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PubMed2026

scRNA-seq and bulk RNA-seq reveal the characteristics of macrophage copper metabolism and establish a risk signature in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent malignancy with an urgent need for improved prognostic stratification and treatment-response prediction. This study aimed to explore a macrophage copper metabolism-associated prognostic model and to investigate the relationship between this risk model and the tumor immune microenvironment. METHODS: The FindClusters function was used to analyze cell clusters, and CellChat and CellPhoneDB/LIANA were employed for cell-cell communication analysis. Copper metabolism-related genes were sourced from the MSigDB database. A prognostic risk model was established using least absolute shrinkage and selection operator (LASSO) analysis and multivariate Cox regression analysis, and a nomogram was constructed by integrating the prognostic model with clinicopathological factors. Additional analyses were performed to map the seven model genes in single-cell data, assess model uncertainty and robustness, evaluate macrophage/copper/cuproptosis-related transcriptional programs, and examine the correlations between risk score, immune infiltration and predicted drug sensitivity. RESULTS: Using single-cell RNA sequencing (scRNA-seq) data, we identified four macrophage subpopulations. Macrophages with high SPP1 expression showed close interaction with T cell populations and were associated with copper ion metabolism. By incorporating 141 copper metabolism-related genes and using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort, we constructed a seven-gene risk prediction model. Additional single-cell mapping showed that the model genes were detectable in the HCC single-cell dataset and showed a macrophage-associated expression pattern. The model showed moderate prognostic discrimination in TCGA-LIHC, whereas its external performance was heterogeneous and remained evaluable across external cohorts, with performance varying among datasets. Immune and mechanism-related analyses suggested that the risk signature was associated with macrophage-related infiltration, copper metabolism and cuproptosis-related transcriptional programs. Drug sensitivity analysis nominated Daporinad as a computationally predicted candidate compound, supporting Daporinad as a pharmacogenomic candidate for follow-up investigation. CONCLUSIONS: By integrating scRNA-seq and bulk RNA sequencing (RNA-seq) data, we constructed a macrophage copper metabolism-associated prognostic signature for HCC. The risk score was associated with survival, immune microenvironment features and predicted drug response, providing a transcriptomic framework for risk stratification and therapeutic hypothesis generation.

Hepatocellular carcinoma (HCC)↗
PubMed2026

Development and validation of a comprehensive prognostic model for 28-day ICU mortality in non-traumatic subarachnoid hemorrhage: an analysis based on the MIMIC-IV database.

BACKGROUND: Due to the complex pathophysiology of non-traumatic subarachnoid hemorrhage (SAH), accurate risk prediction remains a challenge. Our aim is to develop and validate a comprehensive prognostic model that integrates demographic characteristics, vital signs, laboratory parameters, and more, to provide clinical decision-making support in real-world practice. METHODS: We conducted a retrospective cohort study of 785 Non-traumatic subarachnoid hemorrhage patients. The cohort was randomly divided into a training set (n = 549) and a validation set (n = 236). Feature selection was performed using LASSO regression, followed by backward stepwise Cox regression for optimization. A nomogram was constructed based on independent predictive factors, and model performance was assessed using discrimination, calibration, and decision curve analysis. To prevent immortal-time bias, all predictors were anchored to a fixed early (first-24-hour) measurement window, treatment variables were modelled as binary indicators rather than cumulative exposures, and a five-model sensitivity analysis with baseline-severity adjustment was performed. RESULTS: The development of our model followed a systematic approach: first, 15 potential predictive factors were selected via LASSO regression, which were then refined to 12 independent predictors using backward stepwise Cox regression. The final predictive factors included: Ventilation, AHT, Nimodipine 60 mg, Age, SAPS.II, Input amount, Calcium total, Platelet count, White blood cells, Anion gap, pH, and Chloride. The integrated model demonstrated excellent predictive ability for 7-day, 14-day, and 21-day mortality in both the training set (AUC: 0.972, 0.934, 0.898) and the validation set (AUC: 0.968, 0.948, 0.911). Calibration curves and decision curve analysis confirmed the model's reliability and clinical utility across different time points. We constructed a nomogram for individualized risk prediction. Univariate Kaplan-Meier survival analysis demonstrated significant stratification of survival outcomes by each predictor, while restricted cubic spline analysis revealed non-linear relationships between continuous variables and mortality risk. Random survival forest analysis identified the top three predictive factors (Nimodipine 60 mg, Ventilation, AHT) and compared them with our full 12-variable model, confirming superior performance of the integrated model at all time points. At the 28-day primary endpoint, the model achieved a time-dependent AUC of 0.898 (training) and 0.904 (validation); after restricting predictors to the early baseline window, the leakage-controlled model retained good discrimination (validation C-index 0.803). CONCLUSIONS: Our ICU 28-day mortality prognosis model demonstrated robust performance in predicting ICU 28-day mortality in non-traumatic subarachnoid hemorrhage. The model, through the nomogram, provides individualized risk assessment, aiding clinical decision-making and patient stratification.

