Aneuploidy underlies brefeldin A-induced antifungal drug resistance in Cryptococcus neoformans.

Cryptococcus neoformans is at the top of the list of "most wanted" human pathogens. Only three classes of antifungal drugs are available for the treatment of cryptococcosis. Studies on antifungal resistance mechanisms are limited to the investigation of how a particular antifungal drug induces resistance to a particular drug, and the impact of stresses other than antifungals on the development of antifungal resistance and even cross-resistance is largely unexplored. The endoplasmic reticulum (ER) is a ubiquitous subcellular organelle of eukaryotic cells. Brefeldin A (BFA) is a widely used chemical inducer of ER stress. Here, we found that both weak and strong selection by BFA caused aneuploidy formation in C. neoformans, mainly disomy of chromosome 1, chromosome 3, and chromosome 7. Disomy of chromosome 1 conferred cross-resistance to two classes of antifungal drugs: fluconazole and 5-flucytosine, as well as hypersensitivity to amphotericin B. However, drug resistance was unstable, due to the intrinsic instability of aneuploidy. We found overexpression of AFR1 on Chr1 and GEA2 on Chr3 phenocopied BFA resistance conferred by chromosome disomy. Overexpression of AFR1 also caused resistance to fluconazole and hypersensitivity to amphotericin B. Furthermore, a strain with a deletion of AFR1 failed to form chromosome 1 disomy upon BFA treatment. Transcriptome analysis indicated that chromosome 1 disomy simultaneously upregulated AFR1, ERG11, and other efflux and ERG genes. Thus, we posit that BFA has the potential to drive the rapid development of drug resistance and even cross-resistance in C. neoformans, with genome plasticity as the accomplice.

Adaptive recognition of machining features in sheet metal parts based on a graph class-incremental learning strategy.

The integration of computer-aided design (CAD), computer-aided process planning (CAPP), and computer-aided manufacturing (CAM) systems is significantly enhanced by employing deep learning-based automatic feature recognition (AFR) methods. These methods outperform traditional, rule-based approaches, particularly in handling the complexities of intersecting features. However, existing deep learning-based AFR methods face two major challenges. The initial challenge stems from the frequent utilization of voxelized or point-cloud representations of CAD models, resulting in the unfortunate loss of valuable geometric and topological information inherent in original Boundary representation (B-Rep) models. The second challenge involves the limitation of supervised deep learning methods in identifying machining features that are not present in the predefined dataset. This constraint renders them suboptimal for the continually evolving datasets of real industrial scenarios. To address the first challenge, this study introduces a graph-structured language, Multidimensional Attributed Face-Edge Graph (maFEG), crafted to encapsulate the intricate geometric and topological details of CAD models. Furthermore, a graph neural network, Sheet-metalNet, is proposed for the efficient learning and interpretation of maFEGs. To tackle the second challenge, a three-component incremental learning strategy is proposed: an initial phase of pre-training and fine-tuning, a prototype sampling-based replay, and a stage employing knowledge distillation for parameter regularization. The effectiveness of Sheet-metalNet and its complementary incremental learning strategy is evaluated using the open-source MFCAD++ dataset and the newly created SMCAD dataset. Experimental results show that Sheet-metalNet surpasses state-of-the-art AFR methods in machining feature recognition accuracy. Moreover, Sheet-metalNet demonstrates adaptability to dynamic dataset changes, maintaining high performance when encountering newly introduced features, thanks to its innovative incremental learning strategy.

Correlation analysis between plasma biomarkers albumin, fibrinogen, and their ratio with postoperative delirium in patients undergoing non-cardiac surgery: a systematic review and meta-analysis.

