Background: Immune checkpoint inhibitors (ICIs) have improved survival in non-small cell lung cancer (NSCLC), yet identifying who benefits from treatment remains difficult. Low skeletal muscle mass (SMM) is associated with poor cancer outcomes. We aim to examine the relationship between computed tomography (CT)-assessed sarcopenia and patient trajectories [death, immune-related adverse events (irAEs) and death after irAEs] following ICI initiation. Methods: We conducted a retrospective cohort study of NSCLC patients treated with ICIs at the University Medical Center Groningen [2015-2021] with baseline low-dose computed tomography (LDCT) scans. Sarcopenia was defined using sex-specific SMM thresholds. Multi-state time-to-event models estimated transition probabilities between ICI initiation and three outcomes: direct mortality (without irAEs), development of irAEs, and mortality after irAEs. Models were adjusted for age, sex, performance status, cancer stage, treatment line, body mass index (BMI), and combination therapy. Separate models were built for severe and any-grade irAEs. Results: Among 363 patients (96-month follow-up), 301 (82.9%) died and 166 (45.7%) developed irAEs, including 76 (20.9%) with severe irAEs. In the severe irAE model, sarcopenia was not associated with developing severe irAEs [hazard ratio (HR) =0.81, 95% confidence interval (CI): 0.42-1.58] or with mortality without severe irAEs (HR =1.19, 95% CI: 0.82-1.74). However, sarcopenia was associated with reduced mortality after severe irAEs (HR =0.39, 95% CI: 0.23-0.65). In the any-grade irAEs model, sarcopenic patients were less likely to develop irAEs (HR =0.63, 95% CI: 0.42-0.93). Sarcopenia was not linked to mortality without irAEs (HR =1.08, 95% CI: 0.70-1.67) or after any-grade irAEs (HR =0.81, 95% CI: 0.52-1.26). Conclusions: In this NSCLC cohort, CT-assessed sarcopenia was not associated with direct mortality without irAEs but was linked to a lower likelihood of developing irAEs and reduced mortality after severe irAEs. These findings suggest that body composition may have prognostic value and influence responses to immunotherapy.

External comparator cohort (ECC) studies with real-world data (RWD) may provide more reliable estimates of treatment differences compared to single-arm trials (SAT), yet they face limitations such as selection bias and data heterogeneity. This study assessed the perceived strength of evidence of ECC studies compared to SAT and randomized controlled studies (RCT). The study included healthcare professionals (HCP) from the European Hematology Association (EHA), the European Society for Medical Oncology (ESMO), and assessors from international regulatory agencies (RA). A conjoint analysis evaluated strength of evidence ratings for establishing an effect on OS for different hypothetical scenarios, based on different designs, RWD quality, and observed OS improvement, for a new cancer treatment for advanced disease and no effective treatments. Participants from HCP organizations rated RWD studies favorably (advantages outweigh disadvantages) more frequently (47.6%; n = 103) compared to RA participants (12.9%; n = 116). Compared to a SAT, a high-quality RWD ECC study showing a 1.5-month and 3-month OS improvement had 2.7 (95% CI: 1.9-3.8) and 14.7 (95% CI: 10.0-21.5) times higher odds of receiving a higher strength of evidence rating, respectively. The OR for RCT v. SAT was 36.4 (95% CI: 24.0-55.2) and 358.4 (95% CI: 217.3-591.3), respectively. Strength of evidence ratings were associated with maximum acceptable risk of severe or symptomatic toxicity. In conclusion, when evaluating the OS of new therapies, ECC studies with RWD, especially when based on high-quality RWD or demonstrating a larger OS benefit, were rated as more convincing than SAT without a formal control.

