Evidence map›Paper›PMID 34274008›Full record

ArticleHereditary cancer in clinical practice2021

Evaluation and comparison of hereditary Cancer guidelines in the population.

Jordon B Ritchie, Cecelia Bellcross, Caitlin G Allen, Lewis Frey, Heath Morrison, Joshua D Schiffman, Brandon M Welch

Abstract read
In one paragraph

Article in Hereditary cancer in clinical practice, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Article
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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

7 authors.

Jordon B RitchieMedical University of South Carolina, 22 WestEdge St, Ste 200, Charleston, SC, 29403, USA. ritchiej@musc.edu.ORCID http://orcid.org/0000-0001-7503-6073
Cecelia BellcrossEmory University, Atlanta, USA.
Caitlin G AllenEmory University, Atlanta, USA.
Lewis FreyMedical University of South Carolina, 22 WestEdge St, Ste 200, Charleston, SC, 29403, USA.
Heath MorrisonItRunsInMyFamily.com, Charleston, SC, USA.
Joshua D SchiffmanUniversity of Utah, Salt Lake City, USA.
Brandon M WelchMedical University of South Carolina, 22 WestEdge St, Ste 200, Charleston, SC, 29403, USA.

Funding

Improving cancer family history collection through social networking and artificial intelligenceK07CA211786 · NCI · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI WELCH, BRANDON M · 2016 to 2020
$867k
Identifying hereditary cancer patients in low-resource community cancer settings using an innovative informatics solutionR41CA239867 · NCI · ITRUNSINMYFAMILY.COM, INC. · PI HUGHES-HALBERT, CHANITA A., WELCH, BRANDON M · 2019 to 2019
$300k
NCI NIH HHS K07 CA211786NCI NIH HHS R41 CA239867
6 · The paper itself

Abstract

backgroundFamily health history (FHx) is an effective tool for identifying patients at risk of hereditary cancer. Hereditary cancer clinical practice guidelines (CPG) contain criteria used to evaluate FHx and to make recommendations for genetic consultation. Comparing different CPGs used to evaluate a common set of FHx provides insight into how well the CPGs perform, the extent of agreement across guidelines, and how well they identify patients who should consider a cancer genetic consultation.

methodsWe compare the American College of Medical Genetics and Genomics (ACMG) and the National Comprehensive Cancer Networks (NCCN) (2019) CPG criteria for FHx collected by a chatbot and evaluated by ontologies and web services in a previous study. Collected FHx met criteria from seven groups: Gene Mutation, Breast and Ovarian, Li-Fraumeni syndrome (LFS), Colorectal and Endometrial, Relative Meets Criteria, ACMG Only Criteria, and NCCN Testing. CPG Criteria were coded and matched across 12 ACMG sub-guidelines and 6 NCCN sub-guidelines for comparison purposes.

resultsThe dataset contains 4915 records, of which 2221 met either ACMG or NCCN criteria and 2694 did not. There was significant overlap-1179 probands met both ACMG and NCCN criteria. The greatest similarities were for Gene Mutation and Breast and Ovarian criteria and the greatest disparity existed among Colorectal and Endometrial criteria. Only 156 positive gene mutations were reported and of the 2694 probands who did not meet criteria, 90.6% of them reported at least one cancer in their personal or family cancer history.

conclusionHereditary cancer CPGs are useful for identifying patients at risk of developing cancer based on FHx. This comparison shows that with the aid of chatbots, ontologies, and web services, CPGs can be more efficiently applied to identify patients at risk of hereditary cancer. Additionally this comparison examines similarities and differences between ACMG and NCCN and shows the importance of using both guidelines when evaluating hereditary cancer risk.

Indexed as

Clinical practice guidelinesFamily health historyHereditary cancerRisk assessment

Identifiers

PMID34274008
PMCPMC8285854

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LicenceCC BY
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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.