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Background: Radical esophagectomy, including thoracic duct resection (TDR), has been proposed to improve regional lymphadenectomy and possibly reduce the risk of locoregional recurrence. However, because of its impact on immunoregulation, some authors have expressed concerns about its possible detrimental effect on long-term survival. The purpose of this review was to assess the influence of TDR on long-term survival. Patients and Methods: PubMed, MEDLINE, Scopus, and Web of Science databases were searched through 15 March 2024. Overall survival (OS), cancer specific survival (CSS), and disease-free survival (DFS) were primary outcomes. Restricted mean survival time difference (RMSTD), risk ratio (RR), standardized mean difference (SMD), and 95% confidence intervals (CI) were used as pooled effect size measures. The Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) methodology was employed to evaluate the certainty of evidence. Results: The analysis included six studies with 5756 patients undergoing transthoracic esophagectomy. TDR was reported in 49.1%. Patients' ages ranged from 27 to 79 years and 86% were males. At 4-year follow-up, the multivariate meta-analysis showed similar results for the comparison noTDR versus TDR in term of OS [− 0.8 months, 95% confidence interval (CI) − 3.1, 1.3], CSS (0.1 months, 95% CI − 0.9, 1.2), and DFS (1.5 months, 95% CI − 2.6, 5.5). TDR was associated with a significantly higher number of harvested mediastinal lymph nodes (SMD 0.57, 95% CI 0.01–1.13) and higher risk of postoperative chylothorax (RR = 1.32; 95% CI 1.04–2.23). Anastomotic leak and pulmonary complications were comparable. Conclusions: TDR seems not to improve long-term OS, CSS, and DFS regardless of tumor stage. Routine TDR should not be routinely recommended during esophagectomy. [ABSTRACT FROM AUTHOR]

Objective: Accurate prognosis prediction is critical for individualized-therapy making of gastric cancer patients. We aimed to develop and test 6-month, 1-, 2-, 3-, 5-, and 10-year overall survival (OS) and cancer-specific survival (CSS) prediction models for gastric cancer patients following gastrectomy. Methods: We derived and tested Survival Quilts, a machine learning-based model, to develop 6-month, 1-, 2-, 3-, 5-, and 10-year OS and CSS prediction models. Gastrectomy patients in the development set (n = 20,583) and the internal validation set (n = 5,106) were recruited from the Surveillance, Epidemiology, and End Results (SEER) database, while those in the external validation set (n = 6,352) were recruited from the China National Cancer Center Gastric Cancer (NCCGC) database. Furthermore, we selected gastrectomy patients without neoadjuvant therapy as a subgroup to train and test the prognostic models in order to keep the accuracy of tumor-node-metastasis (TNM) stage. Prognostic performances of these OS and CSS models were assessed using the Concordance Index (C-index) and area under the curve (AUC) values. Results: The machine learning model had a consistently high accuracy in predicting 6-month, 1-, 2-, 3-, 5-, and 10-year OS in the SEER development set (C-index = 0.861, 0.832, 0.789, 0.766, 0.740, and 0.709; AUC = 0.784, 0.828, 0.840, 0.849, 0.869, and 0.902, respectively), SEER validation set (C-index = 0.782, 0.739, 0.712, 0.698, 0.681, and 0.660; AUC = 0.751, 0.772, 0.767, 0.762, 0.766, and 0.787, respectively), and NCCGC set (C-index = 0.691, 0.756, 0.751, 0.737, 0.722, and 0.701; AUC = 0.769, 0.788, 0.790, 0.790, 0.787, and 0.788, respectively). The model was able to predict 6-month, 1-, 2-, 3-, 5-, and 10-year CSS in the SEER development set (C-index = 0.879, 0.858, 0.820, 0.802, 0.784, and 0.774; AUC = 0.756, 0.827, 0.852, 0.863, 0.874, and 0.884, respectively) and SEER validation set (C-index = 0.790, 0.763, 0.741, 0.729, 0.718, and 0.708; AUC = 0.706, 0.758, 0.767, 0.766, 0.766, and 0.764, respectively). In multivariate analysis, the high-risk group with risk score output by 5-year OS model was proved to be a strong survival predictor both in the SEER development set (hazard ratio [HR] = 14.59, 95% confidence interval [CI]: 1.872–2.774, P < 0.001), SEER validation set (HR = 2.28, 95% CI: 13.089–16.293, P < 0.001), and NCCGC set (HR = 1.98, 95% CI: 1.617–2.437, P < 0.001). We further explored the prognostic value of risk score resulted 5-year CSS model of gastrectomy patients, and found that high-risk group remained as an independent CSS factor in the SEER development set (HR = 12.81, 95% CI: 11.568–14.194, P < 0.001) and SEER validation set (HR = 1.61, 95% CI: 1.338–1.935, P < 0.001). Conclusion: Survival Quilts could allow accurate prediction of 6-month, 1-, 2-, 3-, 5-, and 10-year OS and CSS in gastric cancer patients following gastrectomy.

Simple Summary: Over the last decade, early-onset colorectal cancer incidence has continued to increase. The disparities in outcomes and overall survival (OS) between early-onset colorectal cancer and average-onset colorectal cancer remain controversial. The aim of our study was to compare survival rates and identify potential influential factors affecting outcomes between these two groups. Our results show better overall survival and cancer specific survival in patients with early-onset colorectal cancer which could be contributed to better general health, fewer comorbidities and higher likelihood of receiving aggressive cancer treatments. Background: Early-onset colorectal cancer (EO-CRC) is defined as colorectal cancer diagnosed before the age of 50 years, and its incidence has been increasing over the last decade, now accounting for 10% of all new CRC diagnoses. Average-onset colorectal cancer (AO-CRC) has shown a steady decline in its incidence and related mortality over the past 20 years. The disparities in outcomes and overall survival (OS) between EO-CRC and AO-CRC are controversial. Our study compared OS and cause-specific survival (CSS) between metastatic EO-CRC (mEO-CRC) and metastatic AO-CRC (mAO-CRC) and identified the associated factors. Methods: Data on patient characteristics, tumor characteristics, incidence, and mortality were obtained from the SEER database from 2010 to 2020. We identified 23,278 individuals aged > 18 years with a confirmed diagnosis of all histological subtypes of metastatic CRC (M1 on TNM stage) using ICD-O-3 site codes. mEO-CRC and mAO-CRC were compared. OS distributions and CCS were analyzed using the Kaplan–Meier method and log-rank test to assess differences. A Cox regression model was used to assess the associations between variables. Results: mEO-CRC constituted 17.79% of the cases, whereas 82.21% had mAO-CRC. Most patients with mEO-CRC were 45–49 years old (47.66%), male (52.16%) and White (72.57%) and had adenocarcinoma histology (87.30%). Left colon tumors were most prevalent in both groups (40.26%) but were more prevalent in mEO-CRC patients than in mAO-CRC patients (49.63% vs. 38.23%, p < 0.001). Patients with mEO-CRC had higher OS (p < 0.001) and CSS (p < 0.001) than those with mAO-CRC. Patients with mEO-CRC also had significantly better median overall survival (30 months vs. 18 months, p < 0.001). The factors associated with worse OS included mAO-CRC (p < 0.001), mucinous adenocarcinoma (p < 0.001), male sex (p = 0.003), and a lack of surgical intervention (p < 0.001). Conclusions: Most patients with mEO-CRC fall within the range of 45 to 49 years of age. Patients with mEO-CRC were more likely to receive cancer-directed therapy (including chemotherapy and radiotherapy) and had better OS and CSS than those with mAO-CRC. This is likely attributable to the better performance status, fewer comorbidities, and better tolerance to cancer-directed therapy in mEO-CRC patients. The factors associated with worse OS and CSS were age > 50 years, mucinous adenocarcinoma, male sex, and no surgical treatment. [ABSTRACT FROM AUTHOR]

Abstract Background The recurrence rate and mortality rate among postoperative pancreatic cancer patients remain elevated. This study aims to develop and validate the cancer-specific survival period for individuals who have undergone pancreatic cancer surgery. Methods We extracted eligible data from the Surveillance, Epidemiology, and End Results database and randomly divided all patients into a training cohort and an internal validation cohort. External validation was performed using a separate Chinese cohort. The nomogram was developed using significant risk factors identified through univariate and multivariate Cox proportional hazards regression. The effectiveness of the nomogram was assessed using the area under the time-dependent curve, calibration plots, and decision curve analysis. Kaplan–Meier survival curves were utilized to visualize the risk stratification of nomogram and AJCC stage. Results Seven variables were identified through univariate and multivariate analysis to construct the nomogram. The consistency index of the nomogram for predicting overall survival was 0.683 (95% CI: 0.675–0.690), 0.689 (95% CI: 0.677–0.701), and 0.823 (95% CI: 0.786–0.860). The AUC values for the 1- and 2-year time-ROC curves were 0.751 and 0.721 for the training cohort, 0.731 and 0.7554 for the internal validation cohort, and 0.901 and 0.830 for the external validation cohorts, respectively. Calibration plots demonstrated favorable consistency between the predictions of the nomogram and actual observations. Moreover, the decision curve analysis indicated the clinical utility of the nomogram, and the risk stratification of the nomogram effectively identified high-risk patients. Conclusion The nomogram guides clinicians in assessing the survival period of postoperative pancreatic cancer patients, identifying high-risk groups, and devising tailored follow-up strategies.

In the era of target therapy and personalized medicine, BRCA mutational status has a major influence on survival in ovarian cancer patients. Our aim is to verify if the poorer prognosis of elderly ovarian cancer patients can be related to the biology of the tumor beyond their own morbidities and/or suboptimal treatments. This is a retrospective single-institution study evaluating prognosis of patients with a diagnosis of ovarian cancer and known BRCA status. We collected clinical and surgical characteristics and the distribution of BRCA mutational status according to age groups. 1840 patients were included in the analysis. The rate of BRCA mutated decreased over age-range from 49.7% in patients aged <50 years to 18.8% in ≥80 years old women. The prognostic role of BRCA status on survival is maintained when focusing on the elderly population, with improved Disease Free Survival (27.2 months vs 16.5 months for BRCA mutated and wild type respectively, p = 0.001) and Cancer Specific Survival (117.6 months vs 43.1 months for BRCA mutated and wild type respectively, p = 0.001) for BRCAmut compared to BRCAwt patients. In the multivariable analysis, among elderly women, upfront surgery and BRCA mutation are independent factors affecting survival. Elderly patients experiment a poorer prognosis due to multiple factors that include both their medical condition and comorbidities, under-treatment and most importantly disease characteristics. We found that beyond disparities, BRCA mutation is still the strongest independent prognostic factor affecting both the risk of recurrence and death due to disease. • The rate of BRCA mutated tumors decreases with age. • Tumor biology in elderly patients could be a crucial determinant of treatment. • BRCA mutation remains the strongest independent factor for survival. • Tumor biology is responsible of the worst prognosis of elderly population [ABSTRACT FROM AUTHOR]

