NuGenA (Nurse Led Genetic Counselling and Awareness): A proof-of-concept to implementation of genetic counseling for HBOC in LMICs.
Bibliographic record
Abstract
10583 Background: Poor access to genetic testing and counselling represents a major gap in cancer care in resource-restricted-settings. Our pilot work in Eastern India (2017-2019) demonstrated improved uptake of BRCA genetic testing (89% vs.55%) in ovarian cancer (OC) after training one nurse specialist in genetic counselling. We introduced NuGenA program in 2020 to scale-up this effort as proof-of-concept. Methods: Ethical approvals were obtained (KolGo/CTRI/2021/06/034308/HMSC). A nurse-led structured training program combining lectures/modules/live-demonstration-workshops/role-playing using offline and virtual learning methods were administered to sensitize/train all tiers of nurses including train-the-trainers in genetic counselling. A comprehensive NuGenA questionnaire including demographic, family history, CAM, pre/post-test counselling satisfaction-regret scale, QOL and willingness-to-pay (WTP) for genetic testing was administered by trained nurses. Physician and nursing interviews were conducted at 1 year to assess barriers/challenges/success of program. KolGoTrg EASE (Ethical/Acceptable/Affordable/Sustainable/Scalable/Effective/Early-diagnosis-and-treatment of barriers) matrix was used to measure key performance indicators and impact of implementation. Results: Through 40 sessions/workshops, 126 nurses were trained across India (8 centres, 34 nurses), Nepal (10 centres,30 nurses), Bangladesh (2 centres,60 nurses) and Africa (2 centres,2 nurses) with significant improvement in post training KAP scores. 7 genetic clinic/set-ups were created. 270 OC patients and 458 family members were counselled by nurses. 159 OC patients had BRCA testing, 48 (30%) being positive. Until now, out of 235 at-risk family members identified, 90 were counselled and 12 tested for BRCA (6 positive);2 opted for risk-reducing surgery. Unique barriers/challenges were identified including cost of BRCA test, provider hesitancy, social stigma, requiring customised solutions. WTP for genetic testing using CoPay model was accepted by 99/158 (62%). Another 100 community-nurses were sensitized through NuGenA camps/sessions approved by government/health authorities resulting in conduct of >150 COBRA (cervix/oral/ovary/breast-cancer awareness) sessions and patient-public-engagement initiatives. NuGenA modules are being included in national/international nursing curriculums. A World Ovarian Cancer Coalition charter-champion award and adoption by IGCS training sites exemplify global recognition/outreach. Conclusions: Nurse-led model proved scalable and impactful in resource-restricted settings, facilitating transformative changes in provider/patient-public engagement, attitude and practice towards genetic testing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".