Predictive Performance of Current Nodal Staging Systems in Various Categories of Pancreatic Cancer

Prognostic significance of three lymph node staging systems in pancreatic cancer with ≤ 12 and > 12 retrieved lymph nodes

This study aimed to evaluate and compare the predictive performance of negative lymph nodes (NLN), lymph node ratio (LNR), and N stage in pancreatic ductal adenocarcinoma (PDAC) among patients with ≤ 12 retrieved lymph nodes and those with > 12 retrieved lymph nodes. Moreover, the association between the three nodal staging systems and survival was also explored. Clinical data on patients diagnosed with PDAC between 2004 and 2020 were downloaded from the Surveillance, Epidemiology, and End Results (SEER) database. Cox regression was performed to identify independent predictors of cancer specific survival (CSS) and overall survival (OS). Survival probability was calculated and compared by the Kaplan-Meier method and log rank test. Akaike information criterion (AIC) and Harrell's C-index were used to evaluate the prognostic ability of each nodal staging system. All three lymph node staging systems were independent predictors of CSS and OS. A higher NLN, a lower N stage, and a lower LNR were associated with improved survival. Compared with N stage, LNR staging performed better with a lower AIC and higher C-index for predicting the prognosis regardless of the sufficiency of retrieved lymph nodes, while NLN staging performed poorly in both the training and validation set. Subgroup analyses showed that the NLN successfully predicted survival outcomes in both lymph node-positive and node-negative patients. LNR demonstrated better predictive performance in PDAC patients regardless of the sufficiency of retrieved lymph nodes. Notably, for stage N0 disease, NLN was a more important prognostic predictor. The combination of LNR and NLN may offer more precise information on lymph node staging than the current staging system.

Application and subgroup analysis of competing risks model based on different lymph node staging systems in differentiated thyroid cancer

Differentiated thyroid cancer (DTC) is the most common endocrine malignancy, with a rising incidence worldwide. Accurate prognostic models are essential for effective patient management. This study evaluates the prognostic value of various lymph node staging systems in DTC using a competing risks model. We used SEER database records (1998-2016) of 16,527 DTC patients, analyzing N stage, positive lymph node numbers (PLNNs), metastatic lymph node ratio (MLNR), log odds of positive lymph nodes (LODDS), and log odds of the negative lymph node (NLN)/T stage ratio (LONT). Univariate and multivariate analyses in a competing risks model were performed, along with subgroup analyses based on demographic and clinical characteristics. In this study of 16,527 patients with DTC, different lymph node staging systems showed different prognostic correlations in univariate and multivariate analyses. In particular, PLNNs showed significant prognostic correlations in several subgroups. Additionally, PLNNs were more suitable as a lymph node staging system for DTC than LODDS and MLNR in N1 stage subgroups, with an optimal cut-off of 13. Receiver operating characteristic curves, calibration curves and nomograms improved the clinical utility of the prognostic model based on PLNNs. Using competing risks model and subgroup analyses, we found that PLNNs had the best prognostic discriminatory efficacy for patients with DTC, especially those with N1 stage disease, and had an optimal cut-off value of 13.

Pancreatic mucinous adenocarcinoma has different clinical characteristics and better prognosis compared to non-specific PDAC: A retrospective observational study

BACKGROUND

Pancreatic mucinous adenocarcinoma (PMAC) is a rare malignant tumour, and there is limited understanding of its epidemiology and prognosis. Initially, PMAC was considered a metastatic manifestation of other cancers; however, instances of non-metastatic PMAC have been documented through monitoring, epidemiological studies, and data from the Surveillance, Epidemiology, and End Results (SEER) database. Therefore, it is crucial to investigate the epidemiological characteristics of PMAC and discern the prognostic differences between PMAC and the more prevalent pancreatic ductal adenocarcinoma (PDAC).

METHODS

The study used data from the SEER database from 2000 to 2018 to identify patients diagnosed with PMAC or PDAC. To ensure comparable demographic characteristics between PDAC and PMAC, propensity score matching was employed. Kaplan-Meier analysis was used to analyse overall survival (OS) and cancer-specific survival (CSS). Univariate and multivariate Cox regression analyses were used to determine independent risk factors influencing OS and CSS. Additionally, the construction and validation of risk-scoring models for OS and CSS were achieved through the least absolute shrinkage and selection operator-Cox regression technique.

