Multivariable Risk Score Research Articles

Risk Score for Hepatocellular Cancer in Adults Without Viral Hepatitis or Cirrhosis

Hepatocellular carcinoma (HCC) is typically detected only at advanced stages when treatment options are limited. Most of the current HCC risk models focus on patients with viral hepatitis or diagnosed cirrhosis or require variables not routinely available in clinical care. To identify modifiable HCC risk factors in the general population and to develop a risk score to inform HCC screening and risk-factor modification interventions for high-risk individuals without viral hepatitis or decompensated cirrhosis. This cohort study analyzed demographic, clinical, laboratory, and diagnostic data from the US Department of Veterans Affairs (VA) electronic health records. Data were divided into development and validation samples. Veterans aged 30 to 95 years were included, and those with hepatitis B or C virus infection, hepatic decompensation, or prevalent HCC were excluded. Patients were followed up until the occurrence of HCC diagnosis, death, or December 31, 2021. A Cox proportional hazards regression model for 10-year risk of HCC was developed and used to create an HCC risk score, and performance in development and validation samples and in patient subgroups was evaluated. One outpatient visit date per person at least 18 months after VA entry, between October 1, 2007, and March 31, 2020, was randomly selected and used as the index date for the start of follow-up. Analyses were performed from March 2023 to May 2024. Age, sex, race and ethnicity, body mass index, liver fibrosis (detected with Fibrosis-4 Index [FIB-4]), diabetes status, smoking status, and alcohol use. First HCC diagnosis during follow-up. This information was ascertained from VA national cancer registry topography and histology codes and from International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes for the inpatient or outpatient visits. This study of 6 509 288 veterans included 6 048 917 males (92.9%), with a median (IQR) age of 65 (54-74) years, who identified as being of Hispanic (5.3%), non-Hispanic Black (15.0%), non-Hispanic White (68.9%), or other (4.6%) race and ethnicity. Overall, 15 142 patients (0.2%) developed HCC, 69.5% of whom had FIB-4 of 3.25 or lower at baseline. While FIB-4 was the most important variable, age, sex, race and ethnicity, body mass index, diabetes, smoking, and alcohol use were also informative. Discrimination in the development sample was better than FIB-4 alone (C statistic, 0.83 [95% CI, 0.82-0.85] vs 0.79 [95% CI, 0.77-0.80]). The HCC risk score performed consistently well in the validation sample and in all subgroups. A FIB-4 threshold of 3.25 would screen 5.0% of the cohort at a cost of 28 false-positives for every true-positive; a model risk score of 58 would screen 4.7% of the cohort at a cost of 23 false-positives for every true-positive. Results of this study suggest that a multivariable risk score that uses routinely available clinical data outperforms FIB-4 alone in identifying patients at risk of HCC who do not have viral hepatitis or hepatic decompensation at baseline.

Development of a clinical risk score for the prediction of Pneumocystis jirovecii pneumonia in hospitalised patients

BackgroundThe performance and availability of invasive and non-invasive investigations for the diagnosis of Pneumocystis jirovecii pneumonia (PCP) vary across clinical settings. Estimating the pre-test probability of PCP is essential to the optimal selection and interpretation of diagnostic tests, such as the 1,3-β-D-glucan assay (BDG), for the prioritization of bronchoscopy, and to guide empiric treatment decisions. We aimed to develop a multivariable risk score to estimate the pre-test probability of PCP.MethodsThe score was developed from a cohort of 626 individuals who underwent bronchoscopy for the purposes of identifying PCP in a Canadian tertiary-care centre, between 2015 and 2018. We conducted a nested case-control study of 57 cases and 228 unmatched controls. Demographic, clinical, laboratory, and radiological data were included in a multivariable logistic regression model to estimate adjusted odds ratios for PCP diagnosis. A clinical risk score was derived from the multivariable model and discrimination was assessed by estimating the score’s receiver operating characteristic curve.ResultsParticipants had a median age of 60 years (interquartile range [IQR] 49–68) and 115 (40%) were female; 40 (14%) had HIV and 49 (17%) had a solid organ transplant (SOT). The risk score included prior SOT or HIV with CD4 ≤ 200/µL (+ 2), serum lactate dehydrogenase ≥ 265.5 IU/mL (+ 2), radiological pattern typical of PCP on chest x-ray (+ 2) or CT scan (+ 2.5), and PCP prophylaxis with trimethoprim-sulfamethoxazole (-3) or other antimicrobials (-2). The median score was 4 points (IQR, 2-4.5) corresponding to a 28% probability of PCP. The risk prediction model had good discrimination with a c-statistic of 0.79 (0.71–0.84). Given the operating characteristics of the BDG assay, scores ≤ 3 in patients without HIV, and ≤ 5.5 in those with HIV, paired with a negative BDG, would be expected to rule out PCP with 95% certainty.ConclusionWe propose the PCP Score to estimate pre-test probability of PCP. Once validated, it should help clinicians determine which patients to refer for invasive investigations, when to rely on serological testing, and in whom to consider pre-emptive treatment.

