Health-related quality-of-life outcomes in patients with advanced renal cell carcinoma treated with lenvatinib plus pembrolizumab or everolimus versus sunitinib (CLEAR): a randomised, phase 3 study

Motzer, Robert J.; Porta, Camillo; Alekseev, B. Ya.; Rha, Sun Young; Choueiri, Toni K.; Mendez-Vidal, María José; Hong, Sung‐Hoo; Kapoor, Anil; Goh, Jeffrey C.; Eto, Masatoshi; Bennett, Lee; Wang, J.; Pan, Jie Janice; Saretsky, T.; Perini, Rodolfo F.; He, Cixin; Mody, Kalgi; Cella, David

doi:10.17650/1726-9776-2022-18-2-39-57

Cited by 4 publications

(4 citation statements)

References 23 publications

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“…Comparative evaluation of various models in the training and validation cohorts. surgery (29,30). Therefore, accurate prediction of patient prognosis and risk of RCC patients is an urgent problem.…”

Section: Discussionmentioning

confidence: 99%

Incremental value of radiomics with machine learning to the existing prognostic models for predicting outcome in renal cell carcinoma

et al. 2023

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PurposeTo systematically evaluate the potential of radiomics coupled with machine-learning algorithms to improve the predictive power for overall survival (OS) of renal cell carcinoma (RCC).MethodsA total of 689 RCC patients (281 in the training cohort, 225 in the validation cohort 1 and 183 in the validation cohort 2) who underwent preoperative contrast-enhanced CT and surgical treatment were recruited from three independent databases and one institution. 851 radiomics features were screened using machine-learning algorithm, including Random Forest and Lasso-COX Regression, to establish radiomics signature. The clinical and radiomics nomogram were built by multivariate COX regression. The models were further assessed by Time-dependent receiver operator characteristic, concordance index, calibration curve, clinical impact curve and decision curve analysis.ResultThe radiomics signature comprised 11 prognosis-related features and was significantly correlated with OS in the training and two validation cohorts (Hazard Ratios: 2.718 (2.246,3.291)). Based on radiomics signature, WHOISUP, SSIGN, TNM Stage and clinical score, the radiomics nomogram has been developed. Compared with the existing prognostic models, the AUCs of 5 years OS prediction of the radiomics nomogram were superior to the TNM, WHOISUP and SSIGN model in the training cohort (0.841 vs 0.734, 0.707, 0.644) and validation cohort2 (0.917 vs 0.707, 0.773, 0.771). Stratification analysis suggested that the sensitivity of some drugs and pathways in cancer were observed different for RCC patients with high-and low-radiomics scores.ConclusionThis study showed the application of contrast-enhanced CT-based radiomics in RCC patients, creating novel radiomics nomogram that could be used to predict OS. Radiomics provided incremental prognostic value to the existing models and significantly improved the predictive power. The radiomics nomogram might be helpful for clinicians to evaluate the benefit of surgery or adjuvant therapy and make individualized therapeutic regimens for patients with renal cell carcinoma.

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Section: Discussionmentioning

confidence: 99%

Incremental value of radiomics with machine learning to the existing prognostic models for predicting outcome in renal cell carcinoma

et al. 2023

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“…В CLEAR в большинстве случаев пациенты уходили с терапии сунитинибом на иммунотерапию, более половины в группе ленватиниба с пембролизумабом -на антиангиогенную терапию, что оказало влияние на результаты. Не отмечено новых сигналов безопасности, связанных с лечением [1,14,15]. Подгрупповой анализ качества жизни (КЖ) пациентов продемонстрировал лучшую переносимость комбинации ленватиниба с пембролизумабом в сравнении с монотерапией сунитинибом, по показателям КЖ, связанного со здоровьем (Health-Related Quality of Life, HRQoL), а также по симптомам заболевания [14].…”

Section: ленватиниб в сочетании с пембролизумабом показали очень высо...unclassified

“…Не отмечено новых сигналов безопасности, связанных с лечением [1,14,15]. Подгрупповой анализ качества жизни (КЖ) пациентов продемонстрировал лучшую переносимость комбинации ленватиниба с пембролизумабом в сравнении с монотерапией сунитинибом, по показателям КЖ, связанного со здоровьем (Health-Related Quality of Life, HRQoL), а также по симптомам заболевания [14]. Сетевой метаанализ P. Lombardi и соавт.…”

