Analysis of risk factors for cancer-specific survival in neoadjuvant chemotherapy nonresponsive disease of muscle-invasive bladder cancer: A multicentre study from the Turkish Urooncology Association Bladder Tumor study group.

OBJECTIVE: To investigate the risk factors affecting cancer-specific survival (CSS) in nonresponsive disease to neoadjuvant chemotherapy (NAC) among patients with muscle-invasive bladder cancer (MIBC) who were treated with NAC and radical cystectomy (RC). METHODS: Patients with MIBC who underwent NAC and RC were retrospectively examined. By comparing clinical and pathological stages, patients whose pathological stage was lower than clinical stage were categorized as "NAC-responsive" and the remainder as "NAC-non-responsive." Apart from pathologic staging, variables compared between groups included age, gender, Eastern Cooperative Oncology Group (ECOG) score, clinical stages, NAC type and cycle number, durations between MIBC diagnosis and NAC initiation and RC, presence of hydronephrosis, number of lymph nodes removed, and variant histology of urothelial bladder cancer. CSS analysis was performed by construction of Kaplan-Meier survival curves and multivariable Cox regression was performed to identify the prognosticators in the NAC-non-responsive-group. RESULTS: Ninety-two patients were included with a mean age was 61.5 ± 8.5 years, of whom 84.8% were men. The NAC regimen used was predominantly gemcitabine-cisplatin (88%) and the median cycle number was 4. Fifty-six (60.9%) patients were NAC-non-responsive. There was a significantly lower proportion of patients receiving ≥4 cycles (46.4% vs. 66.7%) and a higher rate of patients with ECOG score ˃1 (33.9% vs. 11.1%) in the NAC-non-responsive-group compared to the NAC-responsive-group (both P < 0.05). Other variables were similar between groups. In multivariable analysis, only ypN+ was found to be an independent prognosticator for CSS in NAC-non-responsive-group (HR: 2.725, CI95%:1.017-7.303). CONCLUSION: Although higher ECOG scores and lower cycle numbers appears to be associated factors in NAC-non-responsive disease, only ypN(+) status was a prognosticator for CSS in this population.

Establishment and Validation of Prognostic Nomograms for Nonmetastatic Melanoma of the Limbs-A SEER-Based Study.

BACKGROUND: Malignant melanoma, a highly aggressive skin cancer, has remarkable incidence and mortality nowadays. This study aims to explore prognostic factors associated with nonmetastatic cutaneous melanoma of the limbs and to develop nomograms for predicting overall survival (OS) and cancer-specific survival (CSS). METHODS: The study cohort was derived from the Surveillance, Epidemiology, and End Results database. Univariate Cox regression, Lasso regression, and multivariate Cox regression analyses were conducted to identify prognostic factors and construct nomograms. The receiver operating characteristic (ROC) curve, time-dependent C-index, calibration curve, decision curve analysis (DCA) and Kaplan-Meier method were used to evaluate the accuracy and clinical applicability of the nomograms. RESULTS: A total of 15,606 patients were enrolled. Multivariate analysis identified several prognostic factors for OS and CSS including age, sex, histologic type, N stage, tumor thickness, depth of invasion, mitotic rate, ulceration, surgery of primary site, systemic therapy, race, and number of lymph nodes examined. A nomogram incorporating 12 independent predictors for OS was developed, with a C-index of 0.866 (95% confidence interval [CI]: 0.858-0.874) in the training cohort and 0.853 (95% CI: 0.839-0.867) in validation. For CSS, 10 independent predictors and one related factor were included, yielding a C-index of 0.913 (95% CI: 0.903-0.923) in the training cohort and 0.922 (95% CI: 0.908-0.936) in validation. The ROC curve, time-dependent C-index, calibration curve, DCA, and K-M plot demonstrated favorable discrimination, calibration, and clinical utility. CONCLUSION: The developed nomograms provide a precise and personalized predictive tool for risk management of patients with nonmetastatic limb melanoma.

Population-based long-term prognosis analysis of subcutaneous gastrointestinal stromal tumors.

