Management of endometrial cancer in Latin America: raising the standard of care and optimizing outcomes.
Albano BlancoAngélica N RodriguesFilomena Marília Henriques CarvalhoGonzalo GiornelliMansoor Raza MirzaPublished in: International journal of gynecological cancer : official journal of the International Gynecological Cancer Society (2024)
Molecular characterization of endometrial cancer is allowing for increased understanding of the natural history of tumors and paving a more solid pathway for novel therapies. It is becoming increasingly apparent that molecular classification is superior to histological classification in terms of reproducibility and prognostic discrimination. In particular, the Proactive Molecular Risk Classifier for Endometrial Cancer allows classification of endometrial cancer into groups very close to those determined by the Cancer Genome Atlas Research Network-that is, DNA polymerase epsilon-mutated, mismatch repair-deficient, p53 abnormal, and non-specific molecular profile tumors. The transition from the chemotherapy era to the age of targeted agents and immunotherapy, which started later in endometrial cancer than in many other tumor types, requires widespread availability of specialized pathology and access to novel agents. Likewise, surgical expertise and state-of-the-art radiotherapy modalities are required to ensure adequate care. Nevertheless, Latin American countries still face considerable barriers to implementation of international guidelines. As we witness the dawn of precision medicine as applied to endometrial cancer, we must make continued efforts towards improving the quality of care in this region. The current article discusses some of these challenges and possible solutions.
Keyphrases
- endometrial cancer
- quality improvement
- healthcare
- palliative care
- machine learning
- deep learning
- single molecule
- pain management
- locally advanced
- affordable care act
- magnetic resonance
- single cell
- radiation therapy
- magnetic resonance imaging
- young adults
- gene expression
- cell free
- insulin resistance
- adipose tissue
- health insurance
- clinical practice
- lymph node metastasis
- neural network