ReviewTargeted oncology2012
Designs and challenges for personalized medicine studies in oncology: focus on the SHIVA trial.
Review in Targeted oncology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 63 citations in OpenAlex.
- Randomised proof-of-concept phase II trial comparing targeted therapy based on tumour molecular profiling vs conventional therapy in patients with refractory cancer: results of the feasibility part of the SHIVA trial.British journal of cancer · 2014Trial
- The Growth Modulation Index (GMI) as an Efficacy Outcome in Cancer Clinical Trials: A Scoping Review with Suggested Reporting Guidelines.Current oncology reports · 2025Article
- Unveiling the Digital Evolution of Molecular Tumor Boards.Targeted oncology · 2025Review
- From Genomic Exploration to Personalized Treatment: Next-Generation Sequencing in Oncology.Current issues in molecular biology · 2024Review
- Antitumoral and Antimetastatic Activity by Mixed Chelate Copper(II) Compounds (CasiopeínasInternational journal of molecular sciences · 2024Article
- It Is in Our DNA: Bringing Electronic Health Records and Genomic Data Together for Precision Medicine.JMIR bioinformatics and biotechnology · 2024Article
- Statistical classification of treatment responses in mouse clinical trials for stratified medicine in oncology drug discovery.Scientific reports · 2024Article
- The Xiangya Ocular Tumor Bank: A Disease-Specific Biobank for Advancing Translational Research Into Ocular Tumors.Frontiers in medicine · 2021Article
- Insurance Coverage Policies for Pharmacogenomic and Multi-Gene Testing for Cancer.Journal of personalized medicine · 2018Article
- Molecular Tumor Boards: Ethical Issues in the New Era of Data Medicine.Science and engineering ethics · 2018Article
- Physician Experiences and Understanding of Genomic Sequencing in Oncology.Journal of genetic counseling · 2018Article
- Molecular Subtyping of Pancreatic Cancer: Translating Genomics and Transcriptomics into the Clinic.Journal of Cancer · 2017Review
- Future paradigms for precision oncology.Oncotarget · 2016Review
- New generation of breast cancer clinical trials implementing molecular profiling.Cancer biology & medicine · 2016Article
- Clinical Outcomes of Patients with Rare and Heavily Pretreated Solid Tumors Treated according to the Results of Tumor Molecular Profiling.BioMed research international · 2016Article
- Highlights from the 2016 WIN Symposium, 27-29 June 2016, Paris: personalised therapy beyond next-generation sequencing.Ecancermedicalscience · 2016Article
- Review
- Guidance for pharmacogenomic biomarker testing in labels of FDA-approved drugs.Genetics in medicine : official journal of the American College of Medical Genetics · 2015Article
- Optimal design of trials to demonstrate the utility of genomically-guided therapy: Putting Precision Cancer Medicine to the test.Molecular oncology · 2015Review
- Multi-factor data normalization enables the detection of copy number aberrations in amplicon sequencing data.Bioinformatics (Oxford, England) · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 7 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Personalized medicine is defined by the National Cancer Institute as "a form of medicine that uses information about a person's genes, proteins, and environment to prevent, diagnose, and treat disease." In oncology, the term "personalized medicine" arose with the emergence of molecularly targeted agents. The prescription of approved molecularly targeted agents to cancer patients currently relies on the primary tumor location and histological subtype. Predictive biomarkers of efficacy of these modern agents have been exclusively validated in specific tumor types. A major concern today is to determine whether the prescription of molecularly targeted therapies based on tumor molecular abnormalities, independently of primary tumor location and histology, would improve the outcome of cancer patients. This new paradigm requires prospective validation before being implemented in clinical practice. In this paper, we will first review different designs, including observational cohorts, as well as nonrandomized and randomized clinical trials, that have been recently proposed to evaluate the relevance of this approach, and further discuss their advantages and drawbacks. The design of the SHIVA trial, a randomized proof-of-concept phase II trial comparing therapy based on tumor molecular profiling versus conventional therapy in patients with refractory cancer will be detailed. Finally, we will discuss the multiple challenges associated with the implementation of personalized medicine in oncology, as well as perspectives for the future.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.