Personalized four-category staging for predicting prognosis in patients with small bowel Adenocarcinoma: an international development and validation study

Abstract

Background Log odds of positive lymph nodes (LODDS) classification showed superiority over 8 th edition N staging in predicting survival of small bowel adenocarcinoma (SBA) patients. The aim of this study was to develop and validate the Tumor, LODDS, and Metastasis (TLM) staging of SBA. Methods Totally 1789 SBA patients from the Surveillance, Epidemiology, and End Results (SEER) database between 1988–2010, 437 patients from SEER database between 2011–2013 and 166 patients from multicenters were categorized into development, validation and test cohort, respectively. The TLM staging was developed in the development cohort using Ensemble Algorithm for Clustering Cancer Data (EACCD) method. C-index was used to assess the performance of the TLM staging in predicting cancer-specific survival (CSS) and was compared with the traditional 8 th edition TNM staging. Findings Four-category TLM staging designed for the development cohort showed higher discriminatory power than TNM staging in predicting CSS in the development cohort (0.682 vs. 0.650, P < 0.001), validation cohort (0.682 vs. 0.654, P = 0.022), and test cohort (0.659 vs. 0.611, P = 0.023), respectively. TLM staging continued to show its higher predictive efficacy than the 8 th TNM in TNM stage II/III patients or in patients with lymph node yield less than 8. Interpretation TLM staging showed a better prognostic performance than the 8 th TNM staging especially TNM stage II/III or patients with lymph node yield less than 8 and therefore, could serve to complement the TNM staging in patients with SBA. Funding A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Development and validation of a survival nomogram for patients with Siewert type II/III adenocarcinoma of the esophagogastric junction based on real-world data

“…The only proven significant independent prognostic factor in the three cohorts was LODDS. LODDS is a newly identified promising index for prognosis prediction, which has been verified in several malignancies, such as small bowel adenocarcinoma [ 18 , 19 ], gastric cancer [ 20 ], and AEG [ 12 , 21 ]. With data from the SEER database, Xu et al [ 21 ] demonstrated LODDS exhibited greater prognostic prediction accuracy in postoperative patients with Siewert type II AEG when compared to using PLN and LNR.…”

Small bowel adenocarcinoma of the jejunum detected by double contrast enhanced ultrasound: a case report of a novel ultrasound modality

“…Consequently, SBA is often diagnosed at more advanced stages compared to colorectal cancer ( 3 ). Additionally, SBA frequently presents with complications in the immediate area, including obstruction (40%) or bleeding (26%), further complicating its management ( 4 , 10 ). One study indicated that outcomes of SBAs appeared not to have improved with the progress of technology and time ( 10 ).…”

“…Additionally, SBA frequently presents with complications in the immediate area, including obstruction (40%) or bleeding (26%), further complicating its management ( 4 , 10 ). One study indicated that outcomes of SBAs appeared not to have improved with the progress of technology and time ( 10 ). The explanation for this finding may be the lack of screening methods, resulting in missed opportunities for timely operative treatment.…”

Pathological-Features-Modified TNM Staging System Improves Prognostic Accuracy for Rectal Cancer

“…The TNMP stage was developed using a previously reported machine learning algorithm, an ensemble algorithm for clustering cancer data. [10][11][12][13][14] The main idea of ensemble methods is to use information from multiple models using multiple clustering algorithms to improve predictive performance in comparison to a single model. The performances of the TNM and TNMP models were assessed in terms of discriminatory ability (difference in survival between groups), monotonicity (increasing stage groups with decreasing patient survival), and homogeneity (difference in survival among patients within the same group), using multiple methods, including R 2 , linear trend χ 2 test, Cochran Armitage test for trends, Akaike information criterion, C-index, and integrated area under the curve.…”