BACKGROUND: Subcutaneous gastrointestinal stromal tumors (scGISTs) are extremely rare tumors, and the analysis of their long-term prognosis remains unreported. Therefore, our objective is to analyze the long-term prognosis of patients with scGISTs using the Surveillance, Epidemiology, and End Results database. METHODS: Patients diagnosed with GISTs between 2000 and 2019 were included in the study. To handle missing data, multiple imputation techniques were employed. Kaplan-Meier analysis and Cox proportional hazards models were used to evaluate overall survival (OS) and cancer-specific survival (CSS), and subgroup analyses were conducted for various variables. RESULTS: A total of 12,882 patients were enrolled, with 12,636 diagnosed with GISTs and 246 with scGISTs. In comparison to GISTs patients, scGISTs patients exhibited inferior OS [hazard ratio (HR) 1.69, 95% confidence interval (CI) 1.45-1.98, P < 0.001] and CSS (HR 2.16, 95% CI 1.78-2.61, P < 0.001). Across various subgroups, including age, sex, surgical intervention, marital status, and chemotherapy, scGISTs patients consistently demonstrated significantly poorer OS and CSS outcomes compared to GISTs patients (P < 0.05). The 1-, 3-, and 5-year OS rates for scGISTs patients were 78.4%, 60.3%, and 49.3%, respectively, with corresponding CSS rates of 83.3%, 67.8%, and 57.4%. Notably, scGISTs patients who received surgical treatment had significantly higher 5-year OS rates (62.1% vs 30.9%, P < 0.001) and CSS rates (67.8% vs 40.0%, P < 0.001) compared to those who did not undergo surgery. Multivariate Cox regression analysis identified age, surgical status, and mitotic rate as risk factors influencing OS in scGISTs patients, while surgical status and mitotic rate were identified as risk factors affecting CSS. CONCLUSIONS: Compared to GISTs patients, scGIST patients exhibit a less favorable prognosis; nonetheless, surgical intervention has been demonstrated to enhance their prognosis.

Rethinking the prognosis model of differentiated thyroid carcinoma.

Background: The prediction efficiency of long-term cancer-specific survival (CSS) in guiding the treatment of differentiated thyroid carcinoma (DTC) patients is still unsatisfactory. We need to refine the system so that it more accurately correlates with survival. Methods: This is a retrospective study using the Surveillance, Epidemiology, and End Results (SEER) database, and included patients who underwent surgical treatment and were diagnosed with DTC from 2004 to 2020. Patients were divided into a training cohort (2004-2015) and validation cohort (2016-2020). Decision tree methodology was used to build the model in the training cohort. The newly identified groups were verified in the validation cohort. Results: DTC patient totals of 52,917 and 48,896 were included in the training and validation cohorts, respectively. Decision tree classification of DTC patients consisted of five categorical variables, which in order of importance were as follows: M categories, age, extrathyroidal extension, tumor size, and N categories. Then, we identified five TNM groups with similar within-group CSS. More patients were classified as stage I, and the number of stage IV patients decreased significantly. The new system had a higher proportion of variance explained (PVE) (5.04%) and lower Akaike information criterion (AIC) (18,331.906) than the 8th TNM staging system (a PVE of 4.11% and AIC of 18,692.282). In the validation cohort, the new system also showed better discrimination for survival. Conclusion: The new system for DTC appeared to be more accurate in distinguishing stages according to the risk of mortality and provided more accurate risk stratifications and potential treatment selections.

Crafting and Authenticating Prognostic Nomograms for Overall and Cancer-specific Survival in Pediatric Small Renal Masses: A Comprehensive Two-Decade Cohort Study.