Simple Summary: Debate exists regarding the effect of D2 vs. D1 lymphadenectomy on long-term oncological outcomes after gastrectomy for cancer. The aim of our individual patient data meta-analysis was to assess the impact of D2 lymphadenectomy on long-term survival after gastrectomy for gastric cancer. Compared with previous randomized trials, we confirmed a trend toward improved overall survival (1.8 months; 95% CI −4.2, 0.7; p = 0.14), cancer specific survival (1.2 months, 95% CI −3.9, 5.7; p = 0.72), and disease-free survival (0.8 months, 95% CI −1.7, 3.4; p = 0.53) at 60-month follow-up for D2 lymphadenectomy. Compared to D1, D2 lymphadenectomy is associated with a clinical trend toward improved OS, CSS, and DFS at 60-month follow-up. Background: Debate exists concerning the impact of D2 vs. D1 lymphadenectomy on long-term oncological outcomes after gastrectomy for cancer. Methods: PubMed, MEDLINE, Scopus, and Web of Science were searched and randomized controlled trials (RCTs) analyzing the effect of D2 vs. D1 on survival were included. Overall survival (OS), cancer-specific survival (CSS), and disease-free survival (DFS) were assessed. Restricted mean survival time difference (RMSTD) and 95% confidence intervals (CI) were used as effect size measures. Results: Five RCTs (1653 patients) were included. Overall, 805 (48.7%) underwent D2 lymphadenectomy. The RMSTD OS analysis shows that at 60-month follow-up, D2 patients lived 1.8 months (95% CI −4.2, 0.7; p = 0.14) longer on average compared to D1 patients. Similarly, 60-month CSS (1.2 months, 95% CI −3.9, 5.7; p = 0.72) and DFS (0.8 months, 95% CI −1.7, 3.4; p = 0.53) tended to be improved for D2 vs. D1 lymphadenectomy. Conclusions: Compared to D1, D2 lymphadenectomy is associated with a clinical trend toward improved OS, CSS, and DFS at 60-month follow-up. [ABSTRACT FROM AUTHOR]

Purpose: Penile cancer (PC) is a great impact on the quality of life and psychological status of patients. This study aimed to construct nomograms using data from the Surveillance, Epidemiology, and End Results (SEER) database to predict overall survival (OS) and cancer-specific survival (CSS) in patients with penile cancer (PC). Methods: Patients were divided into a training cohort (n = 634) and a validation cohort (n = 272) in a 7:3 ratio. Independent risk factors influencing the prognosis of PC were screened using univariate and multivariate Cox analyses, and models for predicting PC were developed. Data from 203 patients with PC in four tertiary hospitals in Gansu Province from 2012 to 2021 were externally validated. Results: Univariate analysis and multivariate analysis showed revealed that the OS-related factors were age, grade, T stage, N stage, M stage and tumor size (p < 0.05); the CSS-related factors were age, mode of surgery, T stage, N stage, M stage and tumor size (p < 0.05). The C-indices of the OS and CSS nomograms in the training cohort were 0.743 [95% confidence interval (CI) (0.714–0.772)] and 0.797 (0.762–0.832), respectively. The C-indices of the OS and CSS nomograms in the internal validation cohort were 0.735 (0.686–0.784) and 0.755 (0.688–0.822), respectively, and those in the external validation cohort were 0.801 (0.746–0.856) and 0.863 (0.812–0.914), respectively. Receiver operating characteristic (ROC) curves, calibration curves, and survival curves all demonstrated good predictive performance of the nomograms. Conclusion: The nomograms for PC were developed using the SEER database. The accuracy and clinical usefulness of the model were validated through a combination of internal and external validations. [ABSTRACT FROM AUTHOR]

Background and aims: Second primary prostate cancer (SPPCa) is a common type of secondary malignancy that negatively impacts patient prognosis. This study aimed to identify prognostic factors for SPPCa patients and develop nomograms to assess their prognosis. Methods: Patients diagnosed with SPPCa between 2010 and 2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. The study cohort was randomly divided into a training set and a validation set. Cox regression analysis, Kaplan‒Meier survival analysis, and least absolute shrinkage and selection operator regression analysis were used to identify independent prognostic factors and develop the nomogram. The nomograms were evaluated using the concordance index (C-index), calibration curve, area under the curve (AUC), and Kaplan–Meier analysis. Results: A total of 5342 SPPCa patients were included in the study. Independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS) were identified as age, interval between diagnoses, first primary tumor site, and AJCC stage, N stage, M stage, PSA, Gleason score, and SPPCa surgery. Nomograms were constructed based on these prognostic factors, and the performance was evaluated using the C-index (OS: 0.733, CSS: 0.838), AUC, calibration curve, and Kaplan–Meier analysis, which demonstrated excellent predictive accuracy. Conclusion: We successfully established and validated nomograms to predict OS and CSS in SPPCa patients using the SEER database. These nomograms provide an effective tool for risk stratification and prognosis assessment in SPPCa patients, which will aid clinicians in optimizing treatment strategies for this patient population. [ABSTRACT FROM AUTHOR]

Objective: To elucidate the clinicopathological characteristics and prognostic factors of poorly differentiated thyroid carcinoma. Method: A total of 24912 thyroid carcinoma patients admitted to the First Medical Center of Chinese People's Liberation Army General Hospital from 2005 to 2020 were retrospectively reviewed. A total of 94 patients (39 males and 55 females, a male-female ratio of 1:1.4) fulfilled the selection criteria. Of these, 73 patients had undergone surgery. The clinical and pathological data were collected from each enrolled patient. Univariate and multivariate Cox regression analyses were performed to determine independent prognostic factors. All analyses were performed with the SPSS version 26.0 and R version 1.2.5033 in the R Studio environment. Results: The specimens included 20 cases of poorly differentiated thyroid carcinoma complicated with papillary thyroid carcinoma, 17 cases complicated with follicular thyroid carcinoma, 34 cases complicated with other pathological types and 23 with a separate entity. The patient demonstrated a large age span, median age was 57 years (range 8-85 years, average 55.20 ± 15.74 years). The survival time of the 94 cases was calculated, and the mean Overall survival time was 33 (range, 1-170) months, and the mean Recurrence-free survival time was 14 (range, 1-90) months. Recurrence-free mortality is related to the age at diagnosis, extrathyroidal extension and Associated thyroid cancer (p<0.05). In contrast, overall mortality is related to the age at diagnosis, sex, extrathyroidal extension, T stage (AJCC 8th), surgery and radiation (p<0.05). Conclusion: Middle-aged and elderly patients are still at high risk for poorly differentiated thyroid carcinoma. The pathologic results of poorly differentiated thyroid carcinoma are varied, and reasonable treatment has an important impact on the prognosis of poorly differentiated thyroid carcinoma. [ABSTRACT FROM AUTHOR]

Neutrophil–lymphocyte ratio (NLR), as an indicator of heightened systemic inflammatory response, predicts increased disease burden and poor oncological outcomes in urothelial carcinoma (UC). The study was undertaken with an aim to evaluate the association of NLR with clinicopathological variables and survival outcomes. A total of 80 patients of UC were enrolled in the current retrospective study. Pre-operative NLR (within one month prior to the procedure), patient age, sex, tumour grade, pathological stage, recurrence free survival (RFS), progression free survival (PFS) and cancer specific survival (CSS) were recorded. We chose a cut-off value of 2.7 for NLR and patients were divide into two groups (NLR <2.7 and ≥2.7). NLR ≥2.7 was significantly associated with advanced tumour stage (p=0.001), but not with tumour grade (p=0.116). Progression (p=0.032) and death rates (p=0.026) were high in patients with NLR ≥2.7. Mean RFS (p=0.03), PFS (p=0.04) and CSS (p=0.04) were reduced in patients with NLR ≥2.7. On univariate analysis, NLR ≥2.7 predicted worse RFS (HR=2.928, p=0.007), PFS (HR=3.180, p=0.006) and CSS (HR=3.109, p=0.016). However, it was not an independent predictor of outcomes on multivariate analysis. Tumour stage and grade are the only independent predictors of RFS, PFS and CSS. High NLR at a cut-off value of ≥2.7 is associated with advanced pathological stage, but does not have an independent predictive value for RFS, PFS and CSS. [ABSTRACT FROM AUTHOR]

Purpose: One of the best ways to control non-Hodgkin lymphoma (NHL) locally is radiation therapy (RT), which is a crucial component of care for many patients. There has not been any research on the risk and prognosis of secondary breast cancer (SBC) in females with NHL receiving RT. Methods: In our study, females with NHL as their initial cancer diagnosis were included from 1975 to 2018 in the Surveillance, Epidemiology and End Results (SEER) database. Using Fine and Gray's competing risk regression assess the cumulative incidence of SBC. The standardized incidence ratios (SIR) and radiation-attributed risk (RR) for SBC were assessed using Poisson regression analysis. We evaluated the overall survival (OS) of SBC patients using the Kaplan–Meier technique. Results: Of the 41,983 females with NHL, 10,070 received RT and 320 (3.18%) developed SBC. 31,913 females did not receive RT and 805 (2.52%) developed SBC. RT was significantly related with a greater chance of acquiring SBC in the Fine-Gray competing risk regression (adjusted hazard ratios (HR) = 1.14; 95% confidence intervals (CI), 1.09–1.30; P = 0.011). When an NHL diagnosis was made at an older age, the dynamic SIR and RR for SBC also declined over time. Regarding general survivability, there was not statistically significant (P = 0.970) after propensity score matching (PSM). Conclusions: RT is an independent risk factor for SBC in females with NHL. Special attention should be paid to the monitoring of breast cancer indicators in them, especially young. [ABSTRACT FROM AUTHOR]

Abstract Introduction Pre-treatment risk and prognostic groups are the cornerstone for deciding management in non-metastatic prostate cancer. All however, were developed in the pre-MRI era. Here we compared categorisation of cancers using either only clinical parameters or with MRI enhanced information in men referred for suspected prostate cancer from an unscreened population. Patient and methods Data from men referred from primary care to our diagnostic service and with both clinical (digital rectal examination [DRE] and systematic biopsies) and MRI enhanced attributes (MRI stage and combined systematic/targeted biopsies) were used for this study. Clinical vs MRI data were contrasted for clinico-pathological and risk group re-distribution using the European Association of Urology (EAU), American Urological Association (AUA) and UK National Institute for Health Care Excellence (NICE) Cambridge Prognostic Group (CPG) models. Differences were retrofitted to a population cohort with long-term prostate cancer mortality (PCM) outcomes to simulate impact on model performance. We further contrasted individualised overall survival (OS) predictions using the Predict Prostate algorithm. Results Data from 370 men were included (median age 66y). Pre-biopsy MRI stage reassignments occurred in 7.8% (versus DRE). Image-guided biopsies increased Grade Group 2 and ≥ Grade Group 3 assignments in 2.7% and 2.9% respectively. The main change in risk groups was more high-risk cancers (6.2% increase in the EAU and AUA system, 4.3% increase in CPG4 and 1.9% CPG5). When extrapolated to a historical population-based cohort (n = 10,139) the redistribution resulted in generally lower concordance indices for PCM. The 5-tier NICE-CPG system outperformed the 4-tier AUA and 3-tier EAU models (C Index 0.70 versus 0.65 and 0.64). Using an individualised prognostic model, changes in predicted OS were small (median difference 1% and 2% at 10- and 15-years’ respectively). Similarly, estimated treatment survival benefit changes were minimal (1% at both 10- and 15-years’ time frame). Conclusion MRI guided diagnostics does change pre-treatment risk groups assignments but the overall prognostic impact appears modest in men referred from unscreened populations. Particularly, when using more granular tiers or individualised prognostic models. Existing risk and prognostic models can continue to be used to counsel men about treatment option until long term survival outcomes are available.

