Risk prediction of major cardiac adverse events and all-cause death following covid-19 hospitalization at one year follow-up: The HOPE-2 score

BACKGROUND

Long-term consequences of COVID-19 are still partly known.

AIM OF THE STUDY

To derive a clinical score for risk prediction of long-term major cardiac adverse events (MACE) and all cause death in COVID-19 hospitalized patients.

METHODS

2573 consecutive patients were enrolled in a multicenter, international registry (HOPE-2) from January 2020 to April 2021 and identified as the derivation cohort. Five hundred and twenty-six patients from the Cardio-Covid-Italy registry were considered as external validation cohort. A long-term prognostic risk score for MACE and all cause death was derived from a multivariable regression model.

RESULTS

Out of 2573 patients enrolled in the HOPE-2 registry, 1481 (58 %) were male, with mean age of 60±16 years. At long-term follow-up, the overall rate of patients affected by MACE and/or all cause death was 7.8 %. After multivariable regression analysis, independent predictors of MACE and all cause death were identified. The HOPE-2 prognostic score was therefore calculated by giving: 1-4 points for age class (<65 years, 65-74, 75-84, ≥85), 3 points for history of cardiovascular disease, 1 point for hypertension, 3 points for increased troponin serum levels at admission and 2 points for acute renal failure during hospitalization. Score accuracy at ROC curve analysis was 0.79 (0.74 at external validation). Stratification into 3 risk groups (<3, 3-6, >6 points) classified patients into low, intermediate and high risk. The observed MACE and all-cause death rates were 1.9 %, 9.4 % and 26.3 % for low- intermediate and high-risk patients, respectively (Log-rank test p < 0.01).

CONCLUSIONS

The HOPE-2 prognostic score may be useful for long-term risk stratification in patients with previous COVID-19 hospitalization. High-risk patients may require a strict follow-up.

Sodium glucose co-transporter 2 inhibitors and quality of life in patients with heart failure: a comprehensive systematic review and meta-analysis of randomized controlled trials

BACKGROUND

Sodium glucose co-transporter 2 inhibitors (SGLT2i) are one of the cornerstones of heart failure (HF) therapy. While benefits in terms of HF hospitalizations and death are well established, their impact on quality-of-life (QoL) has not been systematically investigated.

OBJECTIVE

This systematic review and meta-analysis aims to evaluate the impact of SGLT2i treatment on QoL in patients with HF, by analysing data from randomized clinical trials (RCTs).

METHODS

We identified a total of 23 RCTs that investigated the role of SGLT2i on quality of life in patients with HF, irrespective of their left ventricular ejection fraction (LVEF). RCTs that used Kansas City Cardiomyopathy Questionnaire overall summary score (KCCQ-OSS) to assess QoL and had a minimum follow-up of 3 months were included. The difference in mean change of the KCCQ-OSS between the SGLT2i group and the standard of care (SOC) group at 3 and 6 months from baseline was considered as the outcome measure.

FINDINGS

Fourteen RCTs (21 737 patients) were included in the analysis. A significant improvement in KCCQ-OSS over time (p < 0.001) was observed in both patients receiving SOC and those receiving SGLT2i in addition. The pooled estimate showed a significant improvement of 1.94 points [95% confidence interval (CI), 1.41-2.46] in KCCQ-OSS mean change at 3 months and of 2.18 points (95% CI, 1.13-3.24) at 6 months from baseline, with SGLT2i compared to SOC alone, irrespective of LVEF. A greater improvement in KCCQ-OSS was observed among patients with a recent episode of worsening HF compared to those with chronic stable HF.

CONCLUSIONS

Among patients with HF, irrespective of their LVEF and clinical status, the addition of SGLT2i to SOC demonstrated a significant improvement in quality of life as early as at 3-month follow-up.

Surrogate endpoints for overall survival in randomized clinical trials testing immune checkpoint inhibitors: a systematic review and meta-analysis

Introduction

There is debate on which are the best surrogate endpoint and metric to capture treatment effect on overall survival (OS) in RCTs testing immune-checkpoint inhibitors (ICIs).

