilitation after surgery: A longitudinal study.

Purpose: To evaluate the nutritional status (NS) of patients planned for maxillectomy and prosthodontic rehabilitation using three nutritional assessment methods. Methods: This longitudinal study enrolled 18 planned maxillectomy patients following the inclusion and exclusion criteria. NS was evaluated at five stages: before surgery (S0), 2 weeks after surgery (S1), 3 months after insertion of intermediate obturator (S2), just before fabrication of definitive obturator (S3), and 3 months after insertion of definitive obturator (S4) using two nutritional assessment tools i.e. Patient Generated -Subjective Global Assessment (PG-SGA) &Nutritional risk index (NRI); and body composition indicators i.e. body mass index (BMI), fat free mass (FFM), total body water (TBW), skeletal muscle mass (SMM) and skeletal muscle mass index (SMMI).To determine the changes in patient's nutritional status among different time points Repeated Measure ANOVA with Bonferroni post hoc adjustments was used. Results: Out of 18 patients, 12 were completed the study. NS of maxillectomy patients deteriorates significantly (p < .05) till stage S2. At S3, significant improvement occurred as compared to stage S2, but it remained significantly less than pre-surgical level. However, at stage S4, all parameters were statistically comparable to S0 (p > .05) except for PG-SGA (p < .001) and SMM (p = .044). Conclusion: NS of maxillectomy patients worsen post surgically due to surgical morbidity and adverse effects of radiotherapy (RT) but improves with post-surgical healing, resolution of sequel of RT and improved oral function due to well-adapted obturator prosthesis.

Generalized linear mixed-effects models for studies using different sets of stimuli across conditions.

A non-repeated item (NRI) design refers to an experimental design in which items used in one level of experimental conditions are not repeatedly used at other levels. Recent literature has suggested the use of generalized linear mixed-effects models (GLMMs) for experimental data analysis, but the existing specification of GLMMs does not account for all possible dependencies among the outcomes in NRI designs. Therefore, the current study proposed a GLMM with a level-specific item random effect for NRI designs. The hypothesis testing performance of the newly proposed model was evaluated via a simulation study to detect the experimental condition effect. The model with a level-specific item random effect performed better than the existing model in terms of power when the variance of the item effect was heterogeneous. Based on these results, we suggest that experimental researchers using NRI designs consider setting a level-specific item random effect in the model.