Value of the log odds of positive lymph nodes for prognostic assessment of colon mucinous adenocarcinoma: Analysis and external validation

Cai, Huajun; Xu, Tan; Zehao, Zhuang; Zhang, Yiyi; Gao, Yuan; Liu, Xing; Zhuang, Jinfu; Yang, Yuanfeng; Guan, Guoxian

doi:10.1002/cam4.4366

Cited by 10 publications

(9 citation statements)

References 40 publications

(85 reference statements)

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“…Construction of the prediction model by RPA analysis was performed by autoRPA, an algorithm located on a web server [ 10 ] ( http://rpa.renlab.org ). It can build a decision tree from survival data through the RPA algorithm and log-rank statistics, providing a reasonable basis for making appropriate clinical decision [ 11 ]. Time-dependent area under the curve (tAUC) was calculated to evaluate the discriminatory ability of the model, and decision curve analysis (DCA) was applied to evaluate the clinical net benefit of the model for predicting prognosis.…”

Section: Methodsmentioning

confidence: 99%

Proposed prognostic subgroups and facilitated clinical decision-making for additional locoregional radiotherapy in de novo metastatic nasopharyngeal carcinoma: a retrospective study based on recursive partitioning analysis

et al. 2023

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Background The high heterogeneity of de novo metastatic nasopharyngeal carcinoma (dmNPC) makes its prognosis and treatment challenging. We aimed to accurately stage dmNPC and assess the patterns of treatment strategies for different risk groups. Methods The study enrolled a total of 562 patients, 264 from 2007 to 2013 in the training cohort and 298 from 2014 to 2017 in the validation cohort. Univariate and multivariate Cox regression analyses were conducted to determine the independent variables for overall survival (OS). Recursive partitioning analysis (RPA) was applied to establish a novel risk-stratifying model based on these variables. Results After pairwise comparisons of OS, three risk groups were generated: low-risk (involved lesions ≤ 4 without liver involvement), intermediate-risk (involved lesions ≤ 4 with liver involvement or involved lesions > 4 with Epstein–Barr virus (EBV)-DNA < 62,000 copies/ml), and high-risk (involved lesions > 4 with EBV-DNA > 62,000 copies/ml). The 3-year OS rate differed significantly between groups (80.4%, 42.0%, and 20.4%, respectively, all P < 0.05). Adding locoregional intensity-modulated radiotherapy (LRRT) followed by palliative chemotherapy (PCT) resulted in a significant OS benefit over PCT alone for the low- and intermediate-risk groups (P = 0.0032 and P = 0.0014, respectively). However, it provided no survival benefits for the high-risk group (P = 0.6). Patients did not benefit from concurrent chemotherapy during LRRT among the three subgroups (P = 0.12, P = 0.13, and P = 0.3, respectively). These results were confirmed with the validation cohort. Conclusions The novel RPA model revealed superior survival performance in subgroup stratification and could facilitate more effective treatment strategies for dmNPC.

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Section: Methodsmentioning

confidence: 99%

Proposed prognostic subgroups and facilitated clinical decision-making for additional locoregional radiotherapy in de novo metastatic nasopharyngeal carcinoma: a retrospective study based on recursive partitioning analysis

et al. 2023

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“…Nomograms have been developed for predicting the prognosis of CRMA patients. Cai et al developed a nomogram for CRMA, and only patients with stage I–III CRMA were included in the study [ 26 ]. Metastasized and non-metastatic CRCs are representations of systemic tumor biology; therefore, excluding patients with metastasis may inherit the limitations of the American Joint Committee on Cancer (AJCC) stages.…”

Section: Discussionmentioning

confidence: 99%

Establishment and validation of a postoperative predictive model for patients with colorectal mucinous adenocarcinoma

