Prognostic nomogram based on the lymph node metastasis indicators for patients with bladder cancer: A SEER population‐based study and external validation

Abstract

Purpose This study aimed to compare the prognostic value of multiple lymph node metastasis (LNM) indicators and to develop optimal prognostic nomograms for bladder cancer (BC) patients. Methods BC patients were obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015, and randomly partitioned into training and internal validation cohorts. Genomic and clinical data were collected from The Cancer Genome Atlas (TCGA) as external validation cohort. The predictive efficiency of LNM indicators was compared by constructing multivariate Cox regression models. We constructed nomograms on basis of the optimal models selected for overall survival (OS) and cause‐specific survival (CSS). The performance of nomograms was evaluated with calibration plot, time‐dependent area under the curve (AUC) and decision curve analysis (DCA) in three cohorts. We subsequently estimated the difference of biological function and tumor immunity between two risk groups stratified by nomograms in TCGA cohort. Results Totally, 10,093 and 107 BC patients were screened from the SEER and TCGA databases. N classification, positive lymph nodes (PLNs), lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS) were all independent predictors for OS and CSS. The filtered models containing LODDS had minimal Akaike Information Criterion, maximal concordance indexes and AUCs. Age, LODDS, T and M classification were integrated into nomogram for OS, while nomogram for CSS included gender, tumor grade, LODDS, T and M classification. The nomograms were successfully validated in predictive accuracy and clinical utility in three cohorts. Additionally, the tumor microenvironment was different between two risk groups. Conclusions LODDS demonstrated superior prognostic performance over N classification, PLN and LNR for OS and CSS of BC patients. The nomograms incorporating LODDS provided appropriate prediction of BC, which could contribute to the tumor assessment and clinical decision‐making.

A novel log odds of positive lymph nodes–based nomogram for predicting overall survival in patients with colorectal signet ring cell carcinoma: a SEER population-based study

“…In other words, the prognosis of patients with 1 positive lymph node out of 1 harvested lymph node is of vital difference from patients with 20 positive lymph nodes out of 20 harvested lymph nodes, which casts doubt on the predictive value of LNR, a metric extensively studied in non-colorectal malignancies, including breast cancer, esophageal cancer, non-small cell lung cancer, and oropharyngeal cancer [ 17 – 20 ], but failing to further stratify patients with 0 or 1 PLN [ 21 ]. Meanwhile, LODDS, a novel LNM-related indicator for predicting cancer prognosis, has been put forward in previous studies where suggesting LODDS outperforms other LN status indicators in predicting the prognosis of bladder cancer, rectal cancer, small cell lung cancer, and so forth [ 22 – 24 ]. Since the presence of LNM is related to poor prognosis and determines the need for adjuvant therapy [ 25 , 26 ], it is imperative to identify independent LN prognostic factors for SRCC and incorporate the indicators with the best predictive performances in an effort to construct a nomogram for SRCC patients.…”

Construction of a novel nomogram for predicting overall survival in patients with Siewert type II AEG based on LODDS: a study based on the seer database and external validation

“…Li et al. compared the predictive efficiency of LNM indexes by constructing a multifactorial Cox regression model, and found that LODDS was superior to N classification, PLN and LNR in prognosticating OS and CSS in prostate cancer patients ( 28 ); Zhao et al. compared the effectiveness of N classification, PLN, LNR and LODDS in predicting cancer-specific survival in patients with small cell lung cancer and found that the LODDS model showed the highest accuracy in predicting cancer-specific survival in patients with small cell lung cancer compared to N classification, PLN and LNR ( 29 ).…”

Prognostic factors in extensive-stage small cell lung cancer patients with organ-specific metastasis: unveiling commonalities and disparities

“…Importantly, no studies have investigated common and distinct prognostic factors for liver, lung, bone, and brain metastasis in extensive-stage SCLC (ES-SCLC) patients. Nomograms, which integrate various predictors to provide comprehensive survival outcomes, have found widespread application in evaluating patient prognosis across different cancer types (Hu et al 2022 ; Li et al 2022 ). However, only two studies have so far involved constructing nomograms for the prognosis of ES-SCLC patients with metastasis, and the predictive performance of these models remains to be improved (Shan et al 2021 ; Fan et al 2021 ).…”