Ferroptosis-Related Gene Signature for Prognosis Prediction in Acute Myeloid Leukemia and Potential Therapeutic Options.

Limited data were available to understand the significance of ferroptosis in leukemia prognosis, regardless of the genomic background. RNA-seq data from 151 AML patients were analyzed from The Cancer Genome Atlas (TCGA) database, along with 70 healthy samples from the Genotype-Tissue Expression (GTEx) database. Ferroptosis-related genes (FRGs) features were constructed by multivariate COX regression analysis and risk scores were calculated for each sample and a novel prediction model was identified. The validation was carried out using data from 35 AML patients and 13 healthy controls in our cohort. Drug sensitivity analysis was conducted on various chemotherapeutic drugs. A signature of 10 FRGs was identified, as prognostic predictors for AML, and the risk scores were calculated to constructed the prognostic features of FRGs. Significantly lower overall survival was observed in the high-risk group. The predictive ability of these features for AML prognosis was confirmed using Cox regression analysis, ROC curves, and DCA. The prediction model performed well in our clinical practices, and had its potential superiority when comparing to classical NCCN risk stratification. Multiple chemotherapy drugs, including paclitaxel, dactinomycin, cisplatin, etc. had a lower IC50 in FRGs high-risk group than low-risk group. The AML prognosis model based on FRGs accurately predicts AML prognosis and drug sensitivity, and the drugs identified worthy further investigation.

Predicting One-Year Mortality after Discharge Using Acute Heart Failure Score (AHFS).

Background: Acute heart failure (AHF) represents a leading cause of unscheduled hospital stays, frequent rehospitalisations, and mortality worldwide. The aim of our study was to develop a bedside prognostic tool, a multivariable predictive risk score, that is useful in daily practice, thus providing an early prognostic evaluation at admission and an accurate risk stratification after discharge in patients with AHF. Methods: This study is a subanalysis of the STADE HF study, which is a single-centre, prospective, randomised controlled trial enrolling 123 patients admitted to hospital for AHF. Here, 117 patients were included in the analysis, due to data exhaustivity. Regression analysis was performed to determine predictive variables for one-year mortality and/or rehospitalisation after discharge. Results: During the first year after discharge, 23 patients died. After modellisation, the variables considered to be of prognostic relevance in terms of mortality were (1) non-ischaemic aetiology of HF, (2) elevated creatinine levels at admission, (3) moderate/severe mitral regurgitation, and (4) prior HF hospitalisation. We designed a linear model based on these four independent predictive variables, and it showed a good ability to score and predict patient mortality with an AUC of 0.84 (95%CI: 0.76-0.92), thus denoting a high discriminative ability. A risk score equation was developed. During the first year after discharge, we observed as well that 41 patients died or were rehospitalised; hence, while searching for a model that could predict worsening health conditions (i.e., death and/or rehospitalisation), only two predictive variables were identified: non-ischaemic HF aetiology and previous HF hospitalisation (also included in the one-year mortality model). This second modellisation showed a more discrete discriminative ability with an AUC of 0.67 (95% C.I. 0.59-0.77). Conclusions: The proposed risk score and model, based on readily available predictive variables, are promising and useful tools to assess, respectively, the one-year mortality risk and the one-year mortality and/or rehospitalisations in patients hospitalised for AHF and to assist clinicians in the management of patients with HF aiming at improving their prognosis.

Development and Validation of a Risk Score for Mild Cognitive Impairment in Individuals with Type 2 Diabetes in China: A Practical Cognitive Prescreening Tool.

