Risk-stratified Approach Research Articles

Association between plasma circulating tumor DNA and the prognosis of esophageal cancer patients: a meta-analysis.

The application of liquid biopsy analysis utilizing circulating tumor DNA (ctDNA) has gained prominence as a biomarker in specific cancer types. Nevertheless, the correlation between ctDNA and the prognostic outcomes of patients with esophageal cancer (EC) remains a subject of controversy. This meta-analysis aims to assess the correlation between ctDNA and the prognosis of EC patients. The authors systematically explored Embase, PubMed, and the Cochrane Database to identify studies reporting on the prognostic value of ctDNA in EC patients before November 2023. The primary outcome involved the determine of associations between ctDNA with overall survival (OS), disease-free survival (DFS)/recurrence-free survival (RFS), as well asprogression-free survival (PFS) among EC patients. Secondary outcomes encompassed a detailed subgroup analysis in the setting of EC, including parameters such as detection time, histological subtypes, treatment modalities, regions, anatomic locations, and detection methods. Publication bias was assessed utilizing Begg's test, Egger's test, and funnel plots. A sensitivity analysis was conducted by systematically excluding individual studies to evaluate the stability of the results. A total of 1203 studies were initially screened, from which 13 studies underwent further analysis, encompassing 604 patients diagnosed with EC. The comprehensive pooled analysis indicated a significant association between the detection of ctDNA and poor OS (HR: 3.65; 95% CI: 1.97-6.75, P <0.001), DFS/RFS (HR: 6.08; 95% CI: 1.21-30.50, P <0.001), and PFS (HR: 2.84; 95% CI: 1.94-4.16, P <0.001). Subgroup analysis showed that ctDNA remained a consistent negative predictor of OS when stratified by different detection time, histological subtypes, regions, anatomic locations, and detection methods. Furthermore, subgroup analysis stratified by regions and study types demonstrated an association between ctDNA detection and poor PFS in EC patients. Our results indicate plasma ctDNA may serve as robust prognostic markers for OS, DFS/RFS, and PFS among EC patients. This finding suggests that plasma ctDNA could offer a highly effective approach for risk stratification and personalized medicine.

Abstract 3510: A radiogenomic approach for triple-negative breast cancer risk stratification

Abstract Background: Triple-negative breast cancer (TNBC) is an aggressive disease that accounts for 15-20% of all breast cancers. Expressions of ER, PR and HER2 receptors are lacking in this disease, and thus targeted therapies are not effective. TNBC has a shorter relapse-free survival, higher metastasis rate and decreased overall survival compared with other breast cancers. However, when undergoing standard treatment, some patients respond well, while others have poor outcome, suggesting TNBC heterogeneity. Early stratification of patients with long versus short survival could identify the subgroup of patients who would not benefit from exposure to toxicity of chemotherapy treatment. Here, we developed a non-invasive radiogenomic approach for TNBC risk stratification. Methods: A transcriptomic-based prognostic gene signature was previously developed using the TCGA-BRCA cohort (n=860). Briefly, LASSO Cox regression model analysis with the ‘glmnet’ R package was used to identify the transcriptomic signature gene-set consisting of 50 genes. We tested this signature to prognosticate overall survival in a Stanford cohort (n=63) and a previously published SCANB cohort (n=604). The patients were stratified into high- and low-risk groups based on the median risk-score. Next, we developed a machine learning model that identified a radiomic feature set to predict the prognostic transcriptomic risk-groups. Radiomic features were extracted from pre-treatment breast MRI. Radiomics features were extracted using PyRadiomics. The model utilized Decision Tree Classifier and LeaveOneOut method was used for cross-validation. Results: The transcriptomic signature low-risk group was significantly associated with improved overall survival in the two TNBC cohorts, with hazard ratios of 0.11 [95% CI: 0.01-0.88] for the Stanford cohort and 0.71 [95% CI: 0.52-0.97] for the SCANB cohort (log-rank p-values p=0.012 and p=0.032, respectively). Including this transcriptomic signature in a multivariate analysis, which adjusted for clinical features (patient age, grade, stage and Ki67%), the transcriptomic prognostic signature remained a significant prognostic factor (p&amp;lt;0.05). The radiomic feature set (consisting of 20 features) predicted the high- and low-risk transcriptomic groups with a mean accuracy of 72.2% and a mean AUROC of 71%. The precision, F1 and recall scores were 67%, 74% and 82%, respectively. In an independent dataset consisting of 116 Stanford TNBC patients, we used this model to predict risk groups based on the MRI radiomics features, and evaluated the prognostic effects of predicted risk groups. The overall survival of the predicted high-risk group was significantly poorer than the predicted low-risk group (p=0.013). Conclusions: We present a prognostic model that can non-invasively stratify TNBC patients for low versus high mortality risk using radiomic features derived from pre-treatment patient MRI data. Citation Format: Humaira Noor, Yuanning Zheng, Adam Mantz, Ryle Zhou, Andrew Kozlov, Wendy B. DeMartini, Shu-tian Chen, Satoko Okamoto, Debra Ikeda, Sarah Mattonen, Sandy Napel, Melinda L. Telli, George Sledge, Allison Kurian, Mina Satoyoshi, Olivier Gevaert, Haruka Itakura. A radiogenomic approach for triple-negative breast cancer risk stratification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3510.

