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PubMed2001

[The role of psychologic factors in adaptive behavior of younger and older people].

Contemporary view on the issue of adjustment potential in an aging human being is presented. In a prognostic model the following features, ranked according to their importance, were identified: for younger individuals--friendship, warmth, responsibility, thoroughness, persistence, control of conditioned and unconditioned reflexes, sensitivity, tenderness, wide range of interests, tolerance towards other people and high level of intellectual efficiency; for older individuals--self control, social maturity and balanced approach to the others, lack of conflicts in interpersonal relationships, self sufficiency and independence, tolerance with a tendency to self subordination and psychological immunity. Attention is drawn to the results of the obtained prognostic models which will constitute a reference base for psychologists working in geriatric wards.

Adaptation, Psychological↗
PubMed2024

Exploring the prognostic landscape of oral squamous cell carcinoma through mitochondrial damage-related genes.

Oral squamous cell carcinoma (OSCC), the most prevalent form of oral cancer, poses significant challenges to the medical community due to its high recurrence rate and low survival rate. Mitochondrial Damage-Related Genes (MDGs) have been closely associated with the occurrence, metastasis, and progression of OSCC. Consequently, we constructed a prognostic model for OSCC based on MDGs and identified potential mitochondrial damage-related biomarkers. Gene expression profiles and relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Differential analysis was conducted to identify MDGs associated with OSCC. COX analysis was employed to screen seven prognosis-related MDGs and build a prognostic prediction model for OSCC. Cases were categorized into low-risk or high-risk groups based on the optimal risk score threshold. Kaplan-Meier (KM) analysis revealed significant survival differences (P&#x2009;<&#x2009;0.05). Additionally, the area under the ROC curve (AUC) for patient survival at 1 year, 3 years, and 5 years were 0.687, 0.704, and 0.70, respectively, indicating a high long-term predictive accuracy of the prognostic model. To enhance predictive accuracy, age, gender, risk score, and TN staging were incorporated into a nomogram and verified using calibration curves. Risk scoring based on MDGs was identified as a potential independent prognostic biomarker. Furthermore, BID and SLC25A20 were identified as two potential independent mitochondrial damage-related prognostic biomarkers, offering new therapeutic targets for OSCC.

Humans↗
PubMed1993

High-dose chemotherapy and autologous hematopoietic stem-cell transplantation for aggressive non-Hodgkin's lymphoma.

PURPOSE: To evaluate clinical and tumor characteristics in patients receiving high-dose chemotherapy and autologous peripheral stem-cell transplantation (PSCT) or bone marrow transplantation (ABMT) for relapsed or primary refractory non-Hodgkin's lymphoma (NHL). PATIENTS AND METHODS: One hundred fifty-eight patients with NHL received high-dose chemotherapy and ABMT or PSCT. A multivariate analysis of characteristics was performed for comparison of the long-term failure-free survival (FFS) rate. RESULTS: Using a multivariate analysis, a prognostic model was constructed with patients in the good-prognosis group being those without a mass > or = 10 cm at the time of transplant, and no more than one of the following characteristics: three or more prior chemotherapy regimens, lactate dehydrogenase (LDH) level above normal, and chemotherapy resistance. Patients in the poor-prognosis group had a mass > or = 10 cm, or two of the other characteristics noted. The poor-prognosis group had a 3-year FFS rate of 10%, compared with a 45% 3-year FFS in the good-prognosis group (P < .001). Within the prognostic groups, there was no difference in the 3-year FFS rate of the poor-prognosis patients who received ABMT versus PSCT (10% v 12%; not significant). However, in the good-prognosis group, patients who received ABMT had a 3-year FFS rate of 32%, compared with 70% for those who received PSCT (P < .008). CONCLUSION: This prognostic model can identify patients with good and poor prognoses following high-dose chemotherapy and ABMT or PSCT for aggressive NHL. In good-prognosis patients, those who received PSCT had a superior FFS rate.

Adolescent↗
PubMedDate not supplied

Liver transplantation in autoimmune liver disease--selection of patients.

