High Risk Of Progression Research Articles

Recommendations for Research to Develop a Patient‐Centered Clinical Follow‐Up Protocol for Oral Epithelial Dysplasia

ABSTRACTOral epithelial dysplasia (OED) is the primary histological marker for assessing the progression of oral potentially malignant disorders (OPMDs) to cancer. Despite challenges in grading and low inter‐pathologist reproducibility, OED severity remains the key predictor of malignant transformation. However, globally accepted guidelines for OED monitoring are lacking, despite calls for individualized management based on host and lesion characteristics. The proposed research protocol involves acquiring high‐quality intraoral images, assessing oral hygiene and periodontal status, eliminating chronic mechanical irritation and Candida infections, and applying adjunctive diagnostic methods like toluidine blue staining, optical evaluation, and brush cytology. Tailored follow‐up regimens based on individual risk assessments are emphasized, with frequent monitoring for high‐grade dysplasia or patients at higher risk of progression. Therefore, effective OED management should consider the patient's immune status, dietary habits, and oral microbiota, aiming to develop personalized treatment strategies that optimize patient‐centered care.

Identification of Genomic Biomarkers of Disease Progression and Survival in Primary CNS Lymphoma.

The determination of the genetic subtypes of primary CNS lymphoma (PCNSL) and their relationship to differential chemo-immunotherapeutic response has not been established. There is a particular need for genomic biomarkers that identify patients with newly-diagnosed PCNSL at high risk of early progression and death. We applied targeted next-generation sequencing for detection of recurrent single nucleotide variants, copy number alterations and zygosity abnormalities in diagnostic specimens from 78 PCNSL patients treated with a standard methotrexate-based regimen, to identify prognostically significant molecular subgroups. All patients received induction immunochemotherapy and 44 proceeded to dose-intensive consolidation. Genomic aberrations at four loci were associated with 91% of lymphoma progression events and all 15 deaths: (1) chromosome 6p copy-neutral loss of heterozygosity (CN-LOH) or focal homozygous deletion (HD) at 6p21.3, and mutations of tumor suppressor genes (2) BTG1, (3) ETV6 and (4) TP53. Cox regression multivariate analysis demonstrated a high risk of progression in patients with aberrations at these loci. Genomic aberrations at these loci were also associated with significantly shorter survival. Lower expression of HLA-DR was associated with 6p CN-LOH/6p21.3 HD and inferior prognosis. These genomic aberrations identify a high-risk molecular subgroup that may inform risk stratification in PCNSL. Further elucidation of the mechanisms of therapeutic resistance associated with the high-risk genetic phenotype is requisite to facilitate precision medicine and progress in therapy.

Incidence and predictors of clinical failure after early treatment for mild-to-moderate COVID-19 in high-risk individuals: A multicentric cohort study.

To estimate the risk of COVID-19-related hospitalization and death (CovH/D), among high-risk individuals early treated for COVID-19 and to identify associated factors. A multicenter cohort of 12,475 high-risk outpatients (female 50.2%, median age 70 years [IQR 57-80], fully vaccinated 79.1%, immunocompromised 23.2%) treated with monoclonal antibodies or antivirals for mild-to-moderate COVID-19 (March 2021-May 2023) in the Lazio region, Italy. The unadjusted risk of CovH/D by Day 30 was 3.08% (95% CI 2.7%-3.4%). By means of logistic regression models, which included a specific set of potential confounders for each exposure of interest, we observed a higher risk for the elderly, unvaccinated and immunocompromised participants. Using the "Delta period" as a reference, a decreased risk was observed for Omicron waves. Despite the administration of COVID-19 early treatment and the decreasing risk of CovH/D across the calendar periods, the elderly, the unvaccinated and the immunocompromised people remain at high risk of clinical progression.

