ReviewClinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico2010
Selection of extreme phenotypes: the role of clinical observation in translational research.
Review in Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Associations of Allopregnanolone and Related Steroid Hormones with Prenatal Psychosocial Distress in the Healthy Start Cohort.medRxiv : the preprint server for health sciences · 2026Article
- Extreme phenotype-derived machine learning reveals susceptibility and resilience signatures for severe diabetic retinopathy.Frontiers in endocrinology · 2026Article
- Cytokine-Cytokine Receptor Interaction and Endocytosis are Common Pathways for Symptom Burden and Sickness Behavior Symptoms in Oncology Patients Undergoing Chemotherapy.Cancer medicine · 2025Article
- Article
- Identification of potential pathways and biomarkers linked to progression in ALS.Annals of clinical and translational neurology · 2023Article
- A Guide to Genome-Wide Association Study Design for Diabetic Retinopathy.Methods in molecular biology (Clifton, N.J.) · 2023Review
- Role of germline variants in the metastasis of breast carcinomas.Oncotarget · 2022Article
- Scalable network estimation withStatistical analysis and data mining · 2021Article
- Extreme phenotypes approach to investigate host genetics and COVID-19 outcomes.Genetics and molecular biology · 2021Article
- Genetic and non-genetic factors associated with the phenotype of exceptional longevity & normal cognition.Scientific reports · 2020Article
- When should we order a next generation sequencing test in a patient with cancer?EClinicalMedicine · 2020Review
- Systems genetics identifies a macrophage cholesterol network associated with physiological wound healing.JCI insight · 2019Article
- In vivo phosphoproteomics reveals kinase activity profiles that predict treatment outcome in triple-negative breast cancer.Nature communications · 2018Article
- Genomic characterization of individuals presenting extreme phenotypes of high and low risk to develop tobacco-induced lung cancer.Cancer medicine · 2018Article
- MiR-99b-5p expression and response to tyrosine kinase inhibitor treatment in clear cell renal cell carcinoma patients.Oncotarget · 2016Article
- Statistical power considerations in genotype-based recall randomized controlled trials.Scientific reports · 2016Article
- A trabecular plate-like phenotype is overrepresented in Chinese-American versus Caucasian women.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2014Article
- Identification of tissue microRNAs predictive of sunitinib activity in patients with metastatic renal cell carcinoma.PloS one · 2014Article
- Case Report: Long-Term Survival in Patients with Initial Lung-Only Metastasis from Pancreatic Adenocarcinoma.Journal of gastrointestinal cancer · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Systematic collection of phenotypes and their correlation with molecular data has been proposed as a useful method to advance in the study of disease. Although some databases for animal species are being developed, progress in humans is slow, probably due to the multifactorial origin of many human diseases and to the intricacy of accurately classifying phenotypes, among other factors. An alternative approach has been to identify and to study individuals or families with very characteristic, clinically relevant phenotypes. This strategy has shown increased efficiency to identify the molecular features underlying such phenotypes. While on most occasions the subjects selected for these studies presented harmful phenotypes, a few studies have been performed in individuals with very favourable phenotypes. The consistent results achieved suggest that it seems logical to further develop this strategy as a methodology to study human disease, including cancer. The identification and the study with high-throughput techniques of individuals showing a markedly decreased risk of developing cancer or of cancer patients presenting either an unusually favourable prognosis or striking responses following a specific treatment, might be promising ways to maximize the yield of this approach and to reveal the molecular causes that explain those phenotypes and thus highlight useful therapeutic targets. This manuscript reviews the current status of selection of extreme phenotypes in cancer research and provides directions for future development of this methodology.
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.