Numerous evidence suggests that diabetes increases the risk of cognitive impairment. This study aimed to develop and validate a multivariable risk score model to identify mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM). This cross-sectional study included 1256 inpatients (age: 57.5 ± 11.2 years) with T2DM in a tertiary care hospital in China. MCI was diagnosed according to the criteria recommended by the National Institute on Aging-Alzheimer's Association Workgroup, and a MoCA score of 19-25 indicated MCI. Participants were randomly allocated into the derivation and validation sets at 7:3 ratio. Logistic regression models were used to identify predictors for MCI in the derivation set. A scoring system based on the predictors' beta coefficient was developed. Predictive ability of the risk score was tested by discrimination and calibration methods. Totally 880 (285 with MCI, 32.4%) and 376 (167 with MCI, 33.8%) patients were allocated in the derivation and validation set, respectively. Age, education, HbA1c, self-reported history of severe hypoglycemia, and microvascular disease were identified as predictors for MCI and constituted the risk score. The AUCs (95% CI) of the risk score were 0.751 (0.717, 0.784) in derivation set and 0.776 (0.727, 0.824) in validation set. The risk score showed good apparent calibration of observed and predicted MCI probabilities and was capable of stratifying individuals into 3 risk categories by two cut-off points (low risk: ≤ 3, medium risk: 4-13, and high risk ≥ 14). The risk score based on age, education, HbA1c, self-reported history of severe hypoglycemia, and microvascular disease can effectively assess MCI risk in adults with T2DM at different age. It can serve as a practical prescreening tool for early detection of MCI in daily diabetes care.

A New Scoring System Predicting Side-Branch Occlusion in Patients Undergoing Left Main Bifurcation Intervention: The LM V-RESOLVE Score

BackgroundThe risk of side-branch (SB) occlusion is pivotal for decision making of stenting strategies during unprotected left main (LM) bifurcation percutaneous coronary intervention (PCI). Accordingly, this study aimed to develop a scoring system for predicting SB occlusion during unprotected LM bifurcation PCI. MethodsA total of 855 consecutive patients undergoing unprotected LM bifurcation PCI with provisional strategy at Fuwai Hospital from January 2014 to December 2016 were recruited. A prediction model was selected by means of all-subsets logistic regression, and a multivariable risk score (Left Main Visual Estimation for Risk Prediction of Side Branch Occlusion in Coronary Bifurcation Intervention [LM V-RESOLVE]) was then established with incremental weights attributed to each component variable based on its estimate coefficients. SB occlusion was defined as any decrease in Thrombolysis in Myocardial Infarction (TIMI) flow grade or absence of flow in SB after main vessel (MV) stenting. ResultsSB occlusion occurred in 19 LM bifurcation lesions (2.22%). In multivariable model, 3 variables, including MV/SB diameter ratio, MV plaque ipsilateral to SB, and baseline diameter stenosis of SB, were independent predictors for SB occlusion (model C-statistic 0.829, 95% confidence interval [CI] 0.735-0.923, with good calibration). The risk score had a C-statistics of 0.830 (95% CI 0.738-0.923) with good calibration. Satisfactory discriminative ability of the risk score was also preserved in external validation (C-statistic 0.794, 95% CI 0.691-0.896). ConclusionsThe LM bifurcation–specific novel scoring system, LM V-RESOLVE, based on 3 simple baseline angiographic findings, could help to rapidly discriminate lesions at risk of SB occlusion during LM bifurcation PCI.

Identification and validation of 5-methylcytosine-associated genes in diffuse large B-cell lymphoma