BACKGROUND: The intricate task of diagnosing and managing small renal masses (SRMs) has become progressively convoluted within the realm of clinical practice. Contemporary clinical prediction instruments may succumb to a gradual decay in precision, coupled with an absence of unambiguous guidelines to navigate patient management. METHODS: This investigation was devised to formulate and authenticate nomograms for the overall survival (OS) and cancer- specific survival (CSS) among patients afflicted with SRMs. The study encompassed a cohort of 2558 pediatric patients diagnosed with SRMs over the period of 2000 to 2019. Independent prognostic indicators for OS and CSS, encompassing historical staging, chemotherapy regimens, surgical interventions, and pathological classifications, were ascertained through the employment of multivariate Cox proportional hazards regression analysis and backward stepwise selection. RESULTS: Through the utilization of multivariate Cox regression models, nomograms for OS and CSS were meticulously crafted, demonstrating commendable discrimination and calibration within the training set (OS C-index: 0.762, CSS C-index: 0.779). The validation set further corroborated the exemplary discrimination and calibration of the nomograms. Moreover, these nomograms adeptly differentiated between patient groups at elevated and diminished risk levels. CONCLUSION: The nomograms delineated in this research provide propitious predictive accuracy for overall survival and cancer-specific survival in patients suffering from pediatric SRMs, thereby contributing to refined risk stratification and steering the optimal therapeutic course of action. The necessity for supplementary validation prevails before the translation of these findings into clinical practice.

The prognostic significance of synchronous metastasis in glioblastoma multiforme patients: a propensity score-matched analysis using SEER data.

Background: Glioblastoma multiforme (GBM) with synchronous metastasis(SM) is a rare occurrence. We extracted the data of GBM patients from the SEER database to look into the incidence of SM in GBM, determine the prognostic significance of SM in GBM, and assess therapeutic options for patients presenting with SM. Methods: From 2004 to 2015, information on GBM patients was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The propensity score matching (PSM) method was employed to mitigate confounding factors between SM and non-SM groups, subsequently investigating the prognostic significance of SM in patients with GBM. Multivariate Cox proportional hazards regression analyses were employed to identify independent prognostic variables for GBM patients with SM. A forest plot was used to visualize the results. Results: A cohort of 19,708 patients was obtained from the database, among which 272 (1.4%) had SM at the time of diagnosis. Following PSM at a 3:1 ratio, in both univariate and multivariate cox regression analysis, SM (HR = 1.27, 95% CI: 1.09-1.46) was found to be an independent predictive predictor for GBM patients. Furthermore, the Cox proportional hazard forest plot demonstrated that independent risk variables for GBM patients with SM included age (Old vs. Young, HR = 1.44, 95% CI: 1.11-1.88), surgery (biopsy vs. no surgery, HR = 0.67, 95% CI: 0.46-0.96;Subtotal resection vs. no surgery, HR = 0.47, 95% CI: 0.32-0.68;Gross total resection vs. no surgery, HR = 0.44, 95% CI: 0.31-0.62), radiotherapy (HR = 0.58, 95% CI: 0.41-0.83), and chemotherapy (HR = 0.51, 95% CI: 0.36-0.72). Conclusion: The predictive value of SM in GBM was determined by this propensity-matched analysis using data from the SEER database. Radiotherapy, chemotherapy, and surgery constitute an effective treatment regimen for patients with SM. A more positive approach toward the use of aggressive treatment for GBM patients with SM may be warranted.

Androgen deprivation therapy, neoadjuvant androgen deprivation therapy, and adjuvant androgen deprivation therapy in patients with locally advanced prostate cancer: a multi-center real-world retrospective study.

PURPOSE: Determining the potential benefit of neoadjuvant androgen deprivation therapy (ADT) and adjuvant ADT in patients with locally advanced prostate cancer (LAPC) undergoing complete resection. METHODS: 139 patients diagnosed with cT3-4, or cN+ LAPC in Xiangya Hospital and The First Affiliated Hospital of University of South China from 2010 to 2021 were collected. Cancer-specific survival (CSS) and overall survival (OS) of patients were assessed using Kaplan-Meier and Cox proportional risk analysis. We also analyzed the functional outcomes of two subgroups of patients who underwent radical prostatectomy (RP). RESULTS: Of the 182 patients with cT3-4, or cN+ LAPC, 139 patients (76.4%) were enrolled in the study with a 5-year survival rate of 82.3%. 45 patients (32.4%) received ADT alone, 46 patients (33.1%) received neoadjuvant ADT before surgery, and the remaining 48 patients (34.5%) received surgery with adjuvant ADT. Neoadjuvant ADT before surgery and surgery with adjuvant ADT were associated with significantly improved survival compared with ADT alone. Multivariate Cox models showed that neoadjuvant ADT before surgery (hazard ratio [HR], 0.29; 95% CI 0.13-0.92) or surgery with adjuvant ADT (HR, 0.26; 95% CI 0.16-0.78) was associated with improved CSS compared with ADT alone. Regional lymph node metastasis, positive lymphovascular invasion, and Gleason score 9 + were independent predictors of LAPC CSS and OS. More patients in the neoadjuvant ADT before surgery group achieved final continence status within 12 months after surgery (93.48% v 77.08%). CONCLUSION: CSS and OS were significantly prolonged in cT3-4, or cN+ LAPC patients who received neoadjuvant ADT before surgery and surgery with adjuvant ADT compared to ADT alone.