OBJECTIVES: This meta-analysis aimed to investigate the correlation between plasma biomarkers, such as albumin and fibrinogen, and their ratio with postoperative delirium (POD) in patients undergoing non-cardiac surgery. METHODS: Relevant observational cohort studies were systematically searched in PubMed, EMBASE, CINAHL, and the Cochrane Library databases as of March 2023. This meta-analysis was conducted using RevMan 5.4.1 and Stata 15.0 software. For continuous variables with non-uniform units, the standardized mean difference (SMD) and 95% confidence intervals (CIs) were used; otherwise, the mean difference (MD) and 95% CIs were employed. The Newcastle-Ottawa Scale (NOS) was applied to assess the quality of included literature. RESULTS: Eighteen studies encompassing 7,011 patients were included. The meta-analysis revealed significantly lower albumin levels (sixteen studies, 5,813 patients, SMD = -0.45, 95% CI = -0.64 to -0.26, P < 0.00001, I2 = 80%) and albumin-fibrinogen ratio (AFR) (four studies, 824 patients, MD = -0.62, 95% CI = -0.76 to -0.48, P = 0.56, I2 = 0%) in the delirious group. Conversely, higher fibrinogen concentrations (two studies, 441 patients, MD = 0.13, 95% CI = 0.02 to 0.24, P = 0.69, I2 = 0%) were observed in the delirious group. Due to high heterogeneity in albumin levels (P < 0.00001, I2 = 80%), we conducted a subgroup and sensitivity analysis, and confirmed that the association of albumin levels was not influenced by surgery type, design or delirium evaluation instruments. CONCLUSIONS: Preoperative albumin, fibrinogen and AFR levels were associated with POD, potentially aiding in identifying high-risk patients and playing a key role in preventing POD.

Case report: Beneficial long-term effect of the atrial-flow-regulator device in a pediatric patient with idiopathic pulmonary arterial hypertension and recurring syncope.

We report the long-term effect after successfully implanting an 8 mm Atrial-flow-regulator (AFR) device in a 7-year-old girl with idiopathic pulmonary hypertension with persistent syncope under triple therapy with significant improvement after implantation and absence of any further syncope. Early Implantation of the AFR device (Occlutech, Germany) can be efficient and safe interventional therapy option for pulmonary arterial hypertension with a history of syncope.

The prognostic value of pretreatment albumin-to-fibrinogen ratio in small cell lung cancer patients receiving first-line platinum-based chemotherapy.

This study examined the role of pretreatment albumin-to-fibrinogen ratio (AFR) in the prognosis of small-cell lung cancer (SCLC) patients receiving first-line platinum-based chemotherapy. A total of 131 SCLC patients were enrolled. The predictive value of the AFR for progression free survival (PFS) and overall survival (OS) were evaluated by receiver operating characteristic (ROC) curve analysis. The predictive factor of survival was assessed by univariate and multivariate Cox proportional regression analysis. The correlation between OS, PFS and AFR was determined by the log-rank test using the Kaplan-Meier method. AFR was an effective predictor of OS in SCLC patients with a cut-off value of 7.78. AFR was independent risk factors for OS and PFS. Kaplan Meier analysis showed that PFS and OS in patients with high AFR levels were significantly higher than those with low AFR levels. These results suggest that AFR could be an effective predictor of survival in patients with SCLC.

Staged Acclimatization in a Failing Fontan by AFR in AFR: Ever-Decreasing Circles.

We describe serial implantation of atrial flow regulator (AFR) devices in the Fontan fenestration of a 4-year-old patient. Initially, the fenestration size was decreased using a 6/5 AFR, resulting in improved saturations and hemodynamics. One year later, further improvement was achieved by placing a 4/10 AFR inside the original device. (Level of Difficulty: Advanced.).

Fluconazole Resistance and Virulence in In Vitro Induced-Fluconazole Resistant Strains and in Clinical Fluconazole Resistant Strain of Cryptococcus deuterogattii.