Methods

We systematically searched for RCTs testing ICIs in patients with advanced solid tumors. Inclusion criteria were: RCTs i) assessing PD-(L)1 and CTLA-4 inhibitors either as monotherapy or in combination with another ICI, and/or targeted therapy, and/or chemotherapy, in patients with advanced solid tumors; ii) randomizing at least 100 patients. We performed a meta-analysis of RCTs to compare the surrogacy value of PFS and modified-PFS (mPFS) for OS in RCTs testing ICIs, when the treatment effect is measured by the hazard ratio (HR) for OS, and by the HR and the ratio of restricted mean survival time (rRMST) for PFS and mPFS.

Results

61 RCTs (67 treatment comparisons and 36,034 patients) were included in the analysis. In comparisons testing ICI plus chemotherapy, HRPFS and HRmPFS both had a strong surrogacy value (R2 = 0.74 and R2 = 0.81, respectively). In comparisons testing ICI as monotherapy, HRPFS was the best surrogate, although having a moderate correlation (R2 = 0.58). In comparisons testing ICI plus other treatment(s), the associations were very weak for all the surrogate endpoints and treatment effect measures, with R2 ranging from 0.01 to 0.22.

Conclusion

In RCTs testing ICIs, the value of potential surrogates for HROS was strongly affected by the type of treatment(s) tested. The evidence available supports HRPFS as the best surrogate, and disproves the use of alternative endpoints, such as the mPFS, or treatment effect measures, such as the RMST.

Radiological Features of Male Breast Neoplasms: How to Improve the Management of a Rare Disease

The primary aim of our study was to assess the main mammographic and ultrasonographic features of invasive male breast malignancies. The secondary aim was to evaluate whether a specific radiological presentation would be associated with a worse receptor profile. Radiological images (mammography and/or ultrasound) of all patients who underwent surgery for male invasive breast cancer in our institution between 2008 and 2023 were retrospectively analyzed by two breast radiologists in consensus. All significant features of radiological presentation known in the literature were re-evaluated. Fifty-six patients were selected. The mean age at surgery of patients was 69 years (range: 35-81); in 82% of cases (46 patients), the histologic outcome was invasive ductal carcinoma. A total of 28 out of 56 (50%) patients had preoperative mammography; in 9/28 cases (32%), we found a mass with microcalcifications on mammography. The mass presented high density in 25 out of 28 patients (89%); the mass showed irregular margins in 15/28 (54%) cases. A total of 46 out of 56 patients had preoperative ultrasounds. The lesion showed a solid mass in 41/46 (89%) cases. In 5/46 patients (11%), the lesion was a mass with a mixed (partly liquid-partly solid) structure. We did not find any statistically significant correlation between major types of radiological presentation and tumor receptor arrangement. Knowledge of the main radiologic presentation patterns of malignant male breast neoplasm can help better manage this type of disease, which is rare but whose incidence is increasing.

Right ventricular to pulmonary artery coupling and outcome in patients with cardiac amyloidosis

AIMS

To investigate the prognostic value of the right ventricle-to-pulmonary artery (RV-PA) coupling in patients with either transthyretin (ATTR) or immunoglobulin light-chain (AL) cardiac amyloidosis (CA).

METHODS AND RESULTS

Overall, 283 patients with CA from 3 Italian high-volume centres were included (median age 76 years; 63% males; 53% with ATTR-CA, 47% with AL-CA). The RV-PA coupling was evaluated by using the tricuspid annular plane systolic excursion/pulmonary artery systolic pressure (TAPSE/PASP) ratio. The median value of TAPSE/PASP was 0.45 (0.33-0.63) mm/mmHg. Patients with a TAPSE/PASP ratio <0.45 were older, had lower systolic blood pressure, more severe symptoms, higher cardiac troponin and N-terminal pro-B-type natriuretic peptide levels, greater left ventricular (LV) thickness, and worse LV systolic and diastolic function. A TAPSE/PASP ratio <0.45 was independently associated with a higher risk of all-cause death or heart failure (HF) hospitalization [hazard ratio (HR) 1.98, 95% confidence interval (CI) 1.32-2.96; P = 0.001] and all-cause death (HR 2.18, 95% CI 1.31-3.62; P = 0.003). The TAPSE/PASP ratio reclassified the risk of both endpoints [net reclassification index 0.46 (95% CI 0.18-0.74) P = 0.001 and 0.49 (0.22-0.77) P < 0.001, respectively], while TAPSE or PASP alone did not (all P > 0.05). The prognostic impact of the TAPSE/PASP ratio was significant both in AL-CA patients (HR for the composite endpoint 2.47, 95% CI 1.58-3.85; P < 0.001) and in ATTR-CA (HR 1.81, 95% CI 1.11-2.95; P = 0.017). The receiver operating characteristic curve showed that the optimal cut-off for predicting prognosis was 0.47 mm/mmHg.