TMOD-05. GLIOMA-ASSOCIATED OLIGODENDROCYTE PROGENITOR CELLS’ DYNAMIC PATTERNS SUGGEST FUNCTIONAL ADAPTATIONS DURING GLIOMA PROGRESSION IN A UNIQUE MOUSE MODEL

Abstract Gliomas account for more than one-third of brain tumors in children, with high fatality rate despite aggressive adjuvant treatment. Two-thirds of survivors suffer from health conditions due to the toxicity of conventional therapies. Notably, gliomas with the BRAFV600E mutation, occurring in ~20% of all glioma cases, are difficult to treat and have a high risk for progression, especially when combined with CDKN2A deletion. The mechanisms for glioma progression remain unclear and unraveling them could lead to therapies that inhibit glioma progression, preventing high-grade gliomas. Objectives: To gain mechanistic insights into glioma progression and exploit therapeutically for preventing progression. We developed two novel mouse models for BRAFV600E mutant progressive gliomas – one at high genetic risk for progression and one at intermediate genetic risk for progression. Expression of genetic alterations were induced by injecting compound transgenic mice with adenovirus-Cre. Our new mouse models therefore more faithfully recapitulated the genetic changes accompanying glioma formation and progression from low- to high-grade than earlier mouse models which used the RCAS system to overexpress the oncogene (PMCID: PMC11112369 ). Glioma formation was followed non-invasively by magnetic resonance imaging. Single cell RNA sequencing and spatial transcriptomics were performed and immunofluorescence was used for validation (PMCID: PMC10619673 ). We present new data showing that animal subject survival is significantly shorter in the high risk model than in the low risk model. Our two models with distinct latency can be used for preclinical studies and studies of the changes associated with progression, including in the glioma microenvironment. Analyses revealed temporal, functional, and spatial changes in glioma-associated oligodendrocyte progenitor cells (GA-OPCs) at distinct stages (initiation, expansion, progression) and grades. Our findings that GA-OPCs closely interact with glioma cells and their morphological transformation as gliomas progress, suggest changing functions, including potential roles in phagocytosis and immunomodulation. Understanding the unclear role of glioma microenvironment OPCs in promoting glioma progression could reveal an Achilles heel for targeted therapies.

Use of Artificial Intelligence to Predict Outcomes in Mild Aortic Valve Stenosis

Abstract Background and Aims Aortic stenosis (AS) is a common and progressive disease which, if left untreated, results in increased morbidity and mortality. Monitoring and follow-up care can be challenging due to significant variability in disease progression. This study aimed to develop machine learning models to predict the risks of disease progression and mortality in patients with mild aortic stenosis. Methods A comprehensive database including 9611 patients with serial transthoracic echocardiograms was collected from a single institution across 3 clinical sites. The dataset included parameters from echocardiograms, electrocardiograms, laboratory values, and diagnosis codes. Data from a single clinical site was preserved as an independent test group. Machine learning models were trained to identify progression to severe stenosis and all-cause mortality and tested in their performance for endpoints at 2 and 5 years. Results In the independent test group, the AS progression model differentiated those with progression to severe AS within 2 and 5 years with an area under the curve (AUC) of 0.86 for both. The feature of greatest importance was aortic valve mean gradient, followed by other valve hemodynamic measurements including valve area and dimensionless index. The mortality model identified those with mortality within 2 years and 5 years with an AUC of 0.84 and 0.87, respectively. Smaller reduced-input validation models had similarly robust findings. Conclusions Machine learning models can be used in patients with mild AS to identify those at high risk for disease progression and mortality. Implementation of such models may facilitate real-time, patient-specific follow-up recommendations.

Low antiviral uptake of nirmatrelvir/ritonavir and molnupiravir in adult patients with COVID-19 in Taiwan in 2022.

Antivirals are effective in reducing hospitalisation and death in mild-to-moderate coronavirus 2019 (COVID-19) patients. We estimated the antiviral uptake of nirmatrelvir/ritonavir and molnupiravir in adult patients with a syndrome coronavirus 2 (SARS-CoV-2) infection during the Emergency Use Authorization (EUA) period in Taiwan. A retrospective cohort study was conducted in Taiwan between January 2022 and December 2022. Patients aged ≥18 years with a SARS-CoV-2 infection were included from the Taipei Medical University Clinical Research Database (TMUCRD) and stratified in three risk groups according to World Health Organization criteria. In total, 96 398 COVID-19 patients (mean age 46.7 ± 17.7 years, 45.8% male) were included. Of these patients 69.8% were classified as low risk, 29.8% as moderate risk, and 0.4% as high risk for progression to severe COVID-19. Nirmatrelvir/ritonavir was prescribed in 5.1% of the COVID-19 patients (low risk = 1.0%, moderate risk = 14.3%, high risk = 17.6%). Molnupiravir was prescribed in 1.9% of the COVID-19 patients (low risk = 0.1%, moderate risk = 5.8%, high risk = 6.9%). Nirmatrelvir/ritonavir and molnupiravir were poorly used in the treatment of adult COVID-19 patients in Taiwan during the pandemic in 2022, especially in moderate-to-high risk groups for progression to severe COVID-19.