Neuromeningeal cryptococcosis is a life-threatening infection of the central nervous system, caused by encapsulated yeast belonging to the Cryptococcus neoformans and Cryptococcus gattii species complexes. Recent data showed that virulence and antifungal resistance are variable for yeasts belonging to the C. gattii species complex. There is an increase in resistance to fluconazole for yeasts of the C. gattii species complex and the virulence is variable according to the genotype. In the present study, (i) we explored and compared the mechanisms of resistance to fluconazole between C. deuterogattii clinically resistant strains and induced fluconazole-resistant strains by exposure to fluconazole in vitro, and (ii) we studied their virulence in the Galleria mellonella study model. We demonstrated that the fluconazole resistance mechanisms involved were different between clinically resistant strains and induced resistant strains. We also demonstrated that fluconazole-induced resistant strains are less virulent when compared to the original susceptible strains. On the contrary, the clinically resistant strain tested maintains its virulence compared to fluconazole-susceptible strains of the same sequence type.

Lessons Learned and Future Perspectives for Rotavirus Vaccines Switch in the World Health Organization, Regional Office for Africa.

BACKGROUND: Following the World Health Organization (WHO) recommendation, 38/47 countries have introduced rotavirus vaccines into the program of immunization in the WHO Regional Office for Africa (WHO/AFRO). Initially, two vaccines (Rotarix and Rotateq) were recommended and recently two additional vaccines (Rotavac and Rotasiil) have become available. However, the global supply challenges have increasingly forced some countries in Africa to switch vaccine products. Therefore, the recent WHO pre-qualified vaccines (Rotavac, Rotasiil) manufactured in India, offer alternatives and reduce global supply challenges related to rotavirus vaccines; Methods: Using a questionnaire, we administered to the Program Managers, Expanded Program for Immunization, we collected data on vaccine introduction and vaccine switch and the key drivers of the decisions for switching vaccines products, in the WHO/AFRO. Data was also collected fromliterature review and the global new vaccine introduction status data base maintained by WHO and other agencies. RESULTS: Of the 38 countries that introduced the vaccine, 35 (92%) initially adopted Rotateq or Rotarix; and 23% (8/35) switched between products after rotavirus vaccine introduction to either Rotavac (n = 3), Rotasiil (n = 2) or Rotarix (n = 3). Three countries (Benin, Democratic Republic of Congo and Nigeria) introduced the rotavirus vaccines manufactured in India. The decision to either introduce or switch to the Indian vaccines was predominately driven by global supply challenges or supply shortage. The withdrawal of Rotateq from the African market, or cost-saving for countries that graduated or in transition from Gavi support was another reason to switch the vaccine; Conclusions: The recently WHO pre-qualified vaccines have offered the countries, opportunities to adopt these cost-effective products, particularly for countries that have graduated or transitioning from full Gavi support, to sustain the demand of vaccines products.

Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal cholangiocarcinoma.