Current dietary practices are not sustainable to support the growing global population. Environmental sustainability of diets can be indicated by multiple environmental impact categories (EICs). Generic EIC weights may help identify sustainable diets overall but overlook the environmental impact specific to relevant food groups in different contexts. This paper aims to explore if food group specific EIC weighting schemes improve interpretation of overall impact of foods and to assess the suitability of multi-criteria decision analysis (MCDA) for developing such schemes.First, six EICs and five food groups from the Dutch context were selected for proof of principle (problem structuring). Second, data was normalized using appropriate functional units (scoring alternatives against criteria). Third, a panel of eight Dutch LCA experts answered choice-based questions, facing trade-offs between EICs for each food group (preference modelling).Greenhouse gas emissions (GHGE) were ranked important across all food groups. Importance of blue water consumption (BWC) and freshwater eutrophication varied depending on the food group. MCDA-based food group weighting schemes have benefits over one generic weighting scheme for food groups with specific (local) environmental challenges (e.g., nuts and seeds with considerable BWC) and for foods with distinct EIC trade-offs (e.g., GHGE and BWC).EIC weighting for sustainable diets may thus be improved by considering food group specific environmental challenges. MCDA holds valuable potential to learn more about weighting various EICs, considering spatio-temporal and socio-cultural variability in sustainable diets. Future application of MCDA in the sustainable nutrition transition may navigate evolving priorities by incorporating economic or health-related criteria.

The purpose of this study was to describe the perspectives and trade-offs of EU regulators about expedited approvals for treatments of patients with advanced cancer. The study consisted of a cross-sectional survey with assessors and experts from the network of the European Medicines Agency (EMA). First, general attitudes were collected using a 5-point Likert scale. Second, a conjoint analysis was used to assess the compatibility of "conditional approval" for different scenarios of response rate, response duration, and toxicity from a single-arm trial, and timeliness of confirmatory data. The survey was completed by 60 participants out of 351 invited participants. The majority agreed that outstanding activity is indicative of efficacy, that toxicity is a concern, and that confirmatory trials should be ongoing at the time of approval. The majority also agreed that conditional approval is not well understood by patients and doctors. Opinions varied on the usefulness of external comparator studies. Higher antitumour activity could outweigh higher toxicity or longer time to confirmation. Based on confidence with expedited pathways and evidence generation, participants could be categorized as "supportive," "pragmatic," and "cautious." The importance of toxicity and timeliness of confirmatory studies was similar between groups but varied for antitumour activity. This study highlighted different attitudes when balancing speed of access with incomplete evidence in situations of high unmet medical needs. Confidence in expedited pathways and early evidence varied. There is an opportunity for improving communication and better alignment on evidentiary standards for expedited approvals.

Background:This study aimed to investigate the impact of COVID-19 waves on mental health, pandemic-related wellbeing, and social functioning in adults with moderate-to-severe atopic dermatitis (AD) and without AD in the Dutch general population. Methods:Between 2020 and 2022, 31 COVID-19 questionnaires (COVQs) were sent to 140,145 Lifelines adult participants, collecting data on mental health [major depression disorder (MDD), generalized anxiety disorder (GAD)], pandemic-related wellbeing [COVID-19-related concerns, quality of life (QoL)], and social functioning (loneliness, social relations). AD information was collected through a digital questionnaire sent to all Lifelines adults in 2020. Data were divided into three waves according to the COVID-19 timeline in the Netherlands: March-June 2020 (wave 1); July 2020-June 2021 (wave 2); July 2021-October 2022 (wave 3). Generalized linear mixed models were performed for each outcome. Results:In total, 49,216 participants with 790,936 completed COVQs were included. Compared with wave 1, almost all health-related outcomes, including the prevalence of MDD and GAD, COVID-19-related concerns, loneliness, and QoL, had returned to similar levels by wave 3 in the overall population, while social relations remained impaired. Furthermore, participants with moderate-to-severe AD, women, young adults (18-29 years), and those with a history of mental health problems showed worse health-related outcomes than their counterparts. Conclusion:Both participants with and without moderate-to-severe AD showed partial recovery in mental health and wellbeing by the third COVID-19 wave; however, social relations remained impaired. Individual with moderate-to-severe AD, women, younger adults, and those with pre-existing mental health problems were more affected overall. Future studies should focus on developing strategies to improve social connectedness, and vulnerable groups warrant continued attention.

