By Dr. Priyom Bose, Ph.D.Sep 25 2023Reviewed by Benedette Cuffari, M.Sc. A recent Scientific Reports study discusses the development of an artificial intelligence prognostic model for surgically resected non-small cell lung cancer .
Multiple prognostic factors for postoperative prognosis associated with NSCLC have been identified, including geriatric nutritional risk index, Glasgow prognostic score, neutrophil/lymphocyte ratio, C-reactive protein /albumin ratio, prognostic nutritional index, platelet/lymphocyte ratio, and monocyte/lymphocyte ratio. To date, few studies have described the importance of blood test results in NSCLC prognosis.
A total of 1,049 patients with pathological stage I-IIIA NSCLC who underwent surgery between January 2003 and December 2016 were recruited for the study. The median age of the participants at surgery was 69 years, about 58% of whom were male. XGBoost, a decision-free model, was selected as the algorithm for this AI prognostic model. XGBoost is advantageous as compared to other AI tools due to its ability to use missing values directly as information.
The newly developed AI prognostic model used time-dependent receiver operating characteristic curves and area under the curve values to predict DFS, OS, and CSS, all of which were associated with good prediction accuracy. Notably, the predicted probability of outcome events at five years following surgery was highly accurate.
Histological type was found to be one of the most important factors of prognosis in this AI model. The prognoses of adenosquamous, pleomorphic, and large-cell neuroendocrine carcinoma were worst compared to other histological types. Thus, a more detailed analysis of histological type would improve the prognostic accuracy.
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