Background: Distal cholangiocarcinoma (dCCA), originating from the common bile duct, is greatly associated with a dismal prognosis. A series of different studies based on cancer classification have been developed, aimed to optimize therapy and predict and improve prognosis. In this study, we explored and compared several novel machine learning models that might lead to an improvement in prediction accuracy and treatment options for patients with dCCA. Methods: In this study, 169 patients with dCCA were recruited and randomly divided into the training cohort (n = 118) and the validation cohort (n = 51), and their medical records were reviewed, including survival outcomes, laboratory values, treatment strategies, pathological results, and demographic information. Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). We measured and compared the performance of models using the receiver operating characteristic (ROC) curve, integrated Brier score (IBS), and concordance index (C-index) following cross-validation. The machine learning model with the best performance was screened out and compared with the TNM Classification using ROC, IBS, and C-index. Finally, patients were stratified based on the model with the best performance to assess whether they benefited from postoperative chemotherapy through the log-rank test. Results: Among medical features, five variables, including tumor differentiation, T-stage, lymph node metastasis (LNM), albumin-to-fibrinogen ratio (AFR), and carbohydrate antigen 19-9 (CA19-9), were used to develop machine learning models. In the training cohort and the validation cohort, C-index achieved 0.763 vs. 0.686 (SVM), 0.749 vs. 0.692 (SurvivalTree), 0.747 vs. 0.690 (Coxboost), 0.745 vs. 0.690 (RSF), 0.746 vs. 0.711 (DeepSurv), and 0.724 vs. 0.701 (CoxPH), respectively. The DeepSurv model (0.823 vs. 0.754) had the highest mean area under the ROC curve (AUC) than other models, including SVM (0.819 vs. 0.736), SurvivalTree (0.814 vs. 0.737), Coxboost (0.816 vs. 0.734), RSF (0.813 vs. 0.730), and CoxPH (0.788 vs. 0.753). The IBS of the DeepSurv model (0.132 vs. 0.147) was lower than that of SurvivalTree (0.135 vs. 0.236), Coxboost (0.141 vs. 0.207), RSF (0.140 vs. 0.225), and CoxPH (0.145 vs. 0.196). Results of the calibration chart and decision curve analysis (DCA) also demonstrated that DeepSurv had a satisfactory predictive performance. In addition, the performance of the DeepSurv model was better than that of the TNM Classification in C-index, mean AUC, and IBS (0.746 vs. 0.598, 0.823 vs. 0.613, and 0.132 vs. 0.186, respectively) in the training cohort. Patients were stratified and divided into high- and low-risk groups based on the DeepSurv model. In the training cohort, patients in the high-risk group would not benefit from postoperative chemotherapy (p = 0.519). In the low-risk group, patients receiving postoperative chemotherapy might have a better prognosis (p = 0.035). Conclusions: In this study, the DeepSurv model was good at predicting prognosis and risk stratification to guide treatment options. AFR level might be a potential prognostic factor for dCCA. For the low-risk group in the DeepSurv model, patients might benefit from postoperative chemotherapy.

Versatility of Atrial Flow Regulator Device in Congenital Heart Disease: A Case Series.

The Atrial Flow Regulator (AFR) is a self-expandable double-disk device with a central fenestration, intended to maintain a calibrated communication across the interatrial septum. Only case reports and small case series have been published about its use in the pediatric and congenital heart disease (CHD) population. We described AFR implantation in three congenital patients with different anatomies and indications. In the first case, the AFR was deployed to create a stable fenestration in a Fontan conduit, while in the second, it was used to reduce a Fontan fenestration. In the third case, we implanted an AFR to decompress the left atrium of an adolescent with complex CHD in natural history, with complete mixing, ductal-dependent systemic circulation and combined pulmonary hypertension. This case series demonstrates the great potential of the AFR device in the CHD field, showing versatility, efficacy, and safety in establishing a calibrated and stable shunt, with promising hemodynamic and symptomatic benefits.

Prognostic value of the albumin-to-fibrinogen ratio (AFR) in IgA nephropathy patients.

BACKGROUND: The albumin-to-fibrinogen ratio (AFR), a novel inflammatory marker, has been studied in various diseases. However, whether AFR could act as a prognostic factor for IgAN patients remains unclear. We aimed to investigate the prognostic value of AFR in IgAN. METHODS: A total of 1289 biopsy-confirmed primary IgAN patients from 2008 to 2018 in West China Hospital, Sichuan University, were studied retrospectively. Receiver operating characteristic curve analysis was generated to assess and compare the ability of indicators to predict survival. Based on the cut-off value of AFR, IgAN patients were classified into the low AFR group and the high AFR group. The demographic and clinical-histopathological data were collected. Renal endpoints included eGFR decreased ≥50 % of the baseline level, ESRD, renal transplantation and/or death. Patients were followed up until a composite endpoint. Kaplan-Meier survival curves and Cox proportional hazards models were used to determine independent predictors. RESULTS: The area under the curve (AUC) of AFR was 0.677, with an optimal cut-off value of 12.44. IgAN patients were classified into two groups (low AFR group: AFR < 12.44, n = 541; high AFR group: AFR ≥ 12.44, n = 748) with a median follow-up of 55.3 (36.4-78.6) months. A higher composition of hypertension, worse renal function, higher proteinuria, and more severe pathological lesions were significantly shown in the low AFR group. Further multivariable Cox regression analyses showed that a low AFR was an independent risk factor for renal survival (HR 1.90, 95 % CI 1.29-2.81, p = 0.001). Kaplan-Meier curves showed that the cumulative incidences of both ESRD and composite end point were significantly higher in patients with AFR < 12.44 (both p < 0.001). CONCLUSIONS: Our study demonstrated that a low AFR (<12.44) is an independent prognostic factor of poor renal prognosis in Chinese IgAN patients.