CONCLUSION

In patients with CA, RV-PA coupling predicted the risk of mortality or HF hospitalization. The TAPSE/PASP ratio was more effective than TAPSE or PASP in predicting prognosis.

Association of Anticancer Immune Checkpoint Inhibitors With Patient-Reported Outcomes Assessed in Randomized Clinical Trials: A Systematic Review and Meta-analysis

IMPORTANCE

The association of immune checkpoint inhibitors (ICIs) with patient quality of life has been poorly explored.

OBJECTIVE

To evaluate patient-reported outcomes (PROs) assessed in randomized clinical trials (RCTs) of immunotherapy-based treatments.

DATA SOURCES

This systematic review and random-effects meta-analysis used RCTs identified in PubMed, MEDLINE, Embase, and Scopus from database inception to June 1, 2021.

STUDY SELECTION

A total of 2259 RCTs were identified that assessed ICIs as monotherapy or in combination with chemotherapy or combined with another ICI and/or targeted therapy vs control groups not containing immunotherapy in patients with advanced solid tumors. Studies were reviewed independently by 2 authors.

DATA EXTRACTION AND SYNTHESIS

This meta-analysis followed the PRISMA guidelines and recommendations of the Setting International Standards in Analyzing Patient-Reported Outcomes and Quality of Life Endpoints Data Consortium.

MAIN OUTCOMES AND MEASURES

The coprimary aims of the meta-analysis were (1) pooled differences between treatment groups in the mean change of PRO score from baseline to 12 and 24 weeks of follow-up and (2) pooled differences between treatment groups in the time to deterioration of PRO score. For each end point, RCTs have been analyzed according to the type of treatment administered in the experimental group: ICIs given as monotherapy, ICIs combined with chemotherapy, or ICIs in association with another ICI and/or with targeted therapies.

RESULTS

Of the 2259 identified RCTs, 34 (18 709 patients) met the selection criteria and were analyzed. In the group of 19 RCTs testing ICIs as monotherapy, the pooled between-groups difference of mean change from baseline to 12 weeks of follow-up was 4.6 (95% CI, 2.8-6.4), and the mean change from baseline to 24 weeks of follow-up was 6.1 (95% CI, 4.2-8.1), significantly favoring ICIs. The pooled difference was 1.4 (95% CI, -0.4 to 3.2) at week 12 and 2.5 (95% CI, -0.8 to 5.9) at week 24 in the group of 8 RCTs testing ICIs combined with chemotherapy and 2.1 (95% CI, -0.8 to 5.0) at week 12 and 2.1 (95% CI, -0.4 to 4.5) at week 24 in the group of 8 RCTs testing other ICI-containing combinations. The time to deterioration was significantly longer in the immunotherapy-containing groups compared with control groups in all 3 groups of RCTs evaluated (hazard ratios of 0.80 [95% CI, 0.70-0.91] for ICIs as monotherapy, 0.89 [95% CI, 0.78-1.00] for ICIs plus chemotherapy, and 0.78 [95% CI, 0.63-0.96] for other ICI-containing combinations).

CONCLUSIONS AND RELEVANCE

Immune checkpoint inhibitors as monotherapy appear to have a favorable association with patient-reported quality of life and can be combined with other classes of anticancer drugs without worsening this quality of life.

Machine learning for prediction of in-hospital mortality in coronavirus disease 2019 patients: results from an Italian multicenter study

BACKGROUND

Several risk factors have been identified to predict worse outcomes in patients affected by SARS-CoV-2 infection. Machine learning algorithms represent a novel approach to identifying a prediction model with a good discriminatory capacity to be easily used in clinical practice. The aim of this study was to obtain a risk score for in-hospital mortality in patients with coronavirus disease infection (COVID-19) based on a limited number of features collected at hospital admission.

