CONTEXT:Diabetes mellitus (DM), a possible adverse effect of childhood cancer treatment, is strongly associated with cardiovascular disease and early mortality in adult childhood cancer survivors (CCS). OBJECTIVE:Here, we assess the prevalence and determinants of DM in our nationwide CCS cohort. METHODS:In this cross-sectional study, the prevalence of DM was assessed in 2338 CCS, using the Lifelines cohort (n = 132 226 adults with no history of cancer) as a reference. DM was defined through serum glucose measurement (fasting glucose ≥7.0 mmol/L or nonfasting ≥11.1 mmol/L) and/or self-report (previous diagnosis and/or medication use). Multivariable logistic regression models, adjusted for age, sex, and body mass index (BMI), were used to assess the cohort effect on the presence of DM. Multivariable logistic regression analysis was used to identify determinants of DM in CCS. RESULTS:Survivors (median age 34.7 years, median follow-up time 27.1 years) showed increased odds for hyperglycemia (aOR = 2.72; 95% CI, 2.06-3.59), previous DM diagnosis (aOR = 3.03; 95% CI, 2.33-3.95), and antidiabetic medication use (aOR = 2.94; 95% CI, 2.17-3.99), compared to the reference cohort. Age (OR = 4.32; 95% CI, 1.84-10.15, >35 vs 18-35 years), BMI (OR = 1.12; 95% CI, 1.08-1.16, per point), family history of DM (OR = 2.38; 95% CI, 1.51-3.76), prior abdominal/pelvic radiotherapy (OR = 4.19; 95% CI, 2.32-7.55), total body irradiation (OR = 14.31; 95% CI, 6.98-29.34), hypogonadism (OR = 2.40; 95% CI, 1.15-4.99), hypertension (OR = 1.71; 95% CI, 1.06-2.76), and dyslipidemia (OR = 3.81; 95% CI, 2.15-6.75) were associated with DM in CCS. A statistically significant interaction between age and sex on the development of DM in survivors was identified. CONCLUSION:The identified 3-fold increased risk of DM in CCS, along with the clinically relevant and some modifiable determinants, underscores the importance of early risk-based screening and the exploration of lifestyle interventions in this population.

This pilot study explores the feasibility of using text from Electronic Health Record (EHR) at the University Medical Center Utrecht to classify patient eligibility for cardiovascular risk management. The primary goal is to improve the identification of at-risk patients and facilitate timely, personalized interventions. Through a ResNet architecture, which is used as a feature extractor, the outputs are then passed into a neural network classifier to predict patient eligibility for cardiovascular risk management. Despite excluding numerical data from EHR during model training and inference, and the imbalanced nature of the dataset, the model achieved promising results with an accuracy of 85

Background The routine diagnostic process increasingly entails the processing of high-volume and high-dimensional data that cannot be directly visualised. This processing may provide scaling issues that limit the implementation of these types of data into research as well as integrated diagnostics in routine care. Here, we investigate whether we can use existing dimension reduction techniques to provide visualisations and analyses for a complete bloodcount (CBC) while maintaining representativeness of the original data. We considered over 3 million CBC measurements encompassing over 70 parameters of cell frequency, size and complexity from the UMC Utrecht UPOD database. We evaluated PCA as an example of a linear dimension reduction techniques and UMAP, TriMap and PaCMAP as non-linear dimension reduction techniques. We assessed their technical performance using quality metrics for dimension reduction as well as biological representation by evaluating preservation of diurnal, age and sex patterns, cluster preservation and the identification of leukemia patients. Results We found that, for clinical hematology data, PCA performs systematically better than UMAP, TriMap and PaCMAP in representing the underlying data. Biological relevance was retained for periodicity in the data. However, we also observed a decrease in predictive performance of the reduced data for both age and sex, as well as an overestimation of clusters within the reduced data. Finally, we were able to identify the diverging patterns for leukemia patients after use of dimensionality reduction methods. Conclusions We conclude that for hematology data, the use of unsupervised dimension reduction techniques should be limited to data visualization applications, as implementing them in diagnostic pipelines may lead to decreased quality of integrated diagnostics in routine care.

