Prognostic nomogram to predict cancer-specific survival with small-cell carcinoma of the prostate: a multi-institutional study.

Objective: The aim of this study is to examine the predictive factors for cancer-specific survival (CSS) in patients diagnosed with Small-Cell Carcinoma of the Prostate (SCCP) and to construct a prognostic model. Methods: Cases were selected using the Surveillance, Epidemiology, and End Results (SEER) database. The Kaplan-Meier method was utilized to calculate survival rates, while Lasso and Cox regression were employed to analyze prognostic factors. An independent prognostic factor-based nomogram was created to forecast CSS at 12 and 24 months. The model's predictive efficacy was assessed using the consistency index (C-index), calibration curve, and decision curve analysis (DCA) in separate tests. Results: Following the analysis of Cox and Lasso regression, age, race, Summary stage, and chemotherapy were determined to be significant risk factors (P < 0.05). In the group of participants who received training, the rate of 12-month CSS was 44.6%, the rate of 24-month CSS was 25.5%, and the median time for CSS was 10.5 months. The C-index for the training cohort was 0.7688 ± 0.024. As for the validation cohort, it was 0.661 ± 0.041. According to the nomogram, CSS was accurately predicted and demonstrated consistent and satisfactory predictive performance at both 12 months (87.3% compared to 71.2%) and 24 months (80.4% compared to 71.7%). As shown in the external validation calibration plot, the AUC for 12- and 24-month is 64.6% vs. 56.9% and 87.0% vs. 70.7%, respectively. Based on the calibration plot of the CSS nomogram at both the 12-month and 24-month marks, it can be observed that both the actual values and the nomogram predictions indicate a predominantly stable CSS. When compared to the AJCC staging system, DCA demonstrated a higher level of accuracy in predicting CSS through the use of a nomogram. Conclusion: Clinical prognostic factors can be utilized with nomograms to forecast CSS in Small-Cell Carcinoma of the Prostate (SCCP).

Survival benefit of local consolidative therapy for patients with single-organ metastatic pancreatic cancer: a propensity score-matched cross-sectional study based on 17 registries.

Background: The continuous exploration of oligometastatic disease has led to the remarkable achievements of local consolidative therapy (LCT) and favorable outcomes for this disease. Thus, this study investigated the potential benefits of LCT in patients with single-organ metastatic pancreatic ductal adenocarcinoma (PDAC). Methods: Patients with single-organ metastatic PDAC diagnosed between 2010 - 2019 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (PSM) was performed to minimize selection bias. Factors affecting survival were assessed by Cox regression analysis and Kaplan-Meier estimates. Results: A total of 12900 patients were identified from the database, including 635 patients who received chemotherapy combined with LCT with a 1:1 PSM with patients who received only chemotherapy. Patients with single-organ metastatic PDAC who received chemotherapy in combination with LCT demonstrated extended median overall survival (OS) by approximately 57%, more than those who underwent chemotherapy alone (11 vs. 7 months, p < 0.001). Furthermore, the multivariate Cox regression analysis revealed that patients that received LCT, younger age (< 65 years), smaller tumor size (< 50 mm), and lung metastasis (reference: liver) were favorable prognostic factors for patients with single-organ metastatic PDAC. Conclusion: The OS of patients with single-organ metastatic pancreatic cancer who received LCT may be prolonged compared to those who received only chemotherapy. Nevertheless, additional prospective randomized clinical trials are required to support these findings.

Development and Validation of a Predictive Model to Evaluate the Risk of Dysphagia Following Anterior Cervical Discectomy and Fusion.

STUDY DESIGN: A retrospective study. OBJECTIVE: To investigate the potential risk factors of dysphagia after anterior cervical discectomy and fusion (ACDF) and to establish and validate a prediction model. METHODS: The clinical data of 252 patients who underwent anterior cervical discectomy and fusion in our hospital from January 2018 to October 2020 were retrospectively analyzed and divided into the dysphagia group and the non-dysphagia group according to whether dysphagia occurred after surgery. Age, gender, body mass index, smoking and drinking history, hypertension history, diabetes history, disease duration, placement of Hemovac negative pressure drain, number of segments involved in surgery, whether C4-5/C5-6 segment surgery, incision length, incision position, level of preoperative EAT-10 score, whether preoperative tracheal exercise, and changes in cervical curvature before and after surgery were recorded in both groups. Risk factors for postoperative dysphagia were identified and nomogram prediction models were developed. RESULTS: A total of 252 patients were included in the study, 115 of whom presented with dysphagia within 1 week after anterior cervical fusion. The results of multivariate logistic regression analysis indicated that male gender (OR = .045, 95% CI .223-.889) and whether preoperative tracheal exercise (OR = .260, 95% CI .107-.633) were independent risk factors associated with reduced incidence of postoperative dysphagia. CONCLUSION: The incidence of dysphagia symptoms after anterior cervical decompression and fusion gradually decreased with the extension of follow-up time, and preoperative tracheal exercise and shortening the operation time may help to reduce the occurrence of postoperative dysphagia.

Development and validation of a nomogram to predict cancer-specific survival with unresected cholangiocarcinoma undergoing external radiotherapy.