RESULTS

The SEER database included 84,857 patients with PDAC and 3345 patients with PMAC. Notably, significant distinctions were observed in the distribution of tumour sites, diagnosis time, use of radiotherapy and chemotherapy, tumour size, grading, and staging between the two groups. The prognosis exhibited notable improvement among married individuals, those receiving acceptable chemotherapy, and those with focal PMAC (p < 0.05). Conversely, patients with elevated log odds of positive lymph node scores or higher pathological grades in the pancreatic tail exhibited a more unfavourable prognosis (p < 0.05). The risk-scoring models for OS or CSS based on prognostic factors indicated a significantly lower prognosis for high-risk patients compared to their low-risk counterparts (area under the curve OS: 0.81-0.82, CSS: 0.80-0.82).

CONCLUSION

PMAC exhibits distinct clinical characteristics compared to non-specific PDAC. Leveraging these features and pathological classifications allows for accurate prognostication of PMAC or PDAC.

Lymph node ratio is a superior predictor in surgically treated early-onset pancreatic cancer

Background

The prognostic performance of four lymph node classifications, the 8th American Joint Committee on Cancer (AJCC) Tumor Node Metastasis (TNM) N stage, lymph node ratio (LNR), log odds of positive lymph nodes (LODDS), and examined lymph nodes (ELN) in early-onset pancreatic cancer (EOPC) remains unclear.

Methods

The Surveillance, Epidemiology, and End Results (SEER) database was searched for patients with EOPC from 2004 to 2016. 1048 patients were randomly divided into training (n = 733) and validation sets (n = 315). The predictive abilities of the four lymph node staging systems were compared using the Akaike information criteria (AIC), receiver operating characteristic area under the curve (AUC), and C-index. Multivariate Cox analysis was performed to identify independent risk factors. A nomogram based on lymph node classification with the strongest predictive ability was established. The nomogram’s precision was verified by the C-index, calibration curves, and AUC. Kaplan–Meier analysis and log-rank tests were used to compare differences in survival at each stage of the nomogram.

Results

Compared with the 8th N stage, LODDS, and ELN, LNR had the highest C-index and AUC and the lowest AIC. Multivariate analysis showed that N stage, LODDS, LNR were independent risk factors associated with cancer specific survival (CSS), but not ELN. In the training set, the AUC values for the 1-, 3-, and 5-year CSS of the nomogram were 0.663, 0.728, and 0.760, respectively and similar results were observed in the validation set. In addition, Kaplan–Meier survival analysis showed that the nomogram was also an important factor in the risk stratification of EOPC.

Conclusion

We analyzed the predictive power of the four lymph node staging systems and found that LNR had the strongest predictive ability. Furthermore, the novel nomogram prognostic staging mode based on LNR was also an important factor in the risk stratification of EOPC.

Prognostic value of LODDS in medullary thyroid carcinoma based on competing risk model and propensity score matching analysis

Log odds of positive lymph nodes (LODDS) is an independent prognostic factor for patients with medullary thyroid carcinoma (MTC). However, the optimal cutoff value for LODDS needs to be further confirmed, and previous studies have ignored the prevalent competing events of non-cancer deaths among patients with MTC, thus possibly overestimating the risk of death from cancer. The information of patients with MTC who underwent total thyroidectomy was collected from SEER database. Restricted cubic splines (RCS) were used to determine the optimal cutoff for LODDS. Moreover, patients' overall survival (OS) and disease-specific survival (DSS) were determined using Kaplan-Meier and Cox proportional-hazards model. The competing risk models (CRM) were used to reduce the effect of competing events, and propensity score matching was performed to balance the confounding factors between groups. The cutoff value of LODDS determined by RCS was - 1.004, and a total of 2314 patients with MTC were recruited. In the CRM after PSM, factors such as age over 55 years at diagnosis, being male, treatment with chemotherapy or radiotherapy, unknown tumor size, and LODDS > - 1.004 were significantly associated with poor prognosis of patients both in univariate and multivariate analyses, while the presence of multifocal tumor indicated better prognosis. Patients with MTC who were over 55 years old at diagnosis, were male, received chemotherapy or radiation, had an unclear initial tumor size, and had LODDS > - 1.004 had a worse prognosis than patients with multifocal tumor.