Local haemodynamics control arterial homeostasis and dysfunction by generating wall shear stress (WSS) which regulates endothelial cell (EC) physiology. Here we use a zebrafish model to identify genes that regulate EC proliferation in response to flow. Suppression of blood flow in zebrafish embryos (by targeting cardiac troponin) reduced EC proliferation in the intersegmental vessels (ISVs) compared to controls exposed to flow. The expression of candidate regulators of proliferation was analysed in EC isolated from zebrafish embryos by qRT-PCR. Genes shown to be expressed in EC were analysed for the ability to regulate proliferation in zebrafish vasculature exposed to flow or no-flow conditions using a knockdown approach. wnk1 negatively regulated proliferation in no-flow conditions, whereas fzd5, gsk3β, trpm7 and bmp2a promoted proliferation in EC exposed to flow. Immunofluorescent staining of mammalian arteries revealed that WNK1 is expressed at sites of low WSS in the murine aorta, and in EC overlying human atherosclerotic plaques. We conclude that WNK1 is expressed in EC at sites of low WSS and in diseased arteries and may influence vascular homeostasis by reducing EC proliferation.

Objective Acute kidney injury (AKI) is easily missed and underdiagnosed in routine clinical care. Timely AKI management is important to decrease morbidity and mortality risks. We recently implemented an AKI e-alert at the University Medical Center Utrecht, comparing plasma creatinine concentrations with historical creatinine baselines, thereby identifying patients with AKI. This alert is limited to data from tertiary care, and primary care data can increase diagnostic accuracy for AKI. We assessed the added value of linking primary care data to tertiary care data, in terms of timely diagnosis or excluding AKI. Methods With plasma creatinine tests for 84,984 emergency department (ED) visits, we applied the Kidney Disease Improving Global Outcome guidelines in both tertiary care-only data and linked data and compared AKI cases. Results Using linked data, the presence of AKI could be evaluated in an additional 7886 ED visits. Sex- and age-stratified analyses identified the largest added value for women (an increase of 4095 possible diagnoses) and patients ≥60 years (an increase of 5190 possible diagnoses). We observed 398 additional visits where AKI was diagnosed, as well as 185 cases where AKI could be excluded. We observed no overall decrease in time between baseline and AKI diagnosis (28.4 days vs. 28.0 days). For cases where AKI was diagnosed in both data sets, we observed a decrease of 2.8 days after linkage, indicating a timelier diagnosis of AKI. Conclusions Combining primary and tertiary care data improves AKI diagnostic accuracy in routine clinical care and enables timelier AKI diagnosis.

CD40L–CD40–TRAF signaling plays a role in atherosclerosis progression and affects the pathogenesis of coronary heart disease (CHD). We tested the hypothesis that CD40L–CD40–TRAF signaling is a potential therapeutic target in hyperlipidemia, diabetes, and hypertension. In mouse models of hyperlipidemia plus diabetes (db/db mice) or hypertension (1 mg/kg/d angiotensin-II for 7 days), TRAF6 inhibitor treatment (2.5 mg/kg/d for 7 or 14 days) normalized markers of oxidative stress and inflammation. As diabetes and hypertension are important comorbidities aggravating CHD, we explored whether the CD40L–CD40–TRAF signaling cascade and their associated inflammatory pathways are expressed in CHD patients suffering from comorbidities. Therefore, we analyzed vascular bypass material (aorta or internal mammary artery) and plasma from patients with CHD with diabetes and/or hypertension. Our Olink targeted plasma proteomic analysis using the IMMUNO-ONCOLOGY panel revealed a pattern of step-wise increase for 13/92 markers of low-grade inflammation with significant changes. CD40L or CD40 significantly correlated with 38 or 56 other inflammatory targets. In addition, specific gene clusters that correlate with the comorbidities were identified in isolated aortic mRNA of CHD patients through RNA-sequencing. These signaling clusters comprised CD40L–CD40–TRAF, immune system, hemostasis, muscle contraction, metabolism of lipids, developmental biology, and apoptosis. Finally, immunological analysis revealed key markers correlated with comorbidities in CHD patients, such as CD40L, NOX2, CD68, and 3-nitrotyrosine. These data indicate that comorbidities increase inflammatory pathways in CHD, and targeting these pathways will be beneficial in reducing cardiovascular events in CHD patients with comorbidities.