Humans↗
PubMed2000

Predicting the risk of mobility difficulty in older women with screening nomograms: the Women's Health and Aging Study II.

BACKGROUND: A major obstacle to screening for early mobility disability (ie, mobility difficulty), a major public health concern, is the lack of a method that identifies those who are at high risk. The goal of this study was to develop easy-to-use clinical nomograms for estimation of the probability of incident mobility difficulty. METHODS: We conducted a population-based prospective study using data from 266 high physically and cognitively functioning older women, aged 70 to 80 years, who were free of mobility disability at the baseline evaluation of the Women's Health and Aging Study II. The outcome measure was incident mobility disability within 18 months, defined as self-reported difficulty walking 0.8 km, climbing 10 steps, or transferring from or into a car or bus. Logistic regression and receiver operating characteristic curve analyses were used for evaluation of the optimal combination of self-reported and performance-based mobility measures. Bootstrap sampling and estimation was used for validation. RESULTS: Predictive nomograms were developed based on a final model that included 3 simple-to-obtain measures of preclinical disability: self-report of modification in mobility tasks without having difficulty with them, one-leg stance balance, and time to walk 1 m at a usual pace. Final model accuracy (as estimated by the area under the receiver operating characteristic curve) was 73% (SE = 0.04). Validation analysis confirmed the high accuracy of these nomograms. CONCLUSIONS: An original tool was developed for assessment of the risk of mobility difficulty in older women that can be used to assist physicians and researchers in deciding which women to target for preventive interventions.

Aged↗
PubMed2026

Crucial role of telomere maintenance-related genes in survival prediction and subtype identification in colorectal cancer.

BACKGROUND: Telomere maintenance-related genes (TMRGs) are implicated in Colorectal cancer (CRC) development, but their prognostic value and clinical relevance remain insufficiently explored. This study aims to develop a TMRG-based prognostic model and elucidate its clinical utility in CRC management. METHODS: The Cancer Genome Atlas database was utilized to download RNA-seq data from 638 CRC and 51 control samples. Differential expressed genes were screened and intersected with 2086 TMRGs, resulting in the identification of 976 TMRGs. Through univariate and multivariate Cox regression analysis, a prognostic model comprising three telomere maintenance-related biomarkers (PDE1B, TFAP2B, and HSPA1A) was developed and validated using an external dataset. By integrating the model risk score with clinical features, a nomogram was constructed to predict the survival outcomes of CRC patients. Additionally, an in-depth investigation of the immuno-infiltration, functional variation and drug sensitivity analysis were performed in two risk subgroups defined by the prognostic model. Finally, the functional significance of PDE1B in CRC cell lines was investigated through MTT assays, cell colony formation assays, transwell assays and flow cytometry. RESULTS: A total of 976 DE-TMRGs were enriched in telomere/DNA replication pathways. A three-gene signature (PDE1B, TFAP2B, and HSPA1A) stratified patients into high- and low-risk groups with divergent survival (AUC >0.60, validated externally). High-risk patients had advanced N/M stages, elevated M0/M2 macrophages, reduced CD4+ memory T cells, and upregulated immune checkpoints. Nomogram integrating risk score, age, and N/M stage accurately predicted 1-/3-/5-year survival. Low-risk patients showed greater 5-fluorouracil sensitivity. PDE1B expression was significantly reduced in CRC tissues and correlated with advanced stages. Functional assays confirmed PDE1B overexpression suppressed proliferation, migration, invasion, and induced apoptosis in CRC cells. CONCLUSION: This study identifies a moderately predictive telomere maintenance-related gene signature as an independent prognostic predictor in CRC. The risk stratification model effectively discriminates patients with distinct survival patterns, tumor microenvironments, and therapeutic responses, while the integrated nomogram offers additional reference information for survival analysis, albeit with only moderate predictive accuracy. These findings indicate telomere maintenance-related gene signature could serve as a preliminary auxiliary risk stratification tool for postoperative CRC patients, PDE1B may also serve as a potential epithelial tumor-suppressor target for future preclinical studies.

PDE1B↗
PubMedDate not supplied

A regional blood circulation alternative to in-series two compartment urea kinetic modeling.

