MNMateusz Nikodem

Mateusz Nikodem

*This is an algorithmically generated author record based on publicly available information.

Mateusz Nikodem has a total of 14 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Comparative Efficacy of Finerenone versus Canagliflozin in Patients with Chronic Kidney Disease and Type 2 Diabetes: A Matching-Adjusted Indirect Comparison

    by David Cherney, Kerstin Folkerts, Paul Mernagh, Mateusz Nikodem, Joerg Pawlitschko, Peter Rossing, Neil Hawkins

    This study aimed to close an evidence gap concerning the relative efficacy of finerenone versus SGLT2is in patients with chronic kidney disease (CKD) and type 2 diabetes (T2D). Canagliflozin was selected as a proxy for the SGLT2i class. Patient-level data of two randomized controlled trials (RCTs) of finerenone (FIDELIO-DKD and FIGARO-DKD) were used alongside aggregated data from CREDENCE, an RCT of canagliflozin. To account for meaningful between-study heterogeneity between each finerenone trial and CREDENCE, a matching-adjusted indirect comparison of a range of efficacy outcomes was undertaken for each finerenone study versus CREDENCE. These results were meta-analyzed, enabling the estimation of the relative effects of finerenone against canagliflozin. For the cardiorenal composite endpoint, the hazard ratio (HR) comparing finerenone to canagliflozin was 1.07 (95% CI: 0.83 to 1.36). The corresponding HRs for all-cause mortality, end-stage kidney disease and cardiovascular death were 0.99 (95% CI: 0.73 to 1.34), 1.03 (95% CI: 0.68 to 1.55) and 0.94 (95% CI: 0.64 to 1.37), respectively. The absence of statistically significant differences was consistent throughout the main analysis and a range of sensitivity analyses. Based on this study, using a large sample of data and adjusted for meaningful differences between the baseline characteristics of the included RCTs, there was no statistically significant evidence indicating a difference in the efficacy of finerenone compared to canagliflozin in the treatment of CKD in patients with T2D.


  • Open Access

    Ivabradine in patients with heart failure: a systematic literature review

    by Zeba M. Khan, Jean Baptiste Briere, Elzbieta Olewinska, Fatma Khrouf, Mateusz Nikodem

    Background: Heart failure is a chronic disease linked with significant morbidity and mortality, and uncontrolled resting heart rate is a risk factor for adverse outcomes. This systematic literature review aimed to assess the efficacy, safety, and patient-reported outcomes (PROs) of ivabradine in patients with heart failure (HF) with reduced ejection fraction (HFrEF) in randomized controlled trials (RCTs) and observational studies.


  • Open Access

    FC083: Finerenone and Canagliflozin in the Treatment of Chronic Kidney Disease and Type 2 Diabetes: Matching-Adjusted Indirect Treatment Comparison of Fidelio-DKD and Credence

    by David Cherney, Kerstin Folkerts, Paul Mernagh, Mateusz Nikodem, Joerg Pawlitschko, Peter Rossing

    Finerenone (FIN: an oral, nonsteroidal mineralocorticoid receptor antagonist) and canagliflozin (CAN: a sodium-glucose cotransporter 2 inhibitor) demonstrated cardiorenal efficacy in patients with chronic kidney disease and type 2 diabetes on top of renin–angiotensin system blockade in phase III placebo-controlled studies (FIDELIO-DKD [NCT02540993] for FIN; CREDENCE [NCT02065791] for CAN) [ 3, 2]. In the absence of head-to-head studies, we assessed FIN and CAN in this patient population while appropriately accounting for meaningful differences between the trials. We performed an anchored matching-adjusted indirect comparison (MAIC), with placebo (PBO) as a common comparator, to generate measures of efficacy and safety while accounting for differences between the two study populations [ 3]. Individual patient-level data from FIDELIO-DKD and published data from CREDENCE were used [ 1,[ 2]. Weights were calculated and assigned to each patient in FIDELIO-DKD so the weighted population of FIDELIO-DKD matched that of CREDENCE for selected baseline characteristics, e.g. mean estimated glomerular filtration rate (eGFR; 44.3 and 56.2 mL/min/1.73 m2 in FIDELIO-DKD and CREDENCE, respectively). Weights were obtained from a logistic regression model of the odds of enrolment in CREDENCE and FIDELIO-DKD for baseline characteristics believed to be effect modifiers. Hazard ratios (HRs) with 95% confidence intervals (CIs) comparing FIN and PBO for time-to-event endpoints were estimated based on the weighted population of FIDELIO-DKD. HRs with 95% CIs comparing FIN and CAN were then calculated from results of the previous step and published data from CREDENCE [ 2]. This analysis evaluated the cardiorenal composite endpoint from CREDENCE (kidney failure [dialysis, transplantation or sustained eGFR < 15 mL/min/1.73 m2), a doubling of serum creatinine level or death from kidney or cardiovascular disease) [ 2] and hyperkalaemia. A sensitivity analysis that matched patients based on their history of heart failure was performed. Calculation of the weights for the FIDELIO-DKD population (N = 5674) resulted in an effective sample size of 1288 for the pseudo-population formed by the weighting to compare with the CREDENCE population (N = 4401). For the cardiorenal composite endpoint, the HR (95% CI) for FIN and PBO based on reweighted FIDELIO-DKD data was 0.72 (0.59–0.90) and the MAIC-based HR (95% CI) for FIN and CAN was 1.03 (0.79–1.35) (P = 0.802). For hyperkalaemia, the MAIC-based HR (95% CI) for FIN and CAN was 2.25 (1.67–3.03) (P < 0.001). Similar efficacy and safety results were demonstrated in the sensitivity analysis. The MAIC for FIDELIO-DKD and CREDENCE enabled more robust assessment of FIN and CAN when a similar patient population was considered. There was no evidence of a significant difference between FIN and CAN in the cardiorenal composite endpoint as assessed in CREDENCE. These results are consistent with a recent analysis using a different payer-accepted method that also accounted for differences between the FIDELIO-DKD and CREDENCE inclusion criteria and endpoints [ 3, 4].