Autoimmune hepatitis (AIH), primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC) are autoimmune liver diseases, which are good indications for orthotopic liver transplantation (OLT). While there is effective treatment for AIH (steroids with or without azathioprine) and PBC (Ursodesoxycholic acid) no such treatment is currently established for PSC. The need for transplantation can be delayed for AIH and PBC with appropriate therapies, while treatment options for PSC are still controversially discussed. Although the time point for liver transplantation can be roughly estimated for AIH by failure of immunosuppressive therapy and for PBC by prognostic models, the prediction of survival in patients with PSC is more difficult, and further complicated through the risk of developing cholangiocellular carcinoma (CCC). Long-term (5-year) outcome after liver transplantation approaches 80-90% for autoimmune liver diseases unless CC complicates PSC at the time of OLT. The risk of disease recurrence has been recognized for each of these entities although its clinical relevance is controversial. This gets more important as long-term survival can be achieved for most of these patients today. In this review the natural course of autoimmune liver disease will be discussed and prognostic models will be presented, which are helpful for finding the optimal time point for liver transplantation.

Cholangitis, Sclerosing↗
PubMed1993

[Use of models in prognostication of hearing loss in the assessment of adverse effects of industrial noise].

Actual deafness due to constant and impulsive noise was compared with that calculated according to the Robinson patterns of deaf forecasting and standard 1999. Impulsive noises appeared to be the most aggressive for hearing. Since the amplitude and time parameters are eliminated from account in the patterns, they must be applied with caution to the evaluation of deafness risk.

Hearing Loss, Noise-Induced↗
PubMed1994

[The prognostic relevance of preoperative pulmonary function tests].

At Leipzig University, preoperative pulmonary function testing has been performed for about 3 years in order to detect and classify patients at high pulmonary risk. During the postoperative period, the risk of developing pulmonary complications is particularly high due to factors influencing respiratory mechanics such as the supine position, pain, residual effects of narcotic drugs, etc. It has often been emphasised that an underlying ventilatory disturbance such as obstructive lung disease or smoking may enhance the postoperative pulmonary risk, although the extent of the influence of preoperative pulmonary diseases on the postoperative complication rate is still controversial. The prediction of postoperative lung function from preoperative spirometric values is complicated by factors such as patient cooperation, pulmonary complications secondary to aspiration, infection, peritonitis, etc., and by differing and therefore non-comparable postoperative care. For this reason, the criteria for assessing pulmonary risk vary widely. METHODS. We examined 339 patients (mean age 59.3 years) preoperatively by quiet and forced spirometry; in most cases we also measured airway resistance and functional residual capacity. We estimated the postoperative lung function using the quadrant scheme of Miller and compared this risk class with our spirometric diagnosis and the postoperative clinical course. RESULTS. According to our results, Miller's classification seems inadequately differentiated for patients with mild to moderate ventilatory disturbances. A relatively high percentage of these patients were considered to have normal postoperative lung function. Some patients with severely diminished pulmonary function were classified as having sufficient postoperative lung function. The number and severity of pulmonary complications also corresponded better with the spirometric diagnosis, which was made using all spirometric parameters and not only vital capacity (VC) and 1-s forced expiratory volume (FEV1). We found that the percentage of primary respiratory complications increased with deterioration of the preoperative spirometric values. To provide a prognostic model combining both the advantages of using only a few parameters (FEV1, VC) and appropriate risk assessment, we propose a modification of the Miller scheme consisting of five risk classes. The analysis of the respiratory therapy regimen was unsatisfactory because of discrepancies between the predicted pulmonary risk, the use of respiratory therapy, and the occurrence of pulmonary complications. CONCLUSIONS. For minimising perioperative pulmonary complications, respiratory care (prophylaxis and therapy) adequate for the functional risk of the patient is necessary. We assume that intensive pre- and postoperative respiratory care and therapy in patients with underlying reductions in ventilatory function can help to avoid or reduce respiratory complications. The modification of Miller's scheme proposed after evaluating the postoperative course of our patients provides a differentiated prognostic model that allows the establishment of an appropriate and economical therapeutic regimen of perioperative pulmonary care.

Adult↗
PubMed1999

How concordant are the estimated rates of natural conception and in-vitro fertilization/embryo transfer success?