Background: Some women die despite the favorable prognosis of small breast cancers. Breast ultrasound features may reflect pathological and biological characteristics of a breast tumor. This study aimed to explore whether ultrasound features could identify small breast cancers with poor outcomes. Methods: This retrospective study examined confirmed breast cancers with a size of <20 mm diagnosed in our hospital between 02/2008 and 08/2019. Clinicopathological and ultrasound features were compared between alive and deceased breast cancer patients. Survival was analyzed using the Kaplan-Meier curves. Multivariable Cox proportional hazards models were used to examine the factors associated with breast cancer-specific survival (BCSS) and disease-free survival (DFS). Results: Among the 790 patients, the median follow-up was 3.5 years. The deceased group showed higher frequencies of spiculated (36.7% vs. 11.2%, P<0.001), anti-parallel orientation (43.3% vs. 15.4%, P<0.001), and spiculated morphology combined with anti-parallel orientation (30.0% vs. 2.4%, P<0.001). Among 27 patients with spiculated morphology and anti-parallel orientation, nine cancer-specific deaths and 11 recurrences occurred, for a 5-year BCSS of 77.8% and DFS of 66.7%, while 21 breast-cancer deaths and 41 recurrences occurred among the remaining patients with higher 5-year BCSS (97.8%, P<0.001) and DFS (95.4%, P<0.001). Spiculated and anti-parallel orientation (HR=7.45, 95%CI: 3.26-17.00; HR=6.42, 95%CI: 3.19-12.93), age =55 years (HR=5.94, 95%CI: 2.24-15.72; HR=1.98, 95%CI: 1.11-3.54), and lymph nodes metastasis (HR=3.99, 95%CI: 1.89-8.43; HR=2.99, 95%CI: 1.71-5.23) were independently associated with poor BCSS and DFS. Conclusions: Spiculated and anti-parallel orientation at ultrasound are associated with poor BCSS and DFS in patients with primary breast cancer <20 mm. [ABSTRACT FROM AUTHOR]

Chronic obstructive pulmonary disease (COPD) serves as risk factor for the development of lung cancer and seems to have a prognostic impact after surgery for non-small cell lung cancer (NSCLC). The aim was to investigate the impact of COPD and postoperative mucostasis on the long-term survival after resected NSCLC. We retrospectively reviewed the data from 342 patients with curatively resected NSCLC. The prognostic long-term impact of COPD and postoperative mucostasis on overall survival (OS), recurrence free survival (RFS) and cancer specific survival (CSS) was calculated using univariable and multivariable Cox regression analyses. We found that 52.3% suffered from COPD and 25.4% had postoperative mucostasis. COPD was significantly more common among smokers (59.9%) compared with non-smokers (21.3%), (p < 0.001). There was a significant relationship between COPD and postoperative mucostasis (p = 0.006) and between smoking and mucostasis (p = 0.023). Patients with postoperative mucostasis had a significantly worse OS (p < 0.001), RFS (p = 0.009) and CSS (p = 0.008). The present analysis demonstrated that postoperative mucostasis, but not COPD, was associated with both worse short- and long-term outcomes for OS, RFS and CSS in curatively resected NSCLC. [ABSTRACT FROM AUTHOR]

Abstract Purpose The current study aimed to construct a novel cancer artificial intelligence survival analysis system for predicting the individual mortality risk curves for cervical carcinoma patients receiving different treatments. Methods Study dataset (n = 14,946) was downloaded from Surveillance Epidemiology and End Results database. Accelerated failure time algorithm, multi-task logistic regression algorithm, and Cox proportional hazard regression algorithm were used to develop prognostic models for cancer specific survival of cervical carcinoma patients. Results Multivariate Cox regression identified stage, PM, chemotherapy, Age, PT, and radiation_surgery as independent influence factors for cervical carcinoma patients. The concordance indexes of Cox model were 0.860, 0.849, and 0.848 for 12-month, 36-month, and 60-month in model dataset, whereas it were 0.881, 0.845, and 0.841 in validation dataset. The concordance indexes of accelerated failure time model were 0.861, 0.852, and 0.851 for 12-month, 36-month, and 60-month in model dataset, whereas it were 0.882, 0.847, and 0.846 in validation dataset. The concordance indexes of multi-task logistic regression model were 0.860, 0.863, and 0.861 for 12-month, 36-month, and 60-month in model dataset, whereas it were 0.880, 0.860, and 0.861 in validation dataset. Brier score indicated that these three prognostic models have good diagnostic accuracy for cervical carcinoma patients. The current research lacked independent external validation study. Conclusion The current study developed a novel cancer artificial intelligence survival analysis system to provide individual mortality risk predictive curves for cervical carcinoma patients based on three different artificial intelligence algorithms. Cancer artificial intelligence survival analysis system could provide mortality percentage at specific time points and explore the actual treatment benefits under different treatments in four stages, which could help patient determine the best individualized treatment. Cancer artificial intelligence survival analysis system was available at: https://zhangzhiqiao15.shinyapps.io/Tumor_Artificial_Intelligence_Survival_Analysis_System/ .

Abstract Background Hepato-pulmonary metastasis of colorectal cancer (CRC) is a rare disease with poor prognosis. This study aims to establish a highly efficient nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with colorectal cancer hepato-pulmonary metastasis (CRCHPM). Methods We retrospectively analyzed the data of patients with CRCHPM from SEER database and Wuhan Union Hospital Cancer Center (WUHCC). A total of 1250 CRCHPM patients were randomly assigned to the training, internal validation, and external validation cohorts from 2010 to 2016.Univariate and multivariate cox analysis were performed to identify independent clinicopathological predictors of OS and CSS, and a nomogram was constructed to predict OS and CSS in CRCHPM patients. Results A nomogram of OS was constructed based on seven independent predictors of age, degree of differentiation, T stage, chemotherapy, number of lsampled lymph nodes, number of positive lymph nodes, and tumor size. Nomogram showed favorable sensitivity in predicting OS at 1, 3 and 5 years, with area under the receiver operating characteristic curve (AUROC) values of 0.802, 0.759 and 0.752 in the training cohort;0.814, 0.769 and 0.716 in the internal validation cohort;0.778, 0.756 and 0.753 in the external validation cohort, respectively. A nomogram of CSS was constructed based on three independent predictors of T stage, chemotherapy, and tumor size. The AUROC values of 1, 3 and 5 years were 0.709,0.588,0.686 in the training cohort; 0.751, 0.648,0.666 in the internal validation cohort;0.781,0.588,0.645 in the external validation cohort, respectively. Calibration curves, Concordance index (C-index), and decision curve analysis (DCA) results revealed that using our model to predict OS and CSS is more efficient than other single clinicopathological characteristics. Conclusion A nomogram of OS and CSS based on clinicopathological characteristics can be conveniently used to predict the prognosis of CRCHPM patients.

Abstract Background At present, there are few studies on renal pelvic transitional cell carcinoma (RPTCC) in elderly patients in the literature. The study aims to establish a new nomogram of cancer-specific survival (CSS) in elderly patients with T1-T3N0M0 RPTCC and validate its reliability. Methods This study downloaded the data of 1375 elderly patients with T1-T3N0M0 RPTCC in the Surveillance, Epidemiology, and Final Results (SEER) database from 2004 to 2018. Patients were randomly divided into training cohort (n = 977) and validation cohort (n = 398). Proportional subdistribution hazard analyse was applied to determine independent prognostic factors. Based on these factors, we constructed a compting risk model nomogram. We use the calibration plots, the area under the receiver operating characteristics curve (AUC), concordance index (C-index), and decision curve analysis (DCA) to validate predictive performance and clinical applicability. Patients were divided into low-risk group and high-risk group based on nomogram risk score. Kaplan–Meier curve was applied to analyze the difference in survival curve between the two groups of patients. Results We found that the risk factors affecting CSS in elderly patients with T1-T3N0M0 RPTCC are surgery, AJCC stage, laterality, tumor size, histological grade, and tumour laterality. Based on these factors, we established a nomogram to predict the CSS of RPTCC patients at 1-, 3-, and 5-year. The calibration plots showed that the predicted value was highly consistent with the observed value. In the training cohort and validation cohort, the C-index of the nomogram were 0.671(95% CI 0.622–0.72) and 0.679(95% CI 0.608–0.750), respectively, the AUC showed similar results. The DCA suggests that namogram performs better than the AJCC stage system. The Kaplan–Meier curve showed that CSS of patients was significantly higher in the low-risk group. Conclusions In this study, the SEER database was used for the first time to create and validate a new nomogram prediction model for elderly patients with T1-T3N0M0 RPTCC. Compared with the traditional AJCC stage system, our new nomogram can more accurately predict the CSS of elderly patients with T1-T3N0M0 RPTCC, which is helpful for patient prognosis assessment and treatment strategies selection.

Simple Summary: Early-onset colorectal cancer (EOCRC) is on the rise. Reasons are unknown and comparative results about long-term survival are still widely debated. This study aimed to explore the effect of early age of onset in a surgical population of sporadic colorectal cancer patients. Early age of onset resulted independently and is associated with worse oncologic outcomes also in stage I patients. This study suggested that EOCRC may have a more aggressive tumoral phenotype compared with late-onset CRC. A better understanding of the biology of EOCRC is needed to revise —and eventually modify—current strategies of treatment and surveillance. The incidence of colorectal cancer (CRC) is increasing in the population aged ≤ 49 (early-onset CRC-EOCRC). Recent studies highlighted the biological and clinical differences between EOCRC and late-onset CRC (LOCRC-age ≥ 50), while comparative results about long-term survival are still debated. This study aimed to investigate whether age of onset may impact on oncologic outcomes in a surgical population of sporadic CRC patients. Patients operated on for sporadic CRC from January 2010 to January 2022 were allocated to the EOCRC and LOCRC groups. The primary endpoint was the recurrence/progression-free survival (R/PFS). A total of 423 EOCRC and 1650 LOCRC was included. EOCRC had a worse R/PFS (p < 0.0001) and cancer specific survival (p < 0.0001) compared with LOCRC. At Cox regression analysis, age of onset, tumoral stage, signet ring cells, extramural/lymphovascular/perineural veins invasion, and neoadjuvant therapy were independent risk factors for R/P. The analysis by tumoral stage showed an increased incidence of recurrence in stage I EOCRC (p = 0.014), and early age of onset was an independent predictor for recurrence (p = 0.035). Early age of onset was an independent predictor for worse prognosis, this effect was stronger in stage I patients suggesting a potentially—and still unknown—more aggressive tumoral phenotype in EOCRC. [ABSTRACT FROM AUTHOR]