PURPOSE:Traditional benefit-harm assessments of cancer treatments evaluate morbidity and mortality separately, overlooking how patients experience these outcomes together. This study illustrates how a health profile-based approach using multi-state modelling can complement such assessments. METHODS:To compare the traditional and health profile-based approaches, we simulated a phase 3 trial in newly diagnosed glioblastoma. The traditional analysis estimated median progression-free survival (PFS), overall survival (OS), and grade 3 and 4 (G34) toxicity rates. The health profile-based approach used a multi-state Markov model (MSMM) to estimate time spent in different health states over 36 months. Quality-adjusted life years (QALYs) were calculated by combining time-in-state estimates with utility weights simulated to reflect a patient preference study. RESULTS:The traditional analysis showed a 3.8-month increase in median PFS for the experimental treatment, accompanied by a substantially higher rate of G34 toxicity (48.4 % vs. 15.2 %). This allowed balancing benefits and harms on the basis of population-level effects of median PFS and cumulative incidence of toxicity. The MSMM approach offered a more granular view of the progression-toxicity trade-off, showing that patients in the experimental group spent less time with progressed disease (7.7 vs. 9.4 months), but more time progression-free with G34 toxicity (3.8. vs 0.3 months). When combined with simulated individual-level utility weights, QALY values could be assigned to the experimental treatment and the control. CONCLUSION:Multi-state modelling offers a flexible way to integrate morbidity and mortality in evaluating cancer treatments. By capturing health trajectories and enabling utility-based assessments, it may complement traditional methods to inform treatment decisions.

Randomized controlled trials (RCTs) are the gold standard to establish the benefit-risk ratio of novel drugs. However, the evaluation of mature results often takes many years. We hypothesized that the addition of Bayesian inference methods at interim analysis time points might accelerate and enforce the knowledge that such trials may generate. In order to test that hypothesis, we retrospectively applied a Bayesian approach to the HOVON 132 trial, in which 800 newly diagnosed AML patients aged 18 to 65 years were randomly assigned to a “7 + 3” induction with or without lenalidomide. Five years after the first patient was recruited, the trial was negative for its primary endpoint with no difference in event-free survival (EFS) between experimental and control groups (hazard ratio [HR] 0.99, p = 0.96) in the final conventional analysis. We retrospectively simulated interim analyses after the inclusion of 150, 300, 450, and 600 patients using a Bayesian methodology to detect early lack of efficacy signals. The HR for EFS comparing the lenalidomide arm with the control treatment arm was 1.21 (95% CI 0.81–1.69), 1.05 (95% CI 0.86–1.30), 1.00 (95% CI 0.84–1.19), and 1.02 (95% CI 0.87–1.19) at interim analysis 1, 2, 3 and 4, respectively. Complete remission rates were lower in the lenalidomide arm, and early deaths more frequent. A Bayesian approach identified that the probability of a clinically relevant benefit for EFS (HR < 0.76, as assumed in the statistical analysis plan) was very low at the first interim analysis (1.2%, 0.6%, 0.4%, and 0.1%, respectively). Similar observations were made for low probabilities of any benefit regarding CR. Therefore, Bayesian analysis significantly adds to conventional methods applied for interim analysis and may thereby accelerate the performance and completion of phase III trials.