Prognostic nomograms for young breast cancer: A retrospective study based on the SEER and METABRIC databases.

Background: Young breast cancer (YBC) is a subset of breast cancer that is often more aggressive, but less is known about its prognosis. In this study, we aimed to generate nomograms to predict the overall survival (OS) and breast cancer-specific survival (BCSS) of YBC patients. Methods: Data of women diagnosed with YBC between 2010 and 2020 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly allocated into a training cohort (n = 15,227) and internal validation cohort (n = 6,526) at a 7:3 ratio. With the Cox regression models, significant prognostic factors were identified and used to construct 3-, 5-, and 10-year nomograms of OS and BCSS. Data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database were used as an external validation cohort (n = 90). Results: We constructed nomograms incorporating 10 prognostic factors for OS and BCSS. These nomograms demonstrated strong predictive accuracy for OS and BCSS in the training cohort, with C-indexes of 0.806 and 0.813, respectively. The calibration curves verified that the nomograms have good prediction accuracy. Decision curve analysis demonstrated their practical clinical value for predicting YBC patient survival rates. Additionally, we provided dynamic nomograms to improve the operability of the results. The risk stratification ability assessment also showed that the OS and BCSS rates of the low-risk group were significantly better than those of the high-risk group. Conclusions: Here, we generated and validated more comprehensive and accurate OS and BCSS nomograms than models previously developed for YBC. These nomograms can help clinicians evaluate patient prognosis and make clinical decisions.

Microvascular invasion is associated with poor prognosis in renal cell carcinoma: a retrospective cohort study and meta-analysis.

Background: This retrospective cohort study and meta-analysis aims to explore the association between microvascular invasion (MVI) and clinicopathologiccal features, as well as survival outcomes of patients with renal cell carcinoma (RCC). Material and methods: The retrospective cohort study included 30 RCC patients with positive MVI and another 75 patients with negative MVI as controls. Clinicopathological features and follow-up data were compiled. The meta-analysis conducted searches on PubMed, Cochrane Library, Web of Science, Embase, and WanFang Data from the beginning to 30 September 2023, for comparative studies relevant to MVI patients. The Newcastle-Ottawa Scale and Egger Test were used to assess the risk of biases and certainty of evidence in the included studies. Results: The cohort study showed that MVI was associated with advanced primary tumor stage, high pathological grades, high tumor size, high clinical symptoms and lymph node invasion (P <0.05). Kaplan-Meier analyses demonstrated MVI was associated with worse CSS rates when compared to MVI negative group (P <0.05). However, in the multivariate analysis it was not presented as an independent predictor of cancer survival mortality (P >0.05). The meta-analysis part included 11 cohort studies. The results confirmed that patients with MVI positive had worse 12 and 60 mo CSS rates (HR12mo = 0.86, 95%CI 0.80-0.92; HR60mo = 0.63, 95% CI 0.55-0.72; P < 0.00001). Moreover, the meta-analysis also confirmed that MVI group was associated with higher rate of advanced tumor stage, pathological grades, tumor size diameter, higher rate of clinical symptoms and lymph node invasion (P <0.05). Conclusions: The presence of MVI in renal cell carcinoma patients is linked to poorer survival outcomes and worse clinicopathological features. In spite of this, it does not seem to be an independent predictor for cancer survival mortality in renal cell carcinoma. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023470640, identifier CRD42023470640.

