Baseline retinal nerve fiber layer thickness as a predictor of multiple sclerosis progression: New insights from the FREEDOMS II study.

BACKGROUND AND PURPOSE: The aim was to evaluate the potential of retinal nerve fiber layer thickness (RNFLT) measured with optical coherence tomography in predicting disease progression in relapsing-remitting multiple sclerosis (RRMS). METHODS: Analyses were conducted post hoc of this 24-month, phase III, double-blind study, in which RRMS patients were randomized (1:1:1) to once daily oral fingolimod 0.5 mg, 1.25 mg or placebo. The key outcomes were the association between baseline RNFLT and baseline clinical characteristics and clinical/imaging outcomes up to 24 months. Change of RNFLT with fingolimod versus placebo within 24 months and time to retinal nerve fiber layer (RNFL) thinning were evaluated. RESULTS: Altogether 885 patients were included. At baseline, lower RNFLT was correlated with higher Expanded Disability Status Scale score (r = -1.085, p = 0.018), lower brain volume (r = 0.025, p = 0.006) and deep gray matter volume (r = 0.731, p < 0.0001), worse visual acuity (r = -19.846, p < 0.0001) and longer duration since diagnosis (r = -0.258, p = 0.018). At month 12, low baseline RNFLT (<86 µm) versus high baseline RNFLT (≥99 µm) was associated with a greater brain volume loss (percentage change -0.605% vs. -0.315%, p = 0.035) in patients without optic neuritis history. At month 24, low baseline RNFLT versus high baseline RNFLT was associated with a higher number of new or newly enlarged T2 lesions (mean number 4.0 vs. 2.8, p = 0.014) and a higher risk of subsequent RNFL thinning (hazard ratio 2.55; 95% confidence interval 1.84-3.53; p < 0.001). The atrophy of the RNFL in the inferior quadrant was alleviated with fingolimod 0.5 mg versus placebo at month 24 (Δ(least squares mean) = 1.8, p = 0.047). CONCLUSION: Retinal nerve fiber layer thickness could predict disease progression in RRMS. TRIAL REGISTRATION: Clinicaltrials.gov identifier: NCT00355134, https://clinicaltrials.gov/ct2/show/NCT00355134.

Development and validation of a predictive models for predicting the cardiac events within one year for patients underwent percutaneous coronary intervention procedure at IJN.

PURPOSE: Percutaneous coronary intervention (PCI) is a common treatment modality for coronary artery disease. Accurate prediction of patients at risk for complications and hospital readmission after PCI could improve the overall clinical management. We aimed to develop and validate predictive models to predict any cardiac event within a year post PCI procedure. METHODS: This is a retrospective cohort study utilizing data from the National Cardiovascular Disease (NCVD)-PCI registry. The data collected (N = 28,007) were split into training set (n = 24,409) and testing set (n = 3598). Four predictive models (logistic regression [LR], random forest method, support vector machine [SVM], and artificial neural network) were developed and validated. The outcome on risk prediction were compared. RESULTS: The demographic and clinical features of patients in the training and testing cohorts were similar. Patients had mean age ± standard deviation of 58.15 ± 10.13 years at admission with a male majority (82.66%). In over half of the procedures (50.61%), patients had chronic stable angina. Within 1 year of follow up mortality, target vessel revascularization (TVR), and composite event of mortality and TVR were 3.92%, 9.48%, and 12.98% respectively. LR was the best model in predicting mortality event within 1-year post-PCI (AUC: 0.820). SVM had the highest discrimination power for both TVR event (AUC: 0.720) and composite event of mortality and TVR (AUC: 0.720). CONCLUSIONS: This study successfully identified optimal prediction models with the good discriminatory ability for mortality outcome and good discrimination ability for TVR and composite event of mortality and TVR with a simple machine learning framework.

The Sarawak Myelofibrosis (SaMy) experience: Demographics and outcome of myelofibrosis patients in Sarawak, Malaysia.

Introduction: Myelofibrosis is a rare disease. There is currently no published data reporting the demographics and outcome of myelofibrosis patients in Malaysia. We aimed to study the demographics, clinical characteristics, and outcome of our patients in Sarawak. Materials and methods: This non-interventional, retrospective, and multi-center study was conducted on secondary data of medical records collected at four Sarawak Public Hospitals. All adult myelofibrosis patients diagnosed between January 2001 and December 2021 were included. Results: A total of 63 patients (male 31) with myelofibrosis were included-47 (74.6%) primary and 16 (25.4%) secondary myelofibrosis. Eleven had antecedent polycythaemia vera, whereas five transformed from essential thrombocythaemia. The combined annual incidence rate was 0.182 per 100,000 population. The period prevalence per 100,000 population over the entire study duration was 2.502. The median age was 59.0 years (33.0-93.0). Majority had high-risk (34/63(54.0%)) and intermediate-2 risk disease (19/63(30.2%)). JAK2V617F mutation was identified in 52 patients (82.5%), followed by CALR mutation in 6 (9.5%) and negative for both mutations in 5 (7.9%). Hydroxyurea was used as first-line therapy in 41/63 (65.1%), followed by interferon (8/63(12.7%)) and ruxolitinib (4/63(6.3%)). Out of 46 patients who received second-line therapy, 18 (39.1%) were switched to ruxolitinib and 9 (19.6%) to interferon. The median age of survival for overall patients was 6.8 years. The use of ruxolitinib in myelofibrosis patients showed a better overall 5-year survival compared to the no ruxolitinib arm, despite no statistical significance (p = 0.34). Patients who had good performance status had lower hazard of death than patients who had poor performance status (high-risk (95% confidence intervals): 0.06(0.013-0.239), p < 0.001). Patients with intermediate risk disease had better overall survival compared to those in high-risk group (95% confidence intervals): 0.24(0.082-0.695), p = 0.009). Conclusion: This registry provides a real-world overview of myelofibrosis patients in our state and highlights the key insight into the unmet clinical need.