AIMS:Serelaxin is recombinant human relaxin-2, a hormone responsible for haemodynamic adaptations and organ protection in pregnancy. In the RELAX-AHF trial, serelaxin demonstrated reductions in cardiac, renal and hepatic damage. In RELAX-AHF-2, organ damage-related biomarkers were assessed in a biomarker substudy. METHODS AND RESULTS:Patients enrolled within 16 h of presentation for heart failure hospitalization were randomized to 48-h infusions of either serelaxin (30 μg/kg/day) or placebo, and plasma samples were obtained at baseline, 2, 5, and 14 days in patients participating in the biomarker substudy. Of the 6545 patients analysed in RELAX-AHF-2, 1020 (15.6%) patients (mean age 72 ± 12 years; 61% male) were enrolled in the biomarker substudy. Compared to placebo, serelaxin decreased percentage change from baseline in troponin T through day 14 (serelaxin +0.2% vs. placebo +40.3%; p = 0.042), as well as creatinine (-0.8% vs. +5.8%; p = 0.002), cystatin C (+3.8% vs. +8.3%; p = 0.016), and uric acid (+0.8% vs. +7.2%; p = 0.0014) at day 2. The decrease of N-terminal pro-B-type natriuretic peptide (NT-proBNP) from baseline to day 2 was greater in serelaxin-treated patients (-39.8% vs. -27.6%; p = 0.002). Early changes in NT-proBNP and troponin, but not creatinine, cystatin C and uric acid, were associated with 180-day mortality. In this substudy population, serelaxin did not reduce 180-day cardiovascular death (hazard ratio [HR] 0.78; 95% confidence interval [CI] 0.49-1.25; p = 0.30), but significantly reduced worsening heart failure through day 5 (HR 0.55; 95% CI 0.33-0.93; p = 0.027). CONCLUSION:In this substudy, serelaxin decreased plasma concentrations of cardiac, renal and hepatic injury markers. Changes of most of these markers were associated with cardiovascular mortality. In this pre-specified biomarker subgroup, serelaxin did not reduce 180-day cardiovascular mortality but significantly reduced worsening heart failure through day 5.

Glomerular filtration rate (GFR) decline is used as surrogate endpoint for kidney failure. Interventions that reduce chronic kidney disease (CKD) progression often exert acute GFR reductions which differ from their long-term benefits and complicate the estimation of long-term benefit. Here, we assessed the utility of two alternative trial designs (wash-out design and active run-in randomized withdrawal design) that attempt to exclude the impact of acute effects. Post-hoc analyses of two clinical trials that characterized the effect of an intervention with acute reductions in GFR were conducted. The two trials included a wash-out period (EMPA-REG Outcome testing empagliflozin vs placebo) or an active run-in period with a randomized withdrawal (SONAR testing atrasentan vs placebo). We compared the drug effect on GFR decline calculated from the first on-treatment visit to the end of treatment (chronic slope in a standard randomized trial design) with GFR change calculated from randomization to end of wash out, or GFR change from treatment-specific baseline GFR values (GFR at start-of-run-in for placebo and end-of-run-in for atrasentan) until end-of-treatment. The effect of empagliflozin versus placebo on chronic GFR slope was 1.72 (95% confidence interval 1.49-1.94) mL/min/1.73 m(2)/year, similar to total GFR decline from baseline to the end of wash-out period using a linear mixed model 1.64 (1.44-1.85) mL/min/1.73 m(2)/year). The effect of atrasentan versus placebo on chronic GFR slope was 0.72 (0.32-1.11) mL/min/1.73 m(2)/year, similar to total slope from a single slope model when estimated from treatment specific baseline GFR values 0.77 (0.39-1.14) mL/min/1.73 m(2)/year). Statistical power of the two designs outperformed the standard randomized design. Thus, wash-out and active-run-in randomized-withdrawal trial designs are appropriate models to compute treatment effects on GFR decline.