Involvement of the Noncanonical Polyadenylation Polymerase Cid14 in Fungal Azole Resistance in the Pathogen Cryptococcus neoformans.

The yeast noncanonical polyadenylation polymerase Cid14 was originally identified from fission yeast and plays a critical role in the TRAMP complex. This protein is a cytoplasmic cofactor and regulator of RNA-degrading exosomes. Cid14 is highly conserved from yeast to animals and has been demonstrated to play key roles in the regulation of RNA surveillance, nutrition metabolism, and growth in model organisms, but not yet in Cryptococcus neoformans (C. neoformans). Here, we report the identification of a gene encoding an equivalent Cid14 protein, named CID14, in the fungal pathogen C. neoformans. To obtain insights into the function of Cid14, we created a mutant strain, cid14Δ, with the CRISPR-Cas9 editing tool. Disruption of CID14 impaired cell membrane stability. Further investigations revealed the defects of the cid14Δ mutant in resistance to low carbohydrate levels. Meanwhile, significantly, the ability to grow under flucytosine stress was decreased in the cid14Δ mutant. More importantly, our results showed that the cid14Δ mutant does not affect yeast virulence but exhibits multidrug resistance to azole. Our work is the first to suggest that Cid14 plays critical roles in azole resistance by affecting Afr1, which is chiefly responsible for azole excretion in the ABC (ATP-binding cassette) transporter.

Atrial Flow Regulator for Postcapillary Pulmonary Hypertension: First-in-Human Transcatheter AFR Device Implantations in RCM.

Restrictive cardiomyopathy (RCM) has a poor prognosis and limited treatment options apart from heart transplantation (HTx). We report on the first-in-human interventional atrial flow regulator (AFR) implantations in 3 children with RCM, leading to marked clinical and hemodynamic improvement. We propose the AFR as bridge to HTx or destination therapy in RCM. (Level of Difficulty: Advanced.).

Master Transcription Regulators and Transcription Factors Regulate Immune-Associated Differences Between Patients of African and European Ancestry With Colorectal Cancer.

Background and Aims: Individuals of African (AFR) ancestry have a higher incidence of colorectal cancer (CRC) than those of European (EUR) ancestry and exhibit significant health disparities. Previous studies have noted differences in the tumor microenvironment between AFR and EUR patients with CRC. However, the molecular regulatory processes that underpin these immune differences remain largely unknown. Methods: Multiomics analysis was carried out for 55 AFR and 456 EUR patients with microsatellite-stable CRC using The Cancer Genome Atlas. We evaluated the tumor microenvironment by using gene expression and methylation data, transcription factor, and master transcriptional regulator analysis to identify the cell signaling pathways mediating the observed phenotypic differences. Results: We demonstrate that downregulated genes in AFR patients with CRC showed enrichment for canonical pathways, including chemokine signaling. Moreover, evaluation of the tumor microenvironment showed that cytotoxic lymphocytes and neutrophil cell populations are significantly decreased in AFR compared with EUR patients, suggesting AFR patients have an attenuated immune response. We further demonstrate that molecules called "master transcriptional regulators" (MTRs) play a critical role in regulating the expression of genes impacting key immune processes through an intricate signal transduction network mediated by disease-associated transcription factors (TFs). Furthermore, a core set of these MTRs and TFs showed a positive correlation with levels of cytotoxic lymphocytes and neutrophils across both AFR and EUR patients with CRC, thus suggesting their role in driving the immune infiltrate differences between the two ancestral groups. Conclusion: Our study provides an insight into the intricate regulatory landscape of MTRs and TFs that orchestrate the differences in the tumor microenvironment between patients with CRC of AFR and EUR ancestry.