Simple Summary: Penile Squamous Cell Carcinoma (PSCC) is a rare but aggressive cancer and approximately 30–50% of cases are associated with high risk human papillomavirus (HR-HPV). HR-HPV infection has been shown to correlate with expression of protein p16INK4a (p16). We wanted to determine if HPV-HR or p16 expression is associated with better outcomes in PSCC patients; therefore, we analyzed 143 patients with a diagnosis of PSCC and available tissue was analyzed for p16INK4a expression and HR-HPV status. Patients with p16+ tumors had a significantly longer median cancer specific survival in comparison to the p16-group (p = 0.004), with respective 5-year cancer specific survival probability of 88% (95% CI; 0.84, 1) versus 58% (95% CI; 0.55, 0.76; p = 0.004). HPV status did not predict survival outcomes. Penile Squamous Cell Carcinoma (PSCC) is associated with high-risk human papillomavirus (HR-HPV). The immunohistochemical (IHC) test for p16INK4a (p16) is highly correlated with HR-HPV expression in other SCCs. To investigate whether the expression of p16 IHC or HR-HPV is associated with survival in PSCC, we conducted a single institution analysis of 143 patients with a diagnosis of PSCC and, available tissue were tested for p16 IHC staining patterns, histological subtype, tumor grade, and lymphovascular invasion (LVI) by an experienced pathologist. HR-HPV status using the Cobas PCR Assay or the RNAScope high-risk HPV in situ hybridization kit were also assessed. Patient characteristics were summarized using descriptive statistics of clinico-pathologic variables. Kaplan–Meier was used to estimate median overall survival (OS), cancer specific survival (CSS) and correlated with HPV, p16, and other study variables. Patients with p16+ tumors had a significantly longer median CSS in comparison to the p16– group (p = 0.004), with respective 5-year CSS probability of 88% (95% CI; 0.84, 1) versus 58% (95% CI; 0.55, 0.76; p = 0.004). HPV status did not predict survival outcomes. Multivariable analysis with respect to OS and CSS, showed that p16+ status was associated with a lower risk of death (HR = 0.36, 95%CI; 0.20–0.67, p = 0.001), and improved CSS (HR = 0.20, 95% CI; 0.07–0.54, p = 0.002) after adjusting for covariates. In conclusion, tumor p16 status via IHC was an easy to perform independent prognostic factor for OS and CSS that correlates with HR-HPV expression. [ABSTRACT FROM AUTHOR]

Background: The presence of metastatic tumor cells in regional lymph nodes is considered as a significant indicator for inferior prognosis. This study aimed to construct some predictive models to quantify the probability of lymph node metastasis (LNM) and survival rate of patients with soft tissue sarcoma (STS) with LNM. Methods: Research data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2017, and data of patientswith STS from our medical institution were collected to form an external testing set. Univariate and multivariate logistic regression analyses were used to determine the independent risk factors for developing LNM. On the basis of the identified variables, we developed a diagnostic nomogram to predict the risk of LNM in patients with STS. Those patients with STS presenting with LNM were retrieved to build a cohort for identifying the independent prognostic factors through univariate and multivariate Cox regression analysis. Then, two nomograms incorporating the independent prognostic predictors were developed to predict the overall survival (OS) and cancer-specific survival (CSS) for patientswith STS with LNM. Kaplan--Meier (K-M) survival analysis was conducted to study the survival difference. Moreover, validations of these nomograms were performed by the receiver operating characteristic curves, the area under the curve, calibration curves, and the decision curve analysis (DCA). Results: A total of 16,601 patients with STS from the SEER database were enrolled in our study, of which 659 (3.97%) had LNM at the initial diagnosis. K-M survival analysis indicated that patients with LNM had poorer survival rate. Sex, histology, primary site, grade, M stage, and T stage were found to be independently related with development of LNM in patients with STS. Age, grade, histology, M stage, T stage, chemotherapy, radiotherapy, and surgery were identified as the independent prognostic factors for OS of patients with STS with LNM, and age, grade, M stage, T stage, radiotherapy, and surgery were determined as the independent prognostic factors for CSS. Subsequently, we constructed three nomograms, and their online versions are as follows: https:// tyxupup.shinyapps.io/probabilityofLNMforSTSpatients/, https://tyxupup. shinyapps.io/OSofSTSpatientswithLNM/, and https://tyxupup.shinyapps.io/ CSSofSTSpatientswithLNM/. The areas under the curve (AUCs) of diagnostic nomogram were 0.839 in the training set, 0.811 in the testing set, and 0.852 in the external testing set. For prognostic nomograms, the AUCs of 24-, 36-, and 48-month OS were 0.820, 0.794, and 0.792 in the training set and 0.759, 0.728, and 0.775 in the testing set, respectively; the AUCs of 24-, 36-, and 48-month CSS were 0.793, 0.777, and 0.775 in the training set and 0.775, 0.744, and 0.738 in the testing set, respectively. Furthermore, calibration curves suggested that the predicted values were consistent with the actual values. For the DCA, our nomograms showed a superior net benefit across a wider scale of threshold probabilities for the prediction of risk and survival rate for patients with STS with LNM. Conclusion: These newly proposed nomograms promise to be useful tools in predicting the risk of LNM for patients with STS and individualized survival prediction for patients with STS with LNM, which may help to guide clinical practice. [ABSTRACT FROM AUTHOR]

Background: Many patients with gastric cancer are at a locally advanced stage during initial diagnosis. TNM staging is inaccurate in predicting survival. This study aims to develop two more accurate survival prediction models for patients with locally advanced gastric cancer (LAGC) and guide clinical decision-making. Methods: We recruited 2794 patients diagnosed with LAGC (2010-2015) from the Surveillance, Epidemiology, and End Results (SEER) database and performed external validation using data from 115 patients with LAGC at Yantai Affiliated Hospital of Binzhou Medical University. Univariate and multifactorial survival analyses were screened for meaningful independent prognostic factors and were used to build survival prediction models. Concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were evaluated for nomograms. Finally, the differences and relationships of survival and prognosis between the three different risk groups were described using the Kaplan--Meier method. Results: Cox proportional risk regression model analysis identified independent prognostic factors for patients with LAGC, and variables associated with overall survival (OS) included age, race, marital status, T-stage, N-stage, grade, histologic type, surgery, and chemotherapy. Variables associated with cancer-specific survival (CSS) included age, race, T-stage, N-stage, grade, histological type, surgery, and chemotherapy. In the training cohort, C-index of nomogram for predicting OS was 0.722 (95% confidence interval [95% CI]: 0.708-0.736] and CSS was 0.728 (95% CI: 0.713-0.743). In the external validation cohort, C-index of nomogram for predicted OS was 0.728 (95% CI:0.672-0.784) and CSS was 0.727 (95% CI:0.668-0.786). The calibration curves showed good concordance between the predicted and actual results. C-index, ROC, and DCA results indicated that our nomograms could more accurately predict OS and CSS than TNM staging and had a higher clinical benefit. Finally, to facilitate clinical use, we set up two web servers based on nomograms. Conclusion: The nomograms established in this study have better risk assessment ability than the clinical staging system, which can help clinicians predict the individual survival of LAGC patients more accurately and thus develop appropriate treatment strategies. [ABSTRACT FROM AUTHOR]

Jie Tang,1 Liqun Zhu,1 Yuejiao Huang,2,3 Lixiang Yang,4 Dangen Ge,5 Zhengyu Hu,6 Chun Wang1 1Department of Oncology, Liyang People’s Hospital, Liyang, 213300, People’s Republic of China; 2Medical School, Nantong University, Nantong, 226019, People’s Republic of China; 3Department of Medical Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, 226399, People’s Republic of China; 4Department of Neurosurgery, Affiliated Zhongda Hospital of Southeast University, Nanjing, 210009, People’s Republic of China; 5Department of Pharmacy, Liyang People’s Hospital, Liyang, 213300, People’s Republic of China; 6Department of General Surgery, Shanghai Tenth People’s Hospital, Affiliated to Tongji University School of Medicine, Shanghai, 200072, People’s Republic of ChinaCorrespondence: Chun WangDepartment of Oncology, Liyang People’s Hospital, 70 Jianshe Road, Liyang, Jiangsu, 213300, People’s Republic of ChinaEmail zlkwangchun@163.comObjective: Anal canal cancer is a rare malignancy with increasing incidence in recent times. This study aimed to develop two nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) of patients with anal canal cancer.Methods: Information of patients with anal canal cancer from 2004 to 2015 was extracted from the surveillance, epidemiology, and end results (SEER) database. Cox analysis was used to select the risk factors for prognosis, and nomograms were constructed using the R software. The C-index, area under the curve (AUC) of time-dependent receiver operating characteristic (ROC) curves, calibration plot and decision curve analysis (DCA) were used to assess the clinical utility of the nomograms.Results: A total of 2458 patients with malignant tumours of the anal canal were screened out. Sex, age, marital status, histological type, grade, tumour size, AJCC stage, SEER stage and chemotherapy were independent prognostic factors for OS, whereas sex, age, race, histological type, grade, tumour size, AJCC stage, SEER stage and radiotherapy were independent prognostic factors for CSS. In the training cohort, the C-index value for OS nomogram was 0.73 (95% CI, 0.69– 0.77), and the AUC values that predicted the 1-, 3- and 5-year survival rates were 0.764, 0.758 and 0.760, respectively, whereas the C-index value for CSS nomogram model was 0.74 (95% CI, 0.69– 0.79), and the AUC values were 0.763, 0.769 and 0.763, respectively. The calibration plot and DCA curves demonstrated good prediction performance of the model in both the training and validation cohorts.Conclusion: The established nomogram is a visualisation tool that can effectively predict the OS and CSS of patients with anal canal cancer.Keywords: anal canal cancer, cancer specific survival, nomogram, overall survival, prognosis

ObjectivesThe prognostic impact of marital status on malignant pleural mesothelioma (MPM) is not investigated. This paper probes into the relationship between the prognosis of MPM and marital status.Materials and methodsThe Surveillance, Epidemiology, and End Results (SEER) database of American had been applied to choose eligible patients over the 2004–2015 periods. Moreover, cancer-specific survival (CSS) and overall survival (OS) of unmarried and married groups were compared.ResultsA total of 3,997 patients in total had been identified, including 2,735 (68.43%) married patients. In comparison to unmarried patients, married ones tended to be younger, male, white, and received active treatment (surgery, chemotherapy, or radiotherapy). In addition, the 1, 3, and 5-year CSS rates were 44.40, 12.09, and 6.88% in married patients, while 35.75, 12.12, and 6.37% in unmarried group (p = 0.0014). At the same time, the 1, 3, and 5-year OS rates were 41.84, 10.56, and 5.91% in married patients, while 33.67, 10.44, and 4.93%, respectively, in the unmarried group (p < 0.0001). As revealed by the multivariate analysis results, the marital status was an independent favorable prognostic factor, in which the married groups showed better CSS [hazard ratio (HR): 0.870; 95% confidence interval (CI): 0.808–0.938; p < 0.001] as well as OS (HR: 0.871; 95% CI: 0.810–0.936; p < 0.001). According to the results of subgroup analysis, the CSS and OS survival of married groups were better than the unmarried groups in almost all the subgroups.ConclusionMarital status is an independent favorable prognostic indicator of MPM. Poor prognosis in unmarried patients is likely to be related to insufficient treatments and socioeconomic and psychosocial factors.