BACKGROUND:Immune checkpoint inhibitors (ICIs) can induce immune-related adverse events (irAEs). This study investigates the relationship between CT-assessed sarcopenia and irAEs in patients with lung cancer who are receiving ICIs. METHODS:Patients were enrolled if they had lung cancer treated with ICIs at the University Medical Center Groningen (2015-2021) and had undergone low-dose CT scans that included the third lumbar vertebral level (L3). CT-assessed sarcopenia was defined based on reported L3 skeletal muscle mass index (L3SMI) thresholds. Patients were categorized into no, any-grade, and severe irAE groups. The association between CT-assessed sarcopenia and irAEs was assessed by competing risk time-to-event analysis, accounting for the risk of death. Sub-distribution hazard ratios (SDHR) were calculated using Fine-Gray regression models adjusted for relevant confounders. The association between CT-assessed sarcopenia and overall survival (OS) was evaluated through survival analyses. RESULTS:We included 363 patients; most were male (60.9 %), had favorable Eastern Cooperative Oncology Group (ECOG) performance statuses (0-1; 90.1 %), had stage IV disease (92.8 %), and received ICI monotherapy (82.9 %). Of these, 45.6 % developed any-grade irAEs and 21 % developed severe irAEs. Endocrine disorders were the most common mild irAEs (24.8 %), while respiratory disorders were the most common severe irAEs (24.7 %). CT-assessed sarcopenia was more prevalent in the no irAE group (87 %) compared with the any-grade (77 %) and severe (79 %) irAE groups. Presence of CT-assessed sarcopenia was associated with a lower risk of developing any irAEs (SDHR = 0.62 [95 % CI: 0.41-0.92]). No significant association was found between CT-assessed sarcopenia and severe irAEs (fully adjusted model, SDHR = 0.74 [95 % CI: 0.39-1.4]), or between CT-assessed sarcopenia and OS. CONCLUSION:CT-assessed sarcopenia is associated with a reduced risk of any irAEs in patients with lung cancer receiving ICIs, possibly because higher muscle mass enhances the host response to immunological stimulation. Recognizing sarcopenia as a predictive factor for irAEs is relevant for personalizing treatments.

Objectives: Multiple methods are available for collecting health preference information. However, information on the design and analysis of novel methods is limited. This article aims to provide the first introduction into the design and analysis of multidimensional thresholding (MDT). Methods: We introduce MDT as a 2-step approach: First, participants rank the largest possible improvements in all considered attributes by their importance. Second, participants complete a series of systematically combined trade-off questions. Hit-and-Run sampling is used for obtaining preference weights. We also use a computational experiment to compare different MDT designs. Results: The outlined MDT can generate preference information suitable for specifying a multi-attribute utility function at the individual level. The computational experiment demonstrates the method's ability to recover preference weights at a high level of precision. While all designs in the computation experiment perform comparably well on average, the design outlined in the paper stands out with a high level of precision even if differences in relative attribute importance are large. Conclusion: MDT is suitable for preference elicitation, in particular if sample sizes are small. Future research should help improve the methods (e.g., remove the need for an initial ranking) to increase the potential reach of MDT.

AbstractBackgroundWe recently reported results of the prospective, open‐label HOVON‐100 trial in 334 adult patients with acute lymphoblastic leukemia (ALL) randomized to first‐line treatment with or without clofarabine (CLO). No improvement of event‐free survival (EFS) was observed, while a higher proportion of patients receiving CLO obtained minimal residual disease (MRD) negativity.AimIn order to investigate the effects of CLO in more depth, two multi‐state models were developed to identify why CLO did not show a long‐term survival benefit despite more MRD‐negativity.MethodsThe first model evaluated the effect of CLO on going off‐protocol (not due to refractory disease/relapse, completion or death) as a proxy of severe treatment‐related toxicity, while the second model evaluated the effect of CLO on obtaining MRD negativity. The subsequent impact of these intermediate events on death or relapsed/refractory disease was assessed in both models.ResultsOverall, patients receiving CLO went off‐protocol more frequently than control patients (35/168 [21%] vs. 18/166 [11%], p = 0.019; HR 2.00 [1.13–3.52], p = 0.02), especially during maintenance (13/44 [30%] vs. 6/56 [11%]; HR 2.85 [95%CI 1.08–7.50], p = 0.035). Going off‐protocol was, however, not associated with more relapse or death. Patients in the CLO arm showed a trend towards an increased rate of MRD‐negativity compared with control patients (HR MRD‐negativity: 1.35 [0.95–1.91], p = 0.10), which did not translate into a significant survival benefit.ConclusionWe conclude that the intermediate states, i.e., going off‐protocol and MRD‐negativity, were affected by adding CLO, but these transitions were not associated with subsequent survival estimates, suggesting relatively modest antileukemic activity in ALL.