Assuming that the clearance of urea from total body water (TBW) is flow limited, the authors developed a parallel flow model using physiologic data. Organ systems with a blood flow to water volume ratio of greater than 0.2 min-1 were allocated to the high flow system. Remaining organs were represented in the low flow system. In end-stage renal disease patients with minimal renal blood flow, the high flow system contained 20% TBW and received 70% of the systemic blood flow. The authors used this flow heterogeneity to predict the post-dialysis urea rebound (R) in 12 patients after 1 hr of hemodialysis. Dialyzer clearance was 248 +/- 14.5 ml/min (mean +/- SEM) Access recirculation was obviated by returning cleared blood into a central vein. In these patients, R at 1, 3, 5, 7, 10, and 15 minutes. after slowing dialyzer blood flow (Qb) from 383 +/- 18 to 50 ml/min was 3.8 +/- 2.9, 6.2 +/- 3.4, 7.6 +/- 3.1, 8.8 +/- 3.9, 9.0 +/- 4.1, and 9.9 +/- 4.4%, respectively. CO and QAc were modeled with values of 5.5 and 0.5 L/min, respectively. The modeled TBW was 35 L. Total body water derived by nomogram was 38.1 +/- 2.0 L. Our results suggest that the parallel-flow model for urea transport can be used to explain the amount and time course of post dialysis R on a physiologic basis.

Blood Flow Velocity↗
PubMed1998

Population pharmacokinetics of gentamicin in patients with cancer.

AIMS: The purpose of this study was to describe the population pharmacokinetics of gentamicin in patients with cancer, to identify possible relationships between clinical covariates and population pharmacokinetic parameter estimates and to examine the relevance of existing dosage nomograms in light of the population model developed in these patients. METHODS: Data were collected prospectively from 210 patients with cancer and were analysed with package NONMEM. Data were split into two sets: a population data set and an evaluation set. Creatinine clearance was estimated using measured creatinine concentrations and using 'low' creatinines set to a minimum of 60 micromol l(-1), 70 micromol l(-1) or 88.4 micromol l(-1) RESULTS: A two compartment model was fitted to the concentration-time curve. Two best models were obtained, one that related clearance to estimated creatinine clearance (minimum creatinine value 60 micromol l(-1)) and the other that related clearance to age, creatinine concentration and body surface area. Volume of the central compartment was influenced by body surface area and albumin concentration. For both models 90% of measured concentrations lay within the 95% confidence interval of the simulated concentrations and the mean prediction errors were -7.2% and -6.6%, respectively. A final analysis performed in all patients identified the following relationship CL (1 h(-1))=0.88 x (1 + 0.043 x creatinine clearance) and central volume of distribution V1 (1)=8.59 x body surface area x (albumin/34)(-0.39). The mean population estimate of intercompartmental clearance (Q) was 1.301 h(-1) and peripheral volume of distribution (V2) was 9.801. Coefficient of variation was 18.5% on clearance and 28.2% on Q. Residual error expressed as a standard deviation was 0.36 mg l(-1) at 1.0 mg l(-1) and 1.32 mg l(-1) at 8.0 mg l(-1). The mean population estimate of clearance was 4.21 h(-1) and volume of distribution (Vss) was 24.61 (0.381 kg(-1)). The mean population estimates of half-lives were 1.8 h and 8.0 h. CONCLUSIONS: In the context of published nomograms this analysis indicated that both the traditional approach and the new, 'once daily' approach should achieve satisfactory concentrations in cancer patients although serum concentration monitoring is required to confirm optimal dosing in individual patients.

Adolescent↗
PubMed1976

Maximal oxygen consumption in patients with lung disease.

A theoretical model for oxygen transport assuming a series linkage of ventilation, diffusion, oxygen uptake by erythrocytes, cardiac output, and oxygen release was used to calculate expected values for maximal oxygen intake (VO2max) of patients with various pulmonary disorders 22 patients with either restrictive or obstructive ventilatory impairment were studied at rest and maximal exercise. When exercise measurements of maximal pulmonary blood flow (QCmax), oxygen capacity, membrane diffusing capacity for CO, pulmonary capillary blood volume, alveolar ventilation, and mixed venous oxygen saturation were employed as input values, predictions of VO2max from the model correlated closely with measured values (r = 0.978). Measured VO2max was 976+/-389 ml/min (45.3+/-13% of predicted normal), and VO2max predicted from the model was 1,111+/-427 ml/min. The discrepancy may in part reflect uneven matching of alveolar ventilation, pulmonary capillary blood flow, and membrane diffusing capacity for CO within the lung; uniform matching is assumed in the model so that mismatching will impair gas exchange beyond our predictions. Although QCmax was less than predicted in most patients (63.6+/-19.6% of predicted) the model suggests that raising QCmax to normal could have raised VO2max only 11.6+/-8.8% in the face of existent impairment of intrapulmonary gas exchange. Since pulmonary functions measured at rest correlated well with exercise parameters needed in the model to predict VO2max we developed a nomogram for predicting VO2max from resting CO diffusing capacity, the forced one second expired volume, and the resting ratio of dead space to tidal volume. The correlation coefficient between measured and predicted VO2max, by using this nomogram, was 0.942.