Background: Dilated cardiomyopathy (DCM) involves myocardial remodeling, characterized by significant fibrosis and extracellular matrix expansion. These changes impair heart function, increasing the risk of heart failure and sudden cardiac death. This study investigates the prognostic value of circulating fibrosis biomarkers as a less invasive method in DCM patients. Methods: Plasma samples from 185 patients with confirmed DCM were analyzed to measure 13 circulating biomarkers using Luminex bead-based multiplex assays and ELISA. The prognostic value of these biomarkers was evaluated concerning heart failure-associated events and all-cause mortality. Results: Elevated MMP-2 levels (>1519.3 ng/mL) were linked to older age, higher diabetes prevalence, lower HDL, increased NT-proBNP and hs-TnT levels, and severe systolic dysfunction. High TIMP-1 levels (>124.9 ng/mL) correlated with elevated NT-proBNP, more atrial fibrillation, reduced exercise capacity, and larger right ventricles. Increased GDF-15 levels (>1213.9 ng/mL) were associated with older age, systemic inflammation, renal impairment, and poor exercise performance. Elevated OPN levels (>81.7 ng/mL) were linked to higher serum creatinine and NT-proBNP levels. Over a median follow-up of 32.4 months, higher levels of these biomarkers predicted worse outcomes, including increased risks of heart failure-related events and mortality. Conclusions: Circulating fibrosis biomarkers, particularly MMP-2, TIMP-1, GDF-15, and OPN, are valuable prognostic tools in DCM. They reflect the severity of myocardial remodeling and systemic disease burden, aiding in risk stratification and therapeutic intervention. Integrating these biomarkers into clinical practice could improve DCM management and patient prognosis.

Topic: 29. Iron metabolism, deficiency and overload Background: Red blood cell distribution width (RDW) is a biomarker associated with a variety of clinical outcomes. While anemia and subclinical inflammation have been posed as underlying pathophysiology, it is unclear what mechanisms underlie these associations. Aims: We aimed to unravel the mechanisms in silico by using a large clinical dataset and subsequently validate our findings in vitro. Methods: We retrieved complete blood counts (CBC) from 1,403,663 blood samples from the Utrecht Patient Oriented Database as measured on the Abbott CellDyn Sapphire, in order to model RDW by using gradient boosting regression (XGBoost) with different sets of predictors: one set with all variables (set 1), one set without percentage microcytic (pMIC) and macrocytic erythrocytes (pMAC) and mean corpuscular volume (MCV) (set 2), and one set without these variables and reticulocyte-related variables (set 3). We performed analyses in patients with and without anemia, in men and women, and in patients younger and older than 50. Additionally, we validated our model using data from the Abbott Allinity (n = 70) and data from the Abbott CellDyn Sapphire as measured in primary and secondary care (n = 513,564). We then validated our hypothesis regarding oxidative stress using an in vitro approach, where we induced blood samples with oxidative stress. Additionally, we measured erythrocyte deformability, by using Laser Optical Rotational Red Cell Analyzer techniques, and vesiculation. Results: Only pMIC and macrocytic pMAC erythrocytes and MCV were most important in modelling RDW (RMSE=0.40, R2=0.96), considering removing the variables in sets 2 (RMSE=1.00, R2=0.76) and 3 (RMSE=1.34, R2=0.57) resulted in significantly worse performance. Subgroup analyses showed similar performance pattern, and validation in both Allinity data (RMSE=0.75, R2=0.87) and primary and secondary care data (RMSE=0.45, R2=0.94) confirmed the generalizability of the model as built on set 1. Our In vitro result after induction of oxidative stress underscored our results, as we observed an increased RDW and decreased erythrocyte volume, as well as increased pMIC, yet no vesiculation was observed. Furthermore, we found that deformability decreased as a result of oxidative stress possibly affecting sphericity of erythrocytes. Summary/Conclusion: We found that erythrocyte size, especially pMIC, is most informative in modelling RDW, but no role for anemia or chronic subclinical inflammation. Furthermore, oxidative stress may affect deformability of erythrocytes, and may therefore play a role in the association between RDW and clinical outcomes.Keywords: Red blood cell, Erythrocyte, Machine learning