Missing data and unmeasured confounding are key challenges for external comparator studies. This work evaluates bias and other performance characteristics depending on missingness and unmeasured confounding by means of two case studies and simulations. Two case studies were constructed by taking the treatment arms from two randomised controlled trials and an external real-world data source that exhibited substantial missingness. The indications of the randomised controlled trials were multiple myeloma and metastatic hormone-sensitive prostate cancer. Overall survival was taken as the main endpoint. The effects of missing data and unmeasured confounding were assessed for the case studies by reporting estimated external comparator versus randomised controlled trial treatment effects. Based on the two case studies, simulations were performed broadening the settings by varying the underlying hazard ratio, the sample size, the sample size ratio between the experimental arm and the external comparator, the number of missing covariates and the percentage of missingness. Thereby, bias and other performance metrics could be quantified dependent on these factors. For the multiple myeloma external comparator study, results were in line with the randomised controlled trial, despite missingness and potential unmeasured confounding, while for the metastatic hormone-sensitive prostate cancer case study missing data led to a low sample size, leading overall to inconclusive results. Furthermore, for the metastatic hormone-sensitive prostate cancer study, missing data in important eligibility criteria led to further limitations. Simulations were successfully applied to gain a quantitative understanding of the effects of missing data and unmeasured confounding. This exploratory study confirmed external comparator strengths and limitations by quantifying the impact of missing data and unmeasured confounding using case studies and simulations. In particular, missing data in key eligibility criteria were seen to limit the ability to derive the external comparator target analysis population accurately, while simulations demonstrated the magnitude of bias to expect for various settings.

AIMS:Acute heart failure (AHF) is a major cause of hospitalizations and death in the elderly. However, elderly patients are often underrepresented in randomized clinical trials. We analysed the impact of age on clinical outcomes and response to treatment in patients enrolled in Relaxin in Acute Heart Failure (RELAX-AHF-2), a study that included older patients than in previous AHF trials. METHODS AND RESULTS:The RELAX-AHF-2 randomized patients admitted for AHF to infusion of serelaxin or placebo. We examined the association of pre-specified clinical outcomes and treatment effect according to age categories [(years): <65 (n = 1411), 65-74 (n = 1832), 75-79 (n = 1222), 80-84 (n = 1156) and ≥85 (n = 924)]. The mean age of the 6545 patients enrolled in RELAX-AHF-2 was 73.0 ± 11 years. The risk of all-cause and cardiovascular (CV) death (all p < 0.001) as well as the composite endpoint of CV death or heart failure/renal failure rehospitalization through 180 days (p = 0.002) and hospital discharge through day 60 (p = 0.013) were all directly associated with age categories. Age remained independently associated with outcomes after adjustment for clinical confounders and the results were consistent when age was analysed continuously. No clinically significant change in treatment effects of serelaxin was observed across age categories for the pre-specified endpoints (interaction p > 0.05). CONCLUSION:Elderly patients are at higher risk of short- and long-term CV outcomes after a hospitalization for AHF. Further efforts are needed to improve CV outcomes in this population.

Background:Treatment guidelines recommend metformin as initial drug in many people with type 2 diabetes (T2D) and low risk of cardiovascular disease, with the possibility to switch to or add other drug classes. A decision aid (DA) could be useful to incorporate a patient's preferences in the decision of which drug class to choose. We developed such a DA and assessed the perspectives of people with T2D towards its comprehensibility and usability. Methods:The DA consists of a paper-based leaflet followed by a web-based preference elicitation exercise. The leaflet aims at informing patients about drug characteristics (eg, efficacy, safety). The relative importance of these drug characteristics for each participant are then assessed in a web-based exercise, which results in a ranking of the preferred drug classes. A qualitative study using semi-structured interviews was conducted among Dutch patients with T2D who were or had ever been under pharmacological treatment for T2D. The audio-recorded interviews were transcribed verbatim. Thematic analysis was conducted. Results:Fifteen patients participated (median age 64 years, nine women, and most had T2D >10 years). Risk of hypoglycaemia was most often the characteristic to which patients attached the highest importance (n=5). A glucagon-like peptide-1-antagonist weekly injection fitted best the preferences of most patients (n=8). The interviews revealed improvements for text, pictograms and figures, and formatting, and increased comprehension of how patients completed the DA. Regarding usability, missing information was identified, as well as patients' perspectives about the usefulness of the DA and its role in shared-decision making. Conclusion:The DA was considered promising for shared-decision making but further improvements regarding its comprehensibility and usability are needed, for which this study provides clear guidance.