Adolescent↗
PubMedDate not supplied

Pharmacodynamic optimization of warfarin therapy II.

A pharmacodynamic (E(max)) model for optimizing warfarin initiation had previously been reported. This study assessed the validity of this model, adjusted further for age in both the initial cohort and another cohort distinct from that used for the formulation of the model. Thirty-one patients undergoing oral anticoagulation for mainly cardiac indications were recruited from Kuala Lumpur. Thirty-four patients undergoing oral anticoagulation for deep vein thrombosis were recruited from Cambridge. They were studied for their anticoagulant response to the initiation of warfarin. The former were intuitively dosed after a 2-day loading of 10 mg warfarin/d. The latter all were commenced on warfarin via a standard 4-day induction protocol of Fennerty et al that allows early estimation of the required maintenance dose. The actual maintenance doses in both cohorts were compared with their predicted doses on the initiation of therapy that was calculated both from this model and from the induction protocol of Fennerty et al. The third day's international normalized ratio and age combination was additive in terms of their influence on the maintenance dose. The predictive model in both cohorts returned similar results and explained at least two thirds of the interindividual variability in warfarin maintenance dose requirements, whereas the induction protocol of Fennerty et al explained only one third of this interindividual variability. Use of this model in the form of the included nomogram should be able to decrease both the occurrence of either under- or overanticoagulation as well as the time taken to initiate treatment and decide the correct maintenance dose during the initiation of oral anticoagulation with warfarin in hospitals. A prospective evaluation of the nomogram is recommended.

Administration, Oral↗
PubMed1998

Alzheimer's disease risk factors as related to cerebral blood flow: additional evidence.

In a previous report, Alzheimer's disease risk factors, including alcohol abuse, depression, Down's syndrome, cerebral glucose metabolism defect, head trauma, old age, Parkinson's disease, sleep disturbance, and underactivity, were shown to have an association with reduced cerebral blood flow. In this report an attempt is made to strengthen a hypothesis that reduced cerebral blood flow may be a required cofactor in the cause of Alzheimer's disease with examples of additional putative risks, including aluminum, ApoE 4 alleles, estrogen deficiency, family history of dementia, low education-attainment, olfactory deficit, and underactivity coupled with gender, considered to have a relationship or potential relationship with reduced cerebral blood flow. Factors, believed to ameliorate Alzheimer's disease, associated with improved or stabilized cerebral blood flow are tabulated. A tentative cerebral blood flow nomogram is shown as a potential model to possibly help predict Alzheimer's disease susceptibility.

Alleles↗
PubMed1976

Errors involved in instantaneous intravascular input assumptions.

A comparative evaluation of a zero-order input and the generally accepted instantaneous intravascular input assumption is made for two- and three-compartment open model systems. Equations are derived and a nomogram is prepared to calculate the magnitude of error involved in instantaneous input assumptions. It is suggested that all intravascular administrations be considered as zero-order inputs.

Injections, Intra-Arterial↗
PubMed1999

Fat-free mass qualitative assessment with bioelectric impedance analysis (BIA).

Body composition studies, when based on two-compartment volumetric estimates, can hardly assess nutritional states. Phase-sensitive impedance analysis can be used to reflect directly the proportions between intra- and extracellular spaces (ECM/BCM), which is one of the most sensitive indexes of malnutrition. Resistance and reactance values actually measured with BIA are referred to as the series RC model; however, due to the morphology of the FFM, which is composed of cells surrounded by interstitial fluids, in reality this should be modeled as a parallel RC circuit. A nomogram developed with series-to-parallel transformations of resistance and reactance measured with commercial BIA on controls and patients shows interesting gender and disease sensitivity and specificity.

Anorexia Nervosa↗
PubMed1999

Postoperative nomogram for disease recurrence after radical prostatectomy for prostate cancer.