Patient and health professional views on risk-stratified monitoring of immune-suppressing treatment in adults with inflammatory diseases.

To explore the acceptability of an individualised risk-stratified approach to monitoring for target-organ toxicity in adult patients with immune-mediated inflammatory diseases established on immune-suppressing treatment(s). Adults (≥18 years) taking immune-suppressing treatment(s) for at-least six months, and healthcare professionals (HCPs) with experience of either prescribing and/or monitoring immune-suppressing drugs were invited to participate in a single, remote, one-to-one, semi-structured interview. Interviews were conducted by a trained qualitative researcher and explored their views and experiences of current monitoring and acceptability of a proposed risk-stratified monitoring plan. Interviews were transcribed verbatim and inductively analysed using thematic analysis in NVivo. Eighteen patients and 13 HCPs were interviewed. While participants found monitoring of immune-suppressing drugs with frequent blood-tests reassuring, the current frequency of these was considered burdensome by patients and HCPs alike, and to be a superfluous use of healthcare resources. Given abnormalities rarely arose during long-term treatment, most felt that monitoring blood-tests were not needed as often. Patients and HCPs found it acceptable to increase the interval between monitoring blood-tests from three-monthly to six-monthly or annually depending on the patients' risk profiles. Conditions of accepting such a change included: allowing for clinician and patient autonomy in determining an individuals' frequency of monitoring blood-tests, the flexibility to change monitoring frequency if someone's risk profile changed, and endorsement from specialist societies and healthcare providers such as the National Health Service. A risk-stratified approach to monitoring was acceptable to patients and HCPs. Guideline groups should consider these findings when recommending blood-test monitoring intervals.

Pulmonary gangliocytic paraganglioma: An under-recognized mimic of carcinoid tumor

Gangliocytic paragangliomas are rare neoplasms occurring almost exclusively in the ampullary region of the gastrointestinal tract. Although these tumors are not typically considered in the differential diagnosis of primary pulmonary neoplasia, 5 cases of primary pulmonary gangliocytic paragangliomas have been previously reported. Herein we report our experience with 3 additional examples, all referred to our Anatomic Pathology Consultation service. The patients (a 32-year-old man, a 69-year-old woman and a 55-year-old man) each presented with an endobronchial (2 cases) or upper lobe lung mass, ranging from 1.5 to 2.5 cm in maximum dimension. Biopsy and endobronchial debulking specimens demonstrated the classic triphasic morphology of gangliocytic paraganglioma, with epithelial, spindled and ganglion-like cells. By immunohistochemistry, the tumors were positive for keratin, synaptophysin and chromogranin A in the epithelial component, S100 protein and glial fibrillary acidic protein (GFAP) in the Schwannian spindled cells, and synaptophysin in ganglion cells. TTF1 expression was seen in the epithelial components of 2 cases. The Ki-67 labelling index was low (<2%). Primary pulmonary gangliocytic paragangliomas should be distinguished from carcinoid tumors, given the different natural histories and risk stratification approaches for these morphologically similar tumors. Awareness that gangliocytic paraganglioma may occur in the lung and appropriate immunohistochemical studies are key to correct diagnosis.