Wang

Song

et al. 2022

World J Surg Onc

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Background The aim of this study was to develop comprehensive and effective nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) rates in patients with colorectal mucinous adenocarcinoma (CRMA). Methods A total of 4711 CRMA patients who underwent radical surgery between 2010 and 2018 from the Surveillance, Epidemiology, and End Results (SEER) database were collected and randomized into development (n=3299) and validation (n=1412) cohorts at a ratio of 7:3 for model development and validation. OS and CSS nomograms were developed using the prognostic factors from the development cohort after multivariable Cox regression analysis. The performance of the nomograms was evaluated using Harrell’s concordance index (C-index), calibration diagrams, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Results The study included 4711 patients. Multivariate Cox regression analysis demonstrated that age, tumor size, grade, pT stage, pN stage, M stage, carcinoembryonic antigen, perineural invasion, tumor deposits, regional nodes examined, and chemotherapy were correlated with OS and CSS. Marital status was independently related to OS. In the development and validation cohorts, the C-index of OS was 0.766 and 0.744, respectively, and the C-index of CSS was 0.826 and 0.809, respectively. Calibration curves and ROC curves showed predictive accuracy. DCA showed that the nomograms had excellent potency over the 8th edition of the TNM staging system with higher clinical net benefits. Significant differences in OS and CSS were observed among low-, medium-, and high-risk groups. Conclusions Nomograms were developed for the first time to predict personalized 1-, 3-, and 5-year OS and CSS in CRMA postoperative patients. External and internal validation confirmed the excellent discrimination and calibration ability of the nomograms. The nomograms can help clinicians design personalized treatment strategies and assist with clinical decisions.

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“…As a statistical method of multivariate analysis, RPA divides patients into different homogeneous risk groups by constructing a decision tree and divides predictors into several groups,whose effects have been reported many times [11,12]. In every node, each predictor was examined for the best split within that variable and the optimal split it corresponds to, which has the greatest difference between patient groups.…”

Section: Recursive Partitioning Analysis (Rpa)mentioning

confidence: 99%

A good preoperative immune prognostic index is predictive of better prognosis for locally advanced rectal cancer patients with ypTNM stage II who underwent radical resection after neoadjuvant chemoradiotherapy

Wang

Cai

et al. 2023

Preprint

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Background: No studies have investigated the role of IPI in assessing the prognosis for LARC patients undergoing nCRT. Objective: We attempted to combine neutrophil-to-lymphocyte ratio (NLR) and serum lactate dehydrogenase (sLDH) to generate a new rectal immune prognostic index (RIPI) to explore whether RIPI is associated with the prognosis of LARC. And try to find out whether there is a population that might benefit from RIPI in LARC. Methods: Locally advanced rectal cancer (LARC) patients who underwent radical surgery after Neoadjuvant chemoradiotherapy (nCRT) from February 2012 to May 2017 were enrolled. Based on the best cut-off points of NLR and sLDH, we developed rectal immune prognostic index (RIPI). Patients were grouped as follows: 1) good, RIPI = 0, good, 0 factors; 2) poor, RIPI = 1, 1 or 2 factors. Results: A total of 642 patients were enrolled. In yp TNM stage II patients, there was a statistically significant difference in 5-year disease-free survival (DFS) (p=0.03) between RIPI=1 and RIPI=0 groups. In ypCR, stage I, stage II, and stage III, there was no significant difference in 5-year DFS between IPI=0 and IPI=1 groups. In multivariate analysis, the significant factor predicting DFS was RIPI score (p=0.035) Conclusion: RIPI was closely related to the prognosis of LARC patients undergoing nCRT. In particular, RIPI is of great significance in evaluating the prognosis of LARC patients with ypTNM stage II who underwent radical resection after nCRT.

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Value of the log odds of positive lymph nodes for prognostic assessment of colon mucinous adenocarcinoma: Analysis and external validation

Abstract: This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 10 publications

References 40 publications

Proposed prognostic subgroups and facilitated clinical decision-making for additional locoregional radiotherapy in de novo metastatic nasopharyngeal carcinoma: a retrospective study based on recursive partitioning analysis

Proposed prognostic subgroups and facilitated clinical decision-making for additional locoregional radiotherapy in de novo metastatic nasopharyngeal carcinoma: a retrospective study based on recursive partitioning analysis

Establishment and validation of a postoperative predictive model for patients with colorectal mucinous adenocarcinoma

A good preoperative immune prognostic index is predictive of better prognosis for locally advanced rectal cancer patients with ypTNM stage II who underwent radical resection after neoadjuvant chemoradiotherapy

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