Prognostic Potential of Electrocardiographic Parameters in Patients with Multiple Myeloma: A Retrospective Analysis of the Multiple Myeloma Population

Incidence of Arrhythmias and Their Prognostic Value in Patients With Multiple Myeloma

Background: Arrhythmias are common cardiovascular complications in multiple myeloma (MM) patients and are related to a poor prognosis.

Objective: This study aimed to assess the burden of arrhythmias and their prognostic value in patients with MM.

Methods: This was a retrospective study of patients with MM between January 2015 and April 2020 at the First Affiliated Hospital of Xi'an Jiaotong University. The incidence of arrhythmia and associated risk factors were evaluated. The relationship between the type of arrhythmia and survival was analyzed.

Results: A total of 319 patients with MM were identified, and 48.0% (153/319) had arrhythmias. The most common type of arrhythmia was sinus tachycardia (ST) (15.0%, 48/319), followed by sinus bradycardia (SB) (14.4%, 46/319), premature atrial contractions (PACs) (6.3%, 20/319), conduction disorders (CDs) (6.0%, 19/319), atrial fibrillation (AF) (6.0%, 19/319), premature ventricular contractions (PVCs) (4.4%, 14/319) and paroxysmal supraventricular tachycardia (PSVT) (0.6%, 2/319). The patients with arrhythmias had higher levels of log NT-proBNP and creatinine, greater bortezomib use, and a higher incidence of diabetes than those without arrhythmias (P < 0.05). The all-cause mortality rates of patients without arrhythmias and those with AF, ST, PACs, CDs, SB, and PVCs were 50.6% (84/166), 73.7% (14/19), 60.4% (29/48), 60.0% (12/20), 52.6% (10/19), 34.8% (16/46), and 28.6% (4/14), respectively. In a subgroup analysis of patients experiencing different types of arrhythmias, patients with SB had lower all-cause mortality than patients with AF (P < 0.01). Univariate and multivariate Cox analyses showed that there was a positive statistically significant association between SB and survival (HR: 0.592 [0.352–0.998], P = 0.049) in a subgroup analysis of different arrhythmias.

Conclusions: Patients with MM had a heavy arrhythmia burden, and in this study, approximately half of MM patients had arrhythmias. MM patients with SB were associated with lower all-cause mortality than those with AF. SB might be an independent positive factor for prognosis.

Prognostic Potential of Heart Rate and Hypertension in Multiple Myeloma Patients

Background: The prognosis of patients with multiple myeloma (MM) is variable and partly depends on their cardiovascular status. The presence of arrhythmias can lead to worse outcomes. Therefore, this study aimed to evaluate the potential of heart rate (HR) and hypertension in predicating the outcomes of MM patients. Methods: This study retrospectively enrolled patients with MM between January 1, 2010, and December 31, 2018, at the First Affiliated Hospital of Xi'an Jiaotong University. The endpoint was all-cause mortality. The Pearson's chi-square test was used to assess the association between hypertension and outcomes. Univariate and multivariate Cox proportional hazards models were developed to evaluate the relationship between HR and all-cause mortality. Results: A total of 386 patients were included. The mean HR was 83.8 ± 23.1 beats per minute (bpm). Patients with HR >100 bpm had a higher all-cause mortality (79.4%, 50/63) than those with 60 ≤ HR ≤ 100 bpm (39.9%, 110/276) and <60 bpm (19.1%, 9/47) (p < 0.001). Subgroup analysis based on the International Staging System and sex revealed similar relationships (p < 0.01). When stratified by age, patients with HR >100 bpm had higher all-cause mortality than those with a lower HR when age was <65 years or 65-75 years (p < 0.001) but not >75 years. The proportion of patients with hypertension was 54.7% (211/386). However, hypertension was not associated with all-cause mortality in MM patients (χ²=1.729, p > 0.05). MM patients with HR >100 bpm had the highest all-cause mortality. Conclusions: The prognostic potential of HR may be useful in aiding risk stratification and promoting the management of these patients.

Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma Patients

Multiple myeloma (MM) is a malignant plasma cell tumor with high heterogeneity, characterized by anemia, hypercalcemia, renal failure, and lytic bone lesions. Although various powerful prognostic factors and models have been exploited, the development of more accurate prognosis and treatment for MM patients is still facing many challenges. Given the essential roles of super-enhancer (SE) associated genes in the tumorigenesis of MM, we tried to initially screen and identify the significant prognostic factors from SE associated genes in MM by the least absolute shrinkage and selection operator (Lasso) penalized Cox regression, univariate and multivariate Cox regression analysis using GSE24080 and GSE9782 datasets. Risk score model of five genes including CSGALNACT1, FAM53B, TAPBPL, REPIN1, and DDX11, was further constructed and the Kaplan-Meier (K-M) curves showed that the low-risk group seems to have better clinical outcome of survival compared to the high-risk group. Time-dependent receiver operating characteristic (ROC) curves presented the favorable performance of the model. An interactive nomogram consisting of the five-gene risk group and eleven clinical traits was established and identified by calibration curves. Therefore, the risk score model of SE associated five genes developed here could be used to predict the prognosis of MM patients, which may assist the clinical treatment of MM patients in the future.

Identification of important risk factors for all-cause mortality of acquired long QT syndrome patients using random survival forests and non-negative matrix factorization

BACKGROUND

Acquired long QT syndrome (aLQTS) is often associated with poor clinical outcomes.

OBJECTIVE

The purpose of this study was to examine the important predictors of all-cause mortality of aLQTS patients by applying both random survival forest (RSF) and non-negative matrix factorization (NMF) analyses.

METHODS

Clinical characteristics and manually measured electrocardiographic (ECG) parameters were initially entered into the RSF model. Subsequently, latent variables identified using NMF were entered into the RSF as additional variables. The primary outcome was all-cause mortality.

RESULTS

A total of 327 aLQTS patients were included. The RSF model identified 16 predictive factors with positive variable importance values: cancer, potassium, RR interval, calcium, age, JT interval, diabetes mellitus, QRS duration, QTp interval, chronic kidney disease, QTc interval, hypertension, QT interval, female, JTc interval, and cerebral hemorrhage. Increasing the number of latent features between ECG indices, which incorporated from n = 0 to n = 4 by NMF, maximally improved the prediction ability of the RSF-NMF model (C-statistic 0.77 vs 0.89).

CONCLUSION

Cancer and serum potassium and calcium levels can predict all-cause mortality of aLQTS patients, as can ECG indicators including JTc and QRS. The present RSF-NMF model significantly improved mortality prediction.