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

A log odds of positive lymph nodes-based predictive model effectively forecasts prognosis and guides postoperative adjuvant chemotherapy duration in stage III colon cancer: a multi-center retrospective cohort study

BACKGROUND

The log odds of positive lymph nodes (LODDS) was considered a superior staging system to N stage in colon cancer, yet its value in determining the optimal duration of adjuvant chemotherapy for stage III colon cancer patients has not been evaluated. This study aims to assess the prognostic value of a model that combines LODDS with clinicopathological information for stage III colon cancer patients and aims to stratify these patients using the model, identifying individuals who could benefit from varying durations of adjuvant chemotherapy.

METHOD

A total of 663 consecutive patients diagnosed with stage III colon cancer, who underwent colon tumor resection between November 2007 and June 2020 at Sun Yat-sen University Cancer Center and Longyan First Affiliated Hospital of Fujian Medical University, were enrolled in this study. Survival outcomes were analyzed using Kaplan-Meier, Cox regression. Nomograms were developed to forecast patient DFS, with the Area Under the Curve (AUC) values of time-dependent Receiver Operating Characteristic (timeROC) and calibration plots utilized to assess the accuracy and reliability of the nomograms.

RESULTS

Multivariate analysis revealed that perineural invasion (HR = 1.776, 95% CI: 1.052-3.003, P = 0.032), poor tumor differentiation (HR = 1.638, 95% CI: 1.084-2.475, P = 0.019), and LODDS groupings of 2 and 1 (HR = 1.920, 95% CI: 1.297-2.842, P = 0.001) were independent predictors of disease-free survival (DFS) in the training cohort. Nomograms constructed from LODDS, perineural invasion, and poor tumor differentiation demonstrated robust predictive performance for 3-year and 5-year DFS in both training (3-year AUC = 0.706, 5-year AUC = 0.678) and validation cohorts (3-year AUC = 0.744, 5-year AUC = 0.762). Stratification according to this model showed that patients in the high-risk group derived significant benefit from completing 8 cycles of chemotherapy (training cohort, 82.97% vs 67.17%, P = 0.013; validation cohort, 89.49% vs 63.97%, P = 0.030).

CONCLUSION

The prognostic model, integrating LODDS, pathological differentiation, and neural invasion, demonstrates strong predictive accuracy for stage III colon cancer prognosis. Moreover, stratification via this model offers valuable insights into optimal durations of postoperative adjuvant chemotherapy.

Log odds of positive lymph nodes (LODDS)-based novel nomogram for survival estimation in patients with invasive micropapillary carcinoma of the breast

BACKGROUND

Invasive micropapillary carcinoma (IMPC) of the breast is known for its high propensity for lymph node (LN) invasion. Inadequate LN dissection may compromise the precision of prognostic assessments. This study introduces a log odds of positive lymph nodes (LODDS) method to address this issue and develops a novel LODDS-based nomogram to provide accurate prognostic information.

METHODS

The study analyzed data from 1,901 patients with breast IMPC from the Surveillance, Epidemiology, and End Results database. It assessed the relationships between LODDS and the number of excised LN (eLN), positive LN (pLN), and the pLN ratio (pLNR), identifying an optimal threshold value using a restricted cubic spline method. Predictive factors were identified by the Cox least absolute shrinkage and selection operator (Cox-LASSO) regression and validated through multivariate Cox regression to construct a nomogram. The model's accuracy, discrimination, and utility were assessed. The study also explored the consequences of excluding LODDS from the nomogram and compared its effectiveness with the tumor-node-metastasis (TNM) staging system.

RESULTS

LODDS improved N status classification by identifying heterogeneity in patients with pLN ratios of 0% (pLN =0) or 100% (pLN =eLN) and setting -1.08 as the ideal cutoff. Five independent prognostic factors for breast cancer-specific survival (BCSS) were identified: tumor size, N status, LODDS, progesterone receptor status, and histological grade. The LODDS-based nomogram achieved a strong concordance index of 0.802 (95% CI: 0.741-0.863), surpassing both the version without LODDS and the conventional TNM staging in all tests.

CONCLUSIONS

For breast IMPC, LODDS served as an independent prognostic factor, its effectiveness unaffected by the anatomical LN count, enhancing the accuracy of N staging. The LODDS-based nomogram showed promise in offering more personalized prognostic information.

Log odds of positive lymph nodes show better predictive performance on the prognosis of early-onset colorectal cancer

BACKGROUND

As the incidence of colorectal cancer tends to be younger, early-onset colorectal cancer (EOCRC) has attracted more attention in recent years. We aimed to assess the optimal lymph node staging system among EOCRC patients, and then, establish informative assessment models for prognosis prediction.

