Prognostic Nomograms Based on Three Lymph Node Classification Systems for Resected Gastric Adenocarcinoma: A Large Population-Based Cohort Study and External Validation

Prognostic significance of an innovative staging system based on the logarithmic odds of positive lymph nodes for resectable gastroesophageal cancer after neoadjuvant chemoradiation: a population-based study with external validation of data

BACKGROUND

After receiving neoadjuvant chemoradiation, the number of examined lymph nodes in resectable gastroesophageal cancer (GEC) will decrease, this may not accurately determine the N staging. So our study evaluates the clinical significance of a new staging model based on the logarithmic odds of positive lymph nodes (LODDS) in patients with GEC after receiving neoadjuvant chemoradiation.

METHODS

A total of 1 130 patients with pathologically diagnosed GEC who received neoadjuvant chemoradiation from 2004 to 2019 included in the National Cancer Institute Surveillance, Epidemiology, and Results (SEER) database were selected for analysis. Lymph nodes were staged according to the AJCC TNM staging system (eighth edition) and LODDS. Patient prognosis across the two systems were evaluated by the Kaplan-Meier method, differences in node staging were evaluated by the Akaike information criterion and Bayesian information criterion. In addition, 914 patients from our center were externally validated.

RESULTS

Compared to the traditional TNM staging system, the new TLODDSM staging system was comprised of stage I, stage II, stage IIIA, stage IIIB, and stage IVA, and decision curve analysis showed that the new staging system had higher benefits for different decision thresholds than the old staging system. The Akaike information criterion and Bayesian information criterion of the new staging system was lower than those of the old staging system, indicating the sensitivity of the TLODDSM staging system for predicting the prognosis of patients was higher. In addition, stage-IIIB or -IVA patients in the new staging system benefited from adjuvant chemotherapy. The externally validated data from our center supported this conclusion.

CONCLUSIONS

Compared to the TNM staging system, the TLODDSM staging system has significant advantages in predicting prognosis of patients with GEC who have completed neoadjuvant chemoradiation, guiding the adjuvant chemotherapy for patients.

Comparison of the predictive performance of three lymph node staging systems for late-onset gastric cancer patients after surgery

Introduction

Lymph node (LN) status is a vital prognostic factor for patients. However, there has been limited focus on predicting the prognosis of patients with late-onset gastric cancer (LOGC). This study aimed to investigate the predictive potential of the log odds of positive lymph nodes (LODDS), lymph node ratio (LNR), and pN stage in assessing the prognosis of patients diagnosed with LOGC.

Methods

The LOGC data were obtained from the Surveillance, Epidemiology, and End Results database. This study evaluated and compared the predictive performance of three LN staging systems. Univariate and multivariate Cox regression analyses were carried out to identify prognostic factors for overall survival (OS). Three machine learning methods, namely, LASSO, XGBoost, and RF analyses, were subsequently used to identify the optimal LN staging system. A nomogram was built to predict the prognosis of patients with LOGC. The efficacy of the model was demonstrated through receiver operating characteristic (ROC) curve analysis and decision curve analysis.

Results

A total of 4,743 patients with >16 removed lymph nodes were ultimately included in this investigation. Three LN staging systems demonstrated significant performance in predicting survival outcomes (P < 0.001). The LNR exhibited the most important prognostic ability, as evidenced by the use of three machine learning methods. Utilizing independent factors derived from multivariate Cox regression analysis, a nomogram for OS was constructed.

Discussion

The calibration, C-index, and AUC revealed their excellent predictive performance. The LNR demonstrated a more powerful performance than other LN staging methods in LOGC patients after surgery. Our novel nomogram exhibited superior clinical feasibility and may assist in patient clinical decision-making.

What determines complications and prognosis among patients subject to multivisceral resections for locally advanced gastric cancer?

BACKGROUND

Locally advanced gastric cancer (GC) extending to the surrounding tissues may require a multivisceral resection (MVR) to provide the best chance of cure. However, little is known about how the extent of organ resection affects the risks and benefits of surgery.

METHODS

An electronic database of patients treated between 1996 and 2020 in an academic surgical centre was reviewed. MVRs were defined as partial or total gastrectomy combined with splenectomy, distal pancreatectomy, or partial colectomy.

