Molecularly targeted therapy based on tumour molecular profiling versus conventional therapy for advanced cancer (SHIVA): a multicentre, open-label, proof-of-concept, randomised, controlled phase 2…

By C. Le tourneau, J. Delord, A. Gonçalves, C. Gavoille, C. Dubot, N. Isambert, Mario Campone, O. Trédan, M. Massiani, C. Mauborgne and 13 more. The Lancet Oncology, 2015

959 citations recorded by the source corpus.

Subfields: Molecular Biology, Oncology, Pulmonary and Respiratory Medicine

View Paper: https://www.semanticscholar.org/paper/322218c1dfa41f76f9710129ba8ae645e1341e16

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In Oncology

Citations in the corpus

Current Challenges in Cancer Treatment. (2016, background): “The recently reported, histology-agnostic, French SHIVA (A Randomized Proof-of-Concept Phase II Trial Comparing Therapy Based on Tumor Molecular Profiling Versus Conventional Therapy in Patients With Refractory Cancer) study is one example of these trials.(46) Finally, another different strategy to ”
Recommendations for the use of next-generation sequencing (NGS) for patients with metastatic cancers: A report from the ESMO Precision Medicine Working Group. (2020, background): “In the SHIVA trial, the use of multigene sequencing did not improve outcome in patients with metastatic hard-to-treat cancers in comparison with unmatched therapies.(5) In the singlearm MOSCATO trial, the use of multigene sequencing and comparative genomic hybridisation (CGH) arrays was associated w”
Precision Oncology: The Road Ahead (2017, methodology): “For example, the MOSCATO 01 trial [44] that used only lastgeneration drugs with high affinity to a specific target, achieved positive results, whereas the SHIVA study [45], which heavily relied on everolismus -- a drug weakly affecting the Senft et al.”
4th ESO–ESMO International Consensus Guidelines for Advanced Breast Cancer (ABC 4)† (2018, background): “SAFIR and SHIVA trials) that using a multigene panel improves outcome of patients [54, 55].”
ARTIFICIAL INTELLIGENCE AND PERSONALIZED MEDICINE (2019, background): “[74] Third, it may be that the best way to vet at least decision support tools, is not to test them in randomized clinical trials, but rather to implement them in learning systems in which the decision support rules or algorithms are continuously updated.”