METHODS

Data of EOCRC were retrieved from the Surveillance, Epidemiology, and End Results database. Survival prediction ability of three lymph node staging systems including N stage of the tumor node metastasis (TNM) staging system, lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) was assessed and compared using Akaike information criterion (AIC), Harrell's concordance index (C-index), and likelihood ratio (LR) test. Univariate and multivariate Cox regression analyses were conducted to identify the prognostic predictors for overall survival (OS) and cancer-specific survival (CSS). Effectiveness of the model was demonstrated by receiver operative curve and decision curve analysis.

RESULTS

A total of 17,535 cases were finally included in this study. All three lymph node staging systems showed significant performance in survival prediction (p < 0.001). Comparatively, LODDS presented a better ability of prognosis prediction with lower AIC (OS: 70,510.99; CSS: 60,925.34), higher C-index (OS: 0.6617; CSS: 0.6799), and higher LR test score (OS: 998.65; CSS: 1103.09). Based on independent factors identified from Cox regression analysis, OS and CSS nomograms for EOCRC were established and validated.

CONCLUSIONS

LODDS shows better predictive performance than N stage or LNR among patients with EOCRC. Novel validated nomograms based on LODDS could effectively provide more prognostic information than the TNM staging system.

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

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.

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

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.

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

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.

Development and Validation of Novel Nomograms to Predict the Overall Survival and Cancer-Specific Survival of Cervical Cancer Patients With Lymph Node Metastasis

Objective

The objective of this study was to establish and validate novel individualized nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in cervical cancer patients with lymph node metastasis.

Methods

A total of 2,956 cervical cancer patients diagnosed with lymph node metastasis (American Joint Committee on Cancer, AJCC N stage=N1) between 2000 and 2018 were included in this study. Univariate and multivariate Cox regression models were applied to identify independent prognostic predictors, and the nomograms were established to predict the OS and CSS. The concordance index (C-index), calibration curves, and receiver operating characteristic (ROC) curves were applied to estimate the precision and discriminability of the nomograms. Decision-curve analysis (DCA) was used to assess the clinical utility of the nomograms.

Results

Tumor size, log odds of positive lymph nodes (LODDS), radiotherapy, surgery, T stage, histology, and grade resulted as significant independent predictors both for OS and CSS. The C-index value of the prognostic nomogram for predicting OS was 0.788 (95% CI, 0.762–0.814) and 0.777 (95% CI, 0.758–0.796) in the training and validation cohorts, respectively. Meanwhile, the C-index value of the prognostic nomogram for predicting CSS was 0.792 (95% CI, 0.767–0.817) and 0.781 (95% CI, 0.764–0.798) in the training and validation cohorts, respectively. The calibration curves for the nomograms revealed gratifying consistency between predictions and actual observations for both 3- and 5-year OS and CSS. The 3- and 5-year area under the curves (AUCs) for the nomogram of OS and CSS ranged from 0.781 to 0.828. Finally, the DCA curves emerged as robust positive net benefits across a wide scale of threshold probabilities.

Conclusion

We have successfully constructed nomograms that could predict 3- and 5-year OS and CSS of cervical cancer patients with lymph node metastasis and may assist clinicians in decision-making and personalized treatment planning.

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

Purpose

To evaluate the impact of the log odds of positive lymph nodes (LODDS) on cancer‐specific survival (CSS) in colon mucinous adenocarcinoma (MAC) patients, compared with pN stage and the lymph nodes ratio (LNR).

Methods

A total of 10,182 colon MAC patients from the Surveillance, Epidemiology, and End Results database were divided into the training group. The external validation group included 153 patients from Fujian Medical University Union Hospital. The Cox regression method was used to identify prognostic risk factors. Nomograms were evaluated by Harrell's concordance index (C‐index) and calibration curves. Recursive partitioning analysis (RPA) was used to develop a novel staging system.

Results

Time‐dependent receiver operating characteristic curves (ROC) to predict CSS showed the areas under the ROC curve of LODDS were always higher than pN stage and LNR. LNR and LODDS classifications can well distinguish the prognosis of patients with the same pN stage. Cox analyses indicated that age, tumor size, pT stage, pN stage, LNR, and LODDS were independent predictors of CSS (p < 0.05). Based on three lymph nodes classifications, we constructed three prognostic nomograms models for CSS. The C‐index of the pN, LNR, and LODDS classification nomograms were 0.746 (95% confidence interval [95% CI]: 0.736–0.756), 0.750 (95% CI: 0.740–0.760), and 0.758 (95% CI: 0.748–0.768), respectively. In external validation, we observed the C‐index of LODDS classification nomograms was 0.787 (95% CI: 0.648–0.926). RPA stage, including four stages, was constructed successfully based on pT stage and LNR or LODDS, respectively. The 3‐, 5‐, and 8‐year areas under the ROC curve of LNR‐RPA stage and LODDS‐RPA stage were superior to tumor‐node‐metastasis stage.

Conclusion

LODDS to be a better prognostic factor of CSS for colon MAC patients than pN stage and LNR. A nomogram and RPA stage base on LODDS can provide accurate information for personalized cancer treatment.