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Evaluation of a virtual, nurse practitioner–led, pre-counselling seminar for mainstream germline genetic testing using a patient-reported outcomes measure (PROM).

2022· article· en· W4298147396 on OpenAlexaff
Jennifer Rauw, Laurie Barnhardt, Heather Lockyer

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of VictoriaProvincial Health Services AuthorityBC Cancer Agency
Fundersnot available
KeywordsMedicineGenetic counselingFamily medicineGenetic testingAttendancePopulationInternal medicine

Abstract

fetched live from OpenAlex

290 Background: Ovarian cancer (OC) is a common, often fatal disease where 1/4 of cases are due to hereditary syndromes. Genetic screening of OC patients provides access to targeted treatments and screening recommendations. Patients are currently referred to a virtual, group, pre-counseling seminar, delivered by a Nurse Practitioner, where consent for germline genetic testing is obtained and results are delivered later by a Genetic Counsellor (GC). Previously, we found group pre-counseling to be an effective method to decrease wait times from diagnosis to test results. The purpose of this study was to evaluate the patient seminar experience using the previously validated, Genetic Counselling Outcome Scale (GCOS-24). BC Cancer- Victoria is a satellite of BC Cancer, providing tertiary cancer care to a population of ̃1.2 million. Methods: We completed a REB approved, prospective study recruiting patients referred to the group pre-counseling consenting seminar. The GCOS-24 was delivered electronically both pre (1) and post (2) attendance at the seminar, and 4 weeks post genetic counselling visit (3). Inclusion criteria included OC patients referred for germline BRCA testing between Jan 1, 2021, to Feb 28, 2022, > 18 years old who attended the group consenting seminar. Patients who could not communicate in English were excluded. Data was stored electronically via REDCap, a secure web-based platform. Results: Thirty-eight patients attended the seminar and 28 consented to participate and completed the first questionnaire. Twenty-five patients completed the second questionnaire and 21 completed the third. The average age was 67, with 80% high grade serous, 11% low grade, 6% clear cell and 3% endometrioid OC subtypes. Forty- nine percent of participants were from Victoria area, and 11% were 225+ km away. The average GCOS-24 score for pre seminar participants was 111, post seminar 121 and post GC’s appointment 124. Twelve (52%) patients scored minimum clinically important difference (MCID) increase between questionnaires 1 and 2, and 14 (67%) patients scored MCID increase between questionnaires 1 and 3. The questions reflecting the most improvement in average scores between questionnaires 1 and 3 were exploring knowledge and emotions. Conclusions: Virtual group pre-counseling sessions for OC patients are feasible and allow germline genetic testing access to a geographically diverse group of eligible patients. Mean GCO-24 score almost reached MCID between pre seminar and post seminar visit and did reach MCID between pre counselling and post GC visit. There was a general trend to improved scores as patients moved from counselling naïve to pre-counseling to completed GC appointment. Virtual pre-counseling seminars should be considered as high impact, resource light method of improving access to germline genetic counselling for OC patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.135
GPT teacher head0.460
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2022
Admission routes1
Has abstractyes

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