Predictive value of heart rate variability and electrochemical skin conductance measurements for cardiovascular autonomic neuropathy persistence in type 2 diabetes and prediabetes: A 3-year follow-up study

ObjectiveThe study aimed to explore risk stratification approaches for cardiovascular autonomic neuropathy (CAN) in individuals with prediabetes and type 2 diabetes (T2DM) over a three-year follow-up period. MethodsParticipants underwent evaluations of autonomic function encompassing cardiovascular autonomic reflex tests (CARTs), baroreflex sensitivity (BRS), heart rate variability (HRV) in time domains (standard deviation of all normal RR intervals (SDNN)) and frequency domains (high frequency/low frequency ratio), and electrochemical skin conductance (ESC). The diagnosis of CAN relied on abnormal CART results. Subjects were categorized into 4 groups, based on their assessment of cardiac autonomic function at 3-year follow-up, relative to the presence or absence of CAN at baseline assessment: Persistent absence of CAN; Resolution of CAN; Progression to CAN; and Persistent CAN. ResultsParticipants with T2DM/prediabetes (n = 91/7) were categorized as: Persistent absence of CAN (n = 25), Resolution of CAN (n = 10), Progression to CAN (n = 18), and Persistent CAN (n = 45) groups. The Persistent absence of CAN group showed significant associations with SDNN. The Resolution of CAN group exhibited notable associations with mean HbA1C (follow-up), while the Progression to CAN group displayed a significant link with baseline estimated glomerular filtration rate. The Persistent CAN group demonstrated significant associations with SDNN and Sudoscan CAN risk score. Screening recommendations involve biennial to annual assessments based on risk levels, aiding in CAN detection and subsequent comprehensive and time-intensive autonomic function tests for confirmation. The study's findings offer improved risk categorization approaches for detecting CAN, which has relevance for shaping public health strategies.

Computed tomography-based body composition parameters can predict short-term prognosis in ulcerative colitis patients.

Emerging evidence suggests a potential relationship between body composition and short-term prognosis of ulcerative colitis (UC). Early and accurate assessment of rapid remission based on conventional therapy via abdominal computed tomography (CT) images has rarely been investigated. This study aimed to build a prediction model using CT-based body composition parameters for UC risk stratification. In total, 138 patients with abdominal CT images were enrolled. Eleven quantitative parameters related to body composition involving skeletal muscle mass, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) were measured and calculated using a semi-automated segmentation method. A prediction model was established with significant parameters using a multivariable logistic regression. The receiver operating characteristic (ROC) curve was plotted to evaluate prediction performance. Subgroup analyses were implemented to evaluate the diagnostic efficiency of the prediction model between different disease locations, centers, and CT scanners. The Delong test was used for statistical comparison of ROC curves. VAT density, SAT density, gender, and visceral obesity were significantly statistically different between remission and invalidation groups (all p < 0.05). The accuracy, sensitivity, specificity, and area under the ROC curve (AUC) of the prediction model were 82.61%, 95.45%, 69.89%, and 0.855 (0.792-0.917), respectively. The positive predictive value and negative predictive value were 70.79% and 93.88%, respectively. No significant differences in the AUC of the prediction model were found in different subgroups (all p > 0.05). The predicting model constructed with CT-based body composition parameters is a potential non-invasive approach for short-term prognosis identification and risk stratification. Additionally, VAT density was an independent predictor for escalating therapeutic regimens in UC cohorts. The CT images were used for evaluating body composition and risk stratification of ulcerative colitis patients, and a potential non-invasive prediction model was constructed to identify non-responders with conventional therapy for making therapeutic regimens timely and accurately. • CT-based prediction models help divide patients into invalidation and remission groups in UC. • Results of the subgroup analysis confirmed the stability of the prediction model with a high AUC (all > 0.820). • The visceral adipose tissue density was an independent predictor of bad short-term prognosis in UC.

Laparoscopic Dissection of Lymph Node Station 16-Why and How?