We identified the prognostic factors of resected stage IA non-small cell lung cancer (NSCLC) and developed a nomogram, with purpose of defining the high-risk population who may need closer follow-up or more intensive care. Eligible stage IA NSCLC cases from the Surveillance, Epidemiology, and End Results (SEER) database and the Sun Yat-sen University Cancer Center (SYSUCC) were included. Stage IB NSCLCs were also included for evaluating the risk stratification efficacy. Cancer specific survival (CSS) was compared between groups. Statistically significant factors from multivariate analysis were entered into the nomogram. The performance of the nomogram was evaluated by concordance index (C-index) and calibration plots. A total of 23,112 NSCLC cases (SEER stage IA training cohort, N=7,777; SEER stage IA validation cohort, N=7,776; SEER stage IB cohort, N=7,559) from the SEER database were included. 1,304 NSCLC cases (SYSUCC stage IA validation cohort, N=684; SYSUCC stage IB cohort, N=620) from the SYSUCC were also included. Younger age, female, lobectomy, well differentiated, smaller size and more examined lymph nodes were identified as favorable prognostic factors. A nomogram was established. The C-index was 0.68 (95%CI, 0.67-0.69), 0.66 (95% CI, 0.64-0.68) and 0.66 (95% CI, 0.61-0.71) for the SEER training cohort, SEER validation cohort and SYSUCC validation cohort. A risk classification system was constructed to stratify stage IA NSCLC into low-risk subgroup and high-risk subgroup. The CSS curves of these two subgroups showed statistically significant distinctions. This nomogram delivered a prognostic prediction for stage IA NSCLC and may aid individual clinical practice. [ABSTRACT FROM AUTHOR]

Background: To test the effect of race/ethnicity on cancer-specific mortality (CSM) after salvage radical prostatectomy (SRP). Material and methods: We relied on the Surveillance, Epidemiology and End Results database (SEER, 2004-2016) to identify SRP patients of all race/ethnicity background. Univariate and multivariate Cox regression models addressed CSM according to race/ethnicity. Results: Of 426 assessable SRP patients, Caucasians accounted for 299 (69.9%) vs. 68 (15.9%) African-Americans vs. 39 (9.1%) Hispanics vs. 20 (4.7%) Asians. At diagnosis, African-Americans (64 years) were younger than Caucasians (66 years), but not younger than Hispanics (66 years) and Asians (67 years). PSA at diagnosis was significantly higher in African-Americans (13.2 ng/ml), Hispanics (13.0 ng/ml), and Asians (12.2 ng/ml) than in Caucasians (7.8 ng/ml, p = 0.01). Moreover, the distribution of African-Americans (10.3%-36.6%) and Hispanics (0%-15.8%) varied according to SEER region. The 10-year CSM was 46.5% in African-Americans vs. 22.4% in Caucasians vs. 15.4% in Hispanics vs. 15.0% in Asians. After multivariate adjustment (for age, clinical T stage, lymph node dissection status), African-American race/ethnicity was an independent predictor of higher CSM (HR: 2.2, p < 0.01), but not Hispanic or Asian race/ethnicity. The independent effect of African-American race/ethnicity did not persist after further adjustment for PSA. Conclusion: African-Americans treated with SRP are at higher risk of CSM than other racial/ethnic groups and also exhibited the highest baseline PSA. The independent effect of African-American race/ethnicity on higher CSM no longer applies after PSA adjustment since higher PSA represents a distinguishing feature in African-American patients. [ABSTRACT FROM AUTHOR]

Introduction: Pre-treatment risk and prognostic groups are the cornerstone for deciding management in non-metastatic prostate cancer. All however, were developed in the pre-MRI era. Here we compared categorisation of cancers using either only clinical parameters or with MRI enhanced information in men referred for suspected prostate cancer from an unscreened population.Patient and Methods: Data from men referred from primary care to our diagnostic service and with both clinical (digital rectal examination [DRE] and systematic biopsies) and MRI enhanced attributes (MRI stage and combined systematic/targeted biopsies) were used for this study. Clinical vs MRI data were contrasted for clinico-pathological and risk group re-distribution using the European Association of Urology (EAU), American Urological Association (AUA) and UK National Institute for Health Care Excellence (NICE) Cambridge Prognostic Group (CPG) models. Differences were retrofitted to a population cohort with long-term prostate cancer mortality (PCM) outcomes to simulate impact on model performance. We further contrasted individualised overall survival (OS) predictions using the Predict Prostate algorithm.Results: Data from 370 men were included (median age 66y). Pre-biopsy MRI stage reassignments occurred in 7.8% (versus DRE). Image-guided biopsies increased Grade Group 2 and ≥ Grade Group 3 assignments in 2.7% and 2.9% respectively. The main change in risk groups was more high-risk cancers (6.2% increase in the EAU and AUA system, 4.3% increase in CPG4 and 1.9% CPG5). When extrapolated to a historical population-based cohort (n = 10,139) the redistribution resulted in generally lower concordance indices for PCM. The 5-tier NICE-CPG system outperformed the 4-tier AUA and 3-tier EAU models (C Index 0.70 versus 0.65 and 0.64). Using an individualised prognostic model, changes in predicted OS were small (median difference 1% and 2% at 10- and 15-years' respectively). Similarly, estimated treatment survival benefit changes were minimal (1% at both 10- and 15-years' time frame).Conclusion: MRI guided diagnostics does change pre-treatment risk groups assignments but the overall prognostic impact appears modest in men referred from unscreened populations. Particularly, when using more granular tiers or individualised prognostic models. Existing risk and prognostic models can continue to be used to counsel men about treatment option until long term survival outcomes are available. [ABSTRACT FROM AUTHOR]

BackgroundFor patients with locally advanced breast cancer (LABC), conventional TNM staging is not accurate in predicting survival outcomes. The aim of this study was to develop two accurate survival prediction models to guide clinical decision making.MethodsA retrospective analysis of 22,842 LABC patients was performed from 2010 to 2015 using the Surveillance, Epidemiology and End Results (SEER) database. An additional cohort of 200 patients from the Binzhou Medical University Hospital (BMUH) was analyzed. The least absolute shrinkage and selection operator (LASSO) regression was used to screen for variables. The identified variables were used to build a survival prediction model. The performance of the nomogram models was assessed based on the concordance index (C-index), calibration plot, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA).ResultsThe LASSO analysis identified 9 variables in patients with LABC, including age, marital status, Grade, histological type, T-stage, N-stage, surgery, radiotherapy, and chemotherapy. In the training cohort, the C-index of the nomogram in predicting the overall survival (OS) was 0.767 [95% confidence intervals (95% CI): 0.751–0.775], cancer specific survival (CSS) was 0.765 (95% CI: 0.756–0.774). In the external validation cohort, the C-index of the nomogram in predicting the OS was 0.858 (95% CI: 0.812–0.904), the CSS was 0.866 (95% CI: 0.817–0.915). In the training cohort, the area under the receiver operator characteristics curve (AUC) values of the nomogram in prediction of the 1, 3, and 5-year OS were 0.836 (95% CI: 0.821–0.851), 0.769 (95% CI: 0.759–0.780), and 0.750 (95% CI: 0.738–0.762), respectively. The AUC values for prediction of the 1, 3, and 5-year CSS were 0.829 (95% CI: 0.811–0.847), 0.769 (95% CI: 0.757–0.780), and 0.745 (95% CI: 0.732–0.758), respectively. Results of the C-index, ROC curve, and DCA demonstrated that the nomogram was more accurate in predicting the OS and CSS of patients compared with conventional TNM staging.ConclusionTwo prediction models were developed and validated in this study which provided more accurate prediction of the OS and CSS in LABC patients than the TNM staging. The constructed models can be used for predicting survival outcomes and guide treatment plans for LABC patients.

BackgroundTo test the effect of race/ethnicity on cancer-specific mortality (CSM) after salvage radical prostatectomy (SRP).Material and methodsWe relied on the Surveillance, Epidemiology and End Results database (SEER, 2004–2016) to identify SRP patients of all race/ethnicity background. Univariate and multivariate Cox regression models addressed CSM according to race/ethnicity.ResultsOf 426 assessable SRP patients, Caucasians accounted for 299 (69.9%) vs. 68 (15.9%) African-Americans vs. 39 (9.1%) Hispanics vs. 20 (4.7%) Asians. At diagnosis, African-Americans (64 years) were younger than Caucasians (66 years), but not younger than Hispanics (66 years) and Asians (67 years). PSA at diagnosis was significantly higher in African-Americans (13.2 ng/ml), Hispanics (13.0 ng/ml), and Asians (12.2 ng/ml) than in Caucasians (7.8 ng/ml, p = 0.01). Moreover, the distribution of African-Americans (10.3%–36.6%) and Hispanics (0%–15.8%) varied according to SEER region. The 10-year CSM was 46.5% in African-Americans vs. 22.4% in Caucasians vs. 15.4% in Hispanics vs. 15.0% in Asians. After multivariate adjustment (for age, clinical T stage, lymph node dissection status), African-American race/ethnicity was an independent predictor of higher CSM (HR: 2.2, p < 0.01), but not Hispanic or Asian race/ethnicity. The independent effect of African-American race/ethnicity did not persist after further adjustment for PSA.ConclusionAfrican-Americans treated with SRP are at higher risk of CSM than other racial/ethnic groups and also exhibited the highest baseline PSA. The independent effect of African-American race/ethnicity on higher CSM no longer applies after PSA adjustment since higher PSA represents a distinguishing feature in African-American patients.

Purpose: The current study aimed to construct a novel cancer artificial intelligence survival analysis system for predicting the individual mortality risk curves for cervical carcinoma patients receiving different treatments.Methods: Study dataset (n = 14,946) was downloaded from Surveillance Epidemiology and End Results database. Accelerated failure time algorithm, multi-task logistic regression algorithm, and Cox proportional hazard regression algorithm were used to develop prognostic models for cancer specific survival of cervical carcinoma patients.Results: Multivariate Cox regression identified stage, PM, chemotherapy, Age, PT, and radiation_surgery as independent influence factors for cervical carcinoma patients. The concordance indexes of Cox model were 0.860, 0.849, and 0.848 for 12-month, 36-month, and 60-month in model dataset, whereas it were 0.881, 0.845, and 0.841 in validation dataset. The concordance indexes of accelerated failure time model were 0.861, 0.852, and 0.851 for 12-month, 36-month, and 60-month in model dataset, whereas it were 0.882, 0.847, and 0.846 in validation dataset. The concordance indexes of multi-task logistic regression model were 0.860, 0.863, and 0.861 for 12-month, 36-month, and 60-month in model dataset, whereas it were 0.880, 0.860, and 0.861 in validation dataset. Brier score indicated that these three prognostic models have good diagnostic accuracy for cervical carcinoma patients. The current research lacked independent external validation study.Conclusion: The current study developed a novel cancer artificial intelligence survival analysis system to provide individual mortality risk predictive curves for cervical carcinoma patients based on three different artificial intelligence algorithms. Cancer artificial intelligence survival analysis system could provide mortality percentage at specific time points and explore the actual treatment benefits under different treatments in four stages, which could help patient determine the best individualized treatment. Cancer artificial intelligence survival analysis system was available at: https://zhangzhiqiao15.shinyapps.io/Tumor_Artificial_Intelligence_Survival_Analysis_System/ . [ABSTRACT FROM AUTHOR]