METHODS AND RESULTS

We studied an Italian cohort of consecutive adult Caucasian patients with laboratory-confirmed COVID-19 who were hospitalized in 13 cardiology units during Spring 2020. The Lasso procedure was used to select the most relevant covariates. The dataset was randomly divided into a training set containing 80% of the data, used for estimating the model, and a test set with the remaining 20%. A Random Forest modeled in-hospital mortality with the selected set of covariates: its accuracy was measured by means of the ROC curve, obtaining AUC, sensitivity, specificity and related 95% confidence interval (CI). This model was then compared with the one obtained by the Gradient Boosting Machine (GBM) and with logistic regression. Finally, to understand if each model has the same performance in the training and test set, the two AUCs were compared using the DeLong's test. Among 701 patients enrolled (mean age 67.2 ± 13.2 years, 69.5% male individuals), 165 (23.5%) died during a median hospitalization of 15 (IQR, 9-24) days. Variables selected by the Lasso procedure were: age, oxygen saturation, PaO2/FiO2, creatinine clearance and elevated troponin. Compared with those who survived, deceased patients were older, had a lower blood oxygenation, lower creatinine clearance levels and higher prevalence of elevated troponin (all P < 0.001). The best performance out of the samples was provided by Random Forest with an AUC of 0.78 (95% CI: 0.68-0.88) and a sensitivity of 0.88 (95% CI: 0.58-1.00). Moreover, Random Forest was the unique model that provided similar performance in sample and out of sample (DeLong test P = 0.78).

CONCLUSION

In a large COVID-19 population, we showed that a customizable machine learning-based score derived from clinical variables is feasible and effective for the prediction of in-hospital mortality.

Prognostic significance of serum potassium in patients hospitalized for acute heart failure

Aim

We investigated the prognostic significance of serum potassium abnormalities at discharge in patients hospitalized for acute heart failure (AHF).

Methods and results

In a retrospective analysis, we included 926 patients hospitalized for AHF, stratified by serum potassium levels at discharge as hypokalaemia (<3.5 mEq/L), normokalaemia (3.5–5.0 mEq/L), and hyperkalaemia (>5.0 mEq/L). The primary endpoint was all‐cause death at 1 year since hospital discharge. At discharge, 40 patients had hypokalaemia (4.3%), 840 normokalaemia (90.7%), and 46 hyperkalaemia (5.0%). Patients with hyperkalaemia at discharge were more frequently men, had more signs of congestion, and lower LVEF while patients with hypokalaemia were more likely to be women with HFpEF. Treatment with ACEi/ARBs and MRAs ≥50% of target dose at discharge was similar across groups. One year all‐cause death occurred in 10% of the patients with hypokalaemia, 13.9% of those with normokalaemia, and 30.4% of those with hyperkalaemia (P = 0.006). After adjustment for covariates, including renal function, background treatment, and baseline potassium level, hyperkalaemia resulted an independent predictor of the primary endpoint (HR 1.96, 95% IC [1.01–3.82]; P = 0.048).

Conclusions

In patients with AHF, the presence of hyperkalaemia at discharge is an independent predictor of 1 year all‐cause death.

Sex-related differences in patients with coronavirus disease 2019: results of the Cardio-COVID-Italy multicentre study

INTRODUCTION

The role of sex compared to comorbidities and other prognostic variables in patients with coronavirus disease (COVID-19) is unclear.

METHODS

This is a retrospective observational study on patients with COVID-19 infection, referred to 13 cardiology units. The primary objective was to assess the difference in risk of death between the sexes. The secondary objective was to explore sex-based heterogeneity in the association between demographic, clinical and laboratory variables, and patients' risk of death.

RESULTS

Seven hundred and one patients were included: 214 (30.5%) women and 487 (69.5%) men. During a median follow-up of 15 days, deaths occurred in 39 (18.2%) women and 126 (25.9%) men. In a multivariable Cox regression model, men had a nonsignificantly higher risk of death vs. women (P = 0.07).The risk of death was more than double in men with a low lymphocytes count as compared with men with a high lymphocytes count [overall survival hazard ratio (OS-HR) 2.56, 95% confidence interval (CI) 1.72-3.81]. In contrast, lymphocytes count was not related to death in women (P = 0.03).Platelets count was associated with better outcome in men (OS-HR for increase of 50 × 103 units: 0.88 95% CI 0.78-1.00) but not in women. The strength of association between higher PaO2/FiO2 ratio and lower risk of death was larger in women (OS-HR for increase of 50 mmHg/%: 0.72, 95% CI 0.59-0.89) vs. men (OS-HR: 0.88, 95% CI 0.80-0.98; P = 0.05).

CONCLUSIONS

Patients' sex is a relevant variable that should be taken into account when evaluating risk of death from COVID-19. There is a sex-based heterogeneity in the association between baseline variables and patients' risk of death.

