The Distribution of Cardiovascular-Related Comorbidities in Different Adult-Onset Cancers and Related Risk Factors: Analysis of 10 Year Retrospective Data

Investigating modifiable risk factors associated with ideal cardiovascular health among cancer survivors: a scoping review

BACKGROUND

Cancer survivors are at higher risk of developing cardiovascular diseases and face worse morbidity and mortality outcomes than the general population. The American Heart Association (AHA) introduced the Life's Essential 8 framework, encompassing eight modifiable risk factors and lifestyle behaviors for maintaining ideal cardiovascular health (CVH). Although this framework is well-established for predicting CVH in the general population, studies on its association with cardiovascular outcomes among cancer survivors remain scattered across the literature.

OBJECTIVE

This review maps existing literature surrounding modifiable risk factors, lifestyle behaviors, CVH, and cardiovascular outcomes among cancer survivors to take stock of what is known, identify methodological strengths and weaknesses, and propose promising research directions.

METHODS

A scoping review was conducted to identify studies examining different dimensions of ideal CVH in adult cancer survivors. Measurement methods of ideal CVH metrics, and determinants associated with CVH were examined.

RESULTS

Twenty-two articles met eligibility criteria. Of which, 82% (n = 18) were published in or after 2020. Fourteen studies (about 64%) followed the AHA's framework to conceptualize ideal CVH. Higher scores on ideal CVH are linked to better cardiovascular outcomes among cancer survivors with associations noted for social inequalities and neighborhood environmental factors, underscoring the complexity of CVH determinants in this population.

CONCLUSIONS

Research on ideal CVH among cancer survivors appears to have accelerated in recent years, yet many gaps remain to orient clinical and public health practice. Promising research directions include expanding investigations into pre-diagnosis CVH, addressing disparities in CVH across diverse populations, and conducting longitudinal studies to clarify causal pathways between lifestyle behaviors, cancer treatments, and cardiovascular outcomes.

Machine Learning-Based Prediction of Unplanned Readmission Due to Major Adverse Cardiac Events Among Hospitalized Patients with Blood Cancers

BackgroundHospitalized patients with blood cancer face an elevated risk for cardiovascular diseases caused by cardiotoxic cancer therapies, which can lead to cardiovascular-related unplanned readmissions.ObjectiveWe aimed to develop a machine learning (ML) model to predict 90-day unplanned readmissions for major adverse cardiovascular events (MACE) in hospitalized patients with blood cancers.DesignA retrospective population-based cohort study.MethodsWe analyzed patients aged ≥18 with blood cancers (leukemia, lymphoma, myeloma) using the Nationwide Readmissions Database. MACE included acute myocardial infarction, ischemic heart disease, stroke, heart failure, revascularization, malignant arrhythmias, and cardiovascular-related death. Six ML algorithms (L2-Logistic regression, Support Vector Machine, Complement Naïve Bayes, Random Forest, XGBoost, and CatBoost) were trained on 2017-2018 data and tested on 2019 data. The SuperLearner algorithm was used for stacking models. Cost-sensitive learning addressed data imbalance, and hyperparameters were tuned using 5-fold cross-validation with Optuna framework. Performance metrics included the Area Under the Receiver Operating Characteristics Curve (ROCAUC), Precision-Recall AUC (PRAUC), balanced Brier score, and F2 score. SHapley Additive exPlanations (SHAP) values assessed feature importance, and clustering analysis identified high-risk subpopulations.ResultsAmong 76 957 patients, 1031 (1.34%) experienced unplanned 90-day MACE-related readmissions. CatBoost achieved the highest ROCAUC (0.737, 95% CI: 0.712-0.763) and PRAUC (0.040, 95% CI: 0.033-0.050). The SuperLearner algorithm achieved slight improvements in most performance metrics. Four leading predictive features were consistently identified across algorithms, including older age, heart failure, coronary atherosclerosis, and cardiac dysrhythmias. Twenty-three clusters were determined with the highest-risk cluster (mean log odds of 1.41) identified by nonrheumatic/unspecified valve disorders, coronary atherosclerosis, and heart failure.ConclusionsOur ML model effectively predicts MACE-related readmissions in hospitalized patients with blood cancers, highlighting key predictors. Targeted discharge strategies may help reduce readmissions and alleviate the associated healthcare burden.

