Conditional survival analysis and dynamic survival prediction for intracranial solitary-fibrous tumor/hemangiopericytoma.

BACKGROUND: As the form of World Health Organization Central Nervous System (WHO CNS) tumor classifications is updated, there is a lack of research on outcomes for intracranial combined solitary-fibrous tumor and hemangiopericytoma (SFT/HPC). This study aimed to explore conditional survival (CS) pattern and develop a survival prediction tool for intracranial SFT/HPC patients. METHODS: Data of intracranial SFT/HPC patients was gathered from the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute. The patients were split into training and validation groups at a 7:3 ratio for our analysis. CS is defined as the likelihood of surviving for a specified period of time (y years), given that the patient has survived x years after initial diagnosis. Then, we used this definition of CS to analyze the intracranial SFT/HPC patients. The least absolute shrinkage and selection operator (LASSO) regression and best subset regression (BSR) were employed to identify predictive factors. The Multivariate Cox regression analysis was applied to establish a novel CS-based nomogram, and a risk stratification system was developed using this model. RESULTS: From the SEER database, 401 patients who were diagnosed with intracranial SFT/HPC between 2000 and 2019 were identified. Among them, 280 were included in the training group and 121 were included in the internal validation group for analysis. Our study revealed that in intracranial SFT/HPC, 5-year survival rates saw significant improvement ranging from 78% at initial diagnosis to rates of 83%, 87%, 90%, and 95% with each successive year after surviving for 1-4 years. The LASSO regression and BSR identified patient age, tumor behavior, surgery and radiotherapy as predictors of CS-based nomogram development. A risk stratification system was also successfully constructed to facilitate the identification of high-risk patients. CONCLUSION: The CS pattern of intracranial SFT/HPC patients was outlined, revealing a notable improvement in 5-year survival rates after an added period of survival. Our newly-established CS-based nomogram and risk stratification system can provide a real-time dynamic survival estimation and facilitate the identification of high-risk patients, allowing clinicians to better guide treatment decision for these patients.

Nomogram Model for Predicting the Overall Survival of Patients With Meningiomas: a Retrospective Cohort Study.

OBJECTIVE: To identify the significant prognostic factors of overall survival (OS) for patients living with meningiomas (MMs), and establish a novel graphical nomogram and an online dynamic nomogram. METHODS: Patients diagnosed with MMs were identified retrospectively from the SEER database. The cohort was split into training (70%) and test (30%) groups randomly. Univariable and multivariable Cox models were successively used to screen the significant prognostic factors. Subsequently, the independent predictors were used as items to establish the graphic and dynamic nomogram model. To assess the accuracy of the model, a calibration curve was plotted. To assess the discrimination performance, C-index and time-dependent area under the receiver operator characteristic curve (AUC) were selected. Additionally, the decision curve was generated to evaluate the clinical net benefit of the model. RESULTS: A total of 899 patients were involved, of which 629 and 270 were split into training group and test group, respectively. Age, sex, radiotherapy, tumor size, and tumor histology were identified as the significant prognostic factors. Based on these factors, a graphical nomogram and online nomogram (Web site: https://helloshinyweb.shinyapps.io/dynamic_nomogram/) were developed. The calibration curve showed favorable consistence between predicted and actual survival rate. C-index and time-dependent AUC showed good discrimination ability, and the decision curve analysis showed positive net benefit of the model in clinical practice. CONCLUSIONS: Age of diagnosis, sex, tumor size, tumor histology, and radiotherapy were independent predictors for OS, while extent of resection had a borderline significant. A nomogram model was successfully developed and validated to dynamically predict the long-term OS for MM patients, expecting to help neurosurgeons optimize clinical management and treatment strategies.

A systematic review on ethnomedicines of anti-cancer plants.

Cancer is a serious health problem and the second leading cause of death around the globe. Present review is an attempt to provide utmost information based on ethno-pharmacological and toxicological aspects of anti-cancer plants of the world. A total of 276 articles published in English journals and containing maximum ethnomedicinal information were reviewed using several data sources such as; Google scholar, Web of Science, Scopus, PubMed and floras of different countries. A total of 199 anti-cancer plants were recorded in present review and results indicated that traditional medicines are mostly being use in developing countries for cancer treatment. Traditionally and scientifically skin and breast cancer types gained more focus. Seventy plants were reportedly analyzed for in-vitro activities while 32 plants were having in-vivo reports. Twenty nine pure compounds (mostly phenolic) were reportedly isolated from anti-cancer plants and tested against different cancer cell lines. Inspite having better efficiency of ethnomedicines as compared to synthetic drugs, several plants have also shown toxic effects on living system. Therefore, we invite researchers attention to carry out detailed ethno-pharmacological and toxicological studies on un-explored anti-cancer plants in order to provide reliable knowledge to the patients and develop novel anti-cancer drugs. Copyright © 2017 John Wiley & Sons, Ltd.

Adsorptive Removal of Toxic Chromium from Waste-Water Using Wheat Straw and Eupatorium adenophorum.

Environmental pollution with heavy metals is a serious issue worldwide posing threats to humans, animals and plants and to the stability of overall ecosystem. Chromium (Cr) is one of most hazardous heavy metals with a high carcinogenic and recalcitrant nature. Aim of the present study was to select low-cost biosorbent using wheat straw and Eupatorium adenophorum through simple carbonization process, capable of removing Cr (VI) efficiently from wastewater. From studied plants a low cost adsorbent was prepared for removing Cr (VI) from aqueous solution following very simple carbonization method excluding activation process. Several factors such as pH, contact time, sorbent dosage and temperature were investigated for attaining ideal condition. For analysis of adsorption equilibrium isotherm data, Langmuir, Freundlich and Temkin models were used while pseudo-first-order, pseudo-second-order, external diffusion and intra-particle diffusion models were used for the analysis of kinetic data. The obtained results revealed that 99.9% of Cr (VI) removal was observed in the solution with a pH of 1.0. Among all the tested models Langmuir model fitted more closely according to the data obtained. Increase in adsorption capacity was observed with increasing temperature revealing endothermic nature of Cr (VI). The maximum Cr (VI) adsorption potential of E. adenophorum and wheat straw was 89.22 mg per 1 gram adsorbent at 308K. Kinetic data of absorption precisely followed pseudo-second-order model. Present study revealed highest potential of E. adenophorum and wheat straw for producing low cost adsorbent and to remove Cr (VI) from contaminated water.