Knowledge of the chance to conceive for the subfertile couple is important in the process of counselling and clinical decision making. There are no data available on the reproducibility of the clinician's ability to assess the chance to conceive, both after expectant management or treatment with in-vitro fertilization and embryo transfer (IVF-embryo transfer). We evaluated this reproducibility by means of a set of case histories presented to a panel of gynaecologists and endocrinologists. A poor reproducibility would indicate a strong need for the use of prognostic models. In 1995, 57 gynaecologists and 32 reproductive endocrinologists were asked to appraise the 1 year spontaneous conception chance as well as the cumulative success rate of three cycles for IVF-embryo transfer of four couples with different medical histories. The clinical and laboratory data of these couples were presented as case histories. The difference between the estimated spontaneous pregnancy chances and the success rate of IVF-embryo transfer was also calculated. Calculation of intra-class correlation coefficients, which can be considered as measures of the reproducibility, demonstrated a substantial reproducibility of the assessment of spontaneous conception chances, but a slight to fair reproducibility of the assessment of IVF-embryo transfer success rates. We conclude that the use of reliable prognostic models for IVF-embryo transfer in the management of subfertility is warranted.

Adult↗
PubMed2001

A 10-year experience of liver transplantation for hepatitis C: analysis of factors determining outcome in over 500 patients.

OBJECTIVE: To determine the factors affecting the outcome of orthotopic liver transplantation (OLT) for end-stage liver disease caused by hepatitis C virus (HCV) and to identify models that predict patient and graft survival. SUMMARY BACKGROUND DATA: The national epidemic of HCV infection has become the leading cause of hepatic failure that requires OLT. Rapidly increasing demands for OLT and depleted donor organ pools mandate appropriate selection of patients and donors. Such selection should be guided by a better understanding of the factors that influence the outcome of OLT. METHODS: The authors conducted a retrospective review of 510 patients who underwent OLT for HCV during the past decade. Seven donor, 10 recipient, and 2 operative variables that may affect outcome were dichotomized at the median for univariate screening. Factors that achieved a probability value less than 0.2 or that were thought to be relevant were entered into a stepdown Cox proportional hazard regression model. RESULTS: Overall patient and graft survival rates at 1, 5, and 10 years were 84%, 68%, and 60% and 73%, 56%, and 49%, respectively. Overall median time to HCV recurrence was 34 months after transplantation. Neither HCV recurrence nor HCV-positive donor status significantly decreased patient and graft survival rates by Kaplan-Meier analysis. However, use of HCV-positive donors reduced the median time of recurrence to 22.9 months compared with 35.7 months after transplantation of HCV-negative livers. Stratification of patients into five subgroups, based on time of recurrence, revealed that early HCV recurrence was associated with significantly increased rates of patient death and graft loss. Donor, recipient, and operative variables that may affect OLT outcome were analyzed. On univariate analysis, recipient age, serum creatinine, donor length of hospital stay, donor female gender, United Network for Organ Sharing (UNOS) status of recipient, and presence of hepatocellular cancer affected the outcome of OLT. Elevation of pretransplant HCV RNA was associated with an increased risk of graft loss. Of 15 variables considered by multivariate Cox regression analysis, recipient age, UNOS status, donor gender, and log creatinine were simultaneous significant predictors for patient survival. Simultaneously significant factors for graft failure included log creatinine, log alanine transaminase, log aspartate transaminase, UNOS status, donor gender, and warm ischemia time. These variables were therefore entered into prognostic models for patient and graft survival. CONCLUSION: The earlier the recurrence of HCV, the greater the impact on patient and graft survival. The use of HCV-positive donors may accelerate HCV recurrence, and they should be used judiciously. Patient survival at the time of transplantation is predicted by donor gender, UNOS status, serum creatinine, and recipient age. Graft survival is affected by donor gender, warm ischemia time, and pretransplant patient condition. The authors' current survival prognostic models require further multicenter validation.

Adult↗
PubMed2006

Risk stratification for survival and leukemic transformation in essential thrombocythemia: a single institutional study of 605 patients.

Unlike the case with thrombosis, prognostic models for survival and leukemic transformation (LT) in essential thrombocythemia (ET) are not available. Among 605 patients with ET seen at our institution and followed for a median of 84 months, 155 died and LT was documented in 20 patients (3.3%). In a multivariable analysis, hemoglobin level below normal (females<120 g/l; males<135 g/l) was identified as an independent risk factor for both inferior survival and LT. Additional risk factors for survival included age > or =60 years, leukocyte count> or =15 x 10(9)/l, smoking, diabetes mellitus and thrombosis. For LT, platelet count> or =1000 x 10(9)/l but not cytoreductive therapy was flagged as an additional independent risk factor. In fact, four of the 20 patients (20%) with LT were untreated previously. We used the above information to construct prognostic models that effectively discriminated among low-, intermediate- and high-risk groups with respective median survivals of 278, 200 and 111 months (P<0.0001), and LT rates of 0.4, 4.8 and 6.5% (P=0.0009) respectively. Presence of JAK2V617F did not impact either survival or LT and mutational frequency was similar among the different risk groups.