Immunomorphological specifcity of HER2-low breast cancer

Assessment of tumor infltrating lymphocytes (TiLs) has been recognized as an additional tool for predicting survival in triple negative (TN) and HER2/neu positive (HER2+) subtypes of breast cancer (BC). Recently, BC, including the above-mentioned subtypes and characterized by low/undefined expression of HER2/neu, has been isolated into a separate group, designated HER2-low BC. The relationship between clinical and morphological parameters of HER2-low breast cancer and infiltration by immunocompetent cells, including tumor associated macrophages (TAM), has not been studied to date. The purpose of the study was to identify significant relationships between the level of subpopulations of immunocompetent cells (Tils + TAM) and the clinical and morphological parameters of HER2-low BC.Material and Methods. The study examined the surgical specimens of 33 patients with HER2-low BC. Visual counting of TILs and assessment (IHC) of the level of T-helpers, T-killers, M1 and M2 macrophages were carried out in intratumor sites and the invasive edge of the primary tumor.Results. The study of mastectomy specimens showed that infiltration of Tils (Me=5 [5; 10] %) was observed in all 33 patients. The level of M2 of macrophages was found to be the highest both in the invasive margin and in the intratumor sites (CD163inv: Me=20 [10; 40] %; CD163c: Me=15 [7; 30] %, respectively). In patients with high (≥20 %) levels of M2 macrophages in the invasive margin, there was also a high level of other immunocompetent cells, and perineural invasion was detected significantly more often (р=0.019).Conclusion. A high level of infiltration by M2 macrophages of the invasive margin is combined with the detection of perineural invasion in primary HER2-low breast cancer, which is one of the predictors of a high risk of progression. In combination with other clinical and morphological parameters, the level of M2 macrophages in HER2-low breast cancer may become another factor in predicting disease prognosis.

Influence of metastatic sites and burden on oncological outcomes in patients progressing to metastatic castration resistant prostate cancer

PurposeMetastatic castration-resistant prostate cancer (mCRPC) patients harbor reduced life expectancy after first-line treatment progression. Currently, no information is available regarding the influence of metastatic sites and osseous burden on progression-free (PFS) and overall survival (OS) of mCRPC patients.MethodsWe relied on the Frankfurt Metastatic Cancer Database of the Prostate (FRAMCAP) database to select patients progressing to mCRPC and stratified them according to lymph node vs. osseous vs. visceral metastatic sites. Moreover, we stratified osseous mCRPC patients regarding the number of metastatic lesions. Endpoints were PFS and OS in uni- and multivariable Cox regression models.ResultsOf 363 patients, 9.4% harbored M1a vs. 78% M1b vs. 12% M1c mCRPC with significantly higher PSA in M1b (9 vs. 22 vs. 8ng/ml). Rates of DeNovo (15% vs. 60% vs. 56%) were significantly lower in the M1a mCRPC group, compared to M1b and M1c (p < 0.001). In PFS analyses, a median of 12.7 vs. 10.1 vs. 15.9 months for M1a vs. M1b vs. M1c mCRPC was observed (p > 0.05). In multivariable Cox regression models, M1c mCRPC was independently at higher risk for progression (hazard ratio [HR]: 5.93, p = 0.048), relative to M1a. Regarding OS, significant differences were observed (p = 0.002), with median OS of 58 vs. 42 vs. 25 months for M1a vs. M1b vs. M1c mCRPC and corresponding HRs of 1.54 (p = 0.11) and 2.76 (p < 0.01). In multivariable models M1c mCRPC was associated with higher risk of death (HR: 3.56, p = 0.049), relative to M1a. No differences were observed after stratification according to number of bone lesions (all p ≥ 0.05).ConclusionM1c mCRPC patients are independently at higher risk for progression and death, while M1a patients harbor best cancer-control outcomes.