Selection of rhythm intervention strategies in atrial fibrillation patients with cancer and efficacy and safety of catheter ablation

Background

The risk of comorbidity of cancer is increased in atrial fibrillation (AF) patients, which is a massive challenge for clinical management in cardiovascular settings. This study aimed to analyze whether cancer affects the decision of radiofrequency ablation and to explore the efficacy and safety of radiofrequency ablation in AF patients with cancer.

Methods

We conducted a retrospective cohort study of patients who were first diagnosed AF and identified who were with cancer. The propensity score matching method was utilized to balance the differences between the cancer and non-cancer groups. Logistic regression analysis was used to study the related factors affecting the ablation of AF. Cox regression analysis was used to evaluate the effect of cancer on the recurrence of AF after radiofrequency ablation.

Results

Among 9,159 patients who were first diagnosed AF, the prevalence of cancer was 4.48%. Cancer did not affect the decision of rhythm intervention in AF patients (P = 0.46). There was no significant difference in the incidence of perioperative complications, bleeding events, and embolization events between cancer and non-cancer groups (P = 1.000). The median follow-up time was 342 (293,866) days, and 45 patients had AF recurrence. Multivariable Cox regression showed no statistically significant relationship between concomitant cancer and AF recurrence after radiofrequency ablation (hazard ratio = 0.82, 95% confidence interval 0.36-1.83, P = 0.62).

Conclusions

The combination of cancer did not affect the decision of patients to perform ablation therapy. Radiofrequency catheter ablation could be used as a strategy to maintain long-term sinus rhythm in patients with concomitant cancer without affecting AF recurrence.

Cardiovascular mortality risk in patients with ovarian cancer: a population-based study

OBJECTIVES

Ovarian cancer (OC) can occur at different ages and is affected by a variety of factors. In order to evaluate the risk of cardiovascular mortality in patients with ovarian cancer, we included influencing factors including age, histological type, surgical method, chemotherapy, whether distant metastasis, race and developed a nomogram to evaluate the ability to predict occurrence. At present, we have not found any correlation studies on cardiovascular death events in patients with ovarian cancer. This study was designed to provide targeted measures for effective prevention of cardiovascular death in patients with ovarian cancer.

METHODS

Kaplan-Meier analysis and multivariable Cox proportional model were performed to evaluate the effectiveness of cardiovascular diseases on overall survival (OS) and ovarian cancer-specific survival (OCSS). We compared multiple groups including clinical, demographic, therapeutic characteristics and histological types. Cox risk regression analysis, Kaplan-Meier survival curves, and propensity score matching were employed for analyzing the data.

RESULTS

A total of 88,653 ovarian cancer patients were collected, of which 2,282 (2.57%) patients died due to cardiovascular-related diseases. Age, chemotherapy and whether satisfactory cytoreduction surgery is still the most important factors affecting the prognosis of ovarian cancer patients, while different histological types, diagnosis time, and race also have a certain impact on the prognosis. The newly developed nomogram model showed excellent predictive performance, with a C-index of 0.759 (95%CI: 0.757-0.761) for the group. Elderly patients with ovarian cancer are still a high-risk group for cardiovascular death [HR: 21.07 (95%CI: 5.21-85.30), p < 0.001]. The calibration curve showed good agreement from predicted survival probabilities to actual observations.

CONCLUSION

This study found that age, histology, surgery, race, chemotherapy, and tumor metastasis are independent prognostic factors for cardiovascular death in patients with ovarian cancer. The nomogram-based model can accurately predict the OS of ovarian cancer patients. It is expected to inform clinical decision-making and help develop targeted treatment strategies for this population.

Thyroid cancer and cardiovascular diseases: a Mendelian randomization study

Background

Multiple observational studies have shown associations between thyroid cancer (TC) and cardiovascular diseases (CVDs). However, the results were inconsistent, and the potential causal genetic relationship remains unclear.