Adolescent↗
PubMed2026

Integrative single-cell and genomic analysis reveals NMB as a driver of metastatic adaptation in esophageal squamous cell carcinoma via metabolic rewiring and immune evasion.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) has high mortality, and metastasis is the leading cause of patient death. Neuromedin B (NMB) promotes tumor development in various cancers, yet its role in ESCC metastasis remains unclear. METHODS: We integrated single-cell transcriptomic data from matched primary and metastatic ESCC lesions (GSE309392) with bulk transcriptomic cohorts from TCGA and GSE53624. In silico gene perturbation, ligand-receptor communication analysis, and single-cell prognostic model construction were performed, followed by functional validation through siRNA-mediated NMB knockdown in TE-1 and KYSE30 cell lines. RESULTS: NMB was identified as a key gene enriched in metastatic ESCC lesions, and its high expression was associated with coordinated upregulation of oxidative phosphorylation pathway genes and aldo-keto reductase family antioxidant enzymes (AKR1C1, AKR1C2, AKR1B10). Genomic analysis revealed that NMB-high tumors carried a higher clonal mutation burden and a markedly increased frequency of NFE2L2 activating mutations (23% vs. 8%, P = 0.04). In silico knockout and correlation analysis identified AKR1C1 as a downstream effector of NMB. NMB expression was negatively correlated with CD8+ T cell and activated NK cell infiltration. CellChat analysis revealed communication between NMB-positive cells and monocytes via the TGM2-ADGRG1 axis, and specifically detected IFNG signaling. In the single-cell prognostic model, NMB-positive cells accounted for 50% of the high-risk group but only 20% of the low-risk group. TCGA-based survival analysis demonstrated that high NMB expression was associated with shorter overall survival (HR = 2.98, P = 0.03). In vitro NMB-targeted RNA interference markedly inhibited proliferation, colony formation, and migration in TE-1 and KYSE30 cells. CMap screening identified the endothelin-PDE5-cGMP axis as a potential therapeutic target. CONCLUSION: NMB serves as a key driver of metastatic adaptation in ESCC, conferring a survival advantage to tumor cells during metastatic colonization through genomic evolution and immune remodeling, with metabolic adaptation as a downstream consequence of genomic alterations.

NMB↗
PubMed2025

Transcriptome-wide analysis reveals potential roles of CFD and ANGPTL4 in fibroblasts regulating B cell lineage for extracellular matrix-driven clustering and novel avenues for immunotherapy in breast cancer.

BACKGROUND: The remodeling of the extracellular matrix (ECM) plays a pivotal role in tumor progression and drug resistance. However, the compositional patterns of ECM in breast cancer and their underlying biological functions remain elusive. METHODS: Transcriptome and genome data of breast cancer patients from TCGA database was downloaded. Patients were classified into different clusters by using non-negative matrix factorization (NMF) based on signatures of ECM components and regulators. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify core genes related to ECM clusters. Additional 10 independent public cohorts including Metabric, SCAN_B, GSE12276, GSE16446, GSE19615, GSE20685, GSE21653, GSE58644, GSE58812, and GSE88770 were collected to construct Training or Testing cohort, following machine learning calculating ECM correlated index (ECI) for survival analysis. Pathway enrichment and correlation analysis were used to explore the relationship among ECM clusters, ECI and TME. Single-cell transcriptome data from GSE161529 was processed for uncovering the differences among ECM clusters. RESULTS: Using NMF, we identified three ECM clusters in the TCGA database: C1 (Neuron), C2 (ECM), and C3 (Immune). Subsequently, WGCNA was employed to pinpoint cluster-specific genes and develop a prognostic model. This model demonstrated robust predictive power for breast cancer patient survival in both the Training cohort (n&#x2009;=&#x2009;5,392, AUC&#x2009;=&#x2009;0.861) and the Testing cohort (n&#x2009;=&#x2009;1,344, AUC&#x2009;=&#x2009;0.711). Upon analyzing the tumor microenvironment (TME), we discovered that fibroblasts and B cell lineage were the core cell types associated with the ECM cluster phenotypes. Single-cell RNA sequencing data further revealed that angiopoietin like 4 (ANGPTL4)+ fibroblasts were specifically linked to the C2 phenotype, while complement factor D (CFD)+ fibroblasts characterized the other ECM clusters. CellChat analysis indicated that ANGPTL4+ and CFD+ fibroblasts regulate B cell lineage via distinct signaling pathways. Additionally, analysis using the Kaplan-Meier Plotter website showed that CFD was favorable for immunotherapy response, whereas ANGPTL4 negatively impacted the outcomes of cancer patients receiving immunotherapy. CONCLUSION: We identified distinct ECM clusters in breast cancer patients, irrespective of molecular subtypes. Additionally, we constructed an effective prognostic model based on these ECM clusters and recognized ANGPTL4+ and CFD+ fibroblasts as potential biomarkers for immunotherapy in breast cancer.