Objective: To analyze the prognostic factors of patients with cholangiocarcinoma (CCA) who were unresected and received radiotherapy to establish a nomogram model for the prediction of patient cancer-specific survival (CSS). Methods: Suitable patient cases were selected from the Surveillance, Epidemiology, and End Results (SEER) database, survival rates were calculated using the Kaplan-Meier method, prognostic factors were analyzed by Lasso, Cox regression, and nomogram was developed based on independent prognostic factors to predict 6 and 12 months CSS. The consistency index (C-index), calibration curve, and decision curve analysis (DCA) were tested for the predictive efficacy of the model, respectively. Results: The primary site, tumor size, T-stage, M-stage, and chemotherapy (P < 0.05) were identified as independent risk factors after Cox and Lasso regression analysis. Patients in training cohort had a 6 months CSS rates was 68.6 ± 2.6%, a 12-month CSS rates was 49.0 ± 2.8%. The median CSS time of 12.00 months (95% CI: 10.17-13.83 months). The C-index was 0.664 ± 0.039 for the training cohort and 0.645 ± 0.042 for the validation cohort. The nomogram predicted CSS and demonstrated satisfactory and consistent predictive performance in 6 (73.4 vs. 64.9%) and 12 months (72.2 vs. 64.9%), respectively. The external validation calibration plot is shown AUC for 6- and 12-month compared with AJCC stage was (71.2 vs. 63.0%) and (65.9 vs. 59.8%). Meanwhile, the calibration plot of the nomogram for the probability of CSS at 6 and 12 months indicates that the actual and nomogram predict that the CSS remains largely consistent. DCA showed that using a nomogram to predict CSS results in better clinical decisions compared to the AJCC staging system. Conclusion: A nomogram model based on clinical prognostic characteristics can be used to provide CSS prediction reference for patients with CCA who have not undergone surgery but have received radiotherapy.

Development and validation of a nomogram to predict the risk of peripheral artery disease in patients with type 2 diabetes mellitus.

Objective: To develop and validate a nomogram for predicting the risk of peripheral artery disease (PAD) in patients with type 2 diabetes mellitus (T2DM) and assess its clinical application value. Methods: Clinical data were retrospectively collected from 474 patients with T2DM at the Air Force Medical Center between January 2019 and April 2022. The patients were divided into training and validation sets using the random number table method in a ratio of 7:3. Multivariate logistic regression analysis was performed to identify the independent risk factors for PAD in patients with T2DM. A nomogram prediction model was developed based on the independent risk factors. The predictive efficacy of the prediction model was evaluated using the consistency index (C-index), area under the curve (AUC), receiver operating characteristic (ROC) curve, Hosmer-Lemeshow (HL) test, and calibration curve analysis. Additionally, decision curve analysis (DCA) was performed to evaluate the prediction model's performance during clinical application. Results: Age, disease duration, blood urea nitrogen (BUN), and hemoglobin (P<0.05) were observed as independent risk factors for PAD in patients with T2DM. The C-index and the AUC were 0.765 (95% CI: 0.711-0.819) and 0.716 (95% CI: 0.619-0.813) for the training and validation sets, respectively, indicating that the model had good discriminatory power. The calibration curves showed good agreement between the predicted and actual probabilities for both the training and validation sets. In addition, the P-values of the HL test for the training and validation sets were 0.205 and 0.414, respectively, indicating that the model was well-calibrated. Finally, the DCA curve indicated that the model had good clinical utility. Conclusion: A simple nomogram based on three independent factors-duration of diabetes, BUN, and hemoglobin levels-may help clinicians predict the risk of developing PAD in patients with T2DM.

Associations between external beam radiotherapy and overall survival in patients with gallbladder cancer: A population-based study.

Background: There is a lack of studies regarding radiotherapy (RT) in patients with gallbladder cancer (GBC) on the survival benefit after surgery and nonsurgical treatment. Therefore, this study evaluated the impact of external beam RT on the overall survival (OS) of patients with GBC in a real-world setting. Methods: Patients with GBC enrolled from the Surveillance, Epidemiology, and End Results (SEER) database were examined through Kaplan-Meier survival curves and multivariable Cox regression analyses. Results: A total of 7,866 patients with GBC were screened for the current analysis, of whom 2,130 (27.1%) did not undergo RT or surgery, 209 (2.7%) underwent RT, 4,511 (57.3%) underwent surgery, and 1,016 (12.9%) underwent both RT and surgery. The median OS times were 4 months, 8 months, 16 months, and 22 months (p < 0.0001). OS was significantly different between adjuvant RT (p = 0.0002) and palliative RT (p < 0.0001). Multifactorial analysis (controlling for age, sex, year of diagnosis, marital status, race, grade, and stage) showed that both adjuvant RT (surgery and adjuvant RT vs. surgery alone; HR, 0.75; 95% CI, 0.69-0.82, p < 0.001) and palliative RT (RT alone vs. no treatment; HR, 0.80; 95% CI, 0.69-0.92, p = 0.003) had a significant impact on patient OS. The results remained stable following sensitivity analyses. Conclusion: The study results indicate that adjuvant and palliative radiation treatment was associated with a survival benefit. GBC patients can derive a survival benefit from external beam RT.