5-methylcytosine modifications play a significant role in carcinogenesis; however, studies exploring 5-methylcytosine-related genes in diffuse large B-cell lymphoma patients are lacking. In this study, we aimed to understand the potential role and clinical prognostic impact of 5-methylcytosine regulators in diffuse large B-cell lymphoma and identify a prognostic biomarker based on 5-methylcytosine-associated genes. Gene expression profiles and corresponding clinical information of diffuse large B-cell lymphoma patients and normal controls were obtained from The Cancer Genome Atlas, Gene Expression Omnibus, and Genotype-Tissue Expression databases. Diffuse large B-cell lymphoma was divided into three clusters according to the 5-methylcytosine regulators, and differentially expressed genes were screened among the three clusters. Univariate Cox and Lasso-Cox regression analyses were used to screen prognostic genes and construct a prognostic risk model. Kaplan-Meier curve analysis, univariate and multivariate Cox regression analyses, and time-dependent receiver operator characteristic curve analysis were used to evaluate prognostic factors. GSVA was used to enrich potential pathways associated with 5-methylcytosine modification patterns. SsGSEA and CIBERSORT were used to assess immune cell infiltration. Six 5-methylcytosine-related genes (TUBB4A, CD3E, ZNF681, HAP1, IL22RA2, and POSTN) were used to construct a prognostic risk model, which was proved to have a good predictive effect. In addition, univariate and multivariate Cox regression risk scores were independent prognostic factors for diffuse large B-cell lymphoma. Further analysis showed that the 5-methylcytosine risk score was significantly correlated with immune cell infiltration and immune checkpoint of diffuse large B-cell lymphoma. Our study reveals for the first time a potential role for 5-methylcytosine modifications in diffuse large B-cell lymphoma, provides novel insights for future studies on diffuse large B-cell lymphoma, and offers potential prognostic biomarkers and therapeutic targets for patients with diffuse large B-cell lymphoma.

PrOgnosis in Pulmonary Embolism (PoPE): 30-Day mortality risk score based on five admission parameters

Introduction and objectiveSeveral scoring systems have been developed for risk stratification in patients with acute pulmonary embolism (PE). The Pulmonary Embolism Severity Index (PESI) and its simplified version (sPESI) are among the most used, however the high number of variables hinder its application. Our aim was to derive an easy-to-perform score based on simple parameters obtained at admission to predict 30-day mortality in acute PE patients. MethodsRetrospective study in 1115 patients with acute PE from two institutions (derivation cohort n=835, validation cohort n=280). The primary endpoint was all-cause mortality at 30 days. Statistically and clinically relevant variables were selected for multivariable Cox regression analysis. We derived and validated a multivariable risk score model and compared to other established scores. ResultsThe primary endpoint occurred in 207 patients (18.6%). Our model included five variables weighted as follows: modified shock index ≥1.1 (hazard ratio [HR] 2.57, 1.68–3.92, p<0.001), active cancer (HR 2.27, 1.45–3.56, p<0.001), altered mental state (HR 3.82, 2.50–5.83, p<0.001), serum lactate concentration ≥2.50 mmol/L (HR 5.01, 3.25–7.72, p<0.001), and age ≥80 years (HR 1.95, 1.26–3.03, p=0.003). The prognostic ability was superior to other scores (area under curve [AUC] 0.83 [0.79–0.87] vs 0.72 [0.67–0.79] in PESI and 0.70 [0.62–0.75] in sPESI, p<0.001) and its performance in the validation cohort was deemed good (73 events in 280 patients, 26.1%, AUC=0.76, 0.71–0.82, p<0.0001) and superior to other scores (p<0.05). ConclusionsThe PoPE score (https://tinyurl.com/ybsnka8s) is an easy tool with superior performance to predict early mortality in patients admitted for PE with non-high-risk PE.

FAT2 mutation is associated with better prognosis and responsiveness to immunotherapy in uterine corpus endometrial carcinoma.

Uterine corpus endometrial carcinoma (UCEC) ranks sixth among malignant tumors in women and the mortality is still rising. FAT2 gene has been considered to be related to the survival and prognosis of some certain diseases in previous studies, but the FAT2 mutation status in UCEC and its prognostic value has been rarely studied. Hence, the purpose of our study was to explore the role of FAT2 mutations for predicting prognosis and responsiveness to immunotherapy in patients with UCEC. UCEC samples from the Cancer Genome Atlas database were analyzed. We evaluated the impact of FAT2 gene mutation status and clinicopathological characteristics on the prognosis of UCEC patients and used univariate and multivariate Cox analysis risk scores to independently predict patient overall survival (OS). Tumor mutation burden (TMB) values of the FAT2 mutant and non-mutant groups were computed by Wilcoxon rank sum test. The correlation of FAT2 mutation and half maximal inhibitory concentration (IC50) values of various anticancer drugs was analyzed. Gene Ontology data and Gene Set Enrichment Analysis (GSEA) were employed to examine the differential expression of genes between the two groups. Finally, a single-sample GSEA arithmetic was utilized to measure the abundance of tumor-infiltrating immune cells in UCEC patients. FAT2 mutations suggested better OS (p < 0.001) and disease-free survival (DFS) (p=0.007) in UCEC. The IC50 values of 18 anticancer drugs were upregulated in FAT2 mutation patients (p < 0.05). The TMB and microsatellite instability values of patients with FAT2 mutations were significantly higher (p < 0.001). Next, the Kyoto Encyclopedia of Genes and Genomes functional analysis and GSEA revealed the potential mechanism of FAT2 mutation on the tumorigenesis and progression of UCEC. In addition, in reference to the UCEC microenvironment, the infiltration levels of activated CD4/CD8 T cells (p < 0.001/p=0.001) and plasmacytoid dendritic cells (p=0.006) were upregulated in the non-FAT2 mutation group, and Type 2 T helper cells (p=0.001) were downregulated in the FAT2 mutation group. UCEC patients with FAT2 mutations have better prognosis and are more likely to respond to immunotherapy. FAT2 mutation may be a valuable predictor for prognosis and responsiveness to immunotherapy in UCEC patients.