Humans↗
PubMed2001

Predictors of mortality and resource utilization in cirrhotic patients admitted to the medical ICU.

BACKGROUND AND OBJECTIVE: Cirrhotic patients admitted to the medical ICU (MICU) are associated with high mortality rates and high resource utilization. This study identifies specific predictors of increased mortality and resource utilization and uses them to develop and validate prognostic models in cirrhotic patients admitted to the MICU. METHODS: Cirrhotic patients admitted to the MICU were identified from the Critical Care Section database (January 1993 to October 1998). Clinical data were extracted from chart review including hospital course variables, mortality, and length of stay (LOS). Total cost per case (TCPC) was obtained from the Transition System INC: Multivariate logistic and linear regression analyses identified the independent predictors of increased mortality and resource utilization used for model building (MB) and model validation (MV). RESULTS: A total of 582 cases were randomized to the MB and MV groups. Each group contained 240 cases after exclusion criteria were applied. The MICU mortality rate was 36.6%, and the in-hospital mortality rate was 49.0%. Acute physiology, age, and chronic health evaluation (APACHE) III score (odds ratio [OR], 4.7; 95% confidence interval [CI], 2.70 to 8.16; p < 0.001), mechanical ventilation (OR, 4.57; 95% CI, 2.35 to 8.34); p < 0.001), and the use of pressors (OR, 7.57; 95% CI, 4.35 to 13.18; p < 0.001) were independent predictors of MICU mortality. APACHE III score (OR, 4.96; 95% CI, 2.97 to 8.29; p < 0.001), the use of pressors (OR, 6.55; 95% CI, 3.66 to 11.72; p < 0.001), and acute renal failure (ARF) (OR, 4.31; 95% CI, 2.41 to 7.71; p < 0.001) were independent predictors of in-hospital mortality. Increased LOS in the MICU was associated with mechanical ventilation, ARF, bronchoscopy, bacteremia, use of pressors, transjugular intrahepatic portosystemic shunt (TIPS), and never received cardiopulmonary resuscitation (CPR) (p < 0.005). Source of admission, platelet transfusion, bacteremia, pneumonia, and never received CPR were independently associated with increased total LOS (p < 0.001). Mechanical ventilation, platelet transfusion, bronchoscopy, TIPS, sepsis, and never received CPR were independent predictors of increased TCPC (p < 0.001). CONCLUSION: Simple prognostic models for mortality and resource utilization have been developed for cirrhotic patients admitted to the MICU.

APACHE↗
PubMed2006

Transcriptome profiling in clinical breast cancer: from 3D culture models to prognostic signatures.

Early detection has been one of the most effective strategies to control the growing cancer burden. The power of earlier detection has been demonstrated by the impact of pap-smear, mammography, and PSA tests on cancer patient treatment and survival. These tests benefit patients independent of their genetic background or race. However, in many cases, we are still losing the battle against cancer because patients that initially presented with low-grade disease progress rapidly to aggressive forms of the disease. As of yet, we have limited means to predict a particular patient's fate or to specifically treat subtypes of cancer. A combination of earlier detection and targeted therapy, based on information from transcriptome analysis, could be a powerful ally in this battle. The theme of this review article is to briefly summarize innovative strategies using three-dimensional (3D) cell cultures of human mammary epithelial cells to predict clinical outcome in breast cancer. This strategy has the potential to further enhance our understanding of breast cancer biology and to contribute to the identification of biologically significant bio-markers that are also useful drug targets.