Background: Surveillance programs in abdominal aortic aneurysms (AAA) are mainly based on imaging and leave room for improvement to timely identify patients at risk for AAA growth. Many biomarkers are dysregulated in patients with AAA, which fuels interest in biomarkers as indicators of disease progression. We examined associations of 92 cardiovascular disease (CVD)-related circulating biomarkers with AAA and sac volume. Methods: In a cross-sectional analysis, we separately investigated (1) 110 watchful waiting (WW) patients (undergoing periodic surveillance imaging without planned intervention) and (2) 203 patients after endovascular aneurysm repair (EVAR). The Cardiovascular Panel III (Olink Proteomics AB, Sweden) was used to measure 92 CVD-related circulating biomarkers. We used cluster analyses to investigate protein-based subphenotypes, and linear regression to examine associations of biomarkers with AAA and sac volume on CT scans. Results: Cluster analyses revealed two biomarker-based subgroups in both WW and EVAR patients, with higher levels of 76 and 74 proteins, respectively, in one subgroup versus the other. In WW patients, uPA showed a borderline significant association with AAA volume. Adjusting for clinical characteristics, there was a difference of −0.092 (−0.148, −0.036) loge mL in AAA volume per SD uPA. In EVAR patients, after multivariable adjustment, four biomarkers remained significantly associated with sac volume. The mean effects on sac volume per SD difference were: LDLR: −0.128 (−0.212, −0.044), TFPI: 0.139 (0.049, 0.229), TIMP4: 0.110 (0.023, 0.197), IGFBP-2: 0.103 (0.012, 0.194). Conclusion: LDLR, TFPI, TIMP4, and IGFBP-2 were independently associated with sac volume after EVAR. Subgroups of patients with high levels of the majority of CVD-related biomarkers emphasize the intertwined relationship between AAA and CVD. ClinicalTrials.gov Identifier: NCT03703947.

Additional file 5: Table S4. Frequency of lipid-related publications for the PoPS+ prioritized genes.

Purpose Although elective surgery is generally safe, some procedures remain associated with an increased risk of complications. Improved preoperative risk stratification and earlier recognition of these complications may ameliorate postoperative recovery and improve long-term outcomes. The perioperative longitudinal study of complications and long-term outcomes (PLUTO) cohort aims to establish a comprehensive biorepository that will facilitate research in this field. In this profile paper, we will discuss its design rationale and opportunities for future studies.Participants Patients undergoing elective intermediate to high-risk non-cardiac surgery are eligible for enrolment. For the first seven postoperative days, participants are subjected to daily bedside visits by dedicated observers, who adjudicate clinical events and perform non-invasive physiological measurements (including handheld spirometry and single-channel electroencephalography). Blood samples and microbiome specimens are collected at preselected time points. Primary study outcomes are the postoperative occurrence of nosocomial infections, major adverse cardiac events, pulmonary complications, acute kidney injury and delirium/acute encephalopathy. Secondary outcomes include mortality and quality of life, as well as the long-term occurrence of psychopathology, cognitive dysfunction and chronic pain.Findings to date Enrolment of the first participant occurred early 2020. During the inception phase of the project (first 2 years), 431 patients were eligible of whom 297 patients consented to participate (69%). Observed event rate was 42% overall, with the most frequent complication being infection.Future plans The main purpose of the PLUTO biorepository is to provide a framework for research in the field of perioperative medicine and anaesthesiology, by storing high-quality clinical data and biomaterials for future studies. In addition, PLUTO aims to establish a logistical platform for conducting embedded clinical trials.Trial registration number NCT05331118.