Dissection of para-aortic lymph nodes (Station 16) provides an important prognosticator for patients with gastrointestinal, colorectal, and hepatobiliary cancers.1-4 For example, a positive Station 16 lymph node has been shown to lead to 2-year survival of 3% in patients with pancreas adenocarcinoma, akin to stage IV disease.5,6 Thereby, Station 16 involvement can help with the risk/benefit stratification of the decision to move forward with radical surgery.7-9 Furthermore, it has been shown for gallbladder cancer that involvement of Station 16 cannot necessarily be predicted from the dissection of the hepatoduodenal ligament lymph nodes only.10,11 TECHNIQUE: With the patient in the French position, a complete Kocherization and a Cattel-Braasch maneuver is performed, allowing for visualization of LN station 16b. Station 16b is the inferior border of the station 16 compartment. The left renal vein (LRV) serves as an important landmark to identify the superior border of the dissection comprised by Stations 16a2 and 16b1. Station 16a2 dissection may be associated with a traction injury of the left renal vein or damage of right renal or suprarenal arteries and is dissected if there are specific concerns regarding involvement. While station 16 provides important prognostic information for risk stratification, a strategic and stepwise approach is needed for a safe sampling. This is accomplished by wide mobilization of the duodenum, implementation of thermal fusion to minimize chyle leak, and careful dissection below the left renal vein.

Predictive accuracy of boosted regression model in estimating risk of venous thromboembolism following minimally invasive radical surgery in pharmacological prophylaxis-naïve men with prostate cancer.

Venous thromboembolism (VTE) is a potentially life-threatening but preventable complication after urological surgery. Physicians are faced with the challenges of weighing the risks and benefits of thromboprophylaxis given scanty evidence for or against and practice variation worldwide. The primary objective of the study was to explore the possibility of a risk-stratified approach for thromboembolism prophylaxis following radical prostatectomy. A prospective database was accessed to cross-link venous thromboembolism events in 522 men who underwent minimally invasive prostatectomy between February 2010 and October 2021. A deterministic data linkage method was used to record events through electronic systems. Community Health Index (CHI) numbers were used to identify patients via electronic health records. Patient demographics and clinical characteristics such as age, comorbidities, Gleason staging, and readmission details accrued. VTE within 90days and development of a risk-stratified scoring system. All statistical analysis was performed using R-Statistical Software and the risk of VTE within 90days of surgery was estimated via gradient-boosting decision trees (BRT) model. 1.1% (6/522) of patients developed deep vein thrombosis or pulmonary embolism within 3months post-minimally invasive prostatectomy. Statistical analysis demonstrated a significant difference in the body mass index (p = 0.016), duration of hospital stay (p < 0.001), and number of readmissions (p = 0.036) between patients who developed VTE versus patients who did not develop VTE. BRT analysis found 8 variables that demonstrated relative importance in predicting VTE. The receiver operating curves (ROC) were constructed to assess the discrimination power of a new model. The model showed an AUC of 0.97 (95% confidence intervals [CI]: 0.945,0.999). For predicting VTE, a single-center study is a limitation. The incidence of VTE post-minimally invasive prostatectomy in men who did not receive prophylaxis with low molecular weight heparin is low (1.1%). The proposed risk-scoring system may aid in the identification of higher-risk patients for thromboprophylaxis. In this report, we looked at the outcomes of venous thromboembolism following minimally invasive radical prostatectomy for prostate cancer in consecutive men. We developed a new scoring system using advanced statistical analysis. We conclude that the VTE risk is very low and our model, if applied, can risk stratify men for the development of VTE following radical surgery for prostate cancer.

Severe mental illness: cardiovascular risk assessment and management.

Patients with severe mental illness (SMI) including schizophrenia and bipolar disorder die on average 15-20 years earlier than the general population often due to sudden death that, in most cases, is caused by cardiovascular disease. This state-of-the-art review aims to address the complex association between SMI and cardiovascular risk, explore disparities in cardiovascular care pathways, describe how to adequately predict cardiovascular outcomes, and propose targeted interventions to improve cardiovascular health in patients with SMI. These patients have an adverse cardiovascular risk factor profile due to an interplay between biological factors such as chronic inflammation, patient factors such as excessive smoking, and healthcare system factors such as stigma and discrimination. Several disparities in cardiovascular care pathways have been demonstrated in patients with SMI, resulting in a 47% lower likelihood of undergoing invasive coronary procedures and substantially lower rates of prescribed standard secondary prevention medications compared with the general population. Although early cardiovascular risk prediction is important, conventional risk prediction models do not accurately predict long-term cardiovascular outcomes as cardiovascular disease and mortality are only partly driven by traditional risk factors in this patient group. As such, SMI-specific risk prediction models and clinical tools such as the electrocardiogram and echocardiogram are necessary when assessing and managing cardiovascular risk associated with SMI. In conclusion, there is a necessity for differentiated cardiovascular care in patients with SMI. By addressing factors involved in the excess cardiovascular risk, reconsidering risk stratification approaches, and implementing multidisciplinary care models, clinicians can take steps towards improving cardiovascular health and long-term outcomes in patients with SMI.