Combined Role of Troponin and Natriuretic Peptides Measurements in Patients With Covid-19 (from the Cardio-COVID-Italy Multicenter Study)

Data concerning the combined prognostic role of natriuretic peptide (NP) and troponin in patients with COVID-19 are lacking. The aim of the study is to evaluate the combined prognostic value of NPs and troponin in hospitalized COVID-19 patients. From March 1, 2020 to April 9, 2020, consecutive patients with COVID-19 and available data on cardiac biomarkers at admission were recruited. Patients admitted for acute coronary syndrome were excluded. Troponin levels were defined as elevated when greater than the 99^th percentile of normal values. NPs were considered elevated if above the limit for ruling in acute heart failure (HF). A total of 341 patients were included in this study, mean age 68 ± 13 years, 72% were men. During a median follow-up period of 14 days, 81 patients (24%) died. In the Cox regression analysis, patients with elevated both NPs and troponin levels had higher risk of death compared with those with normal levels of both (hazard ratio 2.94; 95% confidence interval 1.31 to 6.64; p = 0.009), and this remained significant after adjustment for age, gender, oxygen saturation, HF history, and chronic kidney disease. Interestingly, NPs provided risk stratification also in patients with normal troponin values (hazard ratio 2.86; 95% confidence interval 1.21 to 6.72; p = 0.016 with high NPs levels). These data show the combined prognostic role of troponin and NPs in COVID-19 patients. NPs value may be helpful in identifying patients with a worse prognosis among those with normal troponin values. Further, NPs’ cut-point used for diagnosis of acute HF has a predictive role in patients with COVID-19.

Evaluation of pathological complete response as surrogate endpoint in neoadjuvant randomised clinical trials of early stage breast cancer: systematic review and meta-analysis

OBJECTIVE

To evaluate pathological complete response as a surrogate endpoint for disease-free survival and overall survival in regulatory neoadjuvant trials of early stage breast cancer.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

Medline, Embase, and Scopus to 1 December 2020.

ELIGIBILITY CRITERIA FOR STUDY SELECTION

Randomised clinical trials that tested neoadjuvant chemotherapy given alone or combined with other treatments, including anti-human epidermal growth factor 2 (anti-HER2) drugs, targeted treatments, antivascular agents, bisphosphonates, and immune checkpoint inhibitors.

DATA EXTRACTION AND SYNTHESIS

Trial level associations between the surrogate endpoint pathological complete response and disease-free survival and overall survival.

METHODS

A weighted regression analysis was performed on log transformed treatment effect estimates (hazard ratio for disease-free survival and overall survival and relative risk for pathological complete response), and the coefficient of determination (R2) was used to quantify the association. The secondary objective was to explore heterogeneity of results in preplanned subgroups analysis, stratifying trials according treatment type in the experimental arm, definition used for pathological complete response (breast and lymph nodes v breast only), and biological features of the disease (HER2 positive or triple negative breast cancer). The surrogate threshold effect was also evaluated, indicating the minimum value of the relative risk for pathological complete response necessary to confidently predict a non-null effect on hazard ratio for disease-free survival or overall survival.

RESULTS

54 randomised clinical trials comprising a total of 32 611 patients were included in the analysis. A weak association was observed between the log(relative risk) for pathological complete response and log(hazard ratio) for both disease-free survival (R2=0.14, 95% confidence interval 0.00 to 0.29) and overall survival (R2 =0.08, 0.00 to 0.22). Similar results were found across all subgroups evaluated, independently of the definition used for pathological complete response, treatment type in the experimental arm, and biological features of the disease. The surrogate threshold effect was 5.19 for disease-free survival but was not estimable for overall survival. Consistent results were confirmed in three sensitivity analyses: excluding small trials (<200 patients enrolled), excluding trials with short median follow-up (<24 months), and replacing the relative risk for pathological complete response with the absolute difference of pathological complete response rates between treatment arms.

CONCLUSION

A lack of surrogacy of pathological complete response was identified at trial level for both disease-free survival and overall survival. The findings suggest that pathological complete response should not be used as primary endpoint in regulatory neoadjuvant trials of early stage breast cancer.

