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BACKGROUND: The variety of therapeutic associations in first-line treatment of advanced and metastatic renal cell cancer (mRCC) illustrates the complexity of toxicity management that can affect patients' health-related quality of life (HRQOL). Electronic monitoring applications have become part of the daily practice of providers in following up with people with cancer. OBJECTIVES: This article offers perspectives for electronic patient-reported outcome measures (ePROMs) in clinical practice to enhance symptom management and HRQOL for patients with mRCC. METHODS: A narrative review combines the results of searches conducted on MEDLINE®, Embase®, and Cochrane Library for articles that identify therapeutic combinations used in treating mRCC, extract HRQOL data, and evaluate the benefits of ePROMs. FINDINGS: ePROMs can be adapted to the toxicity and symptom specificities encountered in patients with mRCC undergoing front-line treatment. Combined with multidimensional HRQOL indicators, these tools can improve symptom management and provide early support adapted to the patient's needs. [ABSTRACT FROM AUTHOR]

Aims: The hyperglycaemic stress induces the release of inflammatory proteins such as S100A12, one of the endogenous ligands of the receptors for advanced glycation end products (RAGE). Chronic activation of RAGE has multiple deleterious effects in target tissues such as the heart and the vessels by promoting oxidative stress, inflammation by the release of cytokines, macrophages infiltration, and vascular cell migration and proliferation, causing ultimately endothelial cell and cardiomyocyte dysfunction. The aim of our study was to investigate the prognostic value of circulating S100A12 beyond established cardiovascular risk factors (CVRF) for heart failure (HF) and major adverse cardiovascular events (MACE) in a cohort of patients with type 2 diabetes. Methods and results: Serum S100A12 concentrations were measured at baseline in 1345 type 2 diabetes patients (58% men, 64 ± 11 years) recruited in the SURDIAGENE prospective cohort. Endpoints were the occurrence of acute HF requiring hospitalization (HHF) and MACE. We used a proportional hazard model adjusted for established CVRF (age, sex, duration of diabetes, estimated glomerular filtration rate, albumin/creatinine ratio, history of coronary artery disease) and serum S100A12. During the median follow‐up of 84 months, 210 (16%) and 505 (38%) patients developed HHF and MACE, respectively. Baseline serum S100A12 concentrations were associated with an increased risk of HHF [hazard ratio (HR) (95% confidence interval) 1.28 (1.01–1.62)], but not MACE [1.04 (0.90–1.20)]. After adjustment for CVRF, S100A12 concentrations remained significantly associated with an increased risk of HHF [1.29 (1.01–1.65)]. In a sub‐analysis, patients with high probability of pre‐existing HF [N terminal pro brain natriuretic peptide (NT‐proBNP) >1000 pg/mL, n = 87] were excluded. In the remaining 1258 patients, the association of serum S100A12 with the risk of HHF tended to be more pronounced [1.39 (1.06–1.83)]. When including the gold standard HF marker NT‐proBNP in the model, the prognostic value of S100A12 for HHF did not reach significance. Youden method performed at 7 years for HHF prediction yielded an optimal cut‐off for S100A12 concentration of 49 ng/mL (sensitivity 53.3, specificity 52.2). Compared with those with S100A12 ≤ 49 ng/mL, patients with S100A12 > 49 ng/mL had a significantly increased risk of HHF in the univariate model [HR = 1.58 (1.19–2.09), P = 0.0015] but also in the multivariate model [HR = 1.63 (1.23–2.16), P = 0.0008]. After addition of NT‐proBNP to the multivariate model, S100A12 > 49 ng/mL remained associated with an increased risk of HHF [HR = 1.42 (1.07–1.90), P = 0.0160]. However, the addition of S100A12 categories on top of multivariate model enriched by NT‐pro BNP did not improve the ability of the model to predict HHF (relative integrated discrimination improvement = 1.9%, P = 0.1500). Conclusions: In patients with type 2 diabetes, increased serum S100A12 concentration is independently associated with risk of HHF, but not with risk of MACE. Compared with NT‐proBNP, the potential clinical interest of S100A12 for the prediction of HF events remains limited. However, S100A12 could be a candidate for a multimarker approach for HF risk assessment in diabetic patients. [ABSTRACT FROM AUTHOR]

