Transcatheter Aortic Valve Implantation in Cancer Patients: A Contemporary Review of the Specific Challenges, the Outcomes, Risk Stratification, and Decision-Making
Abstract
1. Introduction
2. Methodology
3. Epidemiological Overlap Between Cancer and Aortic Stenosis
4. Cancer-Specific Challenges in TAVI
4.1. Heterogeneity of Cancer Types, Stages, and Prognoses
4.2. Hematologic Malignancies
4.3. Active Cancer vs. Cancer Survivorship
4.4. Thoracic Radiotherapy
4.5. Competing Thrombotic and Bleeding Risks: Implications for Post-TAVI Antithrombotic Therapy
4.6. Immunosuppression and Risk of Infection
4.7. Frailty, Nutritional Status, Cachexia, and Sarcopenia
5. Clinical Outcomes of TAVI in Cancer Patients
5.1. Procedural Success and Short-Term Outcomes
5.2. Procedural Complications
5.3. Mid- and Long-Term Survival
5.4. Active vs. History of Cancer: Differential Outcomes
5.5. Symptom Relief and Functional Status After TAVI
5.6. Comparison with Surgical Aortic Valve Replacement
6. Risk Stratification and Decision-Making in Cancer Patients
7. Gaps in Evidence and Future Directions
- Under-representation of cancer patients in clinical trials.
- Lack of standardized definitions for cancer status and outcomes.
- Limited integration of oncology-specific prognostic tools.
- Multidimensional geriatric assessment in patient selection.
- Insufficient data on optimal antithrombotic strategies.
- Long-term outcomes and valve durability.
- Patient-reported outcomes and quality-of-life measures.
- Integration of cardio-oncology and structural heart programs.
8. Limitations
9. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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| First Author | Study Design | N | Study Population | Primary Endpoint | Key Findings | Limitations | Potential Bias |
|---|---|---|---|---|---|---|---|
| Mangner 2018 [12] | Prospective cohort | 1821 | Active vs. history vs. no cancer | 1-year mortality | ↑ 1-year mortality in active cancer | Retrospective single-center design with a relatively small number of patients with active cancer (99 of 1821). | Selection bias due to the retrospective, single-center observational design, in which only patients considered suitable for TAVR were included. |
| Felix 2024 [13] | Systematic review & meta-analysis | Pooled cohort | Active cancer vs. no cancer | Mortality and VARC outcomes | ↑ mortality and bleeding; ≈ procedural complications | Study-level meta-analysis, no subgroup or meta-regression analyses based on cancer type and device used due to incomplete reporting and limited number of included studies. | Detection bias: Patients with cancer are often on anticoagulants or have lower baseline platelets, making bleeding events more likely to be reported. |
| Bendary 2020 [14] | Systematic review & meta-analysis | 5162 | Active cancer vs. no cancer | 30-day and 1-year mortality | ≈ 30-day outcomes; ↑ 1-year mortality | Relies on older studies in which TAVI technology and peri-procedural care were less advanced than current standards. | Publication bias: Small studies showing “no difference” are often not published, which can tilt meta-analysis results toward the “positive” (risk). |
| Saberian 2025 [15] | Systematic review & meta-analysis | Pooled cohort | Active cancer vs. no cancer | Mortality and complications | ≈ short-term outcomes; ↑ 1- and 2-year mortality | Heterogeneity in cancer type, stage, and treatment across the studies included, which may affect the outcomes. | Selection bias due to the inclusion of predominantly observational, non-randomized studies in the meta-analysis, which may influence the pooled outcome estimates. |
| Landes 2019 [17] | Multinational registry | 2744 | Active cancer vs. no cancer | Mortality and complications | ≈ 30-day mortality; ↑ long-term mortality | As a multi-national registry, there is significant variation in how “active cancer” is defined across different countries and healthcare systems. | Selection bias: Only patients deemed “operable” by high-volume, specialized centers were included, potentially overestimating survival. |
| Liu 2025 [41] | National cohort study | Large administrative dataset | Hematologic malignancies | Clinical and financial outcomes | ↑ complications and resource utilization | Use of an administrative database lacking detailed clinical and oncologic information (e.g., cancer stage, treatment status, and disease activity), which may lead to residual confounding and limit the interpretation of the results. | Selection bias due to the retrospective observational design using an administrative database, in which patient inclusion depends on coding and clinical decision-making rather than randomization. |
| Biancari 2020 [42] | Retrospective cohort | 2130 | Active cancer vs. no cancer | Mortality and complications | ≈ short-term outcomes; ↑ long-term mortality | High heterogeneity between participating centers regarding patient selection criteria and TAVI techniques. | Reporting/Recall bias: Since this was retrospective, researchers relied on medical records that may have missed minor complications (like small bleeds or delirium), leading to an underestimation of procedural risk. |
| Kosaraju 2022 [72] | Observational cohort | 555 | History of cancer | Mortality and quality of life | Frailty predicts mortality and QoL | The subjectivity of frailty assessment tools can vary significantly between different clinicians in a non-standardized setting. | Information/Observer bias: Frailty is often assessed by different clinicians with different “eyes.” |