554 Machine learning for prediction of in-hospital mortality in COVID-19 patients: results from an Italian multicentre study

Aims

Several risk factors have been identified to predict worse outcomes in patients affected by SARS-CoV-2 infection. Prediction models are needed to optimize clinical management and to early stratify patients at a higher mortality risk. Machine learning (ML) algorithms represent a novel approach to identify a prediction model with a good discriminatory capacity to be easily used in clinical practice.

Methods and results

The Cardio-COVID is a multicentre observational study that involved a cohort of consecutive adult Caucasian patients with laboratory-confirmed COVID-19 [by real time reverse transcriptase—polymerase chain reaction (RT-PCR)] who were hospitalized in 13 Italian cardiology units from 1 March to 9 April 2020. Patients were followed-up after the COVID-19 diagnosis and all causes in-hospital mortality or discharge were ascertained until 23 April 2020. Variables with more than 20% of missing values were excluded. The Lasso procedure was used with a λ = 0.07 for reducing the covariates number. Mortality was estimated by means of a Random Forest (RF). The dataset was randomly divided in two subsamples with the same percentage of death/alive people of the entire sample: training set contained 80% of the data and test set the remaining 20%. The training set was used in the calibration procedure where a RF models in-hospital mortality with the covariates selected by Lasso. Its accuracy was measured by means of the ROC curve, obtaining AUC, sensitivity, specificity, and related 95% confidence interval (CI) computed with 10 000 stratified bootstrap replicates. From the RF the relative Variable Importance Measure (relVIM) was extracted to understand which of the selected variables had the greatest impact on outcome, providing a ranking from the most (relVIM = 100) to the less important variable. The model obtained was compared with the Gradient Boosting Machine (GBM) and with the logistic regression, where the predictions were cross validated. Finally, to understand if each model has the same performance in sample (training) and out of sample (test), the two AUCs were compared by means of the DeLong’s test. Among 701 patients enrolled (mean age 67.2 ± 13.2 years, 69.5% males), 165 (23.5%) died during a median hospitalization of 15 (IQR, 9–24) days. Variables selected by the Lasso were: age, Oxygen saturation, PaO2/FiO2, Creatinine Clearance and elevated Troponin. Compared with those who survived, deceased patients were older, had a lower blood oxygenation, a lower creatinine clearance levels and higher prevalence of elevated Troponin (all P &lt; 0.001). Training set included 561 patients and test set 140 patients. The best performance out of sample was provided by the RF with an AUC of 0.78 (95% CI: 0.68–0.88) and a sensitivity of 0.88 (95% CI: 0.58–1.00). Moreover, RF is the unique methodology that provided similar performance in sample and out of sample (DeLong test P = 0.78). On the contrary, prediction model was less accurate by using GBM and logistic regression. The relVIM ranked the variables from the most to the less important in predicting the outcome as follows: clearance creatinine, PaO2/FiO2, age, oxygen saturation, and elevated Troponin.

Conclusions

In a large COVID-19 population, we showed that a customizable ML-based score derived from clinical variables, is feasible and effective for the prediction of in-hospital mortality.

The prognostic value of serial troponin measurements in patients admitted for COVID-19

Aims

Myocardial injury (MI) in coronavirus disease‐19 (COVID‐19) is quite prevalent at admission and affects prognosis. Little is known about troponin trajectories and their prognostic role. We aimed to describe the early in‐hospital evolution of MI and its prognostic impact.

Methods and results

We performed an analysis from an Italian multicentre study enrolling COVID‐19 patients, hospitalized from 1 March to 9 April 2020. MI was defined as increased troponin level. The first troponin was tested within 24 h from admission, the second one between 24 and 48 h. Elevated troponin was defined as values above the 99th percentile of normal values. Patients were divided in four groups: normal, normal then elevated, elevated then normal, and elevated. The outcome was in‐hospital death. The study population included 197 patients; 41% had normal troponin at both evaluations, 44% had elevated troponin at both assessments, 8% had normal then elevated troponin, and 7% had elevated then normal troponin. During hospitalization, 49 (25%) patients died. Patients with incident MI, with persistent MI, and with MI only at admission had a higher risk of death compared with those with normal troponin at both evaluations (P < 0.001). At multivariable analysis, patients with normal troponin at admission and MI injury on Day 2 had the highest mortality risk (hazard ratio 3.78, 95% confidence interval 1.10–13.09, P = 0.035).

Conclusions

In patients admitted for COVID‐19, re‐test MI on Day 2 provides a prognostic value. A non‐negligible proportion of patients with incident MI on Day 2 is identified at high risk of death only by the second measurement.