QTc intervals at rest and during exercise assessed by group correction formulas in survivors of childhood acute lymphoblastic leukemia

IntroductionEarly signs of subclinical cardiac damage must be identified before they turn into clinical manifestations. Tailoring a formula is relevant for precise QTc evaluation in childhood acute lymphoblastic leukemia (ALL) survivors considering they are at risk of long-term cardiac problems. Therefore, we aim to develop group heart rate correction formulas for QT intervals in childhood ALL survivors at rest and during exercise, and to assess the applicability of these methods across a variety of risk groups exposed to diverse chemotherapy dosages. MethodsTwo hundred and fifty childhood ALL survivors in the PETALE study were classified into 3 groups depending on their prognostic risk group. ECG measurements (QT and RR intervals) were made at rest and during a cardiopulmonary exercise test. QT correction for heart rate was applied using 5 different formulas, which included 2 previously published formulas and 3 group-specific formulas for each sex. ResultsThe QT/RR relation showed 2 different curves between rest and during exercise, which was worse for females. Group-specific QTc formulas allowed adequate heart rate-corrected QT interval, independently of the cumulative dose of doxorubicin received during treatment. Group-specific formulas showed significantly shorter QTc intervals than QTc from Bazett's formula. QTc (Bazett's formula) values surpassed the established clinical norm in 22 males (11%) and 22 females (11%), with a majority occurring during exercise, affecting 15 males (7.5%) and 10 females (5%). ConclusionThis study shows the applicability of personalized group correction of QT/RR data in childhood ALL survivors. Our comprehensive assessments (spanning rest, exercise, and recovery) is an effective approach for risk stratification of cardiac complications in childhood ALL survivors.

Focused UTUC pathways with a risk-stratified approach to diagnostic ureteroscopy: is it the need of the hour? A retrospective cohort analysis.

Upper urinary tract urothelial cancer is a rare, aggressive variant of urinary tract cancer. There is often delay to diagnosis and management for this entity in view of diagnostic and staging challenges needing additional investigations and risk stratifications for improved outcomes. In this article, we share our experience in developing a dedicated diagnostic and treatment pathway for UTUC and assess its impact on time lines to radical nephroureterectomy (RNU). We also evaluate the impact of diagnostic ureteroscopy (DUR) on UTUC care pathways timelines. A prospective database was maintained for all patients who underwent a RNU from January 2015 to August 2022 in a high-volume single tertiary care centre in the UK. In 2019, a Focused UTUC pathway (FUP) was implemented at the centre to streamline diagnostic and RNU pathways. A retrospective analysis of the database was conducted to compare time lines and diagnostic trends between the pre-FUP and FUP cohorts. Primary outcome measures were time to RNU from MDT. Secondary outcome measures were: impact of DUR on time to RNU from MDT and negative UTUC rates between DUR and non-DUR cohorts. Differences in continuous variables across categories were assessed using the independent sample t test. Categorical variables between cohorts were analysed using the chi-square (χ2). Statistical significance in this study was set as p < 0.05. A total of 500 patients with complete data were included in the analysis. The pre-FUP and FUP cohorts consisted of 313 patients and 187 patients, respectively. The overall cohort had a mean age (SD) of 70years (9.3). 66% of the overall cohort were males. The median time to RNU from MDT in the FUP was significantly lower compared to the pre-FUP cohort; 62days (IQR 59) vs. 48days (IQR 41.5), p < 0.0001. The median time to RNU from MDT in patients who underwent a diagnostic URS in the FUP cohort was significantly lower compared to the pre-FUP cohort; 78.5days (IQR 54.8) vs. 68days (IQR 48), p-NS. The non-UTUC rates in the DUR and non-DUR cohorts were 6/248 (2.4%) and 14/251 (5.6%), respectively (NS). In this series, we illustrate the effectiveness of integrating a multidisciplinary approach with specialised personnel, ring-fenced clinics, efficient diagnostic assessment and optimised theatre capacity. By adopting a risk-stratified approach to diagnostic ureteroscopy, we have achieved a significant reduction in time to RNU.