Preoperative hemodynamics as predictors of right heart failure post-left ventricular assist device

BackgroundMechanical circulatory support has garnered significant popularity as both a bridge to transplant as well as a destination therapy for patients with end-stage heart failure. Right heart failure (RHF) is a devastating complication after LVAD placement and is very unpredictable. Assisted circulation of the left ventricle (LV) with an LVAD device could unmask an underlying RHF. However, otherwise healthy right ventricles (RVs) can develop RHF after LVAD placement as well due to poor adaptation to new filling pressures and altered hemodynamics. It has been proposed that preoperative volumetric measurements in the pulmonary and systemic vasculature may serve as indicators for a risk of RHF after LVAD implantation. The aim of this study is to examine a potential relationship of preoperative hemodynamic values such as pulmonary artery pulsatility index (PAPi) and the ratio of central venous pressure to pulmonary wedge pressure (CVP/PWP) as preoperative predictors for RHF post LVAD placement.MethodsWe retrospectively reviewed patients undergoing initially planned isolated LVAD implantation with or without concomitant procedures in our institution from January 1, 2017 to June 12, 2020. Data were gathered from hemodynamic records, echocardiographic interpretations, and clinical notes. Patients who had RHF after LVAD implantation but without hemodynamic data available within 14 days from the operation were excluded. Univariable analysis was performed.ResultsOf the 114 patients who received planned isolated LVAD surgery, 70 (61.4%) experienced RHF within the first 7 days postoperatively. PAPi did not correlate significantly with RHF vs non-RHF among LVAD recipients (3.1 ± 2.1 vs. 3.8 ± 3.4 P = 0.21). Pre-op CVP/PWP did not differ significantly between RHF and non-RHF patients (0.4 ± 0.2 vs. 0.5 ± 0.8 P = 0.28). There was a nonsignificant correlation between elevated pre-op PWP and those with RHF vs those without, OR = 1.05 (95% CI: 1.00, 1.10). Pre-op systolic pulmonary artery pressure (SysPAP) was elevated in patients with post-LVAD RHF compared to those without (51.3 ± 12.3 vs. 47.2 ± 13.0, P = 0.09).ConclusionPreoperative hemodynamic variables such as PAPi or CVP/PWP did not show a significant correlation predicting RHF post LVAD implantation. Acute RHF post LVAD implantation remains a complex medical entity. Several studies have devised multivariable risk scores; however, their performance has been limited. Despite the widespread use of preoperative hemodynamics measurements as risk scores, our study suggests these scores are not as accurate as their use would suggest, particularly among especially morbid patient populations. More prospective studies are needed to accurately demonstrate how preoperative hemodynamics could predict and help prevent this catastrophic complication.

A multistate competing risks framework for preconception prediction of pregnancy outcomes