Atrial fibrillatory rate as predictor of recurrence of atrial fibrillation in horses treated medically or with electrical cardioversion.

BACKGROUND: The recurrence rate of atrial fibrillation (AF) in horses after cardioversion to sinus rhythm (SR) is relatively high. Atrial fibrillatory rate (AFR) derived from surface ECG is considered a biomarker for electrical remodelling and could potentially be used for the prediction of successful AF cardioversion and AF recurrence. OBJECTIVES: Evaluate if AFR was associated with successful treatment and could predict AF recurrence in horses. STUDY DESIGN: Retrospective multicentre study. METHODS: Electrocardiograms (ECG) from horses with persistent AF admitted for cardioversion with either medical treatment (quinidine) or transvenous electrical cardioversion (TVEC) were included. Bipolar surface ECG recordings were analysed by spatiotemporal cancellation of QRST complexes and calculation of AFR from the remaining atrial signal. Kaplan-Meier survival curve and Cox regression analyses were performed to assess the relationship between AFR and the risk of AF recurrence. RESULTS: Of the 195 horses included, 74 received quinidine treatment and 121 were treated with TVEC. Ten horses did not cardiovert to SR after quinidine treatment and AFR was higher in these, compared with the horses that successfully cardioverted to SR (median [interquartile range]), (383 [367-422] vs 351 [332-389] fibrillations per minute (fpm), P < .01). Within the first 180 days following AF cardioversion, 12% of the quinidine and 34% of TVEC horses had AF recurrence. For the horses successfully cardioverted with TVEC, AFR above 380 fpm was significantly associated with AF recurrence (hazard ratio = 2.4, 95% confidence interval 1.2-4.8, P = .01). MAIN LIMITATIONS: The treatment groups were different and not randomly allocated, therefore the two treatments cannot be compared. Medical records and the follow-up strategy varied between the centres. CONCLUSIONS: High AFR is associated with failure of quinidine cardioversion and AF recurrence after successful TVEC. As a noninvasive marker that can be retrieved from surface ECG, AFR can be clinically useful in predicting the probability of responding to quinidine treatment as well as maintaining SR after electrical cardioversion.

An explicit robust stability condition for uncertain time-varying first-order plus dead-time systems.

First-order plus dead-time (FOPDT) models are broadly used in process control to represent damped dynamic processes with time delays. An explicit condition for parameter- and delay-dependent robust stability of FOPDT systems with varying uncertain parameters and delay is derived in this paper. An internal model control (IMC) approach is proposed to parameterize stabilizing controllers that satisfy the output tracking objective in time-varying FOPDT systems represented by an uncertain first-order dynamic model with a time-varying delay in the control input. The small-gain theorem is used to derive an explicit necessary and sufficient parameter-dependent robust stability condition as a function of the nominal system gain, nominal varying delay, nominal time constant, and the bounds of the parameter uncertainties. An equivalent proportional-integral-derivative (PID) controller is then extracted to facilitate the implementation of the proposed IMC-based robust control. The application of the proposed explicit robust stability condition is studied in the context of air-fuel ratio (AFR) control in lean-burn spark ignition (SI) engines with a large time-varying transport delay in the control loop due to the placement of the universal exhaust gas oxygen (UEGO) sensor downstream the catalytic converter.

Seabird meta-Population Viability Model (mPVA) methods.