Choice of wedge resection for selected T1a/bN0M0 non-small cell lung cancer.

Recently, several studies have reported that the survival benefit of wedge resection might not be inferior to that of lobectomy in early-stage NSCLC patients, but there is no unified definition of the details or cutoff value. Patients with early-stage NSCLC with a tumour size ≤ 2.0 cm were chosen from the SEER database. The influence of confounding factors was minimized by 1:1 propensity score matching (PSM). Kaplan‒Meier curves and Cox proportional hazards models were used to evaluate the overall survival (OS) and lung cancer-specific survival (LCSS) of patients undergoing lobectomy and wedge resection. A total of 3891 patients with early-stage NSCLC with tumour size ≤ 2.0 cm were enrolled, of whom 2839 underwent lobectomy and 1052 underwent wedge resection. Both before and after PSM, lobectomy significantly improved OS and LCSS compared with wedge resection in the unstratified study population. In the tumour size ≤ 1 cm group, lobectomy had better OS and LCSS than wedge resection (P < 0.05) before PSM; after PSM, there was no significant difference in OS (P = 0.16) and LCSS (P = 0.17). In Grade I patients, before PSM, lobectomy was superior to wedge resection in LCSS (P = 0.038), while there was no significant difference in OS (P = 0.16); after PSM, there were no significant differences in either OS (P = 0.78) or LCSS (P = 0.11). For early-stage NSCLC patients with a tumour size ≤ 1 cm or with a tumour size ≤ 2 cm and with Grade I, there was no significant difference in survival between wedge resection and lobectomy.

Dedifferentiated liposarcoma of the extremities: a Korean multi-center study of 107 cases.

BACKGROUND: Dedifferentiated liposarcoma of the extremities (DDL-E) is rare in comparison to that of the retroperitoneum. Its clinical features and surgical principle for resection margins at the dedifferentiated and the well-differentiated components are yet to be elucidated. METHODS: This retrospective multi-center study examined patients diagnosed with DDL-E from August 2004 to May 2023 at 5 sarcoma centers. Clinical features, oncologic outcomes, and prognostic factors were analyzed. RESULTS: A total of 107 patients were reviewed. The 5-year local recurrence free survival (LRFS), metastasis-free survival (MFS) and disease specific survival (DSS) were 84.7%, 78.6%, and 87.8%, respectively. Other primary malignancies and extrapulmonary metastasis were observed in 27 and 4 patients, respectively. The independent risk factor for local recurrence was R1/2 margin at the dedifferentiated component of the tumor. Metastasis was associated with tumor size in univariate analysis. The independent risk factor for DSS was tumor grade. Previous unplanned excision, de novo presentation, tumor depth, absence of the well-differentiated component, infiltrative border, R1/2 margin at the well-differentiated component were not associated with oncologic outcomes. CONCLUSIONS: This is the largest study examining DDL-E to-date. Localized DDL-E has low potential for metastasis and carries an excellent prognosis. Other primary malignancy and extrapulmonary metastasis are more frequent in DDL-E, thus close monitoring of other sites during follow-up is recommended. While wide resection margin is the standard surgical approach for DDL-E, further investigation into moderated wide resection margin at the well-differentiated component is warranted.

Role of Surgery in Potentially Resectable Small-Cell Lung Cancer Based on the Eighth Edition of the TNM Classification: A Population Study of the US SEER Database.