IntroductionPatients who have experienced an acute coronary syndrome (ACS) are at risk of a recurrent event, but their level of risk varies. Because of their close temporal relationship with vascular injury, longitudinal measurements of circulating endothelial cells (CECs) carry potential to improve individual risk assessment.MethodsWe conducted an explorative nested case-control study within our multicenter, prospective, observational biomarker study (BIOMArCS) of 844 ACS patients. Following an index ACS, high-frequency blood sampling was performed during 1-year follow-up. CECs were identified using flow cytometric analyses in 15 cases with recurrent event, and 30 matched controls.ResultsCases and controls had a median (25(th)-75(th)percentile) age of 64.1 (58.1-75.1) years and 80% were men. During the months preceding the endpoint, the mean (95%CI) CEC concentration in cases was persistently higher than in controls (12.8 [8.2-20.0] versus 10.0 [7.0-14.4] cells/ml), although this difference was non-significant (P = 0.339). In controls, the mean cell concentration was significantly (P = 0.030) lower in post 30-day samples compared to samples collected within one day after index ACS: 10.1 (7.5-13.6) versus 17.0 (10.8-26.6) cells/ml. Similar results were observed for CEC subsets co-expressing CD133 and CD309 (VEGFR-2) or CD106 (VCAM-1).ConclusionDespite their close relation to vascular damage, no increase in cell concentrations were found prior to the occurrence of a secondary adverse cardiac event.

Background and aims: Patients who underwent carotid endarterectomy (CEA) still have a residual risk of 13% of developing a major adverse cardiovascular event (MACE) within 3 years. Inflammatory processes leading up to MACE are not fully understood. Therefore, we examined blood cell characteristics (BCCs), possibly reflecting inflammatory processes, in relation to MACE to identify BCCs that may contribute to an increased risk. Methods: We analyzed 75 pretreatment BCCs from the Sapphire analyzer, and clinical data from the Athero-Express biobank in relation to MACE after CEA using Random Survival Forests, and a Generalized Additive Survival Model. To understand biological mechanisms, we related the identified variables to intraplaque hemorrhage (IPH).Results: Of 783 patients, 97 (12%) developed MACE within 3 years after CEA. Red blood cell distribution width (RDW) (HR 1.23 [1.02, 1.68], p = 0.022), CV of lymphocyte size (LACV) (HR 0.78 [0.63, 0.99], p = 0.043), neutrophil complexity of the intracellular structure (NIMN) (HR 0.80 [0.64, 0.98], p = 0.033), mean neutrophil size (NAMN) (HR 0.67 [0.55, 0.83], p < 0.001), mean corpuscular volume (MCV) (HR 1.35 [1.09, 1.66], p = 0.005), eGFR (HR 0.65 [0.52, 0.80], p < 0.001); and HDL-cholesterol (HR 0.62 [0.45, 0.85], p = 0.003) were related to MACE. NAMN was related to IPH (OR 0.83 [0.71-0.98], p = 0.02).Conclusions: This is the first study to present a higher RDW and MCV and lower LACV, NIMN and NAMN as biomarkers reflecting inflammatory processes that may contribute to an increased risk of MACE after CEA.& COPY; 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Red blood cell distribution width (RDW) is a biomarker associated with a variety of clinical outcomes. While anemia and subclinical inflammation have been posed as underlying pathophysiology, it is unclear what mechanisms underlie these assocations. Hence, we aimed to unravel the mechanisms in silico using a large clinical dataset and validate our findings in vitro. We retrieved complete blood counts (CBC) from 1,403,663 measurements from the Utrecht Patient Oriented Database, to model RDW using gradient boosting regression. We performed (sex-stratified) analyses in patients with anemia, patients younger/older than 50 and validation across platforms and care settings. We then validated our hypothesis regarding oxidative stress using an in vitro approach. Only percentage microcytic (pMIC) and macrocytic (pMAC) erythrocytes and mean corpuscular volume were most important in modelling RDW (RMSE = 0.40, R 2 = 0.96). Subgroup analyses and validation confirmed our findings. In vitro induction of oxidative stress underscored our results, namely increased RDW and decreased erythrocyte volume, yet no vesiculation was observed. We found that erythrocyte size, especially pMIC, is most informative in predicting RDW, but no role for anemia or inflammation. Oxidative stress affecting the size of the erythrocytes may play a role in the association between RDW and clinical outcomes.