Network-based hub biomarker discovery for glaucoma

ObjectiveGlaucoma is an optic neuropathy and the leading cause of irreversible blindness worldwide. However, the early detection of glaucoma remains challenging, as chronic forms of glaucoma remain largely asymptomatic until...

Clinical trajectories of patients with multiple sclerosis from onset and their relationship with serum neurofilament light chain levels.

Serum neurofilament light chain (sNfL) is a biomarker of neuroaxonal destruction that correlates with acute inflammation (AI) in multiple sclerosis (MS). However, in the treatment era, progression without AI is the main driver of long-term disability. sNfL may provide added value in detecting ongoing axonal damage and neurological worsening in patients without AI. We conducted a prospective three-year study on patients with a first MS relapse to evaluate the basal cut-off value predicting early increased disability unrelated to relapses. sNfL levels and AI presence were measured every 6 months during the first year and the Expanded Disability Status Scale (EDSS) was monitored until the third year. Baseline cohorts were stratified by sNfL levels, using a cut-off derived from patients without AI (absence of clinical relapses, new/enlarging T2 lesions, or gadolinium enhancement in magnetic resonance imaging) at year one. Fifty-one patients were included. A sNfL cut-off of 11 pg/mL predicted sustained neurological worsening independent of AI. Patients exceeding this threshold exhibited features of highly active MS (higher proportion of AI, oligoclonal M bands and higher EDSS). Despite AI ablation, sNfL levels persisted elevated and were significantly associated with increased EDSS at baseline and year 3. Patients with low sNfL and concurrent AI (n = 8) experienced relapses in the optic nerve, brainstem, and spinal cord topographies. sNfL elevation may detect patients with increased disability even when AI is controlled. This may reveal mechanisms associated with early axonal degeneration and help identify patients at higher risk of progression.

Development and internal and external validation of a nomogram model for predicting the risk of chronic kidney disease progression in IgA nephropathy patients.

IgA nephropathy (IgAN) is the most common primary glomerular disease in chronic kidney disease (CKD), exhibiting significant heterogeneity in both clinical and pathological presentations. We aimed to explore the risk factors influencing short-term prognosis (≥90 days) and to construct a nomogram model for evaluating the risk of CKD progression in IgAN patients. Clinical and pathological data of patients diagnosed with IgAN through biopsy at two centers were retrospectively collected. Logistic regression was employed to analyze the training cohort dataset and identify the independent predictors to construct a nomogram model based on the final variables. The predictive model was validated both internally and externally, with its performance assessed using the area under the curve (AUC), calibration curves, and decision curve analysis. Out of the patients in the modeling group, 129 individuals (41.6%) did not achieve remission following 3 months of treatment, indicating a high risk of CKD progression. A multivariate logistic regression analysis demonstrated that body mass index, urinary protein excretion, and tubular atrophy/interstitial fibrosis were identified as independent predictors for risk stratification. A nomogram model was formulated utilizing the final variables. The AUCs for the training set, internal validation set, and external validation set were 0.746 (95% confidence intervals (CI) [0.691-0.8]), 0.764 (95% CI [0.68-0.85]), and 0.749 (95% CI [0.65-0.85]), respectively. The validation of the subgroup analysis also demonstrated a satisfactory AUC. This study developed and validated a practical nomogram that can individually predict short-term treatment outcomes (≥90 days) and the risk of CKD progression in IgAN patients. It provides reliable guidance for timely and personalized intervention and treatment strategies.

Discovery of a blood-based miRNA signature that can predict onset of active tuberculosis among household contacts of TB patients