BACKGROUND: This study aimed to identify a specific SCLC population that would benefit from surgery. METHODS: This study utilized patient data retrieved from the Surveillance, Epidemiology, and End Results (SEER) database spanning 2010 to 2017. To mitigate clinical biases, the propensity score matching (PSM) technique was employed. Separate cohorts were aligned using PSM according to the AJCC 8th edition TNM classification. The Kaplan-Meier method and a competing risk model were applied to evaluate overall survival (OS) and lung cancer-specific survival (LCSS), respectively. OUTCOMES: Among the 3394 patients with potentially resectable SCLC included in the study, 3062 underwent chemoradiotherapy and 332 underwent surgical treatment with adjuvant chemotherapy. Surgery was associated with better OS (median OS: 49 months; 95% CI: 35-63 months vs. 27 months; 95% CI: 21-33 months, p < 0.001) and LCSS (SHR, 0.578; 95% CI: 0.411-0.815, p < 0.001) in stage I patients after PSM. However, there was no significant difference in OS and LCSS between the surgery and nonsurgery groups in stage II and III patients after PSM. In the entire cohort, lobectomy was associated with improved OS (median OS: 48.6 vs. 28.7 months, p < 0.0001), but not LCSS (SHR, 0.696; 95% CI: 0.466-1.040, p = 0.078) compared with sublobar resection after PSM. CONCLUSION: Surgery with adjuvant chemotherapy significantly improved the survival prognosis of patients with early-stage SCLC. However, surgical treatment should be carefully considered in patients with stage II/III disease. Lobectomy is oncologically equal to sublobar resection.

Retrospective Analysis of Radiofrequency Ablation in Patients with Small Solitary Hepatocellular Carcinoma: Survival Outcomes and Development of a Machine Learning Prognostic Model.

BACKGROUND AND OBJECTIVE: The effectiveness of radiofrequency ablation (RFA) in improving long-term survival outcomes for patients with a solitary hepatocellular carcinoma (HCC) measuring 5 cm or less remains uncertain. This study was designed to elucidate the impact of RFA therapy on the survival outcomes of these patients and to construct a prognostic model for patients following RFA. METHODS: This study was performed using the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2017, focusing on patients diagnosed with a solitary HCC lesion ≤5 cm in size. We compared the overall survival (OS) and cancer-specific survival (CSS) rates of these patients with those of patients who received hepatectomy, radiotherapy, or chemotherapy or who were part of a blank control group. To enhance the reliability of our findings, we employed stabilized inverse probability treatment weighting (sIPTW) and stratified analyses. Additionally, we conducted a Cox regression analysis to identify prognostic factors. XGBoost models were developed to predict 1-, 3-, and 5-year CSS. The XGBoost models were evaluated via receiver operating characteristic (ROC) curves, calibration plots, decision curve analysis (DCA) curves and so on. RESULTS: Regardless of whether the data were unadjusted or adjusted for the use of sIPTWs, the 5-year OS (46.7%) and CSS (58.9%) rates were greater in the RFA group than in the radiotherapy (27.1%/35.8%), chemotherapy (32.9%/43.7%), and blank control (18.6%/30.7%) groups, but these rates were lower than those in the hepatectomy group (69.4%/78.9%). Stratified analysis based on age and cirrhosis status revealed that RFA and hepatectomy yielded similar OS and CSS outcomes for patients with cirrhosis aged over 65 years. Age, race, marital status, grade, cirrhosis status, tumor size, and AFP level were selected to construct the XGBoost models based on the training cohort. The areas under the curve (AUCs) for 1, 3, and 5 years in the validation cohort were 0.88, 0.81, and 0.79, respectively. Calibration plots further demonstrated the consistency between the predicted and actual values in both the training and validation cohorts. CONCLUSION: RFA can improve the survival of patients diagnosed with a solitary HCC lesion ≤5 cm. In certain clinical scenarios, RFA achieves survival outcomes comparable to those of hepatectomy. The XGBoost models developed in this study performed admirably in predicting the CSS of patients with solitary HCC tumors smaller than 5 cm following RFA.

Development and validation of a nomogram to predict cancer-specific survival of patients with large hepatocellular carcinoma accepting surgical resection: a real-world analysis based on the SEER database.