BackgroundPreconception pregnancy risk profiles—characterizing the likelihood that a pregnancy attempt results in a full-term birth, preterm birth, clinical pregnancy loss, or failure to conceive—can provide critical information during the early stages of a pregnancy attempt, when obstetricians are best positioned to intervene to improve the chances of successful conception and full-term live birth. Yet the task of constructing and validating risk assessment tools for this earlier intervention window is complicated by several statistical features: the final outcome of the pregnancy attempt is multinomial in nature, and it summarizes the results of two intermediate stages, conception and gestation, whose outcomes are subject to competing risks, measured on different time scales, and governed by different biological processes. In light of this complexity, existing pregnancy risk assessment tools largely focus on predicting a single adverse pregnancy outcome, and make these predictions at some later, post-conception time point.MethodsWe reframe the individual pregnancy attempt as a multistate model comprised of two nested multinomial prediction tasks: one corresponding to conception and the other to the subsequent outcome of that pregnancy. We discuss the estimation of this model in the presence of multiple stages of outcome missingness and then introduce an inverse-probability-weighted Hypervolume Under the Manifold statistic to validate the resulting multivariate risk scores. Finally, we use data from the Effects of Aspirin in Gestation and Reproduction (EAGeR) trial to illustrate how this multistate competing risks framework might be utilized in practice to construct and validate a preconception pregnancy risk assessment tool.ResultsIn the EAGeR study population, the resulting risk profiles are able to meaningfully discriminate between the four pregnancy attempt outcomes of interest and represent a significant improvement over classification by random chance.ConclusionsAs illustrated in our analysis of the EAGeR data, our proposed prediction framework expands the pregnancy risk assessment task in two key ways—by considering a broader array of pregnancy outcomes and by providing the predictions at an earlier, preconception intervention window—providing obstetricians and their patients with more information and opportunities to successfully guide pregnancy attempts.

Development, validation and comparison of multivariable risk scores for prediction of total stroke and stroke types in Chinese adults: a prospective study of 0.5 million adults

Background and purposeLow-income and middle-income countries have the greatest stroke burden, yet remain understudied. This study compared the utility of Framingham versus novel risk scores for prediction of total stroke...

Pre-diagnosis urine exosomal RNA (ExoDx EPI score) is associated with post-prostatectomy pathology outcome

PurposeExoDx Prostate IntelliScore (EPI) is a non-invasive urine exosome RNA-based test for risk assessment of high-grade prostate cancer. We evaluated the association of pre-biopsy test results with post-radical prostatectomy (RP) outcomes to understand the potential utility of EPI to inform invasive treatment vs active surveillance (AS) decisions.MethodsUrine samples were collected from 2066 men scheduled for initial biopsy with PSA between 2 and 10 ng/mL, no history of prostate cancer, and ≥ 50 years across multiple clinical studies. 310 men proceeded to RP, of which 111 patients had Gleason group grade 1 (GG1) at biopsy and would have been potential candidates for AS. We compared pre-biopsy urine scores with ERSPC and PCPT multivariate risk calculator scores for men with GG1 at biopsy to post-RP pathology.ResultsUrine EPI scores were significantly lower in men with GG1 at biopsy than in men with > GG1 (p = 0.04), while there were no differences in multivariate risk scores used in standard clinical practice (p > 0.05). Further, EPI scores were significantly lower in men with GG1 at biopsy who remained GG1 post-RP compared to men upgraded to ≥ GG3 post-RP (p < 0.001). In contrast, none of the multiparametric risk calculators showed significant differences (p > 0.05). Men with GG1 at biopsy and EPI score < 15.6 had zero rate of upgrading to ≥ GG3 post-RP compared to 16.0% for EPI scores ≥ 15.6.ConclusionsThe EPI urine biomarker outperformed the multivariate risk calculators in a homogenous risk group of pre-biopsy men. The EPI score was associated with low-risk pathology post-RP, with potential implications on informing AS decisions.Trial registration NCT02702856, NCT03031418, NCT03235687, NCT04720599.

Analysis of Ferroptosis-Related Gene Expression and Prognostic Factors of Renal Clear Cell Carcinoma Based on TCGA Database.

IntroductionRenal clear cell carcinoma (ccRCC) is a common tumor of the urinary system, most of which are primary malignant tumors with high metastatic rate and remaining incurable. Ferroptosis is a newly discovered form of iron-dependent programmed cell necrosis in recent years, which is inextricably linked to the occurrence and development of tumors progression. Due to the complexity of the interaction between genes in ccRCC, the research on the pathogenesis of ccRCC is still not remarkably accurate. Therefore, whether ferroptosis-related genes (FRGs) can play a role in predicting prognosis in ccRCC needs to be discussed.MethodsWe entered the Cancer Genome Mapping Project (TCGA) database and downloaded the relevant genes and clinical research data of ccRCC patients. Lasso Cox regression was used to construct a multi-gene prognostic model in the TCGA cohort. R language software was used for drawing pictures related to our study.ResultsMost of the genes involved in ferroptosis (86.2%) existing differences between the tumor and normal tissues in the TCGA public gene database. In terms of univariate Cox regression analysis, 20 differentially expressed genes (DEGs) were associated with prognosis and survival (P<0.05). A prognostic model of 12 FRGs was constructed, and patients were segmented into two different groups depending on how risky they are. Considering overall survival, the high-risk group is dramatically lower than the low-risk group (P<0.001). In multivariate Cox regression analysis, risk scores and stage turned out be an independent prognostic factor (P<0.001). GO and KEGG analysis and ssGSEA analysis of DEGs revealed that these genes were related to immune-related pathways (P<0.05).ConclusionThis study established and identified the changes in FRGs expression and prognostic factors of ccRCC, which can be helpful for prognosis evaluation and clinical treatment of this disease.

