Establishing subdivisions of M1 stage nasopharyngeal carcinoma based on decision tree classification: A multicenter retrospective study.

OBJECTIVES: To meet the demand for personalized treatment, effective stratification of patients with metastatic nasopharyngeal carcinoma (mNPC) is essential. Hence, our study aimed to establish an M1 subdivision for prognostic prediction and treatment planning in patients with mNPC. MATERIALS AND METHODS: This study included 1239 patients with mNPC from three medical centers divided into the synchronous mNPC cohort (smNPC, n = 556) to establish an M1 stage subdivision and the metachronous mNPC cohort (mmNPC, n = 683) to validate this subdivision. The primary endpoint was overall survival. Univariate and multivariate Cox analyses identified covariates for the decision-tree model, proposing an M1 subdivision. Model performance was evaluated using time-dependent receiver operating characteristic curves, Harrell's concordance index, calibration plots, and decision curve analyses. RESULTS: The proposed M1 subdivisions were M1a (≤5 metastatic lesions), M1b (>5 metastatic lesions + absent liver metastases), and M1c (>5 metastatic lesions + existing liver metastases) with median OS of 34, 22, and 13 months, respectively (p < 0.001). This M1 subdivision demonstrated superior discrimination (C-index = 0.698; 3-year AUC = 0.707) and clinical utility over those of existing staging systems. Calibration curves exhibited satisfactory agreement between predictions and actual observations. Internal and mmNPC cohort validation confirmed the robustness. Survival benefits from local metastatic treatment were observed in M1a, while immunotherapy improved survival in patients with M1b and M1c disease. CONCLUSION: This novel M1 staging strategy provides a refined approach for prognostic prediction and treatment planning in patients with mNPC, emphasizing the potential benefits of local and immunotherapeutic interventions based on individualized risk stratification.

Efficacy of metastatic lesion radiotherapy in patients with metastatic nasopharyngeal carcinoma: A multicenter retrospective study.

OBJECTIVE: We investigated the efficacy of metastatic lesion radiotherapy (MLRT) in patients with metastatic nasopharyngeal carcinoma (mNPC). MATERIALS AND METHODS: Patients with mNPC from three institutions were included in this study. Propensity score matching (PSM) was employed to ensure comparability between patient groups. Overall survival (OS) rates were assessed using the Kaplan-Meier method and compared using the log-rank test. Prognostic factors were identified using univariate and multivariate Cox hazard analyses. Subgroup analyses were conducted to assess the effects of MLRT on specific patient populations. RESULTS: We analyzed data from 1157 patients with mNPC. Patients who received MLRT had significantly better OS than those who did not, both in the original (28 vs. 21 months) and PSM cohorts (26 vs. 23 months). MLRT was identified as an independent favorable predictor of OS in multivariate analyses, with hazard ratios of 0.67. The subgroup analysis results indicated that radiotherapy effectively treated liver, lung, and bone metastatic lesions, particularly in patients with a limited tumor burden. Higher total radiation doses of MLRT (biologically effective dose (BED) ≥ 56 Gy) were associated with improved OS, while neither radiation technique nor dose fractionation independently influenced prognosis. CONCLUSIONS: MLRT offers survival advantages to patients diagnosed with mNPC. Patients with limited metastatic burden derive the most benefit from MLRT, and the recommended regimen for MLRT is a minimum BED of 56 Gy for optimal outcomes.

A novel nomogram for the preoperative prediction of sentinel lymph node metastasis in breast cancer.

BACKGROUND OR PURPOSE: A practical noninvasive method to identify sentinel lymph node (SLN) status in breast cancer patients, who had a suspicious axillary lymph node (ALN) at ultrasound (US), but a negative clinical physical examination is needed. To predict SLN metastasis using a nomogram based on US and biopsy-based pathological features, this retrospective study investigated associations between clinicopathological features and SLN status. METHODS: Patients treated with SLN dissection at four centers were apportioned to training, internal, or external validation sets (n = 472, 175, and 81). Lymph node ultrasound and pathological characteristics were compared using chi-squared and t-tests. A nomogram predicting SLN metastasis was constructed using multivariate logistic regression models. RESULTS: In the training set, statistically significant factors associated with SLN+ were as follows: histology type (p < 0.001); progesterone receptor (PR: p = 0.003); Her-2 status (p = 0.049); and ALN-US shape (p = 0.034), corticomedullary demarcation (CMD: p < 0.001), and blood flow (p = 0.001). With multivariate analysis, five independent variables (histological type, PR status, ALN-US shape, CMD, and blood flow) were integrated into the nomogram (C-statistic 0.714 [95% CI: 0.688-0.740]) and validated internally (0.816 [95% CI: 0.784-0.849]) and externally (0.942 [95% CI: 0.918-0.966]), with good predictive accuracy and clinical applicability. CONCLUSION: This nomogram could be a direct and reliable tool for individual preoperative evaluation of SLN status, and therefore aids decisions concerning ALN dissection and adjuvant treatment.

Development and Validation of a Nomogram for Predicting the 1-, 3-, and 5-year Survival in Patients with Acinar-predominant Lung Adenocarcinoma.

OBJECTIVE: This study aimed to develop a nomogram to predict the overall survival (OS) of patients with acinar-predominant adenocarcinoma (APA). METHODS: Data from patients with APA obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2008 and 2016 were used. Significant prognostic factors were incorporated to construct a nomogram for predicting the 1-, 3-, and 5-year OS in these patients. The discrimination and calibration abilities of the nomogram were assessed using a C-index and calibration curves, respectively. RESULTS: A total of 2242 patients with APA were randomly divided into a training cohort (n=1576) and validation cohort (n=666). The independent prognostic factors for OS incorporated into the nomogram included marital status, age, gender, differentiation grade, T stage, N stage, and M stage. The nomogram showed good prediction capability, as indicated by the C-index [0.713, 95% confidence interval (CI): 0.705-0.721 in the training cohort, and 0.662, 95% CI: 0.649-0.775 in the validation cohort]. The calibration curves demonstrated that the 1-, 3-, and 5-year OS probabilities were consistent between the observed and predicted outcome frequencies. Patients were divided into the high-risk and low-risk groups with the former showing significantly worse survival than the latter (P<0.001). CONCLUSION: Using the SEER database, a nomogram was established to predict the 1-, 3-, and 5-year OS of patients with APA and was superior to the tumor size, lymph node, and metastasis staging system in terms of evaluating long-term prognosis.