ReviewNature reviews. Clinical oncology2016
Population genetic testing for cancer susceptibility: founder mutations to genomes.
Review in Nature reviews. Clinical oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 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
57 citing papers in PubMed.
- Trial
- A Risk Model Developed based on Homologous Recombination Deficiency Genes for Evaluating the Drug Sensitivity and Prognostic Prediction of Lung Adenocarcinoma.Current medicinal chemistry · 2025Article
- Molecular and immune landscape of tumours in geriatric patients with non-small cell lung cancer, melanoma and renal cell carcinoma.BMJ oncology · 2025Article
- The Evolution of Genetic Testing from Focused Testing to Panel Testing and from Patient Focused to Population Testing: Are We There Yet?Clinics in colon and rectal surgery · 2024Review
- Development and validation of ultrasound-based radiomics model to predict germline BRCA mutations in patients with breast cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Evolutionary origin of germline pathogenic variants in human DNA mismatch repair genes.Human genomics · 2024Article
- Hereditary cancer testing in a diverse sample across three breast imaging centers.Breast cancer research and treatment · 2024Article
- Navigating the genetic landscape of breast cancer in South Africa amidst a developing healthcare system.Frontiers in genetics · 2023Review
- The cancer-risk variant frequency among Polish population reported by the first national whole-genome sequencing study.Frontiers in oncology · 2023Article
- Article
- Cancer Genetics and Clinical Research.Journal of personalized medicine · 2022Article
- Gynecologic Cancer Risk and Genetics: Informing an Ideal Model of Gynecologic Cancer Prevention.Current oncology (Toronto, Ont.) · 2022Review
- DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data.Genome medicine · 2022Article
- Half of germline pathogenic and likely pathogenic variants found on panel tests do not fulfil NHS testing criteria.Scientific reports · 2022Article
- From the patient to the population: Use of genomics for population screening.Frontiers in genetics · 2022Article
- Barriers, interventions, and recommendations: Improving the genetic testing landscape.Frontiers in digital health · 2022Article
- Identification of molecular subtypes and prognostic signature for hepatocellular carcinoma based on genes associated with homologous recombination deficiency.Scientific reports · 2021Article
- Toward a Population-Based Breast Cancer Risk Stratification Approach? The Needs and Concerns of Healthcare Providers.Journal of personalized medicine · 2021Article
- The ten genes for breast (and ovarian) cancer susceptibility.Nature reviews. Clinical oncology · 2021Article
- Circulating carotenoids and breast cancer among high-risk individuals.The American journal of clinical nutrition · 2021Article
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
The current standard model for identifying carriers of high-risk mutations in cancer-susceptibility genes (CSGs) generally involves a process that is not amenable to population-based testing: access to genetic tests is typically regulated by health-care providers on the basis of a labour-intensive assessment of an individual's personal and family history of cancer, with face-to-face genetic counselling performed before mutation testing. Several studies have shown that application of these selection criteria results in a substantial proportion of mutation carriers being missed. Population-based genetic testing has been proposed as an alternative approach to determining cancer susceptibility, and aims for a more-comprehensive detection of mutation carriers. Herein, we review the existing data on population-based genetic testing, and consider some of the barriers, pitfalls, and challenges related to the possible expansion of this approach. We consider mechanisms by which population-based genetic testing for cancer susceptibility could be delivered, and suggest how such genetic testing might be integrated into existing and emerging health-care structures. The existing models of genetic testing (including issues relating to informed consent) will very likely require considerable alteration if the potential benefits of population-based genetic testing are to be fully realized.
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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.