BackgroundNon-sputum based predictive biomarkers capable of identifying individuals with high risk of progression to active tuberculosis (TB) are critical for global TB control. MicroRNAs (miRNAs) are significant regulators involved in TB pathogenesis and hence we aimed to identify a miRNA signature capable of predicting progression to TB disease.MethodsWe compared the differential miRNA expression profile of QuantiFERON supernatants of TB Progressors, defined as healthy household contacts (HHCs) of TB patients, who developed active TB disease during a 2-year follow-up period, and Non-progressors defined as HHCs from the same longitudinal cohort who did not develop TB disease during the entire follow-up period, using the nanostring nCounter platform. Receiver Operator Characteristic (ROC) analysis was performed to evaluate the diagnostic accuracy of the identified miRNA biomarkers, followed by random forest analysis to determine the best predictive model.ResultsWe identified 30 differentially regulated miRNAs between the two groups. Of these, hsa-miR-585-3p and hsa-miR-92a-3p were up-regulated with a maximum fold change of 1.74 and 1.71 respectively, while hsa-miR-223-3p and hsa-miR-451a were down-regulated by −2.05 and −2.04 fold respectively. Random forest analysis revealed that hsa-miR-181a-5p, hsa-miR-204-5p, hsa-miR-197-3p, hsa-miR-92a-3p, hsa-miR-451a, hsa-miR-24-3p, and hsa-miR-487a-3p exhibited 100% accuracy in identifying Progressors. This panel of 7 miRNAs demonstrated excellent diagnostic performance characteristics with 100% sensitivity and specificity.ConclusionWe propose that the identified miRNA signature has the potential to serve as a very useful tool for early identification of individuals who bear the highest risk of progression to TB, so that they can be targeted for timely intervention.

Incident HFpEF and time-dependent changes in markers of LVDD severity in women and men with pre-clinical LVDD

Abstract Background Over time, left ventricular diastolic dysfunction (LVDD) can progress towards heart failure with preserved ejection fraction (HFpEF). Yet, the identification of those at high risk of progression is challenging, and guidance on follow-up or preventive treatment is lacking. Purpose To study the incidence of HFpEF and changes over time in markers of LVDD severity in women and men with pre-clinical LVDD. In addition, we evaluate whether blood pressure and kidney function affect progression of LVDD. Methods We reinvited 146 participants from the HELPFul study (58% women and 42% men) with pre-clinical LVDD after a median follow-up of 4.3 [IQR: 3.9-4.7] years (Figure 1). The follow-up measurements were similar to baseline and encompassed a structured interview, physical examination, blood draw, electrocardiogram and (exercise) echocardiography. We determined HFpEF incidence and report changes over time in cardiovascular risk factors as well as echocardiographic characteristics and biomarkers of LVDD. Additionally, we studied whether changes in blood pressure and kidney function affected LVDD progression using generalized mixed models. LVDD progression was defined as an increase in plasma NT-proBNP levels and HFA-PEFF major functional and morphological abnormalities. All analyses were performed for women and men combined as well as stratified by sex. Results Fifteen (10%) of the 146 participants developed HF of whom 13 had HFpEF (9 women and 4 men) during follow-up. Over time, systolic and diastolic blood pressure levels remained stable while mean kidney function (eGFR) declined from 89±14 to 81±17 mL/min/1.73m2. Median NT-proBNP plasma levels increased from 71 [IQR: 44, 120] to 100 [IQR: 51, 157] pg/mL. The prevalence of major functional abnormalities according to the HFA-PEFF score increased from 84 to 91%, while the prevalence of morphological abnormalities increased from 25% to 39% (Figure 2). A higher systolic blood pressure in women and a higher diastolic blood pressure in men was associated with an increase in NT-proBNP plasma levels over time. Additionally, lower eGFR levels were related to increased NT-proBNP plasma levels over time in both men and women. There was a significant rise in the prevalence of major functional and morphological abnormalities with time, but blood pressure and kidney function did not affect this change over time. Conclusions A small proportion of women and men with preclinical LVDD developed incident HF over a 5-year follow-up period. High blood pressure and reduced kidney function were associated with increased levels of NT-proBNP over time. This highlights the need to further explore cardiorenal protection as a method to prevent HFpEF.Study design and HF outcomesLongitudinal changes in LVDD markers

Progression of aortic stenosis in patients with diabetes mellitus type 2 compared with matched controls