RESULTS

Suspected intraoperative tumour invasion of perigastric organs (cT4b) was found in 298 of 1476 patients with non-metastatic GC, and 218 were subject to MVRs, including the spleen (n = 126), pancreas (n = 51), and colon (n = 41). MVRs were associated with higher proportions of surgical and general complications, but not mortality. A nomogram was developed to predict the risk of major postoperative morbidity (Clavien-Dindo's grade ≥ 3a), and the highest odds ratio for major morbidity identified by logistic regression modelling was found for distal pancreatectomy (2.53, 95% CI 1.23-5.19, P = 0.012) and colectomy (2.29, 95% CI 1.04-5.09, P = 0.035). Margin-positive resections were identified by the Cox proportional hazards model as the most important risk factor for patients' survival (hazard ratio 1.47, 95% CI 1.10-1.97). The extent of organ resection did not affect prognosis, but a MVR was the only factor reducing the risk of margin positivity (OR 0.44, 95% CI 0.21-0.87).

CONCLUSIONS

The risk of multivisceral resections is associated with the organ being removed, but only MVRs increase the odds of complete tumour clearance for locally advanced gastric cancer.

Log odds of positive lymph nodes as a novel prognostic predictor for gastric cancer: a systematic review and meta-analysis

BACKGROUND

We conducted a systematic review and meta-analysis to summarize the predictive and prognostic ability of the log odds of positive lymph nodes (LODDS) staging system and compare it with pathological N (pN) classification and the ratio-based lymph node system (rN) for the overall survival (OS) of gastric cancer (GC).

METHODS

Through a systematic review till March 7, 2022, we identified population-based studies that reported the prognostic effects of LODDS in patients with GC. We compare the predictive effectiveness of the LODDS staging system with that of the rN and pN classification systems for the OS of GC.

RESULTS

Twelve studies comprising 20,312 patients were included in this systematic review and meta-analysis. The results showed that LODDS1, LODDS2, LODDS3, and LODDS4 in GC patients were correlated with poor OS compared with LODDS0 (LODDS1 vs. LODDS0: HR = 1.62, 95% CI (1.42, 1.85); LODDS2 vs. LODDS0: HR = 2.47, 95% CI (2.02, 3.03); LODDS3 vs. LODDS0: HR = 3.15, 95% CI (2.50, 3.97); LODDS4 vs. LODDS0: HR = 4.55, 95% CI (3.29, 6.29)). Additionally, significant differences in survival were observed among patients with different LODDS classifications (all P-values were < 0.001) with the same rN and pN classifications. Meanwhile, for patients with different pN or rN classifications with the same LODDS classification, prognosis was highly similar.

CONCLUSION

The findings show that LODDS is correlated with the prognosis of GC patients and is superior to the pN and rN classifications for prognostic assessment.

Reliability of the Lymph Node Ratio in the Prediction of Gastric Cancer Survival

Background. Lymph node metastasis is the major determinant factor in the prognosis of gastric cancer. There is still no definite consensus on the lymph node number that should be harvested during gastric cancer surgery. Lymph Node Ratio (LNR) is defined as the ratio of metastatic nodes to the total number of pathologically examined lymph nodes. LNR has been proposed to be a sensitive prognostic factor in patients with gastric cancer. In this study the reliability of the LNR is tested for being a prognostic factor in gastric cancer survival. Methods. Medical records of 244 patients, with neither distant metastases nor neoadjuvant treatment underwent curative gastrectomy, were analyzed retrospectively in terms of survival according to the lymph node ratio (LNR). Patients were divided in two groups by using LNR cut-off value. Results. LNR of 0.4 was proved to be the best cut-off value to predict the prognosis of patients with gastric cancer. Univariate and multivariate analysis revealed that age over 65 (p < 0.001), and LNR ≥ 0.4 (p = 0.02) were independent factors in gastric cancer survival. Patients with LNR ≥ 0.4 presented with worse outcomes regarding other prognostic parameters (tumor differentiation, tumor diameter, lymphovascular invasion or perineural invasion), despite similar numbers of lymph nodes being harvested in both groups during surgery. Conclusion. Lymph node ratio is a reliable parameter to predict the survival in gastric cancer.

Comparison of Four Lymph Node Staging Systems in Gastric Adenocarcinoma after Neoadjuvant Therapy – A Population-Based Study

Introduction

Neoadjuvant treatment leads in a reduction in positive lymph nodes and examined lymph nodes (ELN), which may affect assessment of lymph node staging and postoperative treatment. We aimed to compare the staging systems of lymph node ratio (LNR), the positive logarithm ratio of lymph nodes (LODDS), negative lymph nodes (NLN), and the 8th AJCC ypN stage for patients with gastric adenocarcinoma after neoadjuvant therapy.

Materials and Methods

Data was collected from the Surveillance, Epidemiology, and End Results database and 1,551 patients with gastric adenocarcinoma who underwent neoadjuvant therapy and radical surgery were enrolled. Harrell’s concordance index, the Receiver Operative Curve, the likelihood ratio test, and the Akaike information criterion were used to compare the predictive abilities of the different staging systems.

