| Autor: |
Siddik Sarkar, Sarbar Ali Saha, Abhishek Swarnakar, Arnab Chakrabarty, Avipsa Dey, Poulomi Sarkar, Sarthak Banerjee, Pralay Mitra |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Journal of Ovarian Research, Vol 17, Iss 1, Pp 1-14 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1757-2215 |
| DOI: |
10.1186/s13048-024-01482-5 |
| Popis: |
Abstract Background The clinicopathological parameters such as residual tumor, grade, the International Federation of Gynecology and Obstetrics (FIGO) score are often used to predict the survival of ovarian cancer patients, but the 5-year survival of high grade serous ovarian cancer (HGSOC) still remains around 30%. Hence, the relentless pursuit of enhanced prognostic tools for HGSOC, this study introduces an unprecedented gene expression-based molecular prognostic score (mPS). Derived from a novel 20-gene signature through Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression, the mPS stands out for its predictive prowess. Results Validation across diverse datasets, including training and test sets (n = 491 each) and a large HGSOC patient cohort from the Ovarian Tumor Tissue Analysis (OTTA) consortium (n = 7542), consistently shows an area-under-curve (AUC) around 0.7 for predicting 5-year overall survival. The mPS’s impact on prognosis resonates profoundly, yielding an adjusted hazard-ratio (HR) of 6.1 (95% CI: 3.65–10.3; p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