Methods

The genetic instruments of TC and CVDs were derived from data obtained through genome-wide association studies (GWAS). We performed the two-sample Mendelian randomization(MR) methods to investigate the causality of TC on CVDs. Summary-level statistics for CVDs, including heart failure (HF), atrial fibrillation (AF), coronary artery disease (CAD), myocardial infarction (MI), ischemic stroke (IS) and venous thromboembolism (VTE). The primary method employed in this MR analysis was the Inverse Variance Weighted (IVW) approach, and four additional algorithms were used: MR-Egger, weighted median, simple mode, and weighted mode. Additionally, we assessed the reliability of the causal relationship through pleiotropy, heterogeneity and leave-one-out sensitivity analysis.

Results

In this MR analysis, we only detected causality of genetically predicted TC on HF (IVW method, odds ratio (OR) = 1.00134, 95% confidence interval (CI): 1.00023-1.00244, p = 0.017). However, There were no causal associations of TC with CAD, MI, AF, IS, and VTE.

Conclusion

Our results confirmed the causal association between TC and HF. It is crucial to closely monitor the incidence of HF in TC patients and give comprehensive clinical intervention based on conventional treatment.

Atrial fibrillation in cancer survivors - a systematic review and meta-analysis

BACKGROUND

Atrial fibrillation (AF) is a common cardiac complication during cancer treatment. It is unclear if cancer survivors have increased AF risk when compared to the population. AF screening is now recommended in patients ≥65 years, however there are no specific recommendations in the oncology population. We sought to compare the AF detection rate of cancer survivors compared to the general population.

METHODS

We searched the Pubmed, Embase and Web of Science databases using search terms related to AF and cancer mapped to subject headings. We included English language studies, limited to adults > 18 years who were > 12 months post completion of cancer treatment. Using a random-effects model we calculated the overall AF detection rate. Meta-regression analysis was performed to assess for potential causes for study heterogeneity.

RESULTS

Sixteen studies were included in the study. The combined AF detection rate amongst all the studies was 4.7% (95% C.I 4.0-5.4%), which equated to a combined annualised AF rate of 0.7% (95% C.I 0.1-0.98%). There was significant heterogeneity between studies (I² = 99.8%, p < 0.001). In the breast cancer cohort (n = 6 studies), the combined annualised AF rate was 0.9% (95% C.I 0.1-2.3%), with significant heterogeneity (I² = 99.9%, p < 0.001).

CONCLUSION

Whilst the results should be interpreted with caution due to study heterogeneity, AF rates in patients with cancer survival >12 months were not significantly increased compared to the general population.

STUDY REGISTRATION

Open Science Framework - DOI: https://doi.org/10.17605/OSF.IO/APSYG .

Contribution of serum lipids and cholesterol cellular metabolism in lung cancer development and progression

Neoplasms of the lungs are the leading cause of cancer incidence and mortality worldwide. Although immunotherapy has increased the overall survival of patients with lung cancer, there is the need to improve this treatment. At this regard, blood lipid levels are thought to be linked to cancer risk and thus a preventive intervention through regulation of the nutrition of patients with lung cancer is gaining much attention. In this study, we therefore asked about the contribution of serum lipids and cholesterol cellular metabolism in lung cancer development and progression. We measured different serum lipids and analyzed cholesterol synthesis enzymes 3-hydroxy-3-methyl-glutaryl-CoA reductase (HMGCR) and acetyl-coenzyme A cholesterol acetyltransferase 1 (ACAT1) as well as the cholesterol cellular export protein ATP-binding cassette (ABC) A-1 mRNA by quantitative PCR (qPCR) in the control and tumoral regions of post-surgery lung tissues to analyze the accumulation of cholesterol in cancer cells in a cohort of patients with lung adenocarcinoma (LUAD). We found that triglycerides in serum directly correlated with the body mass index (BMI) in patients with LUAD. By contrast, we found that high-density lipoprotein (HDL) cholesterol inversely correlated with the BMI, C-reactive protein (CRP) and overall survival and total cholesterol inversely correlated with the tumor diameter, serum CRP and overall survival in these LUAD patients. Functionally, the role of cholesterol is indispensable for the growth and development of normal animal cells where it is tightly regulated. Excess of cellular cholesterol regulated by HMGCR is converted to cholesteryl esters by the enzyme ACAT1 and exported extracellularly by the cholesterol transporter ABCA1. Here we found HMGCR and ACAT1 upregulated and ABCA1 downregulated in the lung's tumoral region of our LUAD cohort, indicating cholesterol dysregulated cellular export in lung tumor cells.

