Trial reportAnnals of translational medicine2022
Challenges, opportunities, and innovative statistical designs for precision oncology trials.
Trial report in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Basket trials in oncology: a systematic review of practices and methods, comparative analysis of innovative methods, and an appraisal of a missed opportunity.Frontiers in oncology · 2023Pooled it
- Laboratory diagnostics in personalised medicine - 36th Symposium of the Croatian society of medical biochemistry and laboratory medicine.Biochemia medica · 2026Review
- Interleukin-1α (IL-1α) in pancreatic ductal adenocarcinoma: implications for immunotherapy and molecular biomarkers.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Article
- Clinical trials in otology and neurotology: state of the science.Frontiers in neurology · 2025Review
- A Strategy Utilizing Protein-Protein Interaction Hubs for the Treatment of Cancer Diseases.International journal of molecular sciences · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the era of precision oncology, improved understanding of tumor heterogeneity, particularly at the molecular level, has caused a shift from traditionally histology based cancer drug development to molecularly targeted drug development. The shift to the molecular view of cancer leads to increasingly small cancer populations for clinical trials which may be underpowered using traditional statistical designs. This paradigm shift lead to the recent developments of innovative clinical trial designs to address the challenges from precision oncology clinical trials. Hence, this paper reviewed and described innovative trial designs for precision oncology. Different strategies were discussed to account patient and treatment effect heterogeneity, including precision dose-finding designs that tailor the optimal dose to different patients at different time points, master protocol designs that match patients' molecular alterations with specific targeted agents, and adaptive enrichment designs that dynamically modify eligibility criteria and enroll patients that are most likely to benefit from the novel agents. Despite their superior performance, better understanding of practical barriers is needed to widen their implementation for precision oncology trials. Therefore, this paper also reviewed the practical challenges regarding the implementation of precision oncology clinical trials, along with the strength and weakness of various approaches of precision oncology clinical trial designs.
Indexed as
Identifiers
What OpenQuestion holds
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.