Background: Studies on serially measured GDF-15 (growth differentiation factor 15) in acute heart failure (HF) are limited. Moreover, several pathophysiological pathways contribute to HF. Therefore, we aimed to explore the (additional) prognostic value of serially measured GDF-15 using a multi-marker approach to more accurately predict HF risk. Methods: TRIUMPH (Translational Initiative on Unique and Novel Strategies for Management of Patients With Heart Failure) is a prospective cohort of 496 patients with acute HF who were enrolled in 14 hospitals in the Netherlands between 2009 and 2014. Blood sampling was scheduled at 7 moments during 1-year follow-up. GDF-15, NT-proBNP (N-terminal pro-B-type natriuretic peptide), ST2 (suppression of tumorigenicity 2), galectin-3, troponin I, and creatinine were measured in a central laboratory. We associated repeated measurements of these biomarkers with the composite primary end point of all-cause mortality and HF rehospitalization, using multivariable joint modeling. Results: Median age was 74 years, and 37% were women. Median baseline GDF-15 was 4632 pg/mL. The primary end point was reached in 188 (40%) patients. The average estimated GDF-15 level increased weeks before the primary end point was reached. The hazard ratio per 1 SD difference in log-GDF-15 was 2.14 (95% CI, 1.78–2.57) unadjusted, 1.96 (1.49–2.53) after adjustment for clinical confounders and 1.44 (1.05–1.91) when jointly modeled with all biomarkers. The adjusted HRs for NT-proBNP were 2.38 (1.78–3.33) and 1.52 (1.15–2.08), respectively. The multimarker model combining GDF-15, NT-proBNP, and troponin I provided a favorable risk discrimination (area under the curve=0.785). Conclusions: Sequentially measured GDF-15 independently and dynamically predicts risk of adverse outcomes during 1-year follow-up after index admission for acute HF. NT-proBNP remains a robust predictor among potential candidates. Multiple biomarkers should be considered for stratification in clinical practice. Registration: URL: https://www.trialregister.nl/trial/1783 ; Unique Identifier: NTR1893. (The trial can be found temporarily at https://trialsearch.who.int/Trial2.aspx?TrialID=NTR1893 .)

AIMS:Renal dysfunction is one of the most critical risk factors for developing heart failure (HF). However, the association between repeated measures of renal function and incident HF remains unclear. Therefore, this study investigated the longitudinal trajectories of urinary albumin excretion (UAE) and serum creatinine and their association with new-onset HF and all-cause mortality. METHODS AND RESULTS:Using group-based trajectory analysis, we estimated trajectories of UAE and serum creatinine in 6881 participants from the Prevention of Renal and Vascular End-stage Disease (PREVEND) study and their association with new-onset HF and all-cause death during the 11-years of follow-up. Most participants had stable low UAE or serum creatinine. Participants with persistently higher UAE or serum creatinine were older, more often men, and more often had comorbidities, such as diabetes, a previous myocardial infarction or dyslipidaemia. Participants with persistently high UAE had a higher risk of new-onset HF or all-cause mortality, whereas stable serum creatinine trajectories showed a linear association for new-onset HF and no association with all-cause mortality. CONCLUSION:Our population-based study identified different but often stable longitudinal patterns of UAE and serum creatinine. Patients with persistently worse renal function, such as higher UAE or serum creatinine, were at a higher risk of HF or mortality.