Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Objective:To reveal the coupling mechanism of beam temporal profile and tissue oxygen content on radical kinetics, further explain the potential biological basis of the FLASH effect, and provide a reference for beam optimization and treatment planning design of FLASH radiotherapy (FLASH-RT).Methods:TOPAS-nBio v3.0 was used to simulate the physical and chemical processes of electron beams in water, and a full-scale kinetic model was established covering the generation, diffusion, reaction, and quenching of free radicals such as hydroxyl radical (·OH) and hydrated electrons (e aq-). Under different beam temporal profiles (single pulse, multi-pulses, continuous wave irradiation) and different oxygen concentration conditions, the evolution dynamics of free radicals were systematically simulated. At the same time, the data on e aq- content were obtained by experimental measurement of laser absorption spectroscopy to verify the accuracy of the model prediction. Results:The changing trend of e aq- concentration measured in the experiment was highly consistent with the simulation result, verifying the reliability of the constructed model. The beam time structure had a significant impact on the peak value and duration of free radical concentration. The single-pulse structure can cause the free radicals to rapidly increase and then quickly quench in a short time, while the continuous or long-pulse structure can cause the radical concentration to remain at a high level for a long time. The evolution of ·OH was not sensitive to the oxygen environment, while e aq- are greatly affected by the oxygen environment. The scavenging efficiency of free radicals in a hypoxic environment was significantly decreased, leading to an enhanced accumulation of oxidative damage to biological macromolecules. The lifespan of e aq- in an oxygen-rich environment decreased rapidly. Conclusions:Radical kinetics are regulated by both the beam temporal profile and oxygen content. FLASH-RT can utilize single-pulse or multi-pulses intervals to form periodic windows, reducing normal tissue damage by efficiently scavenging free radicals through antioxidants, while free radicals in tumor tissues continuously accumulate and amplify damage, thus generating a selective protective effect.

Objective:To reveal the coupling mechanism of beam temporal profile and tissue oxygen content on radical kinetics, further explain the potential biological basis of the FLASH effect, and provide a reference for beam optimization and treatment planning design of FLASH radiotherapy (FLASH-RT).Methods:TOPAS-nBio v3.0 was used to simulate the physical and chemical processes of electron beams in water, and a full-scale kinetic model was established covering the generation, diffusion, reaction, and quenching of free radicals such as hydroxyl radical (·OH) and hydrated electrons (e aq-). Under different beam temporal profiles (single pulse, multi-pulses, continuous wave irradiation) and different oxygen concentration conditions, the evolution dynamics of free radicals were systematically simulated. At the same time, the data on e aq- content were obtained by experimental measurement of laser absorption spectroscopy to verify the accuracy of the model prediction. Results:The changing trend of e aq- concentration measured in the experiment was highly consistent with the simulation result, verifying the reliability of the constructed model. The beam time structure had a significant impact on the peak value and duration of free radical concentration. The single-pulse structure can cause the free radicals to rapidly increase and then quickly quench in a short time, while the continuous or long-pulse structure can cause the radical concentration to remain at a high level for a long time. The evolution of ·OH was not sensitive to the oxygen environment, while e aq- are greatly affected by the oxygen environment. The scavenging efficiency of free radicals in a hypoxic environment was significantly decreased, leading to an enhanced accumulation of oxidative damage to biological macromolecules. The lifespan of e aq- in an oxygen-rich environment decreased rapidly. Conclusions:Radical kinetics are regulated by both the beam temporal profile and oxygen content. FLASH-RT can utilize single-pulse or multi-pulses intervals to form periodic windows, reducing normal tissue damage by efficiently scavenging free radicals through antioxidants, while free radicals in tumor tissues continuously accumulate and amplify damage, thus generating a selective protective effect.