| Watanabe 2016 [80] | Multicenter observational cohort | 749 | Active cancer vs. no cancer | 30-day and 1-year mortality | ≈ short-term outcomes; ≈ procedural complications | Lacks data on cancer stage, histology, and specific types of active systemic therapy (chemo/radiation). | Selection bias: TAVI may have been preferentially offered to cancer patients perceived as sufficiently fit, potentially biasing outcomes toward more favorable results. |
| Song 2022 [81] | Systematic review & meta-analysis | pooled cohort | Active cancer vs. no cancer | Mortality and complications | ↑ long-term mortality | No published randomized controlled trials were included. Due to short follow-up, the study only analyzed the outcome indexes in the early and medium-term and failed to explore the longer-term prognosis of TAVI. | Heterogeneity bias: High I2 values (statistical inconsistency) often occur because of different follow-up durations across pooled studies. |
| Aikawa 2023 [82] | Nationwide registry | 122,573 | Active cancer vs. no cancer | Mortality and readmissions | ≈ in-hospital mortality; ↑ readmissions | Nationwide registries often lack “granular” data, such as left ventricular ejection fraction (LVEF), surgical risk scores or specific anatomical challenges (e.g., porcelain aorta). | Confounding by indication: Patients with cancer might be readmitted more often not due to TAVI failure, but due to cancer-related complications (infection, anemia). |
| Osawa 2024 [83] | Systematic review & meta-analysis | Pooled cohort | Active or previous cancer | Mortality and complications | ↑ long-term mortality | Pools “active” and “previous” cancer together; this significantly obscures the actual risk of patients currently undergoing therapy. | Dilution bias: Including patients with a history of cancer (cured) “dilutes” the mortality signal compared to those with truly active, advanced disease. |
| Guha 2020 [84] | National database study | 63,352 | Active cancer vs. no cancer | Procedural outcomes | ≈ short-term mortality; ↑ readmissions | Relies on ICD-10 codes, which often lack details on cancer severity, current chemotherapy status, or biological frailty markers. | Misclassification bias: Coding errors in large databases can lead to patients with a “history of cancer” being labeled as “active cancer,” or vice versa. |
| Kojima 2022 [85] | Multicenter cohort | 1114 | Active cancer vs. no cancer | Survival outcomes | ↑ mortality in metastatic cancer | The number of patients with active malignancy and the follow-up period were limited. | Survival bias: Patients with metastatic cancer who live long enough to be referred for, worked up for, and receive a TAVI are already “biological survivors.” |
| Diaz-Arocutipa 2021 [86] | Systematic review & meta-analysis | 255,840 | Active or previous cancer | Mortality and complications | ↑ long-term mortality; ≈ procedural complications | The massive N (255,840) is driven by administrative databases, which dilutes the precision of “active” vs. “history of” cancer definitions. | Aggregation bias: By pooling very large registry data with small high-quality cohorts, the registry “noise” may drown out specific clinical insights. |
| Lind 2020 [87] | Single-center cohort | 892 | Active cancer vs. no cancer | Mortality and complications | ↑ mortality in cancer patients | Single-center study with a relatively small sample size, limiting the generalizability of the findings to broader populations. Long period of recruitment, during which guidelines for TAVI have changed. | Detection bias: Because cancer patients are monitored more closely by oncologists (scans, blood tests), complications are more likely to be “detected” in this group compared to the general population. |
| Key Priorities for Future Research Regarding TAVI in Cancer Patients and Survivors: |
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© 2026 by the authors. Published by MDPI on behalf of the Lithuanian University of Health Sciences. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
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Keramida, K.; Mavraganis, G.; Masoura, C.; Aznaouridis, K.; Androutsopoulou, V.; Tsioufis, K. Transcatheter Aortic Valve Implantation in Cancer Patients: A Contemporary Review of the Specific Challenges, the Outcomes, Risk Stratification, and Decision-Making. Medicina 2026, 62, 1139. https://doi.org/10.3390/medicina62061139
Keramida K, Mavraganis G, Masoura C, Aznaouridis K, Androutsopoulou V, Tsioufis K. Transcatheter Aortic Valve Implantation in Cancer Patients: A Contemporary Review of the Specific Challenges, the Outcomes, Risk Stratification, and Decision-Making. Medicina. 2026; 62(6):1139. https://doi.org/10.3390/medicina62061139
Chicago/Turabian StyleKeramida, Kalliopi, Georgios Mavraganis, Constantina Masoura, Konstantinos Aznaouridis, Vasiliki Androutsopoulou, and Konstantinos Tsioufis. 2026. "Transcatheter Aortic Valve Implantation in Cancer Patients: A Contemporary Review of the Specific Challenges, the Outcomes, Risk Stratification, and Decision-Making" Medicina 62, no. 6: 1139. https://doi.org/10.3390/medicina62061139
APA StyleKeramida, K., Mavraganis, G., Masoura, C., Aznaouridis, K., Androutsopoulou, V., & Tsioufis, K. (2026). Transcatheter Aortic Valve Implantation in Cancer Patients: A Contemporary Review of the Specific Challenges, the Outcomes, Risk Stratification, and Decision-Making. Medicina, 62(6), 1139. https://doi.org/10.3390/medicina62061139