Abstract Background Degenerative aortic stenosis (AS) and diabetes mellitus type 2 (DM) increase with age1,2 and their prevalence is expected to rise. Patients with DM have a higher risk to develop AS3 and the pathophysiological process leading from a normal aortic valve to AS involves factors associated with DM. AS develops over years, but it can evolve more rapidly. There is insufficient knowledge about risk factors for rapid progression in AS and monitoring strategies among patients at high risk for rapid progression. The aim of this project is to evaluate the AS progression towards combined outcome (incident heart failure, death, need for intervention) in patients with type 2 DM compared with matched controls. Methods From the Swedish National Diabetes Register (NDR) we identified all patients with type 2 DM between 01-01-2001- 31-12-2019 and for each patient 5 controls (matched for age, sex, region) from the Swedish Total Population Register. Afterwards we identified a cohort of individuals with AS from these two groups, by linking the NDR with the National Patient Register. The outcomes were: all- cause and cardiovascular mortality, and combined outcome (mortality, hospitalization for heart failure (HF) or aortic valve replacement (AVR)). We used Kaplan Meier survival curves to detect differences in all-cause mortality, cardiovascular mortality, time until AVR and combined outcome between cases and controls. Cox proportional hazards model adjusted for sex, age, obesity, renal failure, hyperparathyroidism, hypertension, hyperlipidemia was used to study the risk difference between the cases and controls for the combined outcome. Results We identified 16 144 individuals with type 2 DM and AS and 31 206 matched controls. The individuals with type 2 DM were predominately men (59% vs 53%), younger (mean age 70.6 vs 71.9), and had more comorbidities. In unadjusted analysis they were hospitalized for HF more often (8.2% vs 6.8%) and more often underwent AVR (surgically) (22.0% vs 19.0%) or transcatheter(6.6% vs 5.0%). Patients with AS and DM had higher all-cause and cardiovascular mortality and faster progression towards death, AVR or hospitalization for HF (see figure 1, A, B, C). The progression to AVR was significant, although the difference was small and not clinically relevant (plot D). In the adjusted model, the patients with AS and DM had 13% higher hazard to have the combined outcome compared with controls (see figure 2). Sex (female), hypertension and hyperlipidemia lowered the hazard for the combined event, while obesity, hyperparathyroidism and renal failure increased the hazard for the combined event. Conclusions Patients with concomitant AS and DM seem to have faster progression towards death (both all-cause and cardiovascular), and heart failure hospitalization or AVR compared with patients with AS without DM. Therefore, it might be appropriate to be more active regarding follow-up and intervention in these patients.Kaplan Meirer curvesForest plot for adjusted Cox model

Single-cell and bulk transcriptomic datasets enable the development of prognostic models based on dynamic changes in the tumor immune microenvironment in patients with hepatocellular carcinoma and portal vein tumor thrombus.

Hepatocellular carcinoma (HCC) patients exhibiting portal vein tumor thrombosis (PVTT) face a high risk of rapid malignant progression and poor outcomes, with this issue being compounded by a lack of effective treatment options. The integration of bulk RNA-sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) datasets focused on samples from HCC patients with PVTT has the potential to yield unprecedented insight into the dynamic changes in the tumor microenvironment (TME) and associated immunological characteristics in these patients, providing an invaluable tool for the reliable prediction of disease progression and treatment responses. scRNA-seq data from both primary tumor (PT) and PVTT cells were downloaded from the Gene Expression Omnibus (GEO) database, while the International Cancer Genome Consortium (ICGC) and Cancer Genome Atlas (TCGA) databases were used to access bulk RNA-seq datasets. scRNA-seq, clustering, GSVA enrichment, mutational profiling, and predictive immunotherapeutic treatment analyses were conducted using these data with the goal of systematically assessing the heterogeneity of PT and PVTT cells and establishing a model capable of predicting immunotherapeutic and prognostic outcomes in patients with HCC. These analyses revealed that PVTT cells exhibited patterns of tumor proliferation, stromal activation, and low levels of immune cell infiltration, presenting with immune desert and immune rejection-like phenotypes. PT cells, in contrast, were found to exhibit a pattern of immunoinflammatory activity. Core PVTT-associated genes were clustered into three patterns consistent with the tumor immune rejection and immune desert phenotypes. An established clustering model was capable of predicting tumor inflammatory stage, subtype, TME stromal activity, and patient outcomes. PVTT signature genes were further used to establish a risk model, with the risk scores derived from this model providing a tool to evaluate patient clinicopathological features including clinical stage, tumor differentiation, histological subtype, microsatellite instability status, and tumor mutational burden. These risk scores were also able to serve as an independent predictor of patient survival outcomes, responses to adjuvant chemotherapy, and responses to immunotherapy. In vitro experiments were used to partially validate the biological prediction results. These results offer new insight into the biological and immunological landscape of PVTT in HCC patients, By utilizing individual patient risk scores, providing an opportunity to guide more effective immunotherapeutic interventional efforts.