Atrial fibrillation and breast cancer—Vicious twins? A systematic review and meta-analysis

Background

Epidemiological studies suggest a bidirectional association between atrial fibrillation and breast cancer. This study aimed to conduct a meta-analysis to elucidate the prevalence of atrial fibrillation among breast cancer patients, and the bidirectional association between atrial fibrillation and breast cancer.

Methods

PubMed, the Cochrane Library, and Embase were searched to identify studies reporting the prevalence, incidence, and bidirectional association between atrial fibrillation and breast cancer. The study was registered with PROSPERO (CRD42022313251). Levels of evidence and recommendations were assessed by the Grading of Recommendations Assessment, Development and Evaluation (GRADE).

Results

Twenty-three studies (17 retrospective cohort studies, 5 case-control studies and 1 cross-sectional study) involving 8,537,551 participants were included. Among patients with breast cancer, the prevalence of atrial fibrillation was 3% (11 studies; 95% CI: 0.6 to 7.1%) and the incidence was 2.7% (6 studies; 95% CI: 1.1 to 4.9%). Breast cancer was associated with increased risk of atrial fibrillation (5 studies; hazard ratio [HR]: 1.43, 95% CI: 1.12 to 1.82, I2 = 98%). Atrial fibrillation was also significantly associated elevated risk of breast cancer (5 studies HR: 1.18, 95% CI: 1.14 to 1.22, I2 = 0%). Grade assessment shown low certainty of the evidence for the risk of atrial fibrillation and moderate certainty of the evidence for the risk of breast cancer.

Conclusion

Atrial fibrillation is not uncommon in patients with breast cancer and vice versa. There is a bidirectional association between atrial fibrillation (low certainty) and breast cancer (moderate certainty).

Cancer-associated stroke

Background. Systemic cancer and stroke are the most common diseases and the frequent death factors in older people worldwide. The relationship between cancer and stroke is complex, since cancer leads to an increased risk of stroke through specific pathophysiological mechanisms. Purpose. Analyzing possible mechanisms of development of cancer-associated stroke, strategies of diagnosis and treatment. Materials and methods. The contributions were selected based on PubMed (https://pubmed.ncbi.nlm.nih.gov/), Clinical Key Elsevier (https://www.clinicalkey.com), Cochrane Library (https://www.cochranelibrary.com/) and GoogleScholar (https://scholar.google.com/) databases published from 2012 to 2022, dealing with cancer-associated stroke. Results and discussion. There are several underlying pathophysiological mechanisms of cancer-associated stroke, which may be directly related to cancer or caused by cancer complications. The most common ones are intravascular cancer coagulopathy, non-bacterial thrombotic endocarditis, a direct impact of the tumor on the vascular system or therapeutic and diagnostic interventions for the treatment of cancer that is chemotherapy, radiation therapy complications, as well as activation of the usual mechanisms of stroke, atherosclerosis in particular. The risk of stroke is also related to cancer aggressiveness. The characteristic features of cancer-associated stroke which is related to cancer coagulopathy are multiple lesions in various arterial areas, as well as laboratory data indicating coagulopathy in the form of increased level of D-dimer, elevated C-reactive protein, low hematocrit. Conclusions. Cancer leads to an increased risk of stroke due to specific pathophysiological mechanisms. These mechanisms are multiple and complex, but the most well-known and widespread is cancer intravascular coagulopathy, which has specific laboratory biomarkers. Numerous studies continue investigating the factors associated with coagulopathy in stroke patients, cancer characteristics, and evaluation of biological markers of stroke-causing intravascular coagulopathy, as well as monitoring the effects of anticoagulation therapy in patients with cancer-associated stroke.