Is inadequate risk stratification diluting hazard ratio estimates in randomized clinical trials?

In randomized clinical trials, analyses of time-to-event data without risk stratification, or with stratification based on pre-selected factors revealed at the end of the trial to be at most weakly associated with risk, are quite common. We caution that such analyses are likely delivering hazard ratio estimates that unwittingly dilute the evidence of benefit for the test relative to the control treatment. To make our case, first, we use a hypothetical scenario to contrast risk-unstratified and risk-stratified hazard ratios. Thereafter, we draw attention to the previously published 5-step stratified testing and amalgamation routine (5-STAR) approach in which a pre-specified treatment-blinded algorithm is applied to survival times from the trial to partition patients into well-separated risk strata using baseline covariates determined to be jointly strongly prognostic for event risk. After treatment unblinding, a treatment comparison is done within each risk stratum and stratum-level results are averaged for overall inference. For illustration, we use 5-STAR to reanalyze data for the primary and key secondary time-to-event endpoints from three published cardiovascular outcomes trials. The results show that the 5-STAR estimate is typically smaller (i.e. more in favor of the test treatment) than the originally reported (traditional) estimate. This is not surprising because 5-STAR mitigates the presumed dilution bias in the traditional hazard ratio estimate caused by no or inadequate risk stratification, as evidenced by two detailed examples. Pre-selection of stratification factors at the trial design stage to achieve adequate risk stratification for the analysis will often be challenging. In such settings, an objective risk stratification approach such as 5-STAR, which is partly aligned with guidance from the US Food and Drug Administration on covariate-adjustment in clinical trials, is worthy of consideration.

Sickle cell nephropathy; exploring epidemiology, diagnostic challenges, and precision medicine advances

Sickle cell nephropathy (SCN) poses an important challenge in the realm of sickle cell disease (SCD) and sickle cell trait (SCT), especially impacting the pediatric population and progressing to chronic kidney disease (CKD) in adulthood. This review navigates through the epidemiology of SCN, emphasizing its variable clinical course and the age-related dynamics of onset. The intricate challenges in diagnosis are explored, highlighting the evolving landscape of early detection and treatment strategies. The prevalence of SCN is intricately linked to the global distribution of SCD and SCT, with higher incidences in regions where these conditions prevail. Diagnosing SCN presents significant challenges due to its variable clinical course, necessitating advanced imaging techniques and novel biomarkers. Promising biomarkers such as KIM-1 and MCP-1 show potential for early detection and intervention, addressing the limitations of conventional diagnostic methods. Precision medicine, focusing on genetic profiling, emerges as a crucial approach for risk stratification and personalized treatment plans. The multifaceted clinical manifestations of SCN, including hematuria, proteinuria, and hypertension, underscore the importance of timely intervention. Treatment strategies involve the administration of angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, hydroxyurea for preventing chronic organ damage, and kidney transplantation for end-stage renal disease. Early diagnosis and intervention are critical to mitigate the progression of SCN and its associated complications, emphasizing the need for collaborative efforts in research and precision medicine to improve outcomes for individuals with SCN.

Risk Prediction and Management of Chronic Kidney Disease in People Living with Type 2 Diabetes Mellitus.