Improvement of patient stratification in human papilloma virus-associated oropharyngeal squamous cell carcinoma by defining a multivariable risk score.

Precise risk stratification models are necessary to determine patient selection for deintensifying treatment trials in human papilloma virus (HPV)-associated oropharyngeal squamous cell cancer (HPV+ OPSCC). We examined 526 cases with OPSCC treated at our department between 2002 and 2017. Every patient was classified after the 7th and 8th edition UICC staging manual. For HPV+ OPSCC, we calculated a simple risk score with four risk groups based on multivariable Cox regression analysis of clinical and lifestyle parameters (UICC 8th edition stage, tobacco/alcohol abuse, age, gender). Two hundred and thirty-nine patients with OPSCC (45.4%) showed a positive histological HPV status. In comparison to UICC 8th edition stages, our proposed risk model showed a tendency for better stratification between risk strata I/III, I/IV, and II/IV (each p < 0.002) and I/II, II/III, and III/IV (each p < 0.09). Age, gender, tobacco, and alcohol abuse should be added to the current UICC staging system in order to improve risk stratification in HPV+ OPSCC.

Identifying Characteristics Predictive of Lost-to-Follow-Up Status in Amblyopia

To identify demographic and disease-related characteristics predictive of Lost-to-Follow-Up (LTFU) status in amblyopia treatment and create a risk model for predicting LTFU status. Retrospective cohort study METHODS: Setting: Single-center, ophthalmology department at Boston Children's Hospital (BCH). 2037 patients treated for amblyopia at BCH between 2010 and 2014. LTFU was defined as patients who did not return after initial visit, excluding those who came for second opinion. Multiple variables were tested for association with LTFU status. Odds ratio of LTFU risk associated with each variable. Multivariate logistic regression was used to create a risk score for predicting LTFU status. A large proportion of patients (23%) were LTFU after first visit. Older age, nonwhite race, lack of insurance, previous glasses or atropine treatment, and longer requested follow-up intervals were independent predictors of LTFU status. A multivariable risk score was created to predict probability of LTFU (area under the curve 0.68). Our comprehensive amblyopia database allows us to predict which patients are more likely to be LTFU after baseline visit and develop strategies to mitigate these effects. These findings may help with practice efficiency and improve patient outcomes in the future by transitioning these analyses to an electronic medical record that could be programmed to provide continually updated decision support for individual patients based on large data sets.

Abdominal ultrasound findings contribute to a multivariable predictive risk score for surgical necrotizing enterocolitis: A pilot study

BackgroundAbdominal ultrasound (AUS) is a promising adjunct to abdominal x-ray (AXR) for evaluating necrotizing enterocolitis (NEC). We developed a multivariable risk score incorporating AUS to predict surgical NEC. Methods83 patients were evaluated by AXR and AUS for suspected NEC. A subset had surgical NEC. Multivariate logistic regression determined predictors of surgical NEC, which were incorporated into a risk score. Results14/83 patients (16.9%) had surgical NEC. 10/83 (12.0%) patients required acute intervention, while 4/83 (4.8%) patients only required delayed surgery. Four predictors of surgical NEC were identified: abdominal wall erythema (OR: 8.2, p = 0.048), portal venous gas on AXR (OR: 29.8, p = 0.014), and echogenic free fluid (OR: 17.2, p = 0.027) and bowel wall thickening (OR: 12.5, p = 0.030) on AUS. A multivariable risk score incorporating these predictors had excellent area-under-the-curve of 0.937 (95% CI: 0.879–0.994). ConclusionsAUS, as an adjunct to physical exam and AXR, has utility for predicting surgical NEC.

