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1.
ESMO Open ; 7(3): 100510, 2022 06.
Artículo en Inglés | MEDLINE | ID: mdl-35714477

RESUMEN

BACKGROUND: To date, the efficacy of the androgen receptor inhibitors enzalutamide and apalutamide for the treatment of nonmetastatic castration-resistant prostate cancer (nmCRPC) has not been compared directly in a clinical trial setting. Indirect comparisons can be used to assess relative efficacy and provide important information to guide treatment decisions. PROSPER and SPARTAN were double-blind, randomized, placebo-controlled, phase III trials in patients with nmCRPC with overall similar study designs and inclusion and exclusion criteria. Using an anchored matching-adjusted indirect comparison, based on the final data from the PROSPER and SPARTAN studies, we assessed the comparative efficacy of enzalutamide and apalutamide, both plus androgen deprivation therapy. METHODS: Using placebo as the common comparator, individual patient data from PROSPER were matched to the aggregate patient data from SPARTAN and efficacy endpoints from PROSPER were re-weighted accordingly. Patient baseline characteristics and endpoints were clinically and statistically tested to identify potential effect modifiers, according to National Institute for Health and Care Excellence guidelines. Hazard ratios for overall survival (OS), metastasis-free survival (MFS), and time to chemotherapy (TTCx) were re-estimated for PROSPER using weighted Cox proportional hazards models and indirectly compared with those of SPARTAN using a Bayesian network meta-analysis. RESULTS: Estimated hazard ratios [95% credible interval (CrI)] for enzalutamide versus apalutamide were 0.80 (95% CrI 0.58-1.10) for OS, 0.94 (95% CrI 0.69-1.29) for MFS2, and 0.90 (95% CrI 0.63-1.29) for TTCx. Similar results were seen for sensitivity analyses conducted for OS and MFS. Bayesian probability analyses showed a 91.7% favoring enzalutamide for OS, 65.1% for MFS, and 71.4% for TTCx. CONCLUSIONS: The results of this matching-adjusted indirect comparison of final data from PROSPER and SPARTAN indicate comparable efficacy of enzalutamide and apalutamide with potentially a greater probability of longer MFS, OS, and TTCx in patients with nmCRPC treated with enzalutamide versus apalutamide.


Asunto(s)
Neoplasias de la Próstata Resistentes a la Castración , Antagonistas de Andrógenos/uso terapéutico , Teorema de Bayes , Benzamidas , Ensayos Clínicos Fase III como Asunto , Humanos , Masculino , Nitrilos , Feniltiohidantoína , Neoplasias de la Próstata Resistentes a la Castración/tratamiento farmacológico , Neoplasias de la Próstata Resistentes a la Castración/patología , Ensayos Clínicos Controlados Aleatorios como Asunto , Tiohidantoínas , Resultado del Tratamiento
2.
J Digit Imaging ; 25(6): 782-91, 2012 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-22274942

RESUMEN

This paper presents an adaptive denoising approach aiming to improve the visibility and detectability of hemorrhage from brain computed tomography (CT) images. The suggested approach fuses the images denoised by total variation (TV) method, denoised by curvelet-based method, and edge information extracted from the noise residue of TV method. The edge information is extracted from the noise residue of TV method by processing it through curvelet transform. The visual interpretation shows that the proposed approach not only reduces the staircase effect caused by total variation method but also reduces visual distortion induced by curvelet transform in the homogeneous areas of the CT images. The denoising abilities of the proposed method are further evaluated by segmenting the hemorrhagic brain area using region-growing method. The sensitivity, specificity, Jaccard index, and Dice coefficients were calculated for different noise levels. The comparative results show that the significant improvement has yielded in the brain hemorrhage detection from CT images after denoising it with the proposed approach.


Asunto(s)
Hemorragia Cerebral/diagnóstico por imagen , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Tomografía Computarizada por Rayos X/métodos , Algoritmos , Humanos , Sensibilidad y Especificidad
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