Prognostic value of a new staging system based on the retrieved number and metastatic rate of LNs in gastric cancer with ≤15 retrieved LNs

The prognostic ability of radiotherapy of different colorectal cancer histological subtypes and tumor sites

The prognostic significance of radiotherapy (RT) for colorectal cancer (CRC) has shown conflicting results, particularly among different pathological subtypes, including adenocarcinoma (AC), mucinous adenocarcinoma (MC), and signet-ring cell carcinoma (SR). This study analyzed the prognosis of three pathological CRC types and focused on the prognostic significance of RT on three CRC histological subtypes. Patients diagnosed with AC (n = 54,174), MC (n = 3813), and SR (n = 664) in the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database (2010-2017) were evaluated. Cox regression models and competitive risk models were built to assess the effect of RT on the risk of CRC-associated death. Potential interactions between RT and stratified variables including age, sex, and tumor location were examined by multiplicative models. Compared with AC patients, SR patients had the worst overall survival (OS) among 3 subtypes of CRC (log-rank test, p < 0.001). Compared with patients who did not receive radiotherapy, RT was associated with a 1.09-fold (HR = 1.09, 95%[CI]: 1.03, 1.15) elevated risk of death among AC patients. In the SR group, RT significantly reduced the risk of death by 39% (HR = 0.61, 95%[CI]: 0.39-0.95). However, RT did not appear to independently influence survival in the MC group (HR = 0.96, 95%[CI]: 0.77, 1.21). In the subgroup analysis, tumor location (colon and rectum) significantly modified the association between RT and the risk of death among the AC and SR patients (p for interaction < 0.05). SR patients exhibited a worse OS (overall survival) than AC patients, and the effect of RT varied according to CRC histological subtypes. This can ultimately lead to more personalized and effective treatment strategies for CRC patients.

Novel Prognostic Models Predicting the Cancer-Specific Survival in Patients with Cutaneous Melanoma Based on Metastatic Lymph Node Status

BACKGROUND

In cutaneous melanoma (CM), the present methods of lymph node (LN) staging have not sufficiently utilized the prognostic information of metastatic LNs. In this study, we aimed to construct prognostic nomograms based on the number of positive LNs (PLNs) and other clinicopathologic characteristics of CM patients.

METHODS

Two prognostic models were constructed in the none/single PLN (PLN_none/single) and multiple PLN (PLN_multiple) cohorts, respectively. Independent prognostic predictors associated with cancer-specific survival (CSS) in the above two cohorts were integrated to construct two nomograms for predicting the probability of 2-, 4-, and 6-year CSS in the PLN_none/single and PLN_multiple cohorts. The nomograms were evaluated by the area under the receiver operating characteristic curves (AUC), the calibration plots, and the decision curve analyses (DCAs).

RESULTS

A total of 31,065 CM cases were included in this study. Factors included in the prognostic nomogram for patients in the PLN_none/single cohort were age, sex, race, marital status, insurance, primary tumor site, T stage, and number of PLNs, while factors included in the nomogram for cases in the PLN_multiple cohort included age, sex, marital status, insurance, primary tumor site, T stage, and number of PLNs. The AUC values for 2-, 4-, and 6-year CSS in the validation group of the PLN_none/single cohort were 0.833, 0.811, and 0.818, respectively, while in the validation group of the PLN_multiple cohort, the AUC values for 2-, 4,- and 6-year CSS were 0.720, 0.723, and 0.745, respectively. Compared with the American Joint Committee on Cancer 7th edition staging system, our two nomograms showed better predictive values. Additionally, the calibration plots and DCA curves for 2-, 4-, and 6-year CSS prediction demonstrated good coordination and net benefit in both the PLN_none/single and PLN_multiple cohorts.

CONCLUSION

Our nomograms, based on the number of PLNs and other clinicopathologic characteristics, showed good predictive ability for predicting the survival of CM patients.