Waist-to-height ratio and metabolic phenotype compared to the Matsuda index for the prediction of insulin resistance

Current screening algorithms for type 2 diabetes (T2D) rely on fasting plasma glucose (FPG) and/or HbA1c. This fails to identify a sizeable subgroup of individuals in early stages of metabolic dysregulation who are at high risk for developing diabetes or cardiovascular disease. The Matsuda index, a combination of parameters derived from a fasting and postprandial insulin assay, is an early biomarker for metabolic dysregulation (i.e. insulin resistance/compensatory hyperinsulinemia). The aim of this analysis was to compare four widely available anthropometric and biochemical markers indicative of this condition [waist-to-height ratio (WHtR), hypertriglyceridemic-waist phenotype (HTW), triglycerides-to-HDL-C ratio (TG/HDL-C) and FPG] to the Matsuda index. This cross-sectional analysis included 2231 individuals with normal fasting glucose (NFG, n = 1333), impaired fasting glucose (IFG, n = 599) and T2D (n = 299) from an outpatient diabetes clinic in Germany and thus extended a prior analysis from our group done on the first two subgroups. We analyzed correlations of the Matsuda index with WHtR, HTW, TG/HDL-C and FPG and their predictive accuracies by correlation and logistic regression analyses and receiver operating characteristics. In the entire group and in NFG, IFG and T2D, the best associations were observed between the Matsuda index and the WHtR (r = − 0.458), followed by HTW phenotype (r = − 0.438). As for prediction accuracy, WHtR was superior to HTW, TG/HDL-C and FPG in the entire group (AUC 0.801) and NFG, IFG and T2D. A multivariable risk score for the prediction of insulin resistance was tested and demonstrated an area under the ROC curve of 0.765 for WHtR and its interaction with sex as predictor controlled by age and sex. The predictive power increased to 0.845 when FPG and TG/HDL-C were included. Using as a comparator the Matsuda index, WHtR, compared to HTW, TG/HDL-C and FPG, showed the best predictive value for detecting metabolic dysregulation. We conclude that WHtR, a widely available anthropometric index, could refine phenotypic screening for insulin resistance/hyperinsulinemia. This may ameliorate early identification of individuals who are candidates for appropriate therapeutic interventions aimed at addressing the twin epidemic of metabolic and cardiovascular disease in settings where more extended testing such as insulin assays are not feasible.

Abdominal Ultrasound Findings Contribute to a Multivariable Predictive Risk Score for Surgical Necrotizing Enterocolitis

Abdominal Ultrasound Findings Contribute to a Multivariable Predictive Risk Score for Surgical Necrotizing Enterocolitis

Multivariable risk scores for predicting short-term outcomes for emergency department patients with unexplained syncope: A systematic review.

Emergency department (ED) patients with unexplained syncope are at risk of experiencing an adverse event within 30days. Our objective was to systematically review the accuracy of multivariate risk stratification scores for identifying adult syncope patients at high and low risk of an adverse event over the next 30days. We conducted a systematic review of electronic databases (MEDLINE, Cochrane, Embase, and CINAHL) from database creation until May 2020. We sought studies evaluating prediction scores of adults presenting to an ED with syncope. We included studies that followed patients for up to 30days to identify adverse events such as death, myocardial infarction, stroke, or cardiac surgery. We only included studies with a blinded comparison between baseline clinical features and adverse events. We calculated likelihood ratios and confidence intervals (CIs). We screened 13,788 abstracts. We included 17 studies evaluating nine risk stratification scores on 24,234 patient visits, where 7.5% (95% CI= 5.3% to 10%) experienced an adverse event. A Canadian Syncope Risk Score (CSRS) of 4 or more was associated with a high likelihood of an adverse event (LRscore≥4 = 11, 95% CI= 8.9 to 14). A CSRS of 0 or less (LRscore≤0 = 0.10, 95% CI= 0.07 to 0.20) was associated with a low likelihood of an adverse event. Other risk scores were not validated on an independent sample, had low positive likelihood ratios for identifying patients at high risk, or had high negative likelihood ratios for identifying patients at low risk. Many risk stratification scores are not validated or not sufficiently accurate for clinical use. The CSRS is an accurate validated prediction score for ED patients with unexplained syncope. Its impact on clinical decision making, admission rates, cost, or outcomes of care is not known.