Section: ленватиниб в сочетании с пембролизумабом показали очень высо...unclassified

Modern possibilities of first-line therapy for advanced renal cell carcinoma: resolution based on the expert council's findings

Anzhiganova¹,

Бакланова²,

Варламов³

et al. 2023

Voprosy Onkologii

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Представлены результаты заседания Регионального Совета экспертов Сибири и Дальнего Востока в нозологии почечно-клеточный рак, состоявшегося 20 мая 2022 г. в Новосибирске с целью согласования тактики ведения пациентов при системной терапии распространенного ПКР (рПКР), обсуждения клинического опыта применения комбинаций иммунотаргетных режимов, получения экспертного мнения относительно результатов исследования применения ленватиниба в комбинации с пембролизумабом у пациентов с рПКР. В задачах Совета было обсуждение различий подходов к лечению на основе клинических рекомендаций и реальной практики, возможностей обеспечения региональных пациентов современными опциями комбинированной терапии 1-й линии, специфики маршрутизации данной когорты больных. Повестка включала поиск портрета пациента, назначение которому комбинированной иммунотаргетной терапии ленватиниба с пембролизумабом окажет максимальный эффект с возможностью контроля токсичности. Одними из существенных оказались вопросы фармакоэкономики и пути их решения.

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“…Tedesco-Silva, H. et al compared the efficacy of everolimus and low-dose calcineurin inhibitor with standard therapy (calcineurin inhibitor and mycophenolic acid) and found that the incidence of cytomegalovirus (CMV) infection decreased significantly in patients treated with everolimus (258). Moreover, sirolimus also prevents CMV recurrence in CMV-positive kidney transplant recipients (259). Hence, mTOR inhibitor is an effective and safe therapeutic strategy in organ transplant.…”

Section: Mtor Inhibitors In Organ Transplantmentioning

confidence: 99%

Advances in the regulatory mechanisms of mTOR in necroptosis

Xie,

Zhao,

Lei

et al. 2023

Front. Immunol.

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The mammalian target of rapamycin (mTOR), an evolutionarily highly conserved serine/threonine protein kinase, plays a prominent role in controlling gene expression, metabolism, and cell death. Programmed cell death (PCD) is indispensable for maintaining homeostasis by removing senescent, defective, or malignant cells. Necroptosis, a type of PCD, relies on the interplay between receptor-interacting serine-threonine kinases (RIPKs) and the membrane perforation by mixed lineage kinase domain-like protein (MLKL), which is distinguished from apoptosis. With the development of necroptosis-regulating mechanisms, the importance of mTOR in the complex network of intersecting signaling pathways that govern the process has become more evident. mTOR is directly responsible for the regulation of RIPKs. Autophagy is an indirect mechanism by which mTOR regulates the removal and interaction of RIPKs. Another necroptosis trigger is reactive oxygen species (ROS) produced by oxidative stress; mTOR regulates necroptosis by exploiting ROS. Considering the intricacy of the signal network, it is reasonable to assume that mTOR exerts a bifacial effect on necroptosis. However, additional research is necessary to elucidate the underlying mechanisms. In this review, we summarized the mechanisms underlying mTOR activation and necroptosis and highlighted the signaling pathway through which mTOR regulates necroptosis. The development of therapeutic targets for various diseases has been greatly advanced by the expanding knowledge of how mTOR regulates necroptosis.

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Health-related quality-of-life outcomes in patients with advanced renal cell carcinoma treated with lenvatinib plus pembrolizumab or everolimus versus sunitinib (CLEAR): a randomised, phase 3 study

Abstract: .

Cited by 4 publications

References 23 publications

Incremental value of radiomics with machine learning to the existing prognostic models for predicting outcome in renal cell carcinoma

Incremental value of radiomics with machine learning to the existing prognostic models for predicting outcome in renal cell carcinoma

Modern possibilities of first-line therapy for advanced renal cell carcinoma: resolution based on the expert council's findings

Advances in the regulatory mechanisms of mTOR in necroptosis

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