Effect of spironolactone wash-out on albuminuria after long-term treatment in individuals with type 2 diabetes and high risk of kidney disease-An observational follow-up of the PRIORITY study.

This study aimed to explore the effect of discontinuation of long-term spironolactone treatment on markers of kidney function in individuals with type 2 diabetes (T2D) at high risk of kidney disease enrolled in the Proteomic prediction and Renin angiotensin aldosterone system Inhibition prevention Of early diabetic nephRopathy In TYpe 2 diabetic patients with normoalbuminuria (PRIORITY) study. An observational study following the nested randomised part of the PRIORITY study was conducted. A total of 115 individuals with T2D and normoalbuminuria but high risk for progression based on urinary proteomics, randomised to daily spironolactone (n = 50) or placebo (n = 65) for a median of 2.5 years, were re-examined approximately 6 weeks after the final visit in the PRIORITY study. Primary endpoint was relative change in geometric mean of urinary albumin-creatinine ratio (UACR) between the final visit in PRIORITY (baseline) and follow-up. Secondary endpoints were change in estimated glomerular filtration rate (eGFR), systolic blood pressure (SBP) and serum potassium. No change in UACR was observed in neither the spironolactone (geometric mean change: 17%; 95% CI -12, 55; p = 0.28) nor the placebo (5%; 95% CI -13, 26; p = 0.63) group at follow-up. No difference in UACR between the groups was observed at follow-up (relative difference in geometric mean: 11%, 95% CI -26, 67; p = 0.60). For eGFR and SBP, an increase after discontinuation of spironolactone was observed, as well as for SBP after placebo discontinuation. Potassium levels were lower after discontinuation of spironolactone, but higher after placebo discontinuation (all p < 0.05). UACR did not change after discontinuation of long-term treatment with spironolactone. However, an increase in eGFR was observed supporting a haemodynamic effect of spironolactone in the kidneys.

Antiviral combination treatment strategies for SARS-CoV-2 infection in immunocompromised patients.

The purpose of this review is to report the available evidence regarding the use of combination regimens of antivirals and/or antibody-based therapy in the treatment of SARS-CoV-2 in immunocompromised patients. Literature search identified 24 articles, excluding single case reports, which included mainly patients with hematological malignancies and/or B-cell depletion. Data were divided based on the timing and reason for administration of combination treatment, that is, early treatment to prevent progression to severe COVID-19 and treatment of prolonged or relapsed infection. We described the treated populations, treatment duration and composition of combination treatment. We briefly addressed new treatment options and we proposed an algorithm for the management of COVID-19 infection in patients affected by hematological malignancies. Combination treatment seems an effective (73-100%) and well tolerated (<5% reported bradycardia, hepatotoxicity, neutropenia) strategy for treating prolonged/relapsed SARS-CoV-2 infections in the immunocompromised host, although its optimal composition and duration cannot be defined based on the currently available evidence. The role of combination treatment as an early treatment strategy for immunocompromised patients at a high risk of progression to severe disease/persistent shedding requires further evidence from comparison with monotherapy, even though high efficacy was reported for combinations of antivirals plus mAbs in case of previous viral variants.

Individualized, cross-validated prediction of future dementia using cognitive assessments in people with mild cognitive symptoms.