Background and Aims: Primary liver cancer (PLC) is a common malignancy with poor survival and requires long-term follow-up. Hence, nomograms need to be established to predict overall survival (OS) and cancer-specific survival (CSS) from different databases for patients with PLC. Methods: Data of PLC patients were downloaded from Surveillance, Epidemiology, and End Results (SEER) and the Cancer Genome Atlas (TCGA) databases. The Kaplan Meier method and log-rank test were used to compare differences in OS and CSS. Independent prognostic factors for patients with PLC were determined by univariate and multivariate Cox regression analyses. Two nomograms were developed based on the result of the multivariable analysis and evaluated by calibration curves and receiver operating characteristic curves. Results: OS and CSS nomograms were based on age, race, TNM stage, primary diagnosis, and pathologic stage. The area under the curve (AUC) was 0.777, 0.769, and 0.772 for 1-, 3- and 5-year OS. The AUC was 0.739, 0.729 and 0.780 for 1-, 3- and 5-year CSS. The performance of the two new models was then evaluated using calibration curves. Conclusions: We systematically reviewed the prognosis of PLC and developed two nomograms. Both nomograms facilitate clinical application and may benefit clinical decision-making. [ABSTRACT FROM AUTHOR]

Background: Hepato-pulmonary metastasis of colorectal cancer (CRC) is a rare disease with poor prognosis. This study aims to establish a highly efficient nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with colorectal cancer hepato-pulmonary metastasis (CRCHPM).Methods: We retrospectively analyzed the data of patients with CRCHPM from SEER database and Wuhan Union Hospital Cancer Center (WUHCC). A total of 1250 CRCHPM patients were randomly assigned to the training, internal validation, and external validation cohorts from 2010 to 2016.Univariate and multivariate cox analysis were performed to identify independent clinicopathological predictors of OS and CSS, and a nomogram was constructed to predict OS and CSS in CRCHPM patients.Results: A nomogram of OS was constructed based on seven independent predictors of age, degree of differentiation, T stage, chemotherapy, number of lsampled lymph nodes, number of positive lymph nodes, and tumor size. Nomogram showed favorable sensitivity in predicting OS at 1, 3 and 5 years, with area under the receiver operating characteristic curve (AUROC) values of 0.802, 0.759 and 0.752 in the training cohort;0.814, 0.769 and 0.716 in the internal validation cohort;0.778, 0.756 and 0.753 in the external validation cohort, respectively. A nomogram of CSS was constructed based on three independent predictors of T stage, chemotherapy, and tumor size. The AUROC values of 1, 3 and 5 years were 0.709,0.588,0.686 in the training cohort; 0.751, 0.648,0.666 in the internal validation cohort;0.781,0.588,0.645 in the external validation cohort, respectively. Calibration curves, Concordance index (C-index), and decision curve analysis (DCA) results revealed that using our model to predict OS and CSS is more efficient than other single clinicopathological characteristics.Conclusion: A nomogram of OS and CSS based on clinicopathological characteristics can be conveniently used to predict the prognosis of CRCHPM patients. [ABSTRACT FROM AUTHOR]

The Cancer of the Bladder Risk Assessment (COBRA) score is a predictive tool for estimating Cancer Specific Survival (CSS) after Radical Cystectomy (RC) for urothelial carcinoma. COBRA score variables are: age at RC, Tumor stage and Lymph Node Density (LND). We sought to externally validate the COBRA score and to improve its performance in estimating CSS adding Lymphovascular Invasion (LVI) as a further variable (Modified COBRA score). Clinicopathological and survival data from 789 patients who underwent RC and Pelvic Lymph Node Dissection (PLND) between January 2007 and December 2020 in two European referral centers (Paris, France and Badalona, Spain) were analyzed. COBRA score was applied to our cohort and CSS Kaplan-Meier curves were performed. Univariable and Multivariable analysis was performed in order to identify risk factors for Cancer Specific Mortality (CSM) and a score was assigned for any statistically significant risk factor; afterward, c-index calculation was performed and CCS curves have been plotted for the model after having integrated LVI variable to the COBRA score. Finally, we compared both COBRA score and Modified COBRA score models with the established AJCC model. A total of 789 patients underwent RC during the observation period. Complete data were available for 731 patients with a median follow-up of 32 months (8-47). CSM was 27.6% (no. 218 patients) at follow-up. When COBRA score was applied to our cohort, c-index was 0.76. Regression COX analysis has shown HR 0.36, CI 95% (0.16-0.83), P = .016 for patients with COBRA score 1; HR 0, CI 95% (0-1.77), P = .94 for score 2; HR 0.51, CI 95% (0.39 -0.67), P = .001 for score 3; HR 1.67, CI 95% (1.23-2.27), P = .001 for score 4; HR 2.45, CI 95% (1.51-3.99), P = .001 for score 5; HR 2.01, CI 95% (1.42-2.85), P = .001 for score 6 and HR 0.66, CI 95% (0.09-4.73), P = .682 for score 7. When the LVI variable was added to the CSS predictive model the discriminatory power increased to a c-index of 0.78. COBRA score adequately identifies those patients with a higher risk of CSM, with a c-index of 0.76. Moreover, LVI variable further improves its predictive accuracy from c-index of 0.76 to c-index of 0.78. LVI variable could be integrated in the COBRA score to optimizing prognosis stratification for patients who undergo RC. [ABSTRACT FROM AUTHOR]

Background: At present, there are few studies on renal pelvic transitional cell carcinoma (RPTCC) in elderly patients in the literature. The study aims to establish a new nomogram of cancer-specific survival (CSS) in elderly patients with T1-T3N0M0 RPTCC and validate its reliability.Methods: This study downloaded the data of 1375 elderly patients with T1-T3N0M0 RPTCC in the Surveillance, Epidemiology, and Final Results (SEER) database from 2004 to 2018. Patients were randomly divided into training cohort (n = 977) and validation cohort (n = 398). Proportional subdistribution hazard analyse was applied to determine independent prognostic factors. Based on these factors, we constructed a compting risk model nomogram. We use the calibration plots, the area under the receiver operating characteristics curve (AUC), concordance index (C-index), and decision curve analysis (DCA) to validate predictive performance and clinical applicability. Patients were divided into low-risk group and high-risk group based on nomogram risk score. Kaplan-Meier curve was applied to analyze the difference in survival curve between the two groups of patients.Results: We found that the risk factors affecting CSS in elderly patients with T1-T3N0M0 RPTCC are surgery, AJCC stage, laterality, tumor size, histological grade, and tumour laterality. Based on these factors, we established a nomogram to predict the CSS of RPTCC patients at 1-, 3-, and 5-year. The calibration plots showed that the predicted value was highly consistent with the observed value. In the training cohort and validation cohort, the C-index of the nomogram were 0.671(95% CI 0.622-0.72) and 0.679(95% CI 0.608-0.750), respectively, the AUC showed similar results. The DCA suggests that namogram performs better than the AJCC stage system. The Kaplan-Meier curve showed that CSS of patients was significantly higher in the low-risk group.Conclusions: In this study, the SEER database was used for the first time to create and validate a new nomogram prediction model for elderly patients with T1-T3N0M0 RPTCC. Compared with the traditional AJCC stage system, our new nomogram can more accurately predict the CSS of elderly patients with T1-T3N0M0 RPTCC, which is helpful for patient prognosis assessment and treatment strategies selection. [ABSTRACT FROM AUTHOR]

Background and AimsPrimary liver cancer (PLC) is a common malignancy with poor survival and requires long-term follow-up. Hence, nomograms need to be established to predict overall survival (OS) and cancer-specific survival (CSS) from different databases for patients with PLC.MethodsData of PLC patients were downloaded from Surveillance, Epidemiology, and End Results (SEER) and the Cancer Genome Atlas (TCGA) databases. The Kaplan Meier method and log-rank test were used to compare differences in OS and CSS. Independent prognostic factors for patients with PLC were determined by univariate and multivariate Cox regression analyses. Two nomograms were developed based on the result of the multivariable analysis and evaluated by calibration curves and receiver operating characteristic curves.ResultsOS and CSS nomograms were based on age, race, TNM stage, primary diagnosis, and pathologic stage. The area under the curve (AUC) was 0.777, 0.769, and 0.772 for 1-, 3- and 5-year OS. The AUC was 0.739, 0.729 and 0.780 for 1-, 3- and 5-year CSS. The performance of the two new models was then evaluated using calibration curves.ConclusionsWe systematically reviewed the prognosis of PLC and developed two nomograms. Both nomograms facilitate clinical application and may benefit clinical decision-making.

Background: The importance of the negative lymph node (NLN) count has recently attracted attention. This study aimed to determine the prognostic value of NLN count in patients with non-small cell lung cancer (NSCLC) after radical surgery by constructing NLN-based prognostic models. Methods: This study included 33 756 patients pooled from the case listing session of the US Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015 and 545 patients collected from The First Affiliated Hospital of Shandong First Medical University between 2012 and 2016. X-tile software was used to calculate the optimal cutoff value for the NLN count. The associated clinical factors were determined using univariate and multivariate Cox analyses. Nomograms were developed using the SEER database and validated using hospital data. Results: The training cohort was divided into high and low NLN count subgroups based on the cancer-specific survival (CSS) and overall survival (OS), respectively. Multivariate analysis showed that NLN count was an independent prognostic factor, and the high NLN count subgroup had better CSS and OS than those of the low NLN count subgroup (HR =0.632, 95% CI 0.551-0.724, P < .001 for CSS and HR=0.641, 95% CI 0.571-0.720, P < .001 for OS). Nomograms were established, exhibiting good discrimination ability with a C-index of 0.789 (95% CI 0.778-0.798) for CSS and 0.704 (95% CI, 0.694-0.714) for OS. The calibration plots of the validation cohorts showed optimal agreement with the training cohort, with a C-index of 0.681 (95% CI 0.646-0.716) for CSS and 0.645 (95% CI 0.614-0.676) for OS. Conclusions: NLN count is a strong prognostic factor for OS and CSS in NSCLC patients and the prognostic model provides a useful risk stratification for NSCLC patients when applied to clinical practice. [ABSTRACT FROM AUTHOR]

Background: The importance of the negative lymph node (NLN) count has recently attracted attention. This study aimed to determine the prognostic value of NLN count in patients with non-small cell lung cancer (NSCLC) after radical surgery by constructing NLN-based prognostic models. Methods: This study included 33 756 patients pooled from the case listing session of the US Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015 and 545 patients collected from The First Affiliated Hospital of Shandong First Medical University between 2012 and 2016. X-tile software was used to calculate the optimal cutoff value for the NLN count. The associated clinical factors were determined using univariate and multivariate Cox analyses. Nomograms were developed using the SEER database and validated using hospital data. Results: The training cohort was divided into high and low NLN count subgroups based on the cancer-specific survival (CSS) and overall survival (OS), respectively. Multivariate analysis showed that NLN count was an independent prognostic factor, and the high NLN count subgroup had better CSS and OS than those of the low NLN count subgroup (HR = 0.632, 95% CI 0.551-0.724, P <.001 for CSS and HR = 0.641, 95% CI 0.571-0.720, P <.001 for OS). Nomograms were established, exhibiting good discrimination ability with a C-index of 0.789 (95% CI 0.778 −0.798) for CSS and 0.704 (95% CI , 0.694 −0.714) for OS. The calibration plots of the validation cohorts showed optimal agreement with the training cohort, with a C-index of 0.681 (95% CI 0.646 −0.716) for CSS and 0.645 (95% CI 0.614 −0.676) for OS. Conclusions: NLN count is a strong prognostic factor for OS and CSS in NSCLC patients and the prognostic model provides a useful risk stratification for NSCLC patients when applied to clinical practice. [ABSTRACT FROM AUTHOR]

Introduction: The benefit of cytoreductive nephrectomy (CN) for metastatic kidney cancer has been challenged recently. The study aimed to evaluate the prognostic roles of surgical resection of primary tumor site for metastatic kidney cancer under a real-world setting.Methods: The Surveillance, Epidemiology, and End Results (SEER) database (2010–2015) and the overall survival (OS) and cancer-specific survival (CSS) were evaluated using the Cox proportional hazards regression model. One-to-one matching using the propensity score was used to estimate and compare the survival rates.Results: The SEER data contain records of 8,932 patients from 2010 to 2015. The data showed that 61.7% of the patients underwent CN while 38.2% did not receive any surgery. The median survival month for a patient without surgery was 4 months and for a patient with surgery was 19 months. The multivariate analysis showed that surgical resection of the primary tumor site was an independent favorable predictor for both OS and CSS (all p < 0.001) in the original and the matching cohort.Conclusions: In the era of target therapy, CN might still be a vital method to treat metastatic kidney cancer.

