Work overview

Section 01 of 05

Introduction

Multimodality treatment and survival in primary cardiac malignancies: evidence from competing-risk and machine learning analyses

Md Roungu Ahmmad, Morshed Alam, Michael Baine, and Md Tareq Ferdous Khan · 2026

Contents

Section 01 of 05

  1. 01Introduction
  2. 02Methods
  3. 03Results
  4. 04Discussion
  5. 05Conclusion
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Work overview

Section 1 of 5

Introduction

Md Roungu Ahmmad, Morshed Alam, Michael Baine, and Md Tareq Ferdous Khan · about 2 minutes

Primary cardiac cancer, also known as heart cancer, refers to malignant tumors that develop within the heart tissue and are exceedingly rare, approximately 0.001–0.3% of all cancers [1–4]. Among primary cardiac malignancies, angiosarcoma is the most common subtype in adults, whereas rhabdomyosarcoma occurs more frequently in children [5, 6]. These tumors are highly aggressive and generally associated with a poor prognosis [3, 7]. Even with treatment, survival outcomes remain limited, and disease progression is typically rapid [3, 4]. Delayed diagnosis is common due to the nonspecific nature of early symptoms and the anatomical complexity of the heart, which makes detection challenging [8].

Population-based studies indicate that surgery remains the primary intervention for cancer outcomes, offering a survival advantage, while chemotherapy may also provide clinical benefits [9]. Radiotherapy generally plays a more limited role in treatment for rare cancers [10]. Surgical resection, even when not complete, is associated with better outcomes in some patient groups, and multimodal treatment approaches are often considered when clinically feasible [11, 12]. However, the optimal combination and sequencing of these therapies remain undefined due to the rarity of the disease and limited prospective data [13, 14]. Evidence suggests that integrating systemic therapy with surgery may enhance disease control in certain subgroups, but outcomes vary by tumor histology, stage, and patient characteristics [15–17]. Comprehensive, population-based analyses are essential to delineate treatment effectiveness and guide evidence-based strategies for managing this rare and aggressive cancer.

The influence of age on primary cardiac malignancies is well-documented, whereas sex-based differences in prognosis remain unclear [18, 19]. Moreover, limited evidence exists regarding racial or ethnic disparities in outcomes for patients with primary cardiac tumors [20, 21]. Broader oncology research suggests that minority populations frequently experience delayed diagnosis and reduced access to care, which may also affect patients with cardiac sarcomas [20–22]. Given the rarity and highly aggressive nature of cardiac sarcoma and the absence of standardized treatment guidelines, therapeutic decisions are often based on small case series or institutional experience. Most published studies are single-center, including 1 to 27 cases of malignant primary cardiac tumors spanning over 9 to 49 years, highlighting the rarity and variability of the available data [15, 23–27].

Despite advances in oncologic care, the therapeutic impact of multimodal treatment strategies in patients with primary cardiac malignancies remains poorly understood. Existing studies are constrained by small sample sizes and the lack of integrated analyses that account for demographic, multimodal treatment, and advanced computational factors. To address this gap, this study leverages a large, population-based cancer registry and advanced statistical/machine learning methods to evaluate the association between multimodal treatment and survival outcomes, uncover nonlinear interactions, enhance prognostic precision, and inform evidence-based management for this rare and aggressive cancer.