Bibliographic Details
| Title: |
Comparison of eight modern preoperative scoring systems for survival prediction in patients with extremity metastasis |
| Authors: |
Tse‐Ying Lee, Yu‐An Chen, Olivier Q. Groot, Hung‐Kuan Yen, Bas J. J. Bindels, Robert‐Jan Pierik, Hsiang‐Chieh Hsieh, Aditya V. Karhade, Ting‐En Tseng, Yi‐Hsiang Lai, Jing‐Jen Yang, Chia‐Che Lee, Ming‐Hsiao Hu, Jorrit‐Jan Verlaan, Joseph H. Schwab, Rong‐Sen Yang, Wei‐Hsin Lin |
| Source: |
Cancer Medicine, Vol 12, Iss 13, Pp 14264-14281 (2023) |
| Publisher Information: |
Wiley, 2023. |
| Publication Year: |
2023 |
| Collection: |
LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens |
| Subject Terms: |
Asian cohort, external validation, extremity metastasis, survival prediction models, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282 |
| More Details: |
Abstract Background Survival is an important factor to consider when clinicians make treatment decisions for patients with skeletal metastasis. Several preoperative scoring systems (PSSs) have been developed to aid in survival prediction. Although we previously validated the Skeletal Oncology Research Group Machine‐learning Algorithm (SORG‐MLA) in Taiwanese patients of Han Chinese descent, the performance of other existing PSSs remains largely unknown outside their respective development cohorts. We aim to determine which PSS performs best in this unique population and provide a direct comparison between these models. Methods We retrospectively included 356 patients undergoing surgical treatment for extremity metastasis at a tertiary center in Taiwan to validate and compare eight PSSs. Discrimination (c‐index), decision curve (DCA), calibration (ratio of observed:expected survivors), and overall performance (Brier score) analyses were conducted to evaluate these models’ performance in our cohort. Results The discriminatory ability of all PSSs declined in our Taiwanese cohort compared with their Western validations. SORG‐MLA is the only PSS that still demonstrated excellent discrimination (c‐indexes>0.8) in our patients. SORG‐MLA also brought the most net benefit across a wide range of risk probabilities on DCA with its 3‐month and 12‐month survival predictions. Conclusions Clinicians should consider potential ethnogeographic variations of a PSS's performance when applying it onto their specific patient populations. Further international validation studies are needed to ensure that existing PSSs are generalizable and can be integrated into the shared treatment decision‐making process. As cancer treatment keeps advancing, researchers developing a new prediction model or refining an existing one could potentially improve their algorithm's performance by using data gathered from more recent patients that are reflective of the current state of cancer care. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2045-7634 |
| Relation: |
https://doaj.org/toc/2045-7634 |
| DOI: |
10.1002/cam4.6097 |
| Access URL: |
https://doaj.org/article/e2f77021a8e248b5a4462ab12671f3c7 |
| Accession Number: |
edsdoj.2f77021a8e248b5a4462ab12671f3c7 |
| Database: |
Directory of Open Access Journals |