Wilms tumor (WT) is the most common childhood malignant kidney tumor. The aim of the present study was to determine the impact of primary tumor size on the survival of patients with WT. The data of 1,523 patients diagnosed with WT between 2000 and 2017 were retrieved from the Surveillance, Epidemiology, and End Results database. Receiver operating characteristic curves were plotted to determine the optimal cut-off value of primary tumor size. Overall survival (OS) and cancer-specific survival (CSS) were analyzed using the Kaplan-Meier method and the Cox proportional hazards regression model. The optimal cut-off value for primary tumor size was found to be 11.15 cm. No significant difference in the distribution of tumor size was detected between male and female patients. However, lymph node metastasis and distant metastasis were significantly more frequent in patients whose tumor was ≥11.15 cm in size compared with those with smaller tumors. In addition, patients with larger tumors exhibited significantly worse OS and CSS rates compared with those with smaller tumors. Furthermore, primary tumor size was identified as an independent prognostic factor for OS and CSS in the multivariate analyses. In summary, the present study indicates that primary tumor size is an independent prognostic factor for patients with WT, and tumors ≥11.15 cm are associated with worse OS and CSS. [ABSTRACT FROM AUTHOR]

Kexin Ma,* Bing Dong,* Liming Wang, Chongyu Zhao, Zhaoyu Fu, Chi Che, Wuguang Liu, Zexuan Yang, Rui LiangDepartment of Hepatobiliary Surgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning, People’s Republic of China*These authors contributed equally to this workPurpose: To develop and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) in patients with surgically resected intrahepatic cholangiocarcinoma (ICC).Patients and methods: The nomograms were developed using a development cohort of 947 ICC patients after surgery selected from Surveillance, Epidemiology, and End Results database, and externally validated using a training cohort of 159 patients admitted at our institution. Nomograms for OS and CSS were established based on the independent prognostic factors identified by COX regression models and Fine and Grey’s models, respectively. The performance of the nomograms was validated internally and externally by using the concordance index (c-index), and calibration plot, and compared with that of AJCC 8th edition TNM staging system by using c-index and decision curve analysis.Results: Age, T stage, M stage, lymph node ratio (LNR) level and tumor grade were independent prognostic predictors for OS in ICC patients, while T stage, M stage, LNR level and tumor grade were independent prognostic predictors for CSS. Nomogram predicting OS was with a c-index of 0.751 on internal validation and 0.725 up to external validation, while nomogram for CSS was with a c-index of 0.736 on internal validation and 0.718 up to external validation. Calibration plots exhibited that the nomograms-predicted and actual OS/CSS probabilities were fitted well on both internal and external validation. Additionally, the nomograms exhibited superiority over AJCC 8th edition TNM staging system with higher c-indices and net benefit gains, in predicting OS and CSS in ICC patients after surgery.Conclusion: The constructed nomograms could predict OS and CSS with good performance, which could be served as an effective tool for prognostic evaluation and individual treatment strategies optimization in ICC patients after surgery in clinical practice.Keywords: intrahepatic cholangiocarcinoma, overall survival, cancer-specific survival, nomogram

PurposeThe role of surgical resection in the treatment of brainstem glioma (BSG) is poorly understood. For pediatric low-grade (LGBSG) group, several monocentric small-scale retrospective studies reported contradictory conclusions. And there was no clinical study focused on surgical resection for adult or pediatric high-grade (HG) patient groups. This study aims to illustrate whether surgical resection and adjuvant therapy provide survival benefits for patients with histologically confirmed BSG.Patients and MethodsThis retrospective cohort study included 529 patients with histologically confirmed BSG in Surveillance Epidemiology and End Results (SEER) database from 2006-2015. Patients were divided into four groups by age and World Health Organization (WHO) grade. Kaplan-Meier curves of CSS were plotted by different treatment options to compare the survival probability. Univariate and multivariable analyses were then conducted to determine the prognosis effects of surgical resection and adjuvant therapy on cancer specific survival (CSS). All analyses were done in four different groups separately.ResultsThe final sample included 529 patients. The entire study population was divided into groups of pediatric LG (n=236, 44.6%), pediatric HG (n=37, 7.0%), adult LG (n=204, 38.6%) and adult HG (n=52, 9.8%). 52.7% (n=144) of pediatric patients had pilocytic astrocytoma and 45.3% (n=116) of adult patients had ependymoma. Pediatric LGBSG group had the highest gross total resection (GTR) rate (61.4%) and 5-year CSS rate (88.6%). Kaplan-Meier curves of pediatric LGBSG group revealed that patients treated with GTR had significantly better survival probability (P=0.033). Multivariable analysis identified GTR as independently significant predictor for prolonged CSS in pediatric LGBSG group (HR0.29, 95%CI 0.11-0.78, P=0.015); Surgical resection showed no relation to CSS in other patient groups. Kaplan-Meier curves of adult HGBSG group showed that patients treated with both RT and CT in adult HGBSG group had the best survival probability (P=0.02). However, multivariable analysis showed the combination of radiotherapy (RT) and chemotherapy (CT) was not significantly related to better CSS in adult HGBSG group (HR0.35, 95%CI 0.11-1.09, P=0.070). Adjuvant therapy didn’t associate with better CSS in other patient groups.ConclusionPediatric LGBSG group had the highest GTR rate and the most favorable clinical outcome. GTR can provide significant survival benefits for pediatric LGBSG group.

BackgroundAlthough radiation therapy (RT) improves local control for rectal cancer (RC), the long-term risks from RT, including development of a secondary malignancy, are controversial. The risk and prognosis of secondary bladder cancer (SBC) in RC patients undergoing RT have not been adequately studied. Our goal is to investigate the impact of RT on the risk of developing SBC and assess their survival outcomes.MethodsThis large population-based study included RC patients as their initial primary cancer from nine registries of the Surveillance, Epidemiology and End Results (SEER) database between 1973 and 2015. The cumulative incidence of SBC was assessed by using Fine and Gray’s competing risk regression. The standardized incidence ratio (SIR) was used to compare the incidence of SBC in RC survivors to the US general population. The Kaplan-Meier method was used to evaluate the 10-year overall survival (OS) and 10-year cancer specific survival (CSS) for patients with SBC.ResultsOf 74,646 RC patients, 24,522 patients were treated with surgery and RT and 50,124 patients were treated with surgery alone. The incidence of SBC was 1.85% among patients who received RT and 1.24% among patients who did not. The incidence of SBC in RC patients who received RT was higher than the US general population (SIR, 1.35; 95% CI, 1.19-1.53, P

Purpose: The role of surgical resection in the treatment of brainstem glioma (BSG) is poorly understood. For pediatric low-grade (LGBSG) group, several monocentric small-scale retrospective studies reported contradictory conclusions. And there was no clinical study focused on surgical resection for adult or pediatric high-grade (HG) patient groups. This study aims to illustrate whether surgical resection and adjuvant therapy provide survival benefits for patients with histologically confirmed BSG. Patients and Methods: This retrospective cohort study included 529 patients with histologically confirmed BSG in Surveillance Epidemiology and End Results (SEER) database from 2006-2015. Patients were divided into four groups by age and World Health Organization (WHO) grade. Kaplan-Meier curves of CSS were plotted by different treatment options to compare the survival probability. Univariate and multivariable analyses were then conducted to determine the prognosis effects of surgical resection and adjuvant therapy on cancer specific survival (CSS). All analyses were done in four different groups separately. Results: The final sample included 529 patients. The entire study population was divided into groups of pediatric LG (n=236, 44.6%), pediatric HG (n=37, 7.0%), adult LG (n=204, 38.6%) and adult HG (n=52, 9.8%). 52.7% (n=144) of pediatric patients had pilocytic astrocytoma and 45.3% (n=116) of adult patients had ependymoma. Pediatric LGBSG group had the highest gross total resection (GTR) rate (61.4%) and 5-year CSS rate (88.6%). Kaplan-Meier curves of pediatric LGBSG group revealed that patients treated with GTR had significantly better survival probability (P=0.033). Multivariable analysis identified GTR as independently significant predictor for prolonged CSS in pediatric LGBSG group (HR0.29, 95%CI 0.11-0.78, P=0.015); Surgical resection showed no relation to CSS in other patient groups. Kaplan-Meier curves of adult HGBSG group showed that patients treated with both RT and CT in adult HGBSG group had the best survival probability (P=0.02). However, multivariable analysis showed the combination of radiotherapy (RT) and chemotherapy (CT) was not significantly related to better CSS in adult HGBSG group (HR0.35, 95%CI 0.11-1.09, P=0.070). Adjuvant therapy didn't associate with better CSS in other patient groups. Conclusion: Pediatric LGBSG group had the highest GTR rate and the most favorable clinical outcome. GTR can provide significant survival benefits for pediatric LGBSG group. [ABSTRACT FROM AUTHOR]

Background: Although radiation therapy (RT) improves local control for rectal cancer (RC), the long-term risks from RT, including development of a secondary malignancy, are controversial. The risk and prognosis of secondary bladder cancer (SBC) in RC patients undergoing RT have not been adequately studied. Our goal is to investigate the impact of RT on the risk of developing SBC and assess their survival outcomes. Methods: This large population-based study included RC patients as their initial primary cancer from nine registries of the Surveillance, Epidemiology and End Results (SEER) database between 1973 and 2015. The cumulative incidence of SBC was assessed by using Fine and Gray's competing risk regression. The standardized incidence ratio (SIR) was used to compare the incidence of SBC in RC survivors to the US general population. The Kaplan-Meier method was used to evaluate the 10-year overall survival (OS) and 10-year cancer specific survival (CSS) for patients with SBC. Results: Of 74,646 RC patients, 24,522 patients were treated with surgery and RT and 50,124 patients were treated with surgery alone. The incidence of SBC was 1.85% among patients who received RT and 1.24% among patients who did not. The incidence of SBC in RC patients who received RT was higher than the US general population (SIR, 1.35; 95% CI, 1.19-1.53, P<0.05), and decreased with increasing age at diagnosis, and increased with time since diagnosis. In competing risk regression analysis, undergoing RT was associated with a higher risk of SBC (hazard ratio [HR], 1.443, 95% confidence interval [CI], 1.209-1.720; P<0.001). The results of the dynamic SIR for SBC revealed that a slightly increased risk of SBC was observed after RT in the early latency, and was significantly related to the variations of age at RC diagnosis and decreased with time progress. The 10-year OS and CSS among SBC patients after RT were comparable to SBC patients after NRT. Conclusion: Radiation was associated with an increased risk of developing SBC in RC patients, and special attention should be paid to the surveillance of these patients. [ABSTRACT FROM AUTHOR]