Background: Only a small percentage of patients with large hepatocellular carcinoma (HCC) can undergo surgical resection (SR) therapy while the prognosis of patients with large HCC is poor. However, innovations in surgical techniques have expanded the scope of surgical interventions accessible to patients with large HCC. Currently, most of the existing nomograms are focused on patients with large HCC, and research on patients who undergo surgery is limited. This study aimed to establish a nomogram to predict cancer-specific survival (CSS) in patients with large HCC who will undergo SR. Methods: The study retrieved data from the Surveillance, Epidemiology, and End Results (SEER) database encompassing patients with HCC between 2010 and 2015. Patients with large HCC accepting SR were eligible participants. Patients were randomly divided into the training (70%) and internal validation (30%) groups. Patients from Air Force Medical Center between 2012 and 2019 who met the inclusion and exclusion criteria were used as external datasets. Demographic information such as sex, age, race, etc. and clinical characteristics such as chemotherapy, histological grade, fibrosis score, etc. were analyzed. CSS was the primary endpoint. All-subset regression and Cox regression were used to determine the relevant variables required for constructing the nomogram. Decision curve analysis (DCA) was used to evaluate the clinical utility of the nomogram. The area under the receiver operating characteristic curve (AUC) and calibration curve were used to validate the nomogram. The Kaplan-Meier curve was used to assess the CSS of patients with HCC in different risk groups. Results: In total, 1,209 eligible patients from SEER database and 21 eligible patients from Air Force Medical Center were included. Most patients were male and accepted surgery to lymph node. The independent prognostic factors included sex, histological grade, T stage, chemotherapy, α-fetoprotein (AFP) level, and vascular invasion. The CSS rate for training cohort at 12, 24, and 36 months were 0.726, 0.731, and 0.725 respectively. The CSS rate for internal validation cohort at 12, 24, and 36 months were 0.785, 0.752, and 0.734 respectively. The CSS rate for external validation cohort at 12, 24, and 36 months were 0.937, 0.929, and 0.913 respectively. The calibration curve demonstrated good consistency between the newly established nomogram and real-world observations. The Kaplan-Meier curve showed significantly unfavorable CSS in the high-risk group (P<0.001). DCA demonstrated favorable clinical applicability of the nomogram. Conclusions: The nomogram constructed based on sex, histological grade, T stage, chemotherapy and AFP levels can predict the CSS in patients with large HCC accepting SR, which may aid in clinical decision-making and treatment.

No sex-dependent mortality in an amphibian upon infection with the chytrid fungus, Batrachochytrium dendrobatidis.

One of the major factors driving the currently ongoing biodiversity crisis is the anthropogenic spread of infectious diseases. Diseases can have conspicuous consequences, such as mass mortality events, but may also exert covert but similarly severe effects, such as sex ratio distortion via sex-biased mortality. Chytridiomycosis, caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd) is among the most important threats to amphibian biodiversity. Yet, whether Bd infection can skew sex ratios in amphibians is currently unknown, although such a hidden effect may cause the already dwindling amphibian populations to collapse. To investigate this possibility, we collected common toad (Bufo bufo) tadpoles from a natural habitat in Hungary and continuously treated them until metamorphosis with sterile Bd culture medium (control), or a liquid culture of a Hungarian or a Spanish Bd isolate. Bd prevalence was high in animals that died during the experiment but was almost zero in individuals that survived until the end of the experiment. Both Bd treatments significantly reduced survival after metamorphosis, but we did not observe sex-dependent mortality in either treatment. However, a small number of genotypically female individuals developed male phenotype (testes) in the Spanish Bd isolate treatment. Therefore, future research is needed to ascertain if larval Bd infection can affect sex ratio in common toads through female-to-male sex reversal.

The potential benefits of concomitant statins treatment in patients with non-muscle-invasive bladder cancer.

OBJECTIVE: To investigate the influence of statins on the survival outcomes of patients with non-muscle-invasive bladder cancer (NMIBC) treated with adjuvant intravesical bacille Calmette-Guérin (BCG) immunotherapy. PATIENTS AND METHODS: A retrospective cohort of consecutive patients with NMIBC who received intravesical BCG therapy from 2001 to 2020 and statins prescription were identified. Overall survival (OS), cancer-specific survival (CSS), recurrence-free survival (RFS), and progression-free survival (PFS) were analysed between the Statins Group vs No-Statins Group using Kaplan-Meier method and multivariable Cox regression. RESULTS: A total of 2602 patients with NMIBC who received intravesical BCG were identified. The median follow-up was 11.0 years. On Kaplan-Meier analysis, the Statins Group had significant better OS (P < 0.001), CSS (P < 0.001), and PFS (P < 0.001). Subgroup analysis indicated statins treatment started before BCG treatment had better CSS (P = 0.02) and PFS (P < 0.01). Upon multivariable Cox regression analysis, the 'statins before BCG' group was an independent protective factor for OS (hazard ratio [HR] 0.607, 95% confidence interval [CI] 0.514-0.716), and CSS (HR 0.571, 95% CI 0.376-0.868), but not RFS (HR 0.885, 95% CI 0.736-1.065), and PFS (HR 0.689, 95% CI 0.469-1.013). CONCLUSIONS: Statins treatment appears to offer protective effects on OS and CSS for patients with NMIBC receiving adjuvant intravesical BCG.