Adherence and optimization of angiotensin converting enzyme inhibitor/angiotensin II receptors blockers and beta-blockers in patients hospitalized for acute heart failure

Aims

Treatment with angiotensin converting enzyme inhibitor (ACEi)/angiotensin II receptors blockers (ARBs) and beta‐blockers is frequently suboptimal at discharge in patients hospitalized for acute heart failure (AHF). We investigated the prognostic significance of medical treatment at discharge and its changes during hospitalization.

Methods and results

In a retrospective analysis, we included 623 patients hospitalized for AHF with reduced left ventricular ejection fraction (<40%). The primary endpoint was all‐cause mortality and heart failure rehospitalization to Day 180 since hospital discharge. A total of 249 (42.4%) of patients received no ACEi/ARBs/BB or <50% target dose (TD) of these drugs, 249 (42.4%) had either ACEi/ARBs or BB ≥ 50% of TD, and 89 (15.2%) ACEi/ARBs and BB ≥ 50% of TD at discharge. The primary endpoint was significantly lower in patients receiving at least one drug ≥50% of TD compared with no or low‐dose treatment (ACEi/ARBs or BB ≥ 50% TD: adjusted hazard ratio (HR) 0.69, 95% confidence interval (CI) [0.49–0.98], P = 0.04; ACEi/ARBs and BB ≥ 50% TD: adjusted HR 0.54, 95% CI [0.30–0.96], P = 0.03). With regard to treatment changes from admission to discharge, therapy was decreased in 258 (44.6%) patients, stable in 194 (33.6%), and increased in 126 (21.8%). Compared with patients with stable therapy, treatment intensification was associated with a lower rate of the primary endpoint (adjusted HR 0.49, 95% CI [0.29–0.83]; P = 0.01).

Conclusions

In patients with AHF, prescription of ACEi/ARBs/BB ≥ 50% TD at the time of discharge, whether achieved or not through treatment intensification during the hospitalization, is associated with better post‐discharge outcomes.

EGFR-TKI Plus Anti-Angiogenic Drugs in EGFR-Mutated Non-Small Cell Lung Cancer: A Meta-Analysis of Randomized Clinical Trials

Background

Results of several randomized clinical trials (RCTs) testing the combination of an epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) plus an anti-angiogenic drug in advanced EGFR-mutated non–small cell lung cancer were reported.

Methods

We first report a systematic review and meta-analysis of all RCTs to estimate effectiveness and toxicity of this new therapeutic approach compared with first-generation EGFR-TKI monotherapy. Subsequently, we present a network meta-analysis comparing the combination of an EGFR-TKI plus an anti-angiogenic drug with 2 new treatment options: combination of an EGFR-TKI plus chemotherapy or new EGFR-TKIs of second or third generation as monotherapy.

Results

Five RCTs were included in the first meta-analysis. The progression-free survival (PFS) was statistically significantly larger in patients treated with an EGFR-TKI plus an anti-angiogenic drug compared with EGFR-TKI monotherapy: the pooled PFS–hazard ratio (HR) was 0.59 (95% confidence interval [CI] = 0.51 to 0.69). The pooled median-PFS was 17.8 months (95% CI = 16.5 to 19.3 months) for the combination vs 11.7 months (95% CI = 11.1 to 12.7 months) for EGFR-TKI as monotherapy. No statistically significant differences between the 2 treatment arms were observed in overall survival or objective response rate. The rate of grade equal or higher than 3 adverse events was statistically significantly higher in patients treated with EGFR-TKI plus an anti-angiogenic drug: the pooled-relative risk was 1.72 (95% CI = 1.43 to 2.06). Ten RCTs were included in the network meta-analysis. All 3 experimental treatments were associated with a statistically significant improvement in PFS compared with first-generation EGFR-TKIs. When compared to each other, none of the 3 experimental treatments were statistically significantly associated with larger PFS or lower rate of grade 3 or higher adverse events.

Conclusion

Patients with EGFR-mutated non small-cell lung cancer derived clinically meaningful larger PFS benefit from the addition of an anti-angiogenic drug to a first-generation EGFR-TKI at the cost of an increase of toxicities.