Additional file 17: Table S9. PheWAS UKB-MVP meta-analysis results for each index lipid variant at Bonferroni threshold for multiple testing p<=3.5e-8)

C-reactive protein (CRP) is an acute-phase protein involved in inflammation. Furthermore, CRP is an important biomarker used in diagnostics to predict risk of cardiovascular disease (CVD) in addition to monitoring bacterial and viral infections. To measure plasma CRP, venipuncture is still necessitated and has to be performed by trained phlebotomists. As a solution, dried blood spots (DBS) are used for minimally invasive at-home sampling of blood and can be send to diagnostic laboratories by regular mail. In this study, we included 53 patients that presented to the outpatient clinic of the University Medical Center Utrecht. Capillary finger stick was used to spot blood on a filter paper card and allowed to dry. After extraction of DBS, CRP was analyzed on an automated high-throughput chemistry analyzer. Additional validation steps regarding stability, effect of hematocrit, precision, and limits of blank and quantitation were conducted according to corresponding Clinical and Laboratory Standards Institute standards. An excellent regression analysis of R 2 (95% confidence interval) = 0.986 (0.982–0.989) was found. This enabled correct classification for high CVD risk of all 25 cases with sensitivity (95% CI) of 1.00 (1.00–1.00) and specificity (95% CI) of 0.96 (0.89–1.03) and correct diagnosis of inflammation of 12/13 cases with sensitivity (95% CI) of 0.92 (0.77–1.07) and specificity (95% CI) of 1.00 (1.00–1.00). Furthermore, CRP was found to be stable for 31 days and observed hematocrit variation amongst patients was clinically acceptable. CRP from DBS can be accurately measured on an automated high-throughput chemistry analyzer and used to diagnose inflammation and classify high CVD risk. This method enables individuals to engage in at-home sampling of blood on DBS for (tele)diagnostics, screening programs, patient follow-up, and medication management.

Background: Hyper- and hypothyroidism are prevalent in Western countries and often go unnoticed for long periods. Thyrotropin (TSH) as a biomarker of thyroid dysfunction is regularly measured in venous plasma/serum. In newborn screening for congenital hypothyroidism, TSH is measured from dried blood spots (DBSs). DBS enables minimally invasive (at-home) sampling of a small blood volume that can be sent to diagnostic laboratories by regular mail.Methods: In this study, we included 109 patients who presented to the outpatient clinic of the University Medical Center Utrecht. Capillary finger stick was used to spot blood on a filter paper card and was dried. After extraction of TSH from DBS, method comparison with venous TSH was performed on an automated high-throughput immunoassay analyzer. Additional validation steps regarding stability, effect of hematocrit (Hct), precision, and limits of blank and quantitation were conducted according to corresponding Clinical and Laboratory Standards Institute evaluation protocol.Results: Method comparison of TSH from venous plasma versus finger stick DBSs showed an R-2 [95% confidence interval] = 0.988 [0.986-0.990]. This enabled correct diagnosis of hypothyrotropinemia and hypothyroidism in 12 of 14 and 6 of 7 cases, respectively, with no false positives. Furthermore, TSH from DBS was stable for at least 4 days at temperatures between -20 degrees C and +30 degrees C, and the maximum decrease of eluate TSH was 1.13% for 1% increase in Hct.Conclusions: TSH from DBS may be accurately measured on an automated high-throughput immunoassay analyzer and could be used to diagnose hypothyroidism and, for the first time, hypothyrotropinemia. This method, when confirmed in larger field studies, may enable individuals to engage in (at-home) sampling of blood on DBSs for telediagnostics, screening programs, patient follow-up, and medication management.