Postmenopausal Women with Breast, Endometrial, and Ovarian Cancers Have an Increased Risk for Cardiovascular Conditions prior to Active Endocrine Therapy

Background

Patients with active cancer have an increased risk of cardiovascular diseases (CVDs) among cancer patients receiving endocrine therapy. However, little research has explored the distribution of CVD comorbidities and cardiovascular risk factors (CVRFs) among postmenopause women with breast, endometrial, or ovarian cancer prior to active treatment with endocrine therapy. We aimed to explore the distribution of CVD comorbidities and associated CVRF in patients suffering from breast, endometrial, or ovarian cancer prior to the use of endocrine therapy and to assess whether there was compliance with existing hospital recommendations, particularly on the use of lipid-lowering agents to prevent the development of CVD comorbidities in postmenopause women.

Methods

A total of 10,731 postmenopause women with primary breast, endometrial, or ovarian cancer were enrolled between 30th May 2008 and 31st July 2021 from an electronic health record database at the first affiliated hospital of Dalian Medical University. Dyslipidemia was defined according to 2016 Chinese guidelines for adults. Multivariate logistic regression analysis was used to identify the independent predictors of CVD comorbidities in breast, endometrial, and ovarian cancers separately.

Results

Overall, 18.9% of the included women had at least one CVD record before endocrine therapy. The highest prevalence of CVD was identified for hypertension (16.5%), followed by coronary heart disease (4.5%), stroke (2.1%), heart failure (1.2%), and atrial fibrillation (1.1%). The most common CVRF among total cancer patients was dyslipidemia, with a remarkable prevalence of 62.8%, followed by diabetes mellitus (8.6%). Notably, only 11.1% of cancer patients were receiving lipid-lowering agents.

Conclusion

Cancer patients with potential eligibility for endocrine therapy use had an increased risk for CVD comorbidities. Dyslipidemia was the common CVRF. Compliance with recommendations for preventing and managing these comorbidities requires serious attention.

Coronary Atherosclerotic Disease and Cancer: Risk Factors and Interrelation

Background

In our clinical work, we found that cancer patients were susceptible to coronary atherosclerotic heart disease (CAD). However, less is known about the relationship between CAD and cancer. The present study aimed to identify the risk factors for CAD and cancer, as well as the relationship between CAD and cancer.

Methods

In this retrospective study, 1600 patients between January 2012 and June 2019 were enrolled and divided into groups according to whether they had CAD or cancer. Single-factor and multivariate analysis methods were applied to examine the risk factors for CAD and cancer.

Results

(1) Cancer prevalence was significantly higher in patients with CAD than in patients without CAD (47.2 vs. 20.9%). The prevalence of CAD in cancer and non-cancer patients was 78.9 and 52.4%, respectively. (2) Multivariable logistic regression showed that patients with cancer had a higher risk of developing CAD than non-cancer patients (OR: 2.024, 95% CI: 1.475 to 2.778, p &lt; 0.001). Respiratory (OR: 1.981, 95% CI: 1.236–3.175, p = 0.005), digestive (OR: 1.899, 95% CI: 1.177–3.064, p = 0.009) and urogenital (OR: 3.595, 95% CI: 1.696–7.620, p = 0.001) cancers were significantly associated with a higher risk of CAD compared with no cancer. (3) Patients with CAD also had a higher risk of developing cancer than non-CAD patients (OR = 2.157, 95% CI: 1.603 to 2.902, p &lt; 0.001). Patients in the Alanine aminotransferase (ALT) level ≥ 40 U/L group had a lower risk of cancer than patients in the ALT level &lt; 20 U/L group (OR: 0.490, 95% CI: 0.333–0.722, p &lt; 0.001). (4) An integrated variable (Y = 0.205 × 10–1 age − 0.595 × 10–2 HGB − 0.116 × 10–1 ALT + 0.135 FIB) was identified for monitoring the occurrence of cancer among CAD patients, with an AUC of 0.720 and clinical sensitivity/specificity of 0.617/0.711.

Conclusion

(1) We discovered that CAD was an independent risk factor for cancer and vice versa. (2) Digestive, respiratory and urogenital cancers were independent risk factors for CAD. (3) We created a formula for the prediction of cancer among CAD patients. (4) ALT, usually considered a risk factor, was proven to be a protective factor for cancer in this study.