People with type 2 diabetes mellitus have increased risk of chronic kidney disease and atherosclerotic cardiovascular disease. Improved care delivery and implementation of guideline-directed medical therapy have contributed to the declining incidence of atherosclerotic cardiovascular disease in high-income countries. By contrast, the global incidence of chronic kidney disease and associated mortality is either plateaued or increased, leading to escalating direct and indirect medical costs. Given limited resources, better risk stratification approaches to identify people at risk of rapid progression to end-stage kidney disease can reduce therapeutic inertia, facilitate timely interventions and identify the need for early nephrologist referral. Among people with chronic kidney disease G3a and beyond, the kidney failure risk equations (KFRE) have been externally validated and outperformed other risk prediction models. The KFRE can also guide the timing of preparation for kidney replacement therapy with improved healthcare resources planning and may prevent multiple complications and premature mortality among people with chronic kidney disease with and without type 2 diabetes mellitus. The present review summarizes the evidence of KFRE to date and call for future research to validate and evaluate its impact on cardiovascular and mortality outcomes, as well as healthcare resource utilization in multiethnic populations and different healthcare settings.

DNA Sequencing of CD138 Cell Population Reveals TP53 and RAS-MAPK Mutations in Multiple Myeloma at Diagnosis.

Multiple myeloma is a hematologic neoplasm caused by abnormal proliferation of plasma cells. Sequencing studies suggest that plasma cell disorders are caused by both cytogenetic abnormalities and oncogene mutations. Therefore, it is necessary to detect molecular abnormalities to improve the diagnosis and management of MM. The main purpose of this study is to determine whether NGS, in addition to cytogenetics, can influence risk stratification and management. Additionally, we aim to establish whether mutational analysis of the CD138 cell population is a suitable option for the characterization of MM compared to the bulk population. Following the separation of the plasma cells harvested from 35 patients newly diagnosed with MM, we performed a FISH analysis to detect the most common chromosomal abnormalities. Consecutively, we used NGS to evaluate NRAS, KRAS, BRAF, and TP53 mutations in plasma cell populations and in bone marrow samples. NGS data showed that sequencing CD138 cells provides a more sensitive approach. We identified several variants in BRAF, KRAS, and TP53 that were not previously associated with MM. Considering that the presence of somatic mutations could influence risk stratification and therapeutic approaches of patients with MM, sensitive detection of these mutations at diagnosis is essential for optimal management of MM.

Liver T1 Mapping Derived From Cardiac Magnetic Resonance Imaging: A Potential Prognostic Marker in Idiopathic Dilated Cardiomyopathy.

Hepatic alterations are common aftereffects of heart failure (HF) and ventricular dysfunction. The prognostic value of liver injury markers derived from cardiac MRI studies in nonischemic dilated cardiomyopathy (DCM) patients is unclear. Evaluate the prognostic performance of liver injury markers derived from cardiac MRI studies in DCM patients. Prospective. Three hundred fifty-six consecutive DCM patients diagnosed according to ESC guidelines (age 48.7 ± 14.2 years, males 72.6%). Steady-state free precession, modified Look-Locker inversion recovery T1 mapping and phase sensitive inversion recovery late gadolinium enhancement (LGE) sequences at 3 T. Clinical characteristics, conventional MRI parameters (ventricular volumes, function, mass), native myocardial and liver T1, liver extracellular volume (ECV), and myocardial LGE presence were assessed. Patients were followed up for a median duration of 48.3 months (interquartile range 42.0-69.9 months). Primary endpoints included HF death, sudden cardiac death, heart transplantation, and HF readmission; secondary endpoints included HF death, sudden cardiac death, and heart transplantation. Models were developed to predict endpoints and the incremental value of including liver parameters assessed. Optimal cut-off value was determined using receiver operating characteristic curve and Youden method. Survival analysis was performed using Kaplan-Meier and Cox proportional hazard. Discriminative power of models was compared using net reclassification improvement and integrated discriminatory index. P value <0.05 was considered statistically significant. 47.2% patients reached primary endpoints; 25.8% patients reached secondary endpoints. Patients with elevated liver ECV (cut-off 34.4%) had significantly higher risk reaching primary and secondary endpoints. Cox regression showed liver ECV was an independent prognostic predictor, and showed independent prognostic value for primary endpoints and long-term HF readmission compared to conventional clinical and cardiac MRI parameters. Liver ECV is an independent prognostic predictor and may serve as an innovative approach for risk stratification for DCM. 1 TECHNICAL EFFICACY: Stage 2.

