Evidence map›Paper›PMID 38811422›Full record

ReviewFamilial cancer2024

Optimizing the detection of hereditary predisposition in women with epithelial ovarian cancer: nationwide implementation of the Tumor-First workflow.

Vera M Witjes, Dorien M A Hermkens, Julie E M Swillens, Yvonne H C M Smolders, Marian J E Mourits, Margreet G E M Ausems, Joanne A de Hullu, Marjolijn J L Ligtenberg, Nicoline Hoogerbrugge

Abstract readReview
In one paragraph

Review in Familial cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Assessing the Clinical Relevance ofCurrent oncology (Toronto, Ont.) · 2026
    Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Vera M WitjesDepartment of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.
Dorien M A HermkensDepartment of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.
Julie E M SwillensResearch Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, The Netherlands.
Yvonne H C M SmoldersDepartment of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.
Marian J E MouritsDepartment of Obstetrics and Gynecology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Margreet G E M AusemsDivision Laboratories, Pharmacy and Biomedical Genetics, Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands.
Joanne A de HulluResearch Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, The Netherlands.
Marjolijn J L LigtenbergDepartment of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.
Nicoline HoogerbruggeDepartment of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands. Nicoline.Hoogerbrugge@radboudumc.nl.

Funding

KWF Kankerbestrijding 12732/2019-2
6 · The paper itself

Abstract

Genetic testing in patients with ovarian carcinoma (OC) is crucial, as around 10-15% of these women have a genetic predisposition to OC. Although guidelines have recommended universal germline testing for all patients with OC for a decade, implementation has proved challenging, thus resulting in low germline-testing rates (around 30-50%). Many new initiatives to improve genetic-testing rates have emerged, but most have been carried out at the local level, leading to differences in workflows within and between countries. We present an example of a nationwide implementation project that has successfully led to a uniform, high-quality genetic-testing workflow for women with OC. Nationwide multidisciplinary meetings generated consensus on the preferred workflow for OC genetic testing: the "Tumor-First" workflow. This workflow means starting by testing the tumor DNA for the presence of pathogenic variants in OC-risk genes, thus providing a prescreen to germline testing while yielding information on the effectiveness of treatment with PARP inhibitors. This new workflow efficiently stratifies genetic counseling and germline testing and reduces healthcare costs. Although challenging, the nationwide implementation of this workflow was successful, resulting in tumor-DNA testing rates exceeding 80%. In this article, we present our structured implementation approach, illustrate our implementation strategies-which were tailored to identified factors important to implementation-and share the lessons learned from the Tumor-First implementation project. This knowledge could facilitate the future implementation of workflows aimed at optimizing the recognition of hereditary cancers.

Indexed as

Carcinoma, Ovarian EpithelialGenetic Predisposition to DiseaseGenetic TestingOvarian NeoplasmsWorkflowFemaleGenetic CounselingGerm-Line MutationHumansBRCAEpithelial ovarian cancerHeredityImplementationInnovationMultidisciplinary

Identifiers

PMID38811422
PMCPMC11512879

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Registered trials

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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.