Results

Among the 1,551 patients, 689 (44.4%) had ELN < 16 and node-negative patients accounted for 395 (25.5%). When regarded as the categorical variable, LNR had better discrimination power, higher homogeneity, and better model fitness for CSS and OS compared to other stage systems, regardless of the status of ELN. When regarded as the continuos variable, LODDS outperformed others for CSS. Furthermore, the NLN staging system performed superior to others in node-negative patients.

Conclusions

LNR had a better predictive performance than ypN, LODDS and NLN staging systems regardless of the status of ELN when regarded as the categorical variable, whereas LOODS became the better predictive factor for CSS when regarded as the continuos variable. In node-negative patients, NLN might be a feasible option for evaluating prognosis. A combination of LNR and NLN should be considered as user-friendly method in the clinical prognostic assessment.

Log odds of positive lymph nodes as a novel prognostic predictor for colorectal cancer: a systematic review and meta-analysis

BACKGROUND

Colorectal cancer (CRC) is the third most prevalent cancer in the world, which remains one of the leading causes of cancer-related deaths. Accurate prognosis prediction of CRC is pivotal to reduce the mortality and disease burden. Lymph node (LN) metastasis is one of the most commonly used criteria to predict prognosis in CRC patients. However, inaccurate surgical dissection and pathological evaluation may lead to inaccurate nodal staging, affecting the effectiveness of pathological N (pN) classification in survival prediction among patients with CRC. In this meta-analysis, we aimed to estimate the prognostic value of the log odds of positive lymph nodes (LODDS) in patients with CRC.

METHODS

PubMed, Medline, Embase, Web of Science and the Cochrane Library were systematically searched for relevant studies from inception to July 3, 2021. Statistical analyses were performed on Stata statistical software Version 16.0 software. To statistically assess the prognostic effects of LODDS, we extracted the hazard ratio (HR) and 95% confidence interval (CI) of overall survival (OS) and disease-free survival (DFS) from the included studies.

RESULTS

Ten eligible articles published in English involving 3523 cases were analyzed in this study. The results showed that LODDS1 and LODDS2 in CRC patients was correlated with poor OS compared with LODDS0 (LODDS1 vs. LODDS0: HR = 1.77, 95% CI (1.38, 2.28); LODDS2 vs. LODDS0: HR = 3.49, 95% CI (2.88, 4.23)). Meanwhile, LODDS1 and LODDS2 in CRC patients was correlated with poor DFS compared with LODDS0 (LODDS1 vs. LODDS0: HR = 1.82, 95% CI (1.23, 2.68); LODDS2 vs. LODDS0: HR =3.30, 95% CI (1.74, 6.27)).

CONCLUSIONS

The results demonstrated that the LODDS stage was associated with prognosis of CRC patients and could accurately predict the prognosis of patients with CRC.

A prognostic model of patients with ovarian mucinous adenocarcinoma: a population-based analysis

BACKGROUND

Ovarian mucinous carcinoma is a disease that requires unique treatment. But for a long time, guidelines for ovarian serous carcinoma have been used for the treatment of ovarian mucinous carcinoma. This study aimed to construct and validate nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in patients with ovarian mucinous adenocarcinoma.

METHODS

In this study, patients initially diagnosed with ovarian mucinous adenocarcinoma from 2004 to 2015 were screened from the Surveillance, Epidemiology, and End Results (SEER) database, and divided into the training group and the validation group at a ratio of 7:3. Independent risk factors for OS and CSS were determined by multivariate Cox regression analysis, and nomograms were constructed and validated.

RESULTS

In this study, 1309 patients with ovarian mucinous adenocarcinoma were finally screened and randomly divided into 917 cases in the training group and 392 cases in the validation group according to a 7:3 ratio. Multivariate Cox regression analysis showed that the independent risk factors of OS were age, race, T_stage, N_stage, M_stage, grade, CA125, and chemotherapy. Independent risk factors of CSS were age, race, marital, T_stage, N_stage, M_stage, grade, CA125, and chemotherapy. According to the above results, the nomograms of OS and CSS in ovarian mucinous adenocarcinoma were constructed. In the training group, the C-index of the OS nomogram was 0.845 (95% CI: 0.821-0.869) and the C-index of the CSS nomogram was 0.862 (95%CI: 0.838-0.886). In the validation group, the C-index of the OS nomogram was 0.843 (95% CI: 0.810-0.876) and the C-index of the CSS nomogram was 0.841 (95%CI: 0.806-0.876). The calibration curve showed the consistency between the predicted results and the actual results, indicating the high accuracy of the nomogram.

CONCLUSION

The nomogram provides 3-year and 5-year OS and CSS predictions for patients with ovarian mucinous adenocarcinoma, which helps clinicians predict the prognosis of patients and formulate appropriate treatment plans.