Background Childhood cancer survivors appear to be at increased risk of frailty and sarcopenia, but evidence on the occurrence of and high-risk groups for these aging phenotypes is scarce, especially in European survivors. The aim of this cross-sectional study was to assess the prevalence of and explore risk factors for pre-frailty, frailty, and sarcopenia in a national cohort of Dutch childhood cancer survivors diagnosed between 1963 and 2001. Methods Eligible individuals (alive at the time of study, living in the Netherlands, age 18-45 years, and had not previously declined to participate in a late-effects study) from the Dutch Childhood Cancer Survivor Study (DCCSS-LATER) cohort were invited to take part in this cross-sectional study. We defined pre-frailty and frailty according to modified Fried criteria, and sarcopenia according to the European Working Group on Sarcopenia in Older People 2 definition. Associations between these conditions and demographic and treatment-related as well as endocrine and lifestyle-related factors were estimated with two separate multivariable logistic regression models in survivors with any frailty measurement or complete sarcopenia measurements. Findings 3996 adult survivors of the DCCSS-LATER cohort were invited to participate in this cross-sectional study. 1993 non-participants were excluded due to lack of response or a decline to participate and 2003 (50.1%) childhood cancer survivors aged 18-45 years were included. 1114 (55.6%) participants had complete frailty measurements and 1472 (73.5%) participants had complete sarcopenia measurements. Mean age at participation was 33.1 years (SD 7.2). 1037 (51.8%) participants were male, 966 (48.2%) were female, and none were transgender. In survivors with complete frailty measurements or complete sarcopenia measurements, the percentage of pre-frailty was 20.3% (95% CI 18.0-22.7), frailty was 7.4% (6.0-9.0), and sarcopenia was 4.4% (3.5-5.6). In the models for pre-frailty, underweight (odds ratio [OR] 3.38 [95% CI 1.92-5.95]) and obesity (OR 1.67 [1.14-2.43]), cranial irradiation (OR 2.07 [1.47-2.93]), total body irradiation (OR 3.17 [1.77-5.70]), cisplatin dose of at least 600 mg/m2 (OR 3.75 [1.82-7.74]), growth hormone deficiency (OR 2.25 [1.23-4.09]), hyperthyroidism (OR 3.72 [1.63-8.47]), bone mineral density (Z score <=-1 and >-2, OR 1.80 [95% CI 1.31-2.47]; Z score <=-2, OR 3.37 [2.20-5.15]), and folic acid deficiency (OR 1.87 [1.31-2.68]) were considered significant. For frailty, associated factors included age at diagnosis between 10-18 years (OR 1.94 [95% CI 1.19-3.16]), underweight (OR 3.09 [1.42-6.69]), cranial irradiation (OR 2.65 [1.59-4.34]), total body irradiation (OR 3.28 [1.48-7.28]), cisplatin dose of at least 600 mg/m2 (OR 3.93 [1.45-10.67]), higher carboplatin doses (per g/m2; OR 1.15 [1.02-1.31]), cyclophosphamide equivalent dose of at least 20 g/m2 (OR 3.90 [1.65-9.24]), hyperthyroidism (OR 2.87 [1.06-7.76]), bone mineral density Z score <=-2 (OR 2.85 [1.54-5.29]), and folic acid deficiency (OR 2.04 [1.20-3.46]). Male sex (OR 4.56 [95%CI 2.26-9.17]), lower BMI (continuous, OR 0.52 [0.45-0.60]), cranial irradiation (OR 3.87 [1.80-8.31]), total body irradiation (OR 4.52 [1.67-12.20]), hypogonadism (OR 3.96 [1.40-11.18]), growth hormone deficiency (OR 4.66 [1.44-15.15]), and vitamin B12 deficiency (OR 6.26 [2.17-1.81]) were significantly associated with sarcopenia. Interpretation Our findings show that frailty and sarcopenia occur already at a mean age of 33 years in childhood cancer survivors. Early recognition and interventions for endocrine disorders and dietary deficiencies could be important in minimising the risk of pre-frailty, frailty, and sarcopenia in this population. Copyright (C) 2023 The Author(s). Published by Elsevier Ltd.