Paraneoplastic Syndrome Prevalence and Survival in Racially-Diverse Cohort With Renal Cell Carcinoma.

INTRODUCTION: The prevalence of preoperative paraneoplastic syndromes (PNS) in renal cell carcinoma (RCC) is poorly understood. Many laboratory abnormalities representative of PNS have demonstrated prognostic value when incorporated into predictive survival models in RCC. We sought to characterize the relationship between baseline prevalence of PNS with overall survival (OS) and cancer-specific survival (CSS) in RCC patients following nephrectomy. METHODS: Our prospectively maintained nephrectomy database was retrospectively reviewed for any stage, major histology RCC patients that underwent surgery from 2000 to 2022. Baseline laboratory values within 90 days (closest used) were required. Presence of PNS was defined according to established laboratory cutoffs. Kaplan-Meier curves estimated survival rates, and multivariable Cox proportional hazards models examined the association between PNS with OS and CSS following nephrectomy. RESULTS: 2599 patients were included with listed staging: 1494 Stage I; 180 Stage II; 616 Stage III; 306 Stage IV. Proportion of patients presenting with >1 PNS significantly increased from stage I (31.3%) to stage IV (74.2%) RCC (P < .001). Elevated C-reactive protein was the most prevalent PNS (45.4%). On multivariable analysis, the presence of >1 PNS was associated with higher risk of all-cause (HR 2.09; P < .001) and cancer-specific mortality (HR 2.55; P < .001). The 10-year OS estimates as reported: 65.2% (no PNS), 52.3% (1 PNS), 36.6% (>1 PNS); and 10-year CSS estimates: 88.3% (no PNS), 79.3% (1 PNS), 61.6% (>1 PNS). DISCUSSION: Increased prevalence of PNS in major histology RCC was associated with a significant increase in the risk of all-cause and cancer-specific mortality even when accounting for patient and disease characteristics.

Application of Survival Quilts for prognosis prediction of gastrectomy patients based on the Surveillance, Epidemiology, and End Results database and China National Cancer Center Gastric Cancer database.

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.

An ensemble learning model for predicting cancer-specific survival of muscle-invasive bladder cancer patients undergoing bladder preservation therapy.

Background: More muscle-invasive bladder cancer (MIBC) patients are now eligible for bladder-preserving therapy (BPT), underscoring the need for precision medicine. This study aimed to identify prognostic predictors and construct a predictive model among MIBC patients who undergo BPT. Methods: Data relating to MIBC patients were obtained from the Surveillance, Epidemiology and End Results (SEER) database from 2004 to 2016. Eleven features were included to establish multiple models. The predictive effectiveness was assessed using receiver operating characteristic (ROC) curves, calibration plots, decision curve analysis (DCA) and clinical impact curve (CIC). SHapley Additive exPlanations (SHAP) were used to explain the impact of features on the predicted targets. Results: The ROC showed that Catboost and Random Forest (RF) obtained better predictive discrimination in both 3- and 5-year models [test set area under curves (AUC) =0.80 and 0.83, respectively]. Furthermore, Catboost showed better performance in calibration plots, DCA and CIC. SHAP analysis indicated that age, M stage, tumor size, chemotherapy, T stage and gender were the most important features in the model for predicting the 3-year cancer-specific survival (CSS). In contrast, M stage, age, tumor size and gender as well as the N and T stages were the most important features for predicting the 5-year CSS. Conclusions: The Catboost model exhibits the highest predictive performance and clinical utility, potentially aiding clinicians in making optimal individualized decisions for MIBC patients with BPT.