Total risk approach for noncommunicable diseases: A review of cardiovascular disease risk prediction tools for Indian setting

Abstract Risk stratification approach considering total cardiovascular disease (CVD) risk and providing appropriate interventions is one of the WHO best-buys for tackling noncommunicable diseases (NCDs). Various risk prediction tools are available to assess total CVD risk and help identify high-risk individuals. Similarly, tools are available for the prediction of risk for specific NCDs such as diabetes and hypertension. Since these tools are context specific, we reviewed the CVD risk prediction tools and disease-specific risk scores relevant for Indian setting. A literature review was performed in PUBMED and Google Scholar using the keywords. A comparison of CVD risk prediction charts applicable for India has been carried out and includes WHO CVD risk charts, WHO/ISH risk charts, Globorisk, and INTERHEART modifiable risk charts. Among these, WHO CVD risk charts are highly recommended for use in India because of its robust methodology in development and have been externally validated. Disease-specific risk scores for Indian setting include Indian Diabetes Risk Score and Hypertension Risk Prediction Tool.

Advancing Community Care and Access to Follow-up After Acute Kidney Injury Hospitalization: Design of the AFTER AKI Randomized Controlled Trial.

Acute kidney injury (AKI) is a common complication among hospitalized patients with long-term implications including chronic kidney disease (CKD). Although models are available to predict the risk of advanced CKD after AKI, there is limited evidence regarding follow-up for patients with AKI after hospital discharge, resulting in variable follow-up care. A risk-stratified follow-up approach may improve appropriateness and efficiency of management for CKD among patients at risk of declining kidney function following AKI. The objective was to compare and evaluate the use of a risk-stratified approach to follow-up care vs usual care for patients with AKI after hospital discharge. This study was a pragmatic randomized controlled trial. This study was conducted in 2 large urban hospitals in Alberta, Canada. Hospitalized patients with AKI (KDIGO stage 2 or 3) not previously under the care of a nephrologist, expected to survive greater than 90 days being discharged home. We will evaluate whether guideline-recommended CKD care processes are initiated within 90 days, including statin use, angiotensin-converting enzyme inhibitor (ACEi)/angiotensin II receptor blocker (ARB) use in those with proteinuria or diabetes, and nephrologist follow-up if sustained eGFR <30 mL/min/1.73 m2. We will also assess the feasibility of recruitment and the proportion of patients completing the recommended blood and urine tests at 90 days. Patients with AKI will be enrolled and randomized near the time of hospital discharge. In the intervention group, low risk patients will receive information regarding AKI, medium risk patients will additionally receive follow-up guidance sent to their primary care physician, and high-risk patients will additionally receive follow-up with a nephrologist. Participants in the intervention and usual care group will receive a requisition for urine testing and bloodwork at 90 days following hospital discharge. Telephone follow-up will be conducted for all study participants at 90 days and 1 year after hospital discharge. Bivariate tests of association will be conducted to evaluate group differences at the follow-up time points. We expect there may be challenges with recruitment due to the significant co-existence of comorbidity in this population. If the trial shows a positive effect on these processes for kidney care, it will inform larger-scale trial to determine whether this intervention reduces the incidence of long-term clinical adverse events, including CKD progression, cardiovascular events, and mortality following hospitalization with AKI.

Development of network‐guided transcriptomic risk score for disease prediction

SummaryOmics data, routinely collected in various clinical settings, are of a complex and network‐structured nature. Recent progress in RNA sequencing (RNA‐seq) allows us to explore whole‐genome gene expression profiles and to develop predictive model for disease risk. In this study, we propose a novel Bayesian approach to construct RNA‐seq‐based risk score leveraging gene expression network for disease risk prediction. Specifically, we consider a hierarchical model with spike and slab priors over regression coefficients as well as entries in the inverse covariance matrix for covariates to simultaneously perform variable selection and network estimation in high‐dimensional logistic regression. Through theoretical investigation and simulation studies, our method is shown to both enjoy desirable consistency properties and achieve superior empirical performance compared with other state‐of‐the‐art methods. We analyse RNA‐seq gene expression data from 441 asthmatic and 254 non‐asthmatic samples to form a weighted network‐guided risk score and benchmark the proposed method against existing approaches for asthma risk stratification.

Machine learning approaches for neuroblastoma risk prediction and stratification

Machine learning approaches for neuroblastoma risk prediction and stratification