Biomarkers, Tumor↗
PubMed1997

Angioarchitecture associated with haemorrhage in cerebral arteriovenous malformations: a prognostic statistical model.

The overall haemorrhagic risk of a cerebral arteriovenous malformation (cAVM) is 2-4% per year. However, the individual risk of haemorrhage has never been determined. This study was undertaken to assess the haemorrhage risk of an individual cAVM. Neuroangiographic findings of 160 cAVM were analysed retrospectively, looking at 30 angiographic features. A statistical model was established by logistic regression to evaluate the risk of an individual cAVM. We statistically correlated 15 parameters with the haemorrhage risk. The statistical model includes five independent parameters. Four are unfavourable: exclusively deep drainage, venous stenoses, venous reflux and the radio of afferent to efferent systems; one is favourable: venous recruitment. This model quantifies the individual risk of haemorrhage. When this model is applied to the population studied, the error rate is 5%. This model can contribute to therapeutic strategy, and to a better understanding of the natural history of cAVM.

Adolescent↗
PubMed1983

A variable risk clinical prognostic compartmental model.

A model for predicting the occurrence of disease endpoints from a knowledge of baseline variables and intermediate events is described and illustrated with numerical examples. Maximum likelihood equations are developed and maximum likelihood estimates of coefficients in risk functions of variables included in a stepwise upward procedure are applied to a small set of data for illustrative purposes.

Adult↗
PubMed2004

Penalized maximum likelihood estimation to directly adjust diagnostic and prognostic prediction models for overoptimism: a clinical example.

BACKGROUND AND OBJECTIVE: There is growing interest in developing prediction models. The accuracy of such models when applied in new patient samples is commonly lower than estimated from the development sample. This may be because of differences between the samples and/or because the developed model was overfitted (too optimistic). Various methods, including bootstrapping techniques exist for afterwards shrinking the regression coefficients and the model's discrimination and calibration for overoptimism. Penalized maximum likelihood estimation (PMLE) is a more rigorous method because adjustment for overfitting is directly built into the model development, instead of relying on shrinkage afterwards. PMLE has been described mainly in the statistical literature and is rarely applied to empirical data. Using empirical data, we illustrate the use of PMLE to develop a prediction model. METHODS: The accuracy of the final PMLE model will be contrasted with the final models derived by ordinary stepwise logistic regression without and with shrinkage afterwards. The potential advantages and disadvantages of PMLE over the other two strategies are discussed. RESULTS: PMLE leads to smaller prediction errors, provides for model reduction to a user-defined degree, and may differently shrink each predictor for overoptimism without sacrificing much discriminative accuracy of the model. CONCLUSION: PMLE is an easily applicable and promising method to directly adjust clinical prediction models for overoptimism.

Bias↗
PubMed2026

Big data in multiple sclerosis.

PURPOSE OF REVIEW: This review summarizes recent key advancements in multiple sclerosis (MS) achieved through the utilization of big data from diverse sources and advanced analytical techniques. RECENT FINDINGS: Real-world evidence (RWE) derived from MS big data has significantly enhanced treatment strategies, redefined the concept of disease progression, refined prognostic models, and facilitated personalized medicine. RWE has highlighted the long-term benefits of early intensive treatment compared to escalation strategies, the unfavorable risk profile associated with treatment de-escalation and the importance of managing treatments during pregnancy. Additionally, it has revealed similarities and differences in the effectiveness and safety of specific high-efficacy therapies, as well as key predictors for switching treatments. RWE has also emphasized the central role of progression independent of relapse activity as a significant driver of disability and predictor of unfavorable long-term outcomes in both adult and pediatric onset MS. A data-driven approach utilizing artificial intelligence and big data has established a comprehensive framework for understanding the disease's evolution. Multimodal big data frameworks - encompassing clinical data, MRI, genomics, biomarkers, and app-based metrics - have demonstrated their ability to enhance diagnostic performance and risk stratification in MS. SUMMARY: Big data approaches are transforming MS research and clinical practice by providing stronger RWE to guide therapeutic decision-making, refining models of disease progression, and developing more precise prognostic tools.

Humans↗