Association of Troponin Levels With Mortality in Italian Patients Hospitalized With Coronavirus Disease 2019: Results of a Multicenter Study

Importance

Myocardial injury, detected by elevated plasma troponin levels, has been associated with mortality in patients hospitalized with coronavirus disease 2019 (COVID-19). However, the initial data were reported from single-center or 2-center studies in Chinese populations. Compared with these patients, European and US patients are older, with more comorbidities and higher mortality rates.

Objective

To evaluate the prevalence and prognostic value of myocardial injury, detected by elevated plasma troponin levels, in a large population of White Italian patients with COVID-19.

Design, Setting, and Participants

This is a multicenter, cross-sectional study enrolling consecutive patients with laboratory-confirmed COVID-19 who were hospitalized in 13 Italian cardiology units from March 1 to April 9, 2020. Patients admitted for acute coronary syndrome were excluded. Elevated troponin levels were defined as values greater than the 99th percentile of normal values.

Main Outcomes and Measures

Clinical characteristics and outcomes stratified as elevated or normal cardiac troponin levels at admission, defined as troponin T or troponin I at a level greater than the 99th percentile of normal values.

Results

A total of 614 patients with COVID-19 were included in this study (mean age [SD], 67 [13] years; 70.8% male), of whom 148 patients (24.1%) died during the hospitalization. Elevated troponin levels were found in 278 patients (45.3%). These patients were older (mean [SD] age, 64.0 [13.6] years vs 71.3 [12.0] years; P < .001) and had higher prevalence of hypertension (168 patients [50.5%] vs 182 patients [65.9%]; P < .001), heart failure (24 [7.2%]; 63 [22.8%]; P < .001), coronary artery disease (50 [15.0%] vs 87 [31.5%]; P < .001), and atrial fibrillation (33 [9.9%] vs 67 [24.3%]; P < .001). Elevated troponin levels were associated with an increased in-hospital mortality (37% vs 13%; HR, 1.71 [95% CI, 1.13-2.59]; P = .01 via multivariable Cox regression analysis), and this was independent from concomitant cardiac disease. Elevated troponin levels were also associated with a higher risk of in-hospital complications: heart failure (44 patients [19.2%] vs 7 patients [2.9%]; P < .001), sepsis (31 [11.7%] vs 21 [6.4%]; P = .03), acute kidney failure (41 [20.8%] vs 13 [6.2%]; P < .001), multiorgan failure (21 [10.9%] vs 6 [2.9%]; P = .003), pulmonary embolism (27 [9.9%] vs 17 [5.2%]; P = .04), delirium (13 [6.8%] vs 3 [1.5%]; P = .02), and major bleeding (16 [7.0%] vs 4 [1.6%]; P = .008).

Conclusions and Relevance

In this multicenter, cross-sectional study of Italian patients with COVID-19, elevated troponin was an independent variable associated with in-hospital mortality and a greater risk of cardiovascular and noncardiovascular complications during a hospitalization for COVID-19.

Restricted mean survival time analysis in heart failure clinical trials

Background

The hazard ratio (HR) is the most common measure used to quantify treatment effects in heart failure (HF) clinical trials. However, the HR is only valid when the proportional hazards assumption is plausible, and the HR may be difficult to interpret for clinicians and laypeople. Restricted mean survival time (RMST), defined as the average time-to-event before a specific timepoint, is an intuitive summary of group-wise survival. The difference between two RMSTs measures treatment effects without model assumptions and may communicate more clinically interpretable results.

Purpose

To evaluate statistical and clinical properties of RMST-based statistics applied to clinical trial data for treatments of HF with reduced ejection fraction.

Methods

Patient time-to-event data was reconstructed from the published primary and secondary outcome Kaplan-Meier curves from landmark HF clinical trials. We estimated the RMST-differences between treatment groups as a measure of treatment effect with published data, and compared statistical testing results and effect size values to HR analysis results.

Results

We analyzed 7 HF clinical trials, including data from a total of 27,845 patients (Table 1). RMST should be interpreted as the average number of months that the outcome is avoided over the study period. As examples: On average, treatment with enalapril for 12 months extended each patient's life by 2.2 months compared to placebo, and treatment with spironolactone for 34 months extended each patient's life by 2.2 months compared to placebo.

Conclusions

RMST-difference test statistic has identical statistical conclusions as HRs but provided an intuitive estimate of each treatment effect. RMST-based data can potentially be used to better communicate treatment effects to patients, to assist in patient-preference discussions and shared decision-making

Funding Acknowledgement

Type of funding source: None