Background: Heart failure (HF) is a growing complication and one of the leading causes of mortality in people living with type 2 diabetes (T2D). Among the possible causes, the excess of red meat and the insufficiency of vegetables consumption are suspected. Such an alimentation is associated with nutritional biomarkers, including trimethylamine N-oxide (TMAO) and its precursors. Here, we aimed to study these biomarkers as potential prognostic factors for HF in patients with T2D. Methods: We used the SURDIAGENE (SURvival DIAbetes and GENEtics) study, a large, prospective, monocentric cohort study including 1468 patients with T2D between 2001 and 2012. TMAO and its precursors (trimethylamine [TMA], betaine, choline, and carnitine) as well as thio-amino-acids (cysteine, homocysteine and methionine) were measured by liquid chromatography-tandem mass spectrometry. The main outcome was HF requiring Hospitalization (HFrH) defined as the first occurrence of acute HF leading to hospitalization and/or death, established by an adjudication committee, based on hospital records until 31st December 2015. The secondary outcomes were the composite event HFrH and/or cardiovascular death and all-cause death. The association between the biomarkers and the outcomes was studied using cause-specific hazard-models, adjusted for age, sex, history of coronary artery disease, NT-proBNP, CKD-EPI-derived eGFR and the urine albumin/creatinine ratio. Hazard-ratios (HR) are expressed for one standard deviation. Results: The data of interest were available for 1349/1468 of SURDIAGENE participants (91.9%), including 569 (42.2%) women, with a mean age of 64.3 ± 10.7 years and a median follow-up of 7.3 years [25th–75th percentile, 4.7–10.8]. HFrH was reported in 209 patients (15.5%), HFrH and/or cardiovascular death in 341 (25.3%) and all-cause death in 447 (33.1%). In unadjusted hazard-models, carnitine (HR = 1.20, 95% CI [1.05; 1.37]), betaine (HR = 1.34, [1.20; 1.50]), choline (HR = 1.35, [1.20; 1.52]), TMAO (HR = 1.32, [1.16; 1.50]), cysteine (HR = 1.38, [1.21; 1.58]) and homocysteine (HR = 1.28, [1.17; 1.39]) were associated with HFrH, but not TMA and methionine. In the fully adjusted models, none of these associations was significant, neither for HFrH nor for HFrH and/or CV death, when homocysteine only was positively associated with all-cause death (HR = 1.16, [1.06; 1.27]). Conclusions: TMAO and its precursors do not appear to be substantial prognosis factors for HFrH, beyond usual cardiac- and kidney-related risk factors, whereas homocysteine is an independent risk factor for all-cause death in patients with T2D. [ABSTRACT FROM AUTHOR]

Proliferative glomerulonephritis (GN) with monoclonal immunoglobulin deposits (PGNMIDs) is a recently described entity among the spectrum of monoclonal gammopathy of renal significance (MGRS). The disease is renal limited and manifests with chronic glomerular disease, altered renal function and albuminuria, sometimes in the nephrotic range. Acute nephritic syndrome is rare. PGNMID occurs mostly in the sixth decade, but it may affect young adults. Histologically, PGNMID is characterized predominantly by membranoproliferative GN and less frequently by diffuse endocapillary GN, mesangioproliferative GN or atypical membranous GN. Immunofluorescence and electron microscopic studies are the cornerstone of diagnosis, showing granular deposits involving glomeruli only, and composed of monotypic immunoglobulin G (IgG), with a single heavy chain subclass (most commonly IgG3) and light chain (LC) restriction (usually κ), admixed with complement deposits. PGNMID variants with monotypic LC-only, IgA or IgM deposits are uncommon. Ultrastructurally, deposits are amorphous with predominant subendothelial and mesangial distribution. PGNMID should be distinguished from type 1 cryoglobulinemic GN and immunotactoid GN, which share some common pathological features. Contrary to other MGRS lesions, the rate of detection of the nephrotoxic monoclonal Ig in the serum or urine, and of an abnormal bone marrow B-cell clone, is only ∼30%. Renal prognosis is poor, with progression to end-stage renal disease in 25% of patients within 30 months and frequent early recurrence on the renal allograft. The pathophysiology of PGNMID is unclear and its treatment remains challenging. However, recent studies indicate that clone-targeted chemotherapy may significantly improve renal outcomes, opening future perspectives for the management of this rare disease. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Tenascin-C (TN-C) is an extracellular matrix glycoprotein highly expressed in inflammatory and cardiovascular (CV) diseases. Serum TN-C has not yet been specifically studied in individuals with type 2 diabetes, a condition associated with chronic low-grade inflammation and increased CV disease risk. In this study, we hypothesised that elevated serum TN-C at enrolment in participants with type 2 diabetes would be associated with increased risk of death and major adverse CV events (MACE) during follow-up. Methods: We used a prospective, monocentric cohort of consecutive type 2 diabetes participants (the SURDIAGENE [SUivi Rénal, DIAbète de type 2 et GENEtique] cohort) with all-cause death as a primary endpoint and MACE (CV death, non-fatal myocardial infarction or stroke) as a secondary endpoint. We used a proportional hazard model after adjustment for traditional risk factors and the relative integrated discrimination improvement (rIDI) to assess the incremental predictive value of TN-C for these risk factors. Results: We monitored 1321 individuals (58% men, mean age 64 ± 11 years) for a median of 89 months. During follow-up, 442 individuals died and 497 had MACE. Multivariate Cox analysis showed that serum TN-C concentrations were associated with an increased risk of death (HR per 1 SD: 1.27 [95% CI 1.17, 1.38]; p < 0.0001) and MACE (HR per 1 SD: 1.23 [95% CI 1.13, 1.34]; p < 0.0001). Using TN-C concentrations on top of traditional risk factors, prediction of the risk of all-cause death (rIDI: 8.2%; p = 0.0006) and MACE (rIDI: 6.7%; p = 0.0014) improved significantly, but modestly. Conclusions/interpretation: In individuals with type 2 diabetes, increased serum TN-C concentrations were independently associated with death and MACE. Therefore, including TN-C as a prognostic biomarker could improve risk stratification in these individuals. [ABSTRACT FROM AUTHOR]