We aimed to develop an algorithm to predict the individualized risk of future dementia using brief cognitive tests suitable for primary care. We included 612 participants with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, assessed for at least 4 years or until progression to dementia. A logistic regression model, using cognitive tests as predictors and dementia progression as an outcome, stratified participants into low, intermediate, or high risk. A second model, including 1-year cognitive test changes, was applied to the intermediate group. The models were replicated in 392 SCD/MCI participants from the BioFINDER-1 study. The best two-step model for predicting dementia incorporated Trail Making Test B (attention/executive function), Animal Fluency (verbal fluency), Mini-Mental State Examination (global cognition), and 10-word list recall (memory). The model's positive predictive value in ADNI was 85.8% and negative predictive value was 92.2% versus 62.5% and 95.6%, respectively, in BioFINDER-1. This two-step model accurately predicts individualized dementia risk. To our knowledge, this is the first algorithm for predicting all-cause dementia using a novel two-step model utilizing brief cognitive tests. Applying a validated model including the Trail Making Test B, Animal Fluency, MMSE, Alzheimer's Disease Assessment Scale delayed, and immediate recall can robustly and accurately categorize individuals into low, intermediate, or high risk of dementia progression and can facilitate clinical decision-making and personalized patient care. We created an app that is available for research and educational purposes at https://brainapps.shinyapps.io/PredictAllCauseDementia to provide an individualized risk score for dementia progression.

Trends in the Incidence of Renal Replacement Therapy Due to Rapidly Progressive Glomerulonephritis in Japan, 2006-2021.

Objective Patients with rapidly progressive glomerulonephritis (RPGN) are at a high risk of progression to end-stage kidney disease (ESKD), requiring renal replacement therapy (RRT). The present study examined recent trends in the incidence of RRT due to RPGN in Japan. Methods The number of patients with incident RRT due to RPGN by sex from 2006 to 2021 was extracted from the Japanese Society of Dialysis Therapy Registry. The incidence rates of RRT were calculated for four-year periods with the census population as the denominator. Standardized incidence ratios (SIRs) and age-specific incidence rates were also calculated. Results From 2006 to 2021, the crude number of patients with incident RRT due to RPGN increased by 34% and 58% in men and women, respectively. The SIRs decreased significantly in 2010-2013 relative to the first period (2006-2009) for both men [0.90 (95% confidence interval (CI) 0.85-0.96)] and women [0.92 (0.86-0.99)] but then increased to 1.01 (0.96-1.07) for men and 1.20 (1.13-1.27) for women in 2018-2021. In the older age groups (≥70 years old), age-specific incidence rates initially decreased in 2010-2013 but increased thereafter, peaking in 2018-2021. Conclusion From 2006 to 2021, the number of patients with incident RRT due to RPGN increased, with an increase in the age-specific incidence of RRT due to RPGN in the older age groups (≥70 years old), suggesting that the number of patients with incident RRT due to RPGN will continue to increase as the population ages in Japan.

Predicting Response to Intravesical BCG in High-Risk NMIBC Using an Artificial Intelligence-Powered Pathology Assay: Development and Validation in an International 12-Center Cohort.

There are few markers to identify those likely to recur or progress after treatment with intravesical bacillus Calmette-Guérin (BCG). We developed and validated artificial intelligence-based histologic assays that extract interpretable features from transurethral resection of bladder tumor digitized pathology images to predict risk of recurrence, progression, development of BCG-unresponsive disease, and cystectomy. Pre-BCG resection-derived whole-slide images and clinical data were obtained for high-risk NMIBC cases treated with BCG from 12 centers and were analyzed through a segmentation and feature extraction pipeline. Features associated with clinical outcomes were defined and tested on independent development and validation cohorts. Cases were classified into high or low risk for recurrence, progression, BCG-unresponsive disease, and cystectomy. Nine hundred forty-four cases (development: 303, validation: 641, median follow-up: 36 months) representative of the intended use population were included (high-grade Ta: 34.1%, high-grade T1: 54.8%; carcinoma in situ only: 11.1%, any carcinoma in situ: 31.4%). In the validation cohort, "high recurrence risk" cases had inferior high-grade recurrence-free survival vs "low recurrence risk" cases (HR, 2.08, P < .0001). "High progression risk" patients had poorer progression-free survival (HR, 3.87, P < .001) and higher risk of cystectomy (HR, 3.35, P < .001) than "low progression risk" patients. Cases harboring the BCG-unresponsive disease signature had a shorter time to development of BCG-unresponsive disease than cases without the signature (HR, 2.31, P < .0001). AI assays provided predictive information beyond clinicopathologic factors. We developed and validated AI-based histologic assays that identify high-risk NMIBC cases at higher risk of recurrence, progression, BCG-unresponsive disease, and cystectomy, potentially aiding clinical decision making.