The seabird meta-population viability model (mPVA) uses a generalized approach to project abundance and quasi-extinction risk for 102 seabird species under various conservation scenarios. The mPVA is a stage-structured projection matrix that tracks abundance of multiple populations linked by dispersal, accounting for breeding island characteristics and spatial distribution. Data are derived from published studies, grey literature, and expert review (with over 500 contributions). Invasive species impacts were generalized to stage-specific vital rates by fitting a Bayesian state-space model to trend data from Islands where invasive removals had occurred, while accounting for characteristics of seabird biology, breeding islands and invasive species. Survival rates were estimated using a competing hazards formulation to account for impacts of multiple threats, while also allowing for environmental and demographic stochasticity, density dependence and parameter uncertainty.•The mPVA provides resource managers with a tool to quantitatively assess potential benefits of alternative management actions, for multiple species•The mPVA compares projected abundance and quasi-extinction risk under current conditions (no intervention) and various conservation scenarios, including removal of invasive species from specified breeding islands, translocation or reintroduction of individuals to an island of specified location and size, and at-sea mortality amelioration via reduction in annual at-sea deaths.

Research Progress of Preoperative FPR, FAR or AFR in Patients with Colorectal Cancer.

Research has confirmed that plasma albumin (Alb), prealbumin (PA) and fibrinogen (Fib) are involved in regulating the occurrence and development of various tumors. Their levels in peripheral blood are related to the survival outcome and treatment response of patients, but the accuracy and specificity of single application have yet to be fully realized. A growing amount of evidence indicates that predictors such as preoperative fibrinogen to prealbumin ratio (FPR), fibrinogen to albumin ratio (FAR) or albumin to fibrinogen ratio (AFR) are emerging as comprehensive indicators. Indeed, their components play a key regulatory role in the progression of colorectal cancer (CRC). Preoperative FPR, FAR or AFR levels, therefore, are expected to become new biomarkers for prognosis evaluation and curative effect prediction for CRC patients and are significant in the guidance they could provide for the development of individualized treatment strategies.

Prognostic Value of Combined Detection of Preoperative Albumin-to-Fibrinogen Ratio and Neutrophil-to-Lymphocyte Ratio in Operable Esophageal Squamous Cell Carcinoma Patients without Neoadjuvant Therapy.

BACKGROUND: We retrospectively analyzed the prognostic value of the albumin-to-fibrinogen ratio (AFR)-neutrophil-to-lymphocyte ratio (NLR) score, comprising preoperative AFR and NLR, in esophageal squamous cell carcinoma (ESCC) patients after radical resection. PATIENTS AND METHODS: Overall, 215 patients were included. The optimal cutoff value was determined using the receiver operating characteristic (ROC) curve. Based on a low AFR (<12.06) and high NLR (≥1.78), the AFR-NLR score was classified as 2 (both hematological abnormalities present), 1 (one abnormality present), or 0 (both abnormalities absent). Kaplan-Meier curves, Cox regression, and predicted nomogram were used to evaluate the prognostic value of the score. RESULTS: The prognostic value of the AFR-NLR score was better than that of AFR or NLR alone (P <0.05). Multivariate analysis showed that a high AFR-NLR score was an independent predictor of poor prognosis for overall survival (P <0.001). Additionally, in the nomogram including the AFR-NLR score, the net reclassification improvement index increased by 35.5% (P <0.001), and the integrated discrimination improvement index increased by 9.0% (P <0.001). The predictive accuracy of the established nomogram model was proved using Harrell's concordance index (0.811, 95% confidence interval: 0.765-0.856) and calibration curve. Notably, the decision analysis curve showed that the nomogram had a higher net benefit within most of the threshold probability range, indicating better clinical applicability. CONCLUSION: The AFR-NLR score is a useful predictor of the prognosis of ESCC patients after radical resection, and the nomogram established on the basis of this score has a good prognostic value.