PURPOSE: Although models exist that place patients into discrete groups at various risks for disease recurrence after surgery for prostate cancer, we know of no published work that combines pathologic factors to predict an individual's probability of disease recurrence. Because clinical stage and biopsy Gleason grade only approximate pathologic stage and Gleason grade in the prostatectomy specimen, prediction of prognosis should be more accurate when postoperative information is added to preoperative variables. Therefore, we developed a postoperative nomogram that allows more accurate prediction of probability for disease recurrence for patients who have received radical prostatectomy as treatment for prostate cancer, compared with the preoperative nomogram we previously published. PATIENTS AND METHODS: By Cox proportional hazards regression analysis, we modeled the clinical and pathologic data and disease follow-up for 996 men with clinical stage T1a-T3c NXM0 prostate cancer who were treated with radical prostatectomy by a single surgeon at our institution. Prognostic variables included pretreatment serum prostate-specific antigen level, specimen Gleason sum, prostatic capsular invasion, surgical margin status, seminal vesicle invasion, and lymph node status. Treatment failure was recorded when there was either clinical evidence of disease recurrence, a rising serum prostate-specific antigen level (two measurements of 0.4 ng/mL or greater and rising), or initiation of adjuvant therapy. Validation was performed on this set of men and a separate sample of 322 men from five other surgeons' practices from our institution. RESULTS: Cancer recurrence was noted in 189 of the 996 men, and the recurrence-free group had a median follow-up period of 37 months (range, 1 to 168 months). The 7-year recurrence-free probability for the cohort was 73% (95% confidence interval, 68% to 76%). The predictions from the nomogram appeared to be accurate and discriminating, with a validation sample area under the receiver operating characteristic curve (ie, a comparison of the predicted probability with the actual outcome) of 0.89. CONCLUSION: A postoperative nomogram has been developed that can be used to predict the 7-year probability of disease recurrence among men treated with radical prostatectomy.

Adult↗
PubMed1980

Nomograms for precise determination of birth weight for dates.

We have derived a mathematical model (Altman and Coles, 1980) that matches closely the birth weight standards derived from the large Aberdeen survey (Thomson et al, 1968). From this, we have drawn nomograms that can be used to assess an infant's position in relation to these standards. The nomograms are easy to use and give adequate precision.

Birth Weight↗
PubMed1997

Selection of thrombolytic therapy for individual patients: development of a clinical model. GUSTO-I Investigators.

We developed a logistic regression model with data from the GUSTO-I trial to predict mortality rate differences in individual patients who received accelerated tissue plasminogen activator (TPA) versus streptokinase treatment for acute myocardial infarction. A nomogram was developed from a reduced version of this model that approximated the underlying risk of patients treated with streptokinase, and thus the benefit of TPA. The 30-day mortality rate with accelerated TPA was 0.063 versus 0.073 with streptokinase and subcutaneously administered heparin and 0.074 with streptokinase and intravenously administered heparin. No baseline patient characteristics were significantly associated with a different relative effect of TPA. Older patients and those with anterior infarction, higher Killip classification (except Killip class IV), lower blood pressure, and increased heart rate had the greatest absolute benefit with accelerated TPA. Patients with acute myocardial infarction who had more high-risk characteristics derived a greater absolute benefit from treatment with accelerated TPA versus streptokinase.

Age Factors↗
PubMed1999

Naive Bayesian-based nomogram for prediction of prostate cancer recurrence.

This paper introduces a schema with naive-Bayesian classifier and patient weighting technique to develop a prostate cancer recurrence prediction model from patient data. We propose the graphical presentation of naive-Bayesian classifier with a nomogram, which can be used both for prediction or can provide means to data analysis. The resulting model was experimentally evaluated; the results were favorable both in terms of interpretability and predictive accuracy.

Bayes Theorem↗
PubMed1976

Calculations for pH during CO2 and O2 exchange with blood.

New mathematical formulas are presented to calculate directly the change in blood pH during CO2, and O2 exchange with blood. pH changes are calculated from changes in blood PCO2 and saturation values or from changes in blood PCO2 and blood PO2 values. Computational results agree well with information obtained from a Dill nomogram. These new formulas have applicability to the modelling of gas exchange in blood oxygenators as well as to estimating blood acid-base parameters following the mixing of blood samples.

Blood↗
PubMed1991

[Multifactorial experiment on the combined effect of rifampicin and microbial polysaccharide in experimental plague infection].

Multifactorial analysis was applied to the study of the combined effect of rifampicin and a microbial polysaccharide in experimental plague infection. The effect of the antibiotic and immunomodulator was shown to be synergistic. On the basis of the study results polynomial statistic models of the second order were designed and nomograms or equal level lines were plotted which provided optimization of the combined chemo- and immunotherapy.

Animals↗