Objective: To establish nomogram models for predicting the overall survival (OS) and cancer-specific survival (CSS) of gastric cancer liver metastasis (GCLM) patients., Methods: Data from the Surveillance, Epidemiology, and End Results (SEER) database for 5,451 GCLM patients diagnosed between 2010 and 2015 were analyzed. The cohort was divided into a training set (3,815 cases) and an internal validation set (1,636 cases). External validation included 193 patients from the Fourth Hospital of Hebei Medical University and 171 patients from the People's Hospital of Shijiazhuang City, spanning 2016-2018. Multivariable Cox regression analysis identified eight independent prognostic factors for OS and CSS in GCLM patients, including age, histological type, grade, tumor size, surgery, chemotherapy, bone metastasis, and lung metastasis. Two nomogram models were developed based on these factors and evaluated using time-dependent receiver operating characteristic curve analysis, calibration curves, and decision curve analysis., Results: Internal validation showed that the nomogram models outperformed the American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system in predicting 1-year, 2-year, and 3-year OS and CSS in GCLM patients (1-year OS: 0.801 vs. 0.593, P < 0.001; 1-year CSS: 0.807 vs. 0.598, P < 0.001; 2-year OS: 0.803 vs. 0.630, P < 0.001; 2-year CSS: 0.802 vs. 0.633, P < 0.001; 3-year OS: 0.824 vs. 0.691, P < 0.001; 3-year CSS: 0.839 vs. 0.692, P < 0.001)., Conclusion: This study developed and validated nomogram models using SEER database data to predict OS and CSS in GCLM patients. These models offer improved prognostic accuracy over traditional staging systems, aiding in clinical decision-making., Competing Interests: None., (AJCR Copyright © 2024.)

Background: The impact of the timing of bone metastasis (BM) diagnosis on colorectal cancer (CRC) patients is unclear. Our study aimed to explore the differences in clinicopathological characteristics, treatments and prognosis between synchronous BM (SBM) and metachronous BM (MBM) from CRC.Methods: We retrospectively investigated clinical data of CRC patients with SBM or MBM from 2008 to 2017 at Chinese National Cancer Center. Cancer specific survival (CSS) after BM diagnosis was estimated using the Kaplan-Meier method. The multivariable COX regression model identified the prognostic factors of CSS.Results: Finally, 63 CRC patients with SBM and 138 CRC patients with MBM were identified. Compared to SBM from CRC, MBM significantly was more involving multiple bone lesions (63.0 vs. 7.9%; p < 0.001), and more frequently originated from rectal cancer (60.9 vs. 41.3%; p = 0.033). The therapeutic strategies in SBM and MBM group were contrasted including systemic treatment, bisphosphonates, radiotherapy and metastasectomy for BM. 85.5% of patients in MBM group and 25.4% of patients in SBM group underwent primary tumor resection at initial diagnosis (p < 0.001). The median CSS was 11 months in both SBM and MBM group (p = 0.556), yet MBM patients developed from CRC in early AJCC stage presented obviously longer survival than those from advanced stage. Furthermore, patients could have improved CSS from primary tumor resection while there might be no survival benefit from targeted therapy in both SBM and MBM groups. Bisphosphonates was associated with a better CSS for patients with SBM, while radiotherapy for BM was related to a better CSS for patients with MBM.Conclusion: The CRC patients in SBM and MBM group represented different clinicopathological characteristics and treatment modalities, which affected the prognosis in different ways. Distinct consideration for CRC patients with SBM and MBM in clinical decision making is required.

Junmiao Wen,1,2,* Di Liu,1,2,* Xinyan Xu,1,2 Donglai Chen,3 Yongbing Chen,4 Liang Sun,5 Jiayan Chen,1,2 Min Fan1,2 1Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai 200032, People’s Republic of China; 2Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, People’s Republic of China; 3Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200433, People’s Republic of China; 4Department of Thoracic Surgery, The Second Affiliated Hospital of Soochow University, Medical College of Soochow University, Suzhou 215000, People’s Republic of China; 5School of Radiation Medicine and Protection, Medical College of Soochow University, Suzhou 215123, People’s Republic of China *These authors contributed equally to this work Background: The aim of this study was to develop and validate reliable nomograms to predict individual overall survival (OS) and cancer-specific survival (CSS) for patients with primary tracheal tumors and further estimate the role of postoperative radiotherapy (PORT) for these entities.Patients and methods: A total of 405 eligible patients diagnosed between 1988 and 2015 were selected from the Surveillance, Epidemiology, and End Results database. All of them were randomly divided into training (n=303) and validation (n=102) sets. For the purpose of establishing nomograms, the Akaike information criterion was employed to select significant prognostic factors in multivariate Cox regression models. Both internal and external validations of the nomograms were evaluated by Harrell’s concordance index (C-index) and calibration plots. Propensity score matching (PSM) method was performed to reduce the influence of selection bias between the PORT group and the non-PORT group.Results: Two nomograms shared common variables including age at diagnosis, histology, N and M stages, tumor size, and treatment types, while gender was only incorporated in the CSS nomogram. The C-indices of OS and CSS nomograms were 0.817 and 0.813, displaying considerable predictive accuracy. The calibration curves indicated consistency between the nomograms and the actual observations. When the nomograms were applied to the validation set, the results remained reconcilable. Moreover, the nomograms showed superiority over the Bhattacharyya’s staging system with regard to the C-indices. After PSM, PORT was not associated with significantly better OS or CSS. Only squamous cell carcinoma (SCC) patients in the PORT group had improved OS compared to non-PORT group.Conclusion: The first two nomograms for predicting survival in patients with primary tracheal tumors were proposed in the present study. PORT seems to improve the prognosis of SCC patients, which needs further exploration. Keywords: nomogram, primary tracheal tumors, overall survival, cancer-specific survival, propensity score matching analysis

Background/Aims: During the occurrence and progression of hepatocellular carcinoma (HCC), phosphotyrosine phosphatases (PTPs) are usually described as tumor suppressors or proto-oncogenes, and to some degree are correlated with the prognosis of HCC. Methods: A total of 321 patients from the Cancer Genome Atlas (TCGA) database and 180 patients from our validated cohort with hepatocellular carcinoma were recruited in this study. Kaplan-Meier, univariate and multivariate Cox proportional hazards model were used to evaluate the risk factors for survival. Quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) were applied to detect the expression levels of PTP genes. Results: After screening the data of TCGA, we identified five PTPs as HCC overall survival related PTP genes, among which only three (PTPN12, PTPRN, PTPN18) exhibited differential expression levels in our 180 paired HCC and adjacent tissues (P< 0.001). Further analysis revealed that expression of PTPN18 was positively, but PTPRN was negatively associated with prognosis of HCC both in TCGA cohort and our own cohort. As to PTPN12, results turned out to be opposite according to HBV status. In detail, higher expression of PTPN12 was associated with better outcome in HBV group but worse prognosis in Non-HBV group. Conclusion: Our results suggested that PTPN12, PTPRN and PTPN18 were independent prognostic factors in HCC.

Background: The impact of the timing of bone metastasis (BM) diagnosis on colorectal cancer (CRC) patients is unclear. Our study aimed to explore the differences in clinicopathological characteristics, treatments and prognosis between synchronous BM (SBM) and metachronous BM (MBM) from CRC. Methods: We retrospectively investigated clinical data of CRC patients with SBM or MBM from 2008 to 2017 at Chinese National Cancer Center. Cancer specific survival (CSS) after BM diagnosis was estimated using the Kaplan-Meier method. The multivariable COX regression model identified the prognostic factors of CSS. Results: Finally, 63 CRC patients with SBM and 138 CRC patients with MBM were identified. Compared to SBM from CRC, MBM significantly was more involving multiple bone lesions (63.0 vs. 7.9%; p < 0.001), and more frequently originated from rectal cancer (60.9 vs. 41.3%; p = 0.033). The therapeutic strategies in SBM and MBM group were contrasted including systemic treatment, bisphosphonates, radiotherapy and metastasectomy for BM. 85.5% of patients in MBM group and 25.4% of patients in SBM group underwent primary tumor resection at initial diagnosis (p < 0.001). The median CSS was 11 months in both SBM and MBM group (p = 0.556), yet MBM patients developed from CRC in early AJCC stage presented obviously longer survival than those from advanced stage. Furthermore, patients could have improved CSS from primary tumor resection while there might be no survival benefit from targeted therapy in both SBM and MBM groups. Bisphosphonates was associated with a better CSS for patients with SBM, while radiotherapy for BM was related to a better CSS for patients with MBM. Conclusion: The CRC patients in SBM and MBM group represented different clinicopathological characteristics and treatment modalities, which affected the prognosis in different ways. Distinct consideration for CRC patients with SBM and MBM in clinical decision making is required. [ABSTRACT FROM AUTHOR]

Turnover of RNA is a regulated process that in part controls gene expression. This process is partly controlled by the scavenger decapping enzyme (DcpS). This study aimed to investigate the expression of DcpS in colorectal cancer (CRC) tissue, to evaluate its prognostic significance in patients with CRC and to investigate potentially targeted genes by DcpS. Immunohistochemical analysis was used to determine localization of DcpS in normal and CRC tissue, western blot analysis for quantification of protein expression and qPCR for mRNA expression in normal and CRC tissue and expression in cell lines after silencing using siRNA. Gene array analysis was used to study regulation of genes after silencing of DcpS. Proliferation was studied using BRDU. DcpS expression was localized to the epithelial cells of both control and cancer tissue. Tumor and paired control tissue samples from 100 patients who underwent surgical resection for primary colorectal adenocarcinomas were utilized. mRNA and protein of DcpS was significantly up-regulated in the patients with CRC and the mRNA level was higher in rectal cancer tissue compared to colon cancer tissue (p < 0.05). Lowest tertile levels of DcpS mRNA in cancer tissue was associated with a decreased cancer-specific survival rate with a hazard ratio (HR) of 4.7 (95% CI=1.02–12.3), independent of disease stage. The low level of DcpS mRNA was a predictor of poorer survival in patients with rectal and disseminated cancer and in patients receiving adjuvant treatment (p < 0.05). After silencing DcpS in Caco-2 cancer cells, altered expression of several genes associated with RNA, cell cycle regulation, alternative splicing and microRNA was observed and resulted in 23% increase in proliferation. These results indicate that DcpS has potential as a prognostic factor for CRC but further studies in a broader cohort are warranted to evaluate the significance of the findings in the clinic. [ABSTRACT FROM AUTHOR]