A Biomarker-Based Diagnostic Model for Cardiac Dysfunction in Childhood Cancer Survivors

Background: Childhood cancer survivors at risk for heart failure undergo lifelong echocardiographic surveillance. Previous studies reported the limited diagnostic accuracy of N-terminal pro–B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hs-cTnT) in detecting left ventricular (LV) dysfunction. However, potential enhanced diagnostic accuracy through the combination of biomarkers and clinical characteristics has been suggested. Objectives: The aim of this study was to develop and internally validate a diagnostic model that combines cardiac biomarkers with clinical characteristics for effectively ruling in or ruling out LV dysfunction in childhood cancer survivors. Methods: A multicenter cross-sectional study included 1,334 survivors (median age 34.2 years) and 278 siblings (median age 36.8 years). Logistic regression models were developed and validated through bootstrapping, combining biomarkers with clinical characteristics. Results: Abnormal NT-proBNP levels were observed in 22.1% of survivors compared with 5.4% of siblings, whereas hs-cTnT levels exceeding 10 ng/L were uncommon in both survivors (5.9%) and siblings (5.0%). The diagnostic models demonstrated improvement upon the addition of NT-proBNP and hs-cTnT to clinical characteristics, resulting in an increased C statistic from 0.69 to 0.73 for LV ejection fraction (LVEF) &lt;50% and a more accurate prediction of more severe LV dysfunction, with the C statistic increasing from 0.80 to 0.86 for LVEF &lt;45%. For LVEF &lt;50% (prevalence 10.9%), 16.9% of survivors could be effectively ruled out with high sensitivity (95.4%; 95% CI: 90.4%-99.3%) and negative predictive value (97.5%; 95% CI: 94.6%-99.7%). Similarly, for LVEF &lt;45% (prevalence 3.4%), 53.0% of survivors could be ruled out with moderate to high sensitivity (91.1%; 95% CI: 79.2%-100%) and high negative predictive value (99.4%; 95% CI: 98.7%-100%). Conclusions: The biomarker-based diagnostic model proves effective in ruling out LV dysfunction, offering the potential to minimize unnecessary surveillance echocardiography in childhood cancer survivors. External validation is essential to confirm these findings. (Early Detection of Cardiac Dysfunction in Childhood Cancer Survivors; A DCOG LATER Study; https://onderzoekmetmensen.nl/nl/trial/23641)</p

A Biomarker-Based Diagnostic Model for Cardiac Dysfunction in Childhood Cancer Survivors

Background: Childhood cancer survivors at risk for heart failure undergo lifelong echocardiographic surveillance. Previous studies reported the limited diagnostic accuracy of N-terminal pro–B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hs-cTnT) in detecting left ventricular (LV) dysfunction. However, potential enhanced diagnostic accuracy through the combination of biomarkers and clinical characteristics has been suggested. Objectives: The aim of this study was to develop and internally validate a diagnostic model that combines cardiac biomarkers with clinical characteristics for effectively ruling in or ruling out LV dysfunction in childhood cancer survivors. Methods: A multicenter cross-sectional study included 1,334 survivors (median age 34.2 years) and 278 siblings (median age 36.8 years). Logistic regression models were developed and validated through bootstrapping, combining biomarkers with clinical characteristics. Results: Abnormal NT-proBNP levels were observed in 22.1% of survivors compared with 5.4% of siblings, whereas hs-cTnT levels exceeding 10 ng/L were uncommon in both survivors (5.9%) and siblings (5.0%). The diagnostic models demonstrated improvement upon the addition of NT-proBNP and hs-cTnT to clinical characteristics, resulting in an increased C statistic from 0.69 to 0.73 for LV ejection fraction (LVEF) &lt;50% and a more accurate prediction of more severe LV dysfunction, with the C statistic increasing from 0.80 to 0.86 for LVEF &lt;45%. For LVEF &lt;50% (prevalence 10.9%), 16.9% of survivors could be effectively ruled out with high sensitivity (95.4%; 95% CI: 90.4%-99.3%) and negative predictive value (97.5%; 95% CI: 94.6%-99.7%). Similarly, for LVEF &lt;45% (prevalence 3.4%), 53.0% of survivors could be ruled out with moderate to high sensitivity (91.1%; 95% CI: 79.2%-100%) and high negative predictive value (99.4%; 95% CI: 98.7%-100%). Conclusions: The biomarker-based diagnostic model proves effective in ruling out LV dysfunction, offering the potential to minimize unnecessary surveillance echocardiography in childhood cancer survivors. External validation is essential to confirm these findings. (Early Detection of Cardiac Dysfunction in Childhood Cancer Survivors; A DCOG LATER Study; https://onderzoekmetmensen.nl/nl/trial/23641)</p

Echocardiography protocol for early detection of cardiac dysfunction in childhood cancer survivors in the multicenter DCCSS LATER 2 CARD study:Design, feasibility, and reproducibility

Background Cardiotoxicity is a well-known side effect after anthracyclines and chest radiotherapy in childhood cancer survivors (CCS). The DCCSS LATER 2 CARD (cardiology) study includes evaluation of echocardiographic measurements for early identification of CCS at highest risk of developing heart failure. This paper describes the design, feasibility, and reproducibility of the echocardiography protocol. Methods Echocardiograms from CCS and sibling controls were prospectively obtained at the participating centers and centrally analyzed. We describe the image acquisition, measurement protocol, and software-specific considerations for myocardial strain analyses. We report the feasibility of the primary outcomes of systolic and diastolic function, as well as reproducibility analyses in 30 subjects. Results We obtained 1,679 echocardiograms. Biplane ejection fraction (LVEF) measurement was feasible in 91% and 96% of CCS and siblings, respectively, global longitudinal strain (GLS) in 80% and 91%, global circumferential strain (GCS) in 86% and 89%, and >= 2 diastolic function parameters in 99% and 100%, right ventricle free wall strain (RVFWS) in 57% and 65%, and left atrial reservoir strain (LASr) in 72% and 79%. Intra-class correlation coefficients for inter-observer variability were 0.85 for LVEF, 0.76 for GLS, 0.70 for GCS, 0.89 for RVFWS and 0.89 for LASr. Intra-class correlation coefficients for intra-observer variability were 0.87 for LVEF, 0.82 for GLS, 0.82 for GCS, 0.85 for RVFWS and 0.79 for LASr. Conclusion The DCCSS LATER 2 CARD study includes a protocolized echocardiogram, with feasible and reproducible primary outcome measurements. This ensures high-quality outcome data for prevalence estimates and for reliable comparison of cardiac function parameters

Candidate Plasma Biomarkers to Detect Anthracycline‐Related Cardiomyopathy in Childhood Cancer Survivors: A Case Control Study in the Dutch Childhood Cancer Survivor Study

Background Plasma biomarkers may aid in the detection of anthracycline‐related cardiomyopathy (ACMP). However, the currently available biomarkers have limited diagnostic value in long‐term childhood cancer survivors. This study sought to identify diagnostic plasma biomarkers for ACMP in childhood cancer survivors. Methods and Results We measured 275 plasma proteins in 28 ACMP cases with left ventricular ejection fraction <45%, 29 anthracycline‐treated controls with left ventricular ejection fraction ≥53% matched on sex, time after cancer, and anthracycline dose, and 29 patients with genetically determined dilated cardiomyopathy with left ventricular ejection fraction <45%. Multivariable linear regression was used to identify differentially expressed proteins. Elastic net model, including clinical characteristics, was used to assess discrimination of proteins diagnostic for ACMP. NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) and the inflammatory markers CCL19 (C‐C motif chemokine ligands 19) and CCL20, PSPD (pulmonary surfactant protein‐D), and PTN (pleiotrophin) were significantly upregulated in ACMP compared with controls. An elastic net model selected 45 proteins, including NT‐proBNP, CCL19, CCL20 and PSPD, but not PTN, that discriminated ACMP cases from controls with an area under the receiver operating characteristic curve (AUC) of 0.78. This model was not superior to a model including NT‐proBNP and clinical characteristics (AUC=0.75; P=0.766). However, when excluding 8 ACMP cases with heart failure, the full model was superior to that including only NT‐proBNP and clinical characteristics (AUC=0.75 versus AUC=0.50; P=0.022). The same 45 proteins also showed good discrimination between dilated cardiomyopathy and controls (AUC=0.89), underscoring their association with cardiomyopathy. Conclusions We identified 3 specific inflammatory proteins as candidate plasma biomarkers for ACMP in long‐term childhood cancer survivors and demonstrated protein overlap with dilated cardiomyopathy

Candidate Plasma Biomarkers to Detect Anthracycline-Related Cardiomyopathy in Childhood Cancer Survivors: A Case Control Study in the Dutch Childhood Cancer Survivor Study

BACKGROUND: Plasma biomarkers may aid in the detection of anthracycline-related cardiomyopathy (ACMP). However, the cur-rently available biomarkers have limited diagnostic value in long-term childhood cancer survivors. This study sought to identify diagnostic plasma biomarkers for ACMP in childhood cancer survivors. METHODS AND RESULTS: We measured 275 plasma proteins in 28 ACMP cases with left ventricular ejection fraction <45%, 29 anthracycline-treated controls with left ventricular ejection fraction ≥53% matched on sex, time after cancer, and anthracy-cline dose, and 29 patients with genetically determined dilated cardiomyopathy with left ventricular ejection fraction <45%. Multivariable linear regression was used to identify differentially expressed proteins. Elastic net model, including clinical char-acteristics, was used to assess discrimination of proteins diagnostic for ACMP. NT-proBNP (N-terminal pro-B-type natriuretic peptide) and the inflammatory markers CCL19 (C-C motif chemokine ligands 19) and CCL20, PSPD (pulmonary surfactant protein-D), and PTN (pleiotrophin) were significantly upregulated in ACMP compared with controls. An elastic net model selected 45 proteins, including NT-proBNP, CCL19, CCL20 and PSPD, but not PTN, that discriminated ACMP cases from controls with an area under the receiver operating characteristic curve (AUC) of 0.78. This model was not superior to a model including NT-proBNP and clinical characteristics (AUC=0.75; P=0.766). However, when excluding 8 ACMP cases with heart failure, the full model was superior to that including only NT-proBNP and clinical characteristics (AUC=0.75 versus AUC=0.50; P=0.022). The same 45 proteins also showed good discrimination between dilated cardiomyopathy and controls (AUC=0.89), underscoring their association with cardiomyopathy. CONCLUSIONS: We identified 3 specific inflammatory proteins as candidate plasma biomarkers for ACMP in long-term childhood